program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.4"}, {"coremlc-version", "1436.100.10"}, {"coremltools-component-torch", "2.1.0.dev20230718"}, {"coremltools-version", "7.0b1"}})]
{
    func main<ios16>(tensor<int32, [1, 77]> input_ids) {
            tensor<int32, []> var_5 = const()[name = tensor<string, []>("op_5"), val = tensor<int32, []>(-1)];
            tensor<bool, []> var_6 = const()[name = tensor<string, []>("op_6"), val = tensor<bool, []>(false)];
            tensor<int32, []> inputs_embeds_axis_0 = const()[name = tensor<string, []>("inputs_embeds_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> inputs_embeds_batch_dims_0 = const()[name = tensor<string, []>("inputs_embeds_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [49408, 1280]> text_encoder_text_model_embeddings_token_embedding_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor<fp16, [49408, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [1, 77, 1280]> inputs_embeds_cast = gather(axis = inputs_embeds_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = input_ids, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16)[name = tensor<string, []>("inputs_embeds_cast")];
            tensor<fp16, [1, 77, 1280]> position_embeddings_to_fp16 = const()[name = tensor<string, []>("position_embeddings_to_fp16"), val = tensor<fp16, [1, 77, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126484608)))];
            tensor<fp16, [1, 77, 1280]> input_3_cast = add(x = inputs_embeds_cast, y = position_embeddings_to_fp16)[name = tensor<string, []>("input_3_cast")];
            tensor<int32, [1]> hidden_states_1_axes_0 = const()[name = tensor<string, []>("hidden_states_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126681792)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126684416)))];
            tensor<fp16, []> var_13_to_fp16 = const()[name = tensor<string, []>("op_13_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 77, 1280]> hidden_states_1_cast = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_3_cast)[name = tensor<string, []>("hidden_states_1_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126687040)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129963904)))];
            tensor<fp16, [1, 77, 1280]> var_130_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16, x = hidden_states_1_cast)[name = tensor<string, []>("op_130_cast")];
            tensor<fp16, []> var_131_to_fp16 = const()[name = tensor<string, []>("op_131_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_5_cast = mul(x = var_130_cast, y = var_131_to_fp16)[name = tensor<string, []>("tensor_5_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129966528)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133243392)))];
            tensor<fp16, [1, 77, 1280]> tensor_1_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16, x = hidden_states_1_cast)[name = tensor<string, []>("tensor_1_cast")];
            tensor<int32, [4]> var_136 = const()[name = tensor<string, []>("op_136"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_137_cast = reshape(shape = var_136, x = tensor_1_cast)[name = tensor<string, []>("op_137_cast")];
            tensor<int32, [4]> var_138_perm_0 = const()[name = tensor<string, []>("op_138_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133246016)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136522880)))];
            tensor<fp16, [1, 77, 1280]> tensor_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16, x = hidden_states_1_cast)[name = tensor<string, []>("tensor_3_cast")];
            tensor<int32, [4]> var_143 = const()[name = tensor<string, []>("op_143"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_144_cast = reshape(shape = var_143, x = tensor_3_cast)[name = tensor<string, []>("op_144_cast")];
            tensor<int32, [4]> var_145_perm_0 = const()[name = tensor<string, []>("op_145_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_152 = const()[name = tensor<string, []>("op_152"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_153_cast = reshape(shape = var_152, x = tensor_5_cast)[name = tensor<string, []>("op_153_cast")];
            tensor<int32, [4]> var_154_perm_0 = const()[name = tensor<string, []>("op_154_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_156 = const()[name = tensor<string, []>("op_156"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_158 = transpose(perm = var_154_perm_0, x = var_153_cast)[name = tensor<string, []>("transpose_158")];
            tensor<fp16, [20, 77, 64]> query_states_1_cast = reshape(shape = var_156, x = transpose_158)[name = tensor<string, []>("query_states_1_cast")];
            tensor<int32, [3]> var_158 = const()[name = tensor<string, []>("op_158"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_160 = transpose(perm = var_138_perm_0, x = var_137_cast)[name = tensor<string, []>("transpose_160")];
            tensor<fp16, [20, 77, 64]> key_states_3_cast = reshape(shape = var_158, x = transpose_160)[name = tensor<string, []>("key_states_3_cast")];
            tensor<int32, [3]> var_160 = const()[name = tensor<string, []>("op_160"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_159 = transpose(perm = var_145_perm_0, x = var_144_cast)[name = tensor<string, []>("transpose_159")];
            tensor<fp16, [20, 77, 64]> value_states_3_cast = reshape(shape = var_160, x = transpose_159)[name = tensor<string, []>("value_states_3_cast")];
            tensor<int32, [3]> var_163_perm_0 = const()[name = tensor<string, []>("op_163_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_1_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_1_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_1_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_1_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_157 = transpose(perm = var_163_perm_0, x = key_states_3_cast)[name = tensor<string, []>("transpose_157")];
            tensor<fp16, [20, 77, 77]> attn_weights_1_cast = matmul(transpose_x = attn_weights_1_transpose_x_0, transpose_y = attn_weights_1_transpose_y_0, x = query_states_1_cast, y = transpose_157)[name = tensor<string, []>("attn_weights_1_cast")];
            tensor<int32, [4]> var_165 = const()[name = tensor<string, []>("op_165"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_166_cast = reshape(shape = var_165, x = attn_weights_1_cast)[name = tensor<string, []>("op_166_cast")];
            tensor<fp16, [1, 1, 77, 77]> causal_attention_mask_to_fp16 = const()[name = tensor<string, []>("causal_attention_mask_to_fp16"), val = tensor<fp16, [1, 1, 77, 77]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136525504)))];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_3_cast = add(x = var_166_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_3_cast")];
            tensor<int32, [3]> var_171 = const()[name = tensor<string, []>("op_171"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_5_cast = reshape(shape = var_171, x = attn_weights_3_cast)[name = tensor<string, []>("input_5_cast")];
            tensor<fp16, [20, 77, 77]> input_7_cast = softmax(axis = var_5, x = input_5_cast)[name = tensor<string, []>("input_7_cast")];
            tensor<bool, []> attn_output_1_transpose_x_0 = const()[name = tensor<string, []>("attn_output_1_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_1_transpose_y_0 = const()[name = tensor<string, []>("attn_output_1_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_1_cast = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7_cast, y = value_states_3_cast)[name = tensor<string, []>("attn_output_1_cast")];
            tensor<int32, [4]> var_176 = const()[name = tensor<string, []>("op_176"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_3_cast = reshape(shape = var_176, x = attn_output_1_cast)[name = tensor<string, []>("attn_output_3_cast")];
            tensor<int32, [4]> attn_output_5_perm_0 = const()[name = tensor<string, []>("attn_output_5_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_179 = const()[name = tensor<string, []>("op_179"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_156 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast)[name = tensor<string, []>("transpose_156")];
            tensor<fp16, [1, 77, 1280]> input_9_cast = reshape(shape = var_179, x = transpose_156)[name = tensor<string, []>("input_9_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136537472)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139814336)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16, x = input_9_cast)[name = tensor<string, []>("hidden_states_3_cast")];
            tensor<fp16, [1, 77, 1280]> input_11_cast = add(x = input_3_cast, y = hidden_states_3_cast)[name = tensor<string, []>("input_11_cast")];
            tensor<int32, [1]> input_13_axes_0 = const()[name = tensor<string, []>("input_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139816960)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139819584)))];
            tensor<fp16, [1, 77, 1280]> input_13_cast = layer_norm(axes = input_13_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_11_cast)[name = tensor<string, []>("input_13_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139822208)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152929472)))];
            tensor<fp16, [1, 77, 5120]> input_15_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16, x = input_13_cast)[name = tensor<string, []>("input_15_cast")];
            tensor<string, []> input_17_mode_0 = const()[name = tensor<string, []>("input_17_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_17_cast = gelu(mode = input_17_mode_0, x = input_15_cast)[name = tensor<string, []>("input_17_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152939776)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166047040)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_5_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16, x = input_17_cast)[name = tensor<string, []>("hidden_states_5_cast")];
            tensor<fp16, [1, 77, 1280]> input_19_cast = add(x = input_11_cast, y = hidden_states_5_cast)[name = tensor<string, []>("input_19_cast")];
            tensor<int32, [1]> hidden_states_7_axes_0 = const()[name = tensor<string, []>("hidden_states_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166049664)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166052288)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_7_cast = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_19_cast)[name = tensor<string, []>("hidden_states_7_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166054912)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169331776)))];
            tensor<fp16, [1, 77, 1280]> var_217_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16, x = hidden_states_7_cast)[name = tensor<string, []>("op_217_cast")];
            tensor<fp16, []> var_218_to_fp16 = const()[name = tensor<string, []>("op_218_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_11_cast = mul(x = var_217_cast, y = var_218_to_fp16)[name = tensor<string, []>("tensor_11_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169334400)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172611264)))];
            tensor<fp16, [1, 77, 1280]> tensor_7_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16, x = hidden_states_7_cast)[name = tensor<string, []>("tensor_7_cast")];
            tensor<int32, [4]> var_223 = const()[name = tensor<string, []>("op_223"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_224_cast = reshape(shape = var_223, x = tensor_7_cast)[name = tensor<string, []>("op_224_cast")];
            tensor<int32, [4]> var_225_perm_0 = const()[name = tensor<string, []>("op_225_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172613888)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175890752)))];
            tensor<fp16, [1, 77, 1280]> tensor_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16, x = hidden_states_7_cast)[name = tensor<string, []>("tensor_9_cast")];
            tensor<int32, [4]> var_230 = const()[name = tensor<string, []>("op_230"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_231_cast = reshape(shape = var_230, x = tensor_9_cast)[name = tensor<string, []>("op_231_cast")];
            tensor<int32, [4]> var_232_perm_0 = const()[name = tensor<string, []>("op_232_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_239 = const()[name = tensor<string, []>("op_239"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_240_cast = reshape(shape = var_239, x = tensor_11_cast)[name = tensor<string, []>("op_240_cast")];
            tensor<int32, [4]> var_241_perm_0 = const()[name = tensor<string, []>("op_241_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_243 = const()[name = tensor<string, []>("op_243"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_153 = transpose(perm = var_241_perm_0, x = var_240_cast)[name = tensor<string, []>("transpose_153")];
            tensor<fp16, [20, 77, 64]> query_states_3_cast = reshape(shape = var_243, x = transpose_153)[name = tensor<string, []>("query_states_3_cast")];
            tensor<int32, [3]> var_245 = const()[name = tensor<string, []>("op_245"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_155 = transpose(perm = var_225_perm_0, x = var_224_cast)[name = tensor<string, []>("transpose_155")];
            tensor<fp16, [20, 77, 64]> key_states_7_cast = reshape(shape = var_245, x = transpose_155)[name = tensor<string, []>("key_states_7_cast")];
            tensor<int32, [3]> var_247 = const()[name = tensor<string, []>("op_247"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_154 = transpose(perm = var_232_perm_0, x = var_231_cast)[name = tensor<string, []>("transpose_154")];
            tensor<fp16, [20, 77, 64]> value_states_7_cast = reshape(shape = var_247, x = transpose_154)[name = tensor<string, []>("value_states_7_cast")];
            tensor<int32, [3]> var_250_perm_0 = const()[name = tensor<string, []>("op_250_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_7_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_7_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_7_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_7_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_152 = transpose(perm = var_250_perm_0, x = key_states_7_cast)[name = tensor<string, []>("transpose_152")];
            tensor<fp16, [20, 77, 77]> attn_weights_7_cast = matmul(transpose_x = attn_weights_7_transpose_x_0, transpose_y = attn_weights_7_transpose_y_0, x = query_states_3_cast, y = transpose_152)[name = tensor<string, []>("attn_weights_7_cast")];
            tensor<int32, [4]> var_252 = const()[name = tensor<string, []>("op_252"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_253_cast = reshape(shape = var_252, x = attn_weights_7_cast)[name = tensor<string, []>("op_253_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_9_cast = add(x = var_253_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_9_cast")];
            tensor<int32, [3]> var_258 = const()[name = tensor<string, []>("op_258"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_21_cast = reshape(shape = var_258, x = attn_weights_9_cast)[name = tensor<string, []>("input_21_cast")];
            tensor<fp16, [20, 77, 77]> input_23_cast = softmax(axis = var_5, x = input_21_cast)[name = tensor<string, []>("input_23_cast")];
            tensor<bool, []> attn_output_7_transpose_x_0 = const()[name = tensor<string, []>("attn_output_7_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_7_transpose_y_0 = const()[name = tensor<string, []>("attn_output_7_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_7_cast = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast, y = value_states_7_cast)[name = tensor<string, []>("attn_output_7_cast")];
            tensor<int32, [4]> var_263 = const()[name = tensor<string, []>("op_263"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_9_cast = reshape(shape = var_263, x = attn_output_7_cast)[name = tensor<string, []>("attn_output_9_cast")];
            tensor<int32, [4]> attn_output_11_perm_0 = const()[name = tensor<string, []>("attn_output_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_266 = const()[name = tensor<string, []>("op_266"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_151 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast)[name = tensor<string, []>("transpose_151")];
            tensor<fp16, [1, 77, 1280]> input_25_cast = reshape(shape = var_266, x = transpose_151)[name = tensor<string, []>("input_25_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175893376)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179170240)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16, x = input_25_cast)[name = tensor<string, []>("hidden_states_9_cast")];
            tensor<fp16, [1, 77, 1280]> input_27_cast = add(x = input_19_cast, y = hidden_states_9_cast)[name = tensor<string, []>("input_27_cast")];
            tensor<int32, [1]> input_29_axes_0 = const()[name = tensor<string, []>("input_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179172864)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179175488)))];
            tensor<fp16, [1, 77, 1280]> input_29_cast = layer_norm(axes = input_29_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_27_cast)[name = tensor<string, []>("input_29_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179178112)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192285376)))];
            tensor<fp16, [1, 77, 5120]> input_31_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16, x = input_29_cast)[name = tensor<string, []>("input_31_cast")];
            tensor<string, []> input_33_mode_0 = const()[name = tensor<string, []>("input_33_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_33_cast = gelu(mode = input_33_mode_0, x = input_31_cast)[name = tensor<string, []>("input_33_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192295680)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205402944)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_11_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16, x = input_33_cast)[name = tensor<string, []>("hidden_states_11_cast")];
            tensor<fp16, [1, 77, 1280]> input_35_cast = add(x = input_27_cast, y = hidden_states_11_cast)[name = tensor<string, []>("input_35_cast")];
            tensor<int32, [1]> hidden_states_13_axes_0 = const()[name = tensor<string, []>("hidden_states_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205405568)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205408192)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_13_cast = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_35_cast)[name = tensor<string, []>("hidden_states_13_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205410816)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208687680)))];
            tensor<fp16, [1, 77, 1280]> var_304_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16, x = hidden_states_13_cast)[name = tensor<string, []>("op_304_cast")];
            tensor<fp16, []> var_305_to_fp16 = const()[name = tensor<string, []>("op_305_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_17_cast = mul(x = var_304_cast, y = var_305_to_fp16)[name = tensor<string, []>("tensor_17_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208690304)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211967168)))];
            tensor<fp16, [1, 77, 1280]> tensor_13_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16, x = hidden_states_13_cast)[name = tensor<string, []>("tensor_13_cast")];
            tensor<int32, [4]> var_310 = const()[name = tensor<string, []>("op_310"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_311_cast = reshape(shape = var_310, x = tensor_13_cast)[name = tensor<string, []>("op_311_cast")];
            tensor<int32, [4]> var_312_perm_0 = const()[name = tensor<string, []>("op_312_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211969792)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215246656)))];
            tensor<fp16, [1, 77, 1280]> tensor_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16, x = hidden_states_13_cast)[name = tensor<string, []>("tensor_15_cast")];
            tensor<int32, [4]> var_317 = const()[name = tensor<string, []>("op_317"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_318_cast = reshape(shape = var_317, x = tensor_15_cast)[name = tensor<string, []>("op_318_cast")];
            tensor<int32, [4]> var_319_perm_0 = const()[name = tensor<string, []>("op_319_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_326 = const()[name = tensor<string, []>("op_326"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_327_cast = reshape(shape = var_326, x = tensor_17_cast)[name = tensor<string, []>("op_327_cast")];
            tensor<int32, [4]> var_328_perm_0 = const()[name = tensor<string, []>("op_328_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_330 = const()[name = tensor<string, []>("op_330"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_148 = transpose(perm = var_328_perm_0, x = var_327_cast)[name = tensor<string, []>("transpose_148")];
            tensor<fp16, [20, 77, 64]> query_states_5_cast = reshape(shape = var_330, x = transpose_148)[name = tensor<string, []>("query_states_5_cast")];
            tensor<int32, [3]> var_332 = const()[name = tensor<string, []>("op_332"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_150 = transpose(perm = var_312_perm_0, x = var_311_cast)[name = tensor<string, []>("transpose_150")];
            tensor<fp16, [20, 77, 64]> key_states_11_cast = reshape(shape = var_332, x = transpose_150)[name = tensor<string, []>("key_states_11_cast")];
            tensor<int32, [3]> var_334 = const()[name = tensor<string, []>("op_334"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_149 = transpose(perm = var_319_perm_0, x = var_318_cast)[name = tensor<string, []>("transpose_149")];
            tensor<fp16, [20, 77, 64]> value_states_11_cast = reshape(shape = var_334, x = transpose_149)[name = tensor<string, []>("value_states_11_cast")];
            tensor<int32, [3]> var_337_perm_0 = const()[name = tensor<string, []>("op_337_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_13_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_13_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_13_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_13_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_147 = transpose(perm = var_337_perm_0, x = key_states_11_cast)[name = tensor<string, []>("transpose_147")];
            tensor<fp16, [20, 77, 77]> attn_weights_13_cast = matmul(transpose_x = attn_weights_13_transpose_x_0, transpose_y = attn_weights_13_transpose_y_0, x = query_states_5_cast, y = transpose_147)[name = tensor<string, []>("attn_weights_13_cast")];
            tensor<int32, [4]> var_339 = const()[name = tensor<string, []>("op_339"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_340_cast = reshape(shape = var_339, x = attn_weights_13_cast)[name = tensor<string, []>("op_340_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_15_cast = add(x = var_340_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_15_cast")];
            tensor<int32, [3]> var_345 = const()[name = tensor<string, []>("op_345"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_37_cast = reshape(shape = var_345, x = attn_weights_15_cast)[name = tensor<string, []>("input_37_cast")];
            tensor<fp16, [20, 77, 77]> input_39_cast = softmax(axis = var_5, x = input_37_cast)[name = tensor<string, []>("input_39_cast")];
            tensor<bool, []> attn_output_13_transpose_x_0 = const()[name = tensor<string, []>("attn_output_13_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_13_transpose_y_0 = const()[name = tensor<string, []>("attn_output_13_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_13_cast = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39_cast, y = value_states_11_cast)[name = tensor<string, []>("attn_output_13_cast")];
            tensor<int32, [4]> var_350 = const()[name = tensor<string, []>("op_350"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_15_cast = reshape(shape = var_350, x = attn_output_13_cast)[name = tensor<string, []>("attn_output_15_cast")];
            tensor<int32, [4]> attn_output_17_perm_0 = const()[name = tensor<string, []>("attn_output_17_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_353 = const()[name = tensor<string, []>("op_353"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_146 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast)[name = tensor<string, []>("transpose_146")];
            tensor<fp16, [1, 77, 1280]> input_41_cast = reshape(shape = var_353, x = transpose_146)[name = tensor<string, []>("input_41_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215249280)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218526144)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16, x = input_41_cast)[name = tensor<string, []>("hidden_states_15_cast")];
            tensor<fp16, [1, 77, 1280]> input_43_cast = add(x = input_35_cast, y = hidden_states_15_cast)[name = tensor<string, []>("input_43_cast")];
            tensor<int32, [1]> input_45_axes_0 = const()[name = tensor<string, []>("input_45_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218528768)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218531392)))];
            tensor<fp16, [1, 77, 1280]> input_45_cast = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_43_cast)[name = tensor<string, []>("input_45_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218534016)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231641280)))];
            tensor<fp16, [1, 77, 5120]> input_47_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16, x = input_45_cast)[name = tensor<string, []>("input_47_cast")];
            tensor<string, []> input_49_mode_0 = const()[name = tensor<string, []>("input_49_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_49_cast = gelu(mode = input_49_mode_0, x = input_47_cast)[name = tensor<string, []>("input_49_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231651584)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244758848)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_17_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16, x = input_49_cast)[name = tensor<string, []>("hidden_states_17_cast")];
            tensor<fp16, [1, 77, 1280]> input_51_cast = add(x = input_43_cast, y = hidden_states_17_cast)[name = tensor<string, []>("input_51_cast")];
            tensor<int32, [1]> hidden_states_19_axes_0 = const()[name = tensor<string, []>("hidden_states_19_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244761472)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244764096)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_19_cast = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_51_cast)[name = tensor<string, []>("hidden_states_19_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244766720)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(248043584)))];
            tensor<fp16, [1, 77, 1280]> var_391_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16, x = hidden_states_19_cast)[name = tensor<string, []>("op_391_cast")];
            tensor<fp16, []> var_392_to_fp16 = const()[name = tensor<string, []>("op_392_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_23_cast = mul(x = var_391_cast, y = var_392_to_fp16)[name = tensor<string, []>("tensor_23_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(248046208)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(251323072)))];
            tensor<fp16, [1, 77, 1280]> tensor_19_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16, x = hidden_states_19_cast)[name = tensor<string, []>("tensor_19_cast")];
            tensor<int32, [4]> var_397 = const()[name = tensor<string, []>("op_397"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_398_cast = reshape(shape = var_397, x = tensor_19_cast)[name = tensor<string, []>("op_398_cast")];
            tensor<int32, [4]> var_399_perm_0 = const()[name = tensor<string, []>("op_399_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(251325696)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254602560)))];
            tensor<fp16, [1, 77, 1280]> tensor_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16, x = hidden_states_19_cast)[name = tensor<string, []>("tensor_21_cast")];
            tensor<int32, [4]> var_404 = const()[name = tensor<string, []>("op_404"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_405_cast = reshape(shape = var_404, x = tensor_21_cast)[name = tensor<string, []>("op_405_cast")];
            tensor<int32, [4]> var_406_perm_0 = const()[name = tensor<string, []>("op_406_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_413 = const()[name = tensor<string, []>("op_413"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_414_cast = reshape(shape = var_413, x = tensor_23_cast)[name = tensor<string, []>("op_414_cast")];
            tensor<int32, [4]> var_415_perm_0 = const()[name = tensor<string, []>("op_415_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_417 = const()[name = tensor<string, []>("op_417"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_143 = transpose(perm = var_415_perm_0, x = var_414_cast)[name = tensor<string, []>("transpose_143")];
            tensor<fp16, [20, 77, 64]> query_states_7_cast = reshape(shape = var_417, x = transpose_143)[name = tensor<string, []>("query_states_7_cast")];
            tensor<int32, [3]> var_419 = const()[name = tensor<string, []>("op_419"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_145 = transpose(perm = var_399_perm_0, x = var_398_cast)[name = tensor<string, []>("transpose_145")];
            tensor<fp16, [20, 77, 64]> key_states_15_cast = reshape(shape = var_419, x = transpose_145)[name = tensor<string, []>("key_states_15_cast")];
            tensor<int32, [3]> var_421 = const()[name = tensor<string, []>("op_421"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_144 = transpose(perm = var_406_perm_0, x = var_405_cast)[name = tensor<string, []>("transpose_144")];
            tensor<fp16, [20, 77, 64]> value_states_15_cast = reshape(shape = var_421, x = transpose_144)[name = tensor<string, []>("value_states_15_cast")];
            tensor<int32, [3]> var_424_perm_0 = const()[name = tensor<string, []>("op_424_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_19_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_19_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_19_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_19_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_142 = transpose(perm = var_424_perm_0, x = key_states_15_cast)[name = tensor<string, []>("transpose_142")];
            tensor<fp16, [20, 77, 77]> attn_weights_19_cast = matmul(transpose_x = attn_weights_19_transpose_x_0, transpose_y = attn_weights_19_transpose_y_0, x = query_states_7_cast, y = transpose_142)[name = tensor<string, []>("attn_weights_19_cast")];
            tensor<int32, [4]> var_426 = const()[name = tensor<string, []>("op_426"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_427_cast = reshape(shape = var_426, x = attn_weights_19_cast)[name = tensor<string, []>("op_427_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_21_cast = add(x = var_427_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_21_cast")];
            tensor<int32, [3]> var_432 = const()[name = tensor<string, []>("op_432"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_53_cast = reshape(shape = var_432, x = attn_weights_21_cast)[name = tensor<string, []>("input_53_cast")];
            tensor<fp16, [20, 77, 77]> input_55_cast = softmax(axis = var_5, x = input_53_cast)[name = tensor<string, []>("input_55_cast")];
            tensor<bool, []> attn_output_19_transpose_x_0 = const()[name = tensor<string, []>("attn_output_19_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_19_transpose_y_0 = const()[name = tensor<string, []>("attn_output_19_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_19_cast = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55_cast, y = value_states_15_cast)[name = tensor<string, []>("attn_output_19_cast")];
            tensor<int32, [4]> var_437 = const()[name = tensor<string, []>("op_437"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_21_cast = reshape(shape = var_437, x = attn_output_19_cast)[name = tensor<string, []>("attn_output_21_cast")];
            tensor<int32, [4]> attn_output_23_perm_0 = const()[name = tensor<string, []>("attn_output_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_440 = const()[name = tensor<string, []>("op_440"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_141 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast)[name = tensor<string, []>("transpose_141")];
            tensor<fp16, [1, 77, 1280]> input_57_cast = reshape(shape = var_440, x = transpose_141)[name = tensor<string, []>("input_57_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254605184)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257882048)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16, x = input_57_cast)[name = tensor<string, []>("hidden_states_21_cast")];
            tensor<fp16, [1, 77, 1280]> input_59_cast = add(x = input_51_cast, y = hidden_states_21_cast)[name = tensor<string, []>("input_59_cast")];
            tensor<int32, [1]> input_61_axes_0 = const()[name = tensor<string, []>("input_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257884672)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257887296)))];
            tensor<fp16, [1, 77, 1280]> input_61_cast = layer_norm(axes = input_61_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_59_cast)[name = tensor<string, []>("input_61_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257889920)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270997184)))];
            tensor<fp16, [1, 77, 5120]> input_63_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16, x = input_61_cast)[name = tensor<string, []>("input_63_cast")];
            tensor<string, []> input_65_mode_0 = const()[name = tensor<string, []>("input_65_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_65_cast = gelu(mode = input_65_mode_0, x = input_63_cast)[name = tensor<string, []>("input_65_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(271007488)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284114752)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_23_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16, x = input_65_cast)[name = tensor<string, []>("hidden_states_23_cast")];
            tensor<fp16, [1, 77, 1280]> input_67_cast = add(x = input_59_cast, y = hidden_states_23_cast)[name = tensor<string, []>("input_67_cast")];
            tensor<int32, [1]> hidden_states_25_axes_0 = const()[name = tensor<string, []>("hidden_states_25_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284117376)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284120000)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_25_cast = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_67_cast)[name = tensor<string, []>("hidden_states_25_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284122624)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(287399488)))];
            tensor<fp16, [1, 77, 1280]> var_478_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16, x = hidden_states_25_cast)[name = tensor<string, []>("op_478_cast")];
            tensor<fp16, []> var_479_to_fp16 = const()[name = tensor<string, []>("op_479_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_29_cast = mul(x = var_478_cast, y = var_479_to_fp16)[name = tensor<string, []>("tensor_29_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(287402112)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(290678976)))];
            tensor<fp16, [1, 77, 1280]> tensor_25_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16, x = hidden_states_25_cast)[name = tensor<string, []>("tensor_25_cast")];
            tensor<int32, [4]> var_484 = const()[name = tensor<string, []>("op_484"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_485_cast = reshape(shape = var_484, x = tensor_25_cast)[name = tensor<string, []>("op_485_cast")];
            tensor<int32, [4]> var_486_perm_0 = const()[name = tensor<string, []>("op_486_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(290681600)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(293958464)))];
            tensor<fp16, [1, 77, 1280]> tensor_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16, x = hidden_states_25_cast)[name = tensor<string, []>("tensor_27_cast")];
            tensor<int32, [4]> var_491 = const()[name = tensor<string, []>("op_491"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_492_cast = reshape(shape = var_491, x = tensor_27_cast)[name = tensor<string, []>("op_492_cast")];
            tensor<int32, [4]> var_493_perm_0 = const()[name = tensor<string, []>("op_493_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_500 = const()[name = tensor<string, []>("op_500"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_501_cast = reshape(shape = var_500, x = tensor_29_cast)[name = tensor<string, []>("op_501_cast")];
            tensor<int32, [4]> var_502_perm_0 = const()[name = tensor<string, []>("op_502_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_504 = const()[name = tensor<string, []>("op_504"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_138 = transpose(perm = var_502_perm_0, x = var_501_cast)[name = tensor<string, []>("transpose_138")];
            tensor<fp16, [20, 77, 64]> query_states_9_cast = reshape(shape = var_504, x = transpose_138)[name = tensor<string, []>("query_states_9_cast")];
            tensor<int32, [3]> var_506 = const()[name = tensor<string, []>("op_506"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_140 = transpose(perm = var_486_perm_0, x = var_485_cast)[name = tensor<string, []>("transpose_140")];
            tensor<fp16, [20, 77, 64]> key_states_19_cast = reshape(shape = var_506, x = transpose_140)[name = tensor<string, []>("key_states_19_cast")];
            tensor<int32, [3]> var_508 = const()[name = tensor<string, []>("op_508"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_139 = transpose(perm = var_493_perm_0, x = var_492_cast)[name = tensor<string, []>("transpose_139")];
            tensor<fp16, [20, 77, 64]> value_states_19_cast = reshape(shape = var_508, x = transpose_139)[name = tensor<string, []>("value_states_19_cast")];
            tensor<int32, [3]> var_511_perm_0 = const()[name = tensor<string, []>("op_511_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_25_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_25_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_25_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_25_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_137 = transpose(perm = var_511_perm_0, x = key_states_19_cast)[name = tensor<string, []>("transpose_137")];
            tensor<fp16, [20, 77, 77]> attn_weights_25_cast = matmul(transpose_x = attn_weights_25_transpose_x_0, transpose_y = attn_weights_25_transpose_y_0, x = query_states_9_cast, y = transpose_137)[name = tensor<string, []>("attn_weights_25_cast")];
            tensor<int32, [4]> var_513 = const()[name = tensor<string, []>("op_513"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_514_cast = reshape(shape = var_513, x = attn_weights_25_cast)[name = tensor<string, []>("op_514_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_27_cast = add(x = var_514_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_27_cast")];
            tensor<int32, [3]> var_519 = const()[name = tensor<string, []>("op_519"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_69_cast = reshape(shape = var_519, x = attn_weights_27_cast)[name = tensor<string, []>("input_69_cast")];
            tensor<fp16, [20, 77, 77]> input_71_cast = softmax(axis = var_5, x = input_69_cast)[name = tensor<string, []>("input_71_cast")];
            tensor<bool, []> attn_output_25_transpose_x_0 = const()[name = tensor<string, []>("attn_output_25_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_25_transpose_y_0 = const()[name = tensor<string, []>("attn_output_25_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_25_cast = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71_cast, y = value_states_19_cast)[name = tensor<string, []>("attn_output_25_cast")];
            tensor<int32, [4]> var_524 = const()[name = tensor<string, []>("op_524"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_27_cast = reshape(shape = var_524, x = attn_output_25_cast)[name = tensor<string, []>("attn_output_27_cast")];
            tensor<int32, [4]> attn_output_29_perm_0 = const()[name = tensor<string, []>("attn_output_29_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_527 = const()[name = tensor<string, []>("op_527"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_136 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast)[name = tensor<string, []>("transpose_136")];
            tensor<fp16, [1, 77, 1280]> input_73_cast = reshape(shape = var_527, x = transpose_136)[name = tensor<string, []>("input_73_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(293961088)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297237952)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16, x = input_73_cast)[name = tensor<string, []>("hidden_states_27_cast")];
            tensor<fp16, [1, 77, 1280]> input_75_cast = add(x = input_67_cast, y = hidden_states_27_cast)[name = tensor<string, []>("input_75_cast")];
            tensor<int32, [1]> input_77_axes_0 = const()[name = tensor<string, []>("input_77_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297240576)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297243200)))];
            tensor<fp16, [1, 77, 1280]> input_77_cast = layer_norm(axes = input_77_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_75_cast)[name = tensor<string, []>("input_77_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297245824)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(310353088)))];
            tensor<fp16, [1, 77, 5120]> input_79_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16, x = input_77_cast)[name = tensor<string, []>("input_79_cast")];
            tensor<string, []> input_81_mode_0 = const()[name = tensor<string, []>("input_81_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_81_cast = gelu(mode = input_81_mode_0, x = input_79_cast)[name = tensor<string, []>("input_81_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(310363392)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323470656)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_29_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16, x = input_81_cast)[name = tensor<string, []>("hidden_states_29_cast")];
            tensor<fp16, [1, 77, 1280]> input_83_cast = add(x = input_75_cast, y = hidden_states_29_cast)[name = tensor<string, []>("input_83_cast")];
            tensor<int32, [1]> hidden_states_31_axes_0 = const()[name = tensor<string, []>("hidden_states_31_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323473280)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323475904)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_31_cast = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_83_cast)[name = tensor<string, []>("hidden_states_31_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323478528)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326755392)))];
            tensor<fp16, [1, 77, 1280]> var_565_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16, x = hidden_states_31_cast)[name = tensor<string, []>("op_565_cast")];
            tensor<fp16, []> var_566_to_fp16 = const()[name = tensor<string, []>("op_566_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_35_cast = mul(x = var_565_cast, y = var_566_to_fp16)[name = tensor<string, []>("tensor_35_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326758016)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(330034880)))];
            tensor<fp16, [1, 77, 1280]> tensor_31_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16, x = hidden_states_31_cast)[name = tensor<string, []>("tensor_31_cast")];
            tensor<int32, [4]> var_571 = const()[name = tensor<string, []>("op_571"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_572_cast = reshape(shape = var_571, x = tensor_31_cast)[name = tensor<string, []>("op_572_cast")];
            tensor<int32, [4]> var_573_perm_0 = const()[name = tensor<string, []>("op_573_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(330037504)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333314368)))];
            tensor<fp16, [1, 77, 1280]> tensor_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16, x = hidden_states_31_cast)[name = tensor<string, []>("tensor_33_cast")];
            tensor<int32, [4]> var_578 = const()[name = tensor<string, []>("op_578"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_579_cast = reshape(shape = var_578, x = tensor_33_cast)[name = tensor<string, []>("op_579_cast")];
            tensor<int32, [4]> var_580_perm_0 = const()[name = tensor<string, []>("op_580_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_587 = const()[name = tensor<string, []>("op_587"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_588_cast = reshape(shape = var_587, x = tensor_35_cast)[name = tensor<string, []>("op_588_cast")];
            tensor<int32, [4]> var_589_perm_0 = const()[name = tensor<string, []>("op_589_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_591 = const()[name = tensor<string, []>("op_591"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_133 = transpose(perm = var_589_perm_0, x = var_588_cast)[name = tensor<string, []>("transpose_133")];
            tensor<fp16, [20, 77, 64]> query_states_11_cast = reshape(shape = var_591, x = transpose_133)[name = tensor<string, []>("query_states_11_cast")];
            tensor<int32, [3]> var_593 = const()[name = tensor<string, []>("op_593"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_135 = transpose(perm = var_573_perm_0, x = var_572_cast)[name = tensor<string, []>("transpose_135")];
            tensor<fp16, [20, 77, 64]> key_states_23_cast = reshape(shape = var_593, x = transpose_135)[name = tensor<string, []>("key_states_23_cast")];
            tensor<int32, [3]> var_595 = const()[name = tensor<string, []>("op_595"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_134 = transpose(perm = var_580_perm_0, x = var_579_cast)[name = tensor<string, []>("transpose_134")];
            tensor<fp16, [20, 77, 64]> value_states_23_cast = reshape(shape = var_595, x = transpose_134)[name = tensor<string, []>("value_states_23_cast")];
            tensor<int32, [3]> var_598_perm_0 = const()[name = tensor<string, []>("op_598_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_31_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_31_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_31_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_31_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_132 = transpose(perm = var_598_perm_0, x = key_states_23_cast)[name = tensor<string, []>("transpose_132")];
            tensor<fp16, [20, 77, 77]> attn_weights_31_cast = matmul(transpose_x = attn_weights_31_transpose_x_0, transpose_y = attn_weights_31_transpose_y_0, x = query_states_11_cast, y = transpose_132)[name = tensor<string, []>("attn_weights_31_cast")];
            tensor<int32, [4]> var_600 = const()[name = tensor<string, []>("op_600"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_601_cast = reshape(shape = var_600, x = attn_weights_31_cast)[name = tensor<string, []>("op_601_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_33_cast = add(x = var_601_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_33_cast")];
            tensor<int32, [3]> var_606 = const()[name = tensor<string, []>("op_606"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_85_cast = reshape(shape = var_606, x = attn_weights_33_cast)[name = tensor<string, []>("input_85_cast")];
            tensor<fp16, [20, 77, 77]> input_87_cast = softmax(axis = var_5, x = input_85_cast)[name = tensor<string, []>("input_87_cast")];
            tensor<bool, []> attn_output_31_transpose_x_0 = const()[name = tensor<string, []>("attn_output_31_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_31_transpose_y_0 = const()[name = tensor<string, []>("attn_output_31_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_31_cast = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87_cast, y = value_states_23_cast)[name = tensor<string, []>("attn_output_31_cast")];
            tensor<int32, [4]> var_611 = const()[name = tensor<string, []>("op_611"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_33_cast = reshape(shape = var_611, x = attn_output_31_cast)[name = tensor<string, []>("attn_output_33_cast")];
            tensor<int32, [4]> attn_output_35_perm_0 = const()[name = tensor<string, []>("attn_output_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_614 = const()[name = tensor<string, []>("op_614"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_131 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast)[name = tensor<string, []>("transpose_131")];
            tensor<fp16, [1, 77, 1280]> input_89_cast = reshape(shape = var_614, x = transpose_131)[name = tensor<string, []>("input_89_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333316992)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336593856)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16, x = input_89_cast)[name = tensor<string, []>("hidden_states_33_cast")];
            tensor<fp16, [1, 77, 1280]> input_91_cast = add(x = input_83_cast, y = hidden_states_33_cast)[name = tensor<string, []>("input_91_cast")];
            tensor<int32, [1]> input_93_axes_0 = const()[name = tensor<string, []>("input_93_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336596480)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336599104)))];
            tensor<fp16, [1, 77, 1280]> input_93_cast = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_91_cast)[name = tensor<string, []>("input_93_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336601728)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349708992)))];
            tensor<fp16, [1, 77, 5120]> input_95_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16, x = input_93_cast)[name = tensor<string, []>("input_95_cast")];
            tensor<string, []> input_97_mode_0 = const()[name = tensor<string, []>("input_97_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_97_cast = gelu(mode = input_97_mode_0, x = input_95_cast)[name = tensor<string, []>("input_97_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349719296)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362826560)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_35_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16, x = input_97_cast)[name = tensor<string, []>("hidden_states_35_cast")];
            tensor<fp16, [1, 77, 1280]> input_99_cast = add(x = input_91_cast, y = hidden_states_35_cast)[name = tensor<string, []>("input_99_cast")];
            tensor<int32, [1]> hidden_states_37_axes_0 = const()[name = tensor<string, []>("hidden_states_37_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362829184)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362831808)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_37_cast = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_99_cast)[name = tensor<string, []>("hidden_states_37_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362834432)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(366111296)))];
            tensor<fp16, [1, 77, 1280]> var_652_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16, x = hidden_states_37_cast)[name = tensor<string, []>("op_652_cast")];
            tensor<fp16, []> var_653_to_fp16 = const()[name = tensor<string, []>("op_653_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_41_cast = mul(x = var_652_cast, y = var_653_to_fp16)[name = tensor<string, []>("tensor_41_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(366113920)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369390784)))];
            tensor<fp16, [1, 77, 1280]> tensor_37_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16, x = hidden_states_37_cast)[name = tensor<string, []>("tensor_37_cast")];
            tensor<int32, [4]> var_658 = const()[name = tensor<string, []>("op_658"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_659_cast = reshape(shape = var_658, x = tensor_37_cast)[name = tensor<string, []>("op_659_cast")];
            tensor<int32, [4]> var_660_perm_0 = const()[name = tensor<string, []>("op_660_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369393408)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372670272)))];
            tensor<fp16, [1, 77, 1280]> tensor_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16, x = hidden_states_37_cast)[name = tensor<string, []>("tensor_39_cast")];
            tensor<int32, [4]> var_665 = const()[name = tensor<string, []>("op_665"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_666_cast = reshape(shape = var_665, x = tensor_39_cast)[name = tensor<string, []>("op_666_cast")];
            tensor<int32, [4]> var_667_perm_0 = const()[name = tensor<string, []>("op_667_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_674 = const()[name = tensor<string, []>("op_674"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_675_cast = reshape(shape = var_674, x = tensor_41_cast)[name = tensor<string, []>("op_675_cast")];
            tensor<int32, [4]> var_676_perm_0 = const()[name = tensor<string, []>("op_676_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_678 = const()[name = tensor<string, []>("op_678"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_128 = transpose(perm = var_676_perm_0, x = var_675_cast)[name = tensor<string, []>("transpose_128")];
            tensor<fp16, [20, 77, 64]> query_states_13_cast = reshape(shape = var_678, x = transpose_128)[name = tensor<string, []>("query_states_13_cast")];
            tensor<int32, [3]> var_680 = const()[name = tensor<string, []>("op_680"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_130 = transpose(perm = var_660_perm_0, x = var_659_cast)[name = tensor<string, []>("transpose_130")];
            tensor<fp16, [20, 77, 64]> key_states_27_cast = reshape(shape = var_680, x = transpose_130)[name = tensor<string, []>("key_states_27_cast")];
            tensor<int32, [3]> var_682 = const()[name = tensor<string, []>("op_682"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_129 = transpose(perm = var_667_perm_0, x = var_666_cast)[name = tensor<string, []>("transpose_129")];
            tensor<fp16, [20, 77, 64]> value_states_27_cast = reshape(shape = var_682, x = transpose_129)[name = tensor<string, []>("value_states_27_cast")];
            tensor<int32, [3]> var_685_perm_0 = const()[name = tensor<string, []>("op_685_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_37_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_37_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_37_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_37_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_127 = transpose(perm = var_685_perm_0, x = key_states_27_cast)[name = tensor<string, []>("transpose_127")];
            tensor<fp16, [20, 77, 77]> attn_weights_37_cast = matmul(transpose_x = attn_weights_37_transpose_x_0, transpose_y = attn_weights_37_transpose_y_0, x = query_states_13_cast, y = transpose_127)[name = tensor<string, []>("attn_weights_37_cast")];
            tensor<int32, [4]> var_687 = const()[name = tensor<string, []>("op_687"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_688_cast = reshape(shape = var_687, x = attn_weights_37_cast)[name = tensor<string, []>("op_688_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_39_cast = add(x = var_688_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_39_cast")];
            tensor<int32, [3]> var_693 = const()[name = tensor<string, []>("op_693"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_101_cast = reshape(shape = var_693, x = attn_weights_39_cast)[name = tensor<string, []>("input_101_cast")];
            tensor<fp16, [20, 77, 77]> input_103_cast = softmax(axis = var_5, x = input_101_cast)[name = tensor<string, []>("input_103_cast")];
            tensor<bool, []> attn_output_37_transpose_x_0 = const()[name = tensor<string, []>("attn_output_37_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_37_transpose_y_0 = const()[name = tensor<string, []>("attn_output_37_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_37_cast = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103_cast, y = value_states_27_cast)[name = tensor<string, []>("attn_output_37_cast")];
            tensor<int32, [4]> var_698 = const()[name = tensor<string, []>("op_698"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_39_cast = reshape(shape = var_698, x = attn_output_37_cast)[name = tensor<string, []>("attn_output_39_cast")];
            tensor<int32, [4]> attn_output_41_perm_0 = const()[name = tensor<string, []>("attn_output_41_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_701 = const()[name = tensor<string, []>("op_701"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_126 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast)[name = tensor<string, []>("transpose_126")];
            tensor<fp16, [1, 77, 1280]> input_105_cast = reshape(shape = var_701, x = transpose_126)[name = tensor<string, []>("input_105_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372672896)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375949760)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16, x = input_105_cast)[name = tensor<string, []>("hidden_states_39_cast")];
            tensor<fp16, [1, 77, 1280]> input_107_cast = add(x = input_99_cast, y = hidden_states_39_cast)[name = tensor<string, []>("input_107_cast")];
            tensor<int32, [1]> input_109_axes_0 = const()[name = tensor<string, []>("input_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375952384)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375955008)))];
            tensor<fp16, [1, 77, 1280]> input_109_cast = layer_norm(axes = input_109_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_107_cast)[name = tensor<string, []>("input_109_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375957632)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389064896)))];
            tensor<fp16, [1, 77, 5120]> input_111_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16, x = input_109_cast)[name = tensor<string, []>("input_111_cast")];
            tensor<string, []> input_113_mode_0 = const()[name = tensor<string, []>("input_113_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_113_cast = gelu(mode = input_113_mode_0, x = input_111_cast)[name = tensor<string, []>("input_113_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389075200)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402182464)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_41_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16, x = input_113_cast)[name = tensor<string, []>("hidden_states_41_cast")];
            tensor<fp16, [1, 77, 1280]> input_115_cast = add(x = input_107_cast, y = hidden_states_41_cast)[name = tensor<string, []>("input_115_cast")];
            tensor<int32, [1]> hidden_states_43_axes_0 = const()[name = tensor<string, []>("hidden_states_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402185088)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402187712)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_43_cast = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_115_cast)[name = tensor<string, []>("hidden_states_43_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402190336)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405467200)))];
            tensor<fp16, [1, 77, 1280]> var_739_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16, x = hidden_states_43_cast)[name = tensor<string, []>("op_739_cast")];
            tensor<fp16, []> var_740_to_fp16 = const()[name = tensor<string, []>("op_740_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_47_cast = mul(x = var_739_cast, y = var_740_to_fp16)[name = tensor<string, []>("tensor_47_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405469824)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(408746688)))];
            tensor<fp16, [1, 77, 1280]> tensor_43_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16, x = hidden_states_43_cast)[name = tensor<string, []>("tensor_43_cast")];
            tensor<int32, [4]> var_745 = const()[name = tensor<string, []>("op_745"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_746_cast = reshape(shape = var_745, x = tensor_43_cast)[name = tensor<string, []>("op_746_cast")];
            tensor<int32, [4]> var_747_perm_0 = const()[name = tensor<string, []>("op_747_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(408749312)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412026176)))];
            tensor<fp16, [1, 77, 1280]> tensor_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16, x = hidden_states_43_cast)[name = tensor<string, []>("tensor_45_cast")];
            tensor<int32, [4]> var_752 = const()[name = tensor<string, []>("op_752"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_753_cast = reshape(shape = var_752, x = tensor_45_cast)[name = tensor<string, []>("op_753_cast")];
            tensor<int32, [4]> var_754_perm_0 = const()[name = tensor<string, []>("op_754_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_761 = const()[name = tensor<string, []>("op_761"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_762_cast = reshape(shape = var_761, x = tensor_47_cast)[name = tensor<string, []>("op_762_cast")];
            tensor<int32, [4]> var_763_perm_0 = const()[name = tensor<string, []>("op_763_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_765 = const()[name = tensor<string, []>("op_765"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_123 = transpose(perm = var_763_perm_0, x = var_762_cast)[name = tensor<string, []>("transpose_123")];
            tensor<fp16, [20, 77, 64]> query_states_15_cast = reshape(shape = var_765, x = transpose_123)[name = tensor<string, []>("query_states_15_cast")];
            tensor<int32, [3]> var_767 = const()[name = tensor<string, []>("op_767"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_125 = transpose(perm = var_747_perm_0, x = var_746_cast)[name = tensor<string, []>("transpose_125")];
            tensor<fp16, [20, 77, 64]> key_states_31_cast = reshape(shape = var_767, x = transpose_125)[name = tensor<string, []>("key_states_31_cast")];
            tensor<int32, [3]> var_769 = const()[name = tensor<string, []>("op_769"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_124 = transpose(perm = var_754_perm_0, x = var_753_cast)[name = tensor<string, []>("transpose_124")];
            tensor<fp16, [20, 77, 64]> value_states_31_cast = reshape(shape = var_769, x = transpose_124)[name = tensor<string, []>("value_states_31_cast")];
            tensor<int32, [3]> var_772_perm_0 = const()[name = tensor<string, []>("op_772_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_43_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_43_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_43_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_43_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_122 = transpose(perm = var_772_perm_0, x = key_states_31_cast)[name = tensor<string, []>("transpose_122")];
            tensor<fp16, [20, 77, 77]> attn_weights_43_cast = matmul(transpose_x = attn_weights_43_transpose_x_0, transpose_y = attn_weights_43_transpose_y_0, x = query_states_15_cast, y = transpose_122)[name = tensor<string, []>("attn_weights_43_cast")];
            tensor<int32, [4]> var_774 = const()[name = tensor<string, []>("op_774"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_775_cast = reshape(shape = var_774, x = attn_weights_43_cast)[name = tensor<string, []>("op_775_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_45_cast = add(x = var_775_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_45_cast")];
            tensor<int32, [3]> var_780 = const()[name = tensor<string, []>("op_780"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_117_cast = reshape(shape = var_780, x = attn_weights_45_cast)[name = tensor<string, []>("input_117_cast")];
            tensor<fp16, [20, 77, 77]> input_119_cast = softmax(axis = var_5, x = input_117_cast)[name = tensor<string, []>("input_119_cast")];
            tensor<bool, []> attn_output_43_transpose_x_0 = const()[name = tensor<string, []>("attn_output_43_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_43_transpose_y_0 = const()[name = tensor<string, []>("attn_output_43_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_43_cast = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119_cast, y = value_states_31_cast)[name = tensor<string, []>("attn_output_43_cast")];
            tensor<int32, [4]> var_785 = const()[name = tensor<string, []>("op_785"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_45_cast = reshape(shape = var_785, x = attn_output_43_cast)[name = tensor<string, []>("attn_output_45_cast")];
            tensor<int32, [4]> attn_output_47_perm_0 = const()[name = tensor<string, []>("attn_output_47_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_788 = const()[name = tensor<string, []>("op_788"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_121 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast)[name = tensor<string, []>("transpose_121")];
            tensor<fp16, [1, 77, 1280]> input_121_cast = reshape(shape = var_788, x = transpose_121)[name = tensor<string, []>("input_121_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412028800)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415305664)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16, x = input_121_cast)[name = tensor<string, []>("hidden_states_45_cast")];
            tensor<fp16, [1, 77, 1280]> input_123_cast = add(x = input_115_cast, y = hidden_states_45_cast)[name = tensor<string, []>("input_123_cast")];
            tensor<int32, [1]> input_125_axes_0 = const()[name = tensor<string, []>("input_125_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415308288)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415310912)))];
            tensor<fp16, [1, 77, 1280]> input_125_cast = layer_norm(axes = input_125_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_123_cast)[name = tensor<string, []>("input_125_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415313536)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(428420800)))];
            tensor<fp16, [1, 77, 5120]> input_127_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16, x = input_125_cast)[name = tensor<string, []>("input_127_cast")];
            tensor<string, []> input_129_mode_0 = const()[name = tensor<string, []>("input_129_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_129_cast = gelu(mode = input_129_mode_0, x = input_127_cast)[name = tensor<string, []>("input_129_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(428431104)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441538368)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_47_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16, x = input_129_cast)[name = tensor<string, []>("hidden_states_47_cast")];
            tensor<fp16, [1, 77, 1280]> input_131_cast = add(x = input_123_cast, y = hidden_states_47_cast)[name = tensor<string, []>("input_131_cast")];
            tensor<int32, [1]> hidden_states_49_axes_0 = const()[name = tensor<string, []>("hidden_states_49_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441540992)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441543616)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_49_cast = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_131_cast)[name = tensor<string, []>("hidden_states_49_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441546240)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(444823104)))];
            tensor<fp16, [1, 77, 1280]> var_826_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16, x = hidden_states_49_cast)[name = tensor<string, []>("op_826_cast")];
            tensor<fp16, []> var_827_to_fp16 = const()[name = tensor<string, []>("op_827_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_53_cast = mul(x = var_826_cast, y = var_827_to_fp16)[name = tensor<string, []>("tensor_53_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(444825728)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(448102592)))];
            tensor<fp16, [1, 77, 1280]> tensor_49_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16, x = hidden_states_49_cast)[name = tensor<string, []>("tensor_49_cast")];
            tensor<int32, [4]> var_832 = const()[name = tensor<string, []>("op_832"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_833_cast = reshape(shape = var_832, x = tensor_49_cast)[name = tensor<string, []>("op_833_cast")];
            tensor<int32, [4]> var_834_perm_0 = const()[name = tensor<string, []>("op_834_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(448105216)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451382080)))];
            tensor<fp16, [1, 77, 1280]> tensor_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16, x = hidden_states_49_cast)[name = tensor<string, []>("tensor_51_cast")];
            tensor<int32, [4]> var_839 = const()[name = tensor<string, []>("op_839"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_840_cast = reshape(shape = var_839, x = tensor_51_cast)[name = tensor<string, []>("op_840_cast")];
            tensor<int32, [4]> var_841_perm_0 = const()[name = tensor<string, []>("op_841_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_848 = const()[name = tensor<string, []>("op_848"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_849_cast = reshape(shape = var_848, x = tensor_53_cast)[name = tensor<string, []>("op_849_cast")];
            tensor<int32, [4]> var_850_perm_0 = const()[name = tensor<string, []>("op_850_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_852 = const()[name = tensor<string, []>("op_852"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_118 = transpose(perm = var_850_perm_0, x = var_849_cast)[name = tensor<string, []>("transpose_118")];
            tensor<fp16, [20, 77, 64]> query_states_17_cast = reshape(shape = var_852, x = transpose_118)[name = tensor<string, []>("query_states_17_cast")];
            tensor<int32, [3]> var_854 = const()[name = tensor<string, []>("op_854"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_120 = transpose(perm = var_834_perm_0, x = var_833_cast)[name = tensor<string, []>("transpose_120")];
            tensor<fp16, [20, 77, 64]> key_states_35_cast = reshape(shape = var_854, x = transpose_120)[name = tensor<string, []>("key_states_35_cast")];
            tensor<int32, [3]> var_856 = const()[name = tensor<string, []>("op_856"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_119 = transpose(perm = var_841_perm_0, x = var_840_cast)[name = tensor<string, []>("transpose_119")];
            tensor<fp16, [20, 77, 64]> value_states_35_cast = reshape(shape = var_856, x = transpose_119)[name = tensor<string, []>("value_states_35_cast")];
            tensor<int32, [3]> var_859_perm_0 = const()[name = tensor<string, []>("op_859_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_49_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_49_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_49_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_49_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_117 = transpose(perm = var_859_perm_0, x = key_states_35_cast)[name = tensor<string, []>("transpose_117")];
            tensor<fp16, [20, 77, 77]> attn_weights_49_cast = matmul(transpose_x = attn_weights_49_transpose_x_0, transpose_y = attn_weights_49_transpose_y_0, x = query_states_17_cast, y = transpose_117)[name = tensor<string, []>("attn_weights_49_cast")];
            tensor<int32, [4]> var_861 = const()[name = tensor<string, []>("op_861"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_862_cast = reshape(shape = var_861, x = attn_weights_49_cast)[name = tensor<string, []>("op_862_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_51_cast = add(x = var_862_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_51_cast")];
            tensor<int32, [3]> var_867 = const()[name = tensor<string, []>("op_867"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_133_cast = reshape(shape = var_867, x = attn_weights_51_cast)[name = tensor<string, []>("input_133_cast")];
            tensor<fp16, [20, 77, 77]> input_135_cast = softmax(axis = var_5, x = input_133_cast)[name = tensor<string, []>("input_135_cast")];
            tensor<bool, []> attn_output_49_transpose_x_0 = const()[name = tensor<string, []>("attn_output_49_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_49_transpose_y_0 = const()[name = tensor<string, []>("attn_output_49_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_49_cast = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast, y = value_states_35_cast)[name = tensor<string, []>("attn_output_49_cast")];
            tensor<int32, [4]> var_872 = const()[name = tensor<string, []>("op_872"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_51_cast = reshape(shape = var_872, x = attn_output_49_cast)[name = tensor<string, []>("attn_output_51_cast")];
            tensor<int32, [4]> attn_output_53_perm_0 = const()[name = tensor<string, []>("attn_output_53_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_875 = const()[name = tensor<string, []>("op_875"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_116 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast)[name = tensor<string, []>("transpose_116")];
            tensor<fp16, [1, 77, 1280]> input_137_cast = reshape(shape = var_875, x = transpose_116)[name = tensor<string, []>("input_137_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451384704)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454661568)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16, x = input_137_cast)[name = tensor<string, []>("hidden_states_51_cast")];
            tensor<fp16, [1, 77, 1280]> input_139_cast = add(x = input_131_cast, y = hidden_states_51_cast)[name = tensor<string, []>("input_139_cast")];
            tensor<int32, [1]> input_141_axes_0 = const()[name = tensor<string, []>("input_141_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454664192)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454666816)))];
            tensor<fp16, [1, 77, 1280]> input_141_cast = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_139_cast)[name = tensor<string, []>("input_141_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454669440)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467776704)))];
            tensor<fp16, [1, 77, 5120]> input_143_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16, x = input_141_cast)[name = tensor<string, []>("input_143_cast")];
            tensor<string, []> input_145_mode_0 = const()[name = tensor<string, []>("input_145_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_145_cast = gelu(mode = input_145_mode_0, x = input_143_cast)[name = tensor<string, []>("input_145_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467787008)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480894272)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_53_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16, x = input_145_cast)[name = tensor<string, []>("hidden_states_53_cast")];
            tensor<fp16, [1, 77, 1280]> input_147_cast = add(x = input_139_cast, y = hidden_states_53_cast)[name = tensor<string, []>("input_147_cast")];
            tensor<int32, [1]> hidden_states_55_axes_0 = const()[name = tensor<string, []>("hidden_states_55_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480896896)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480899520)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_55_cast = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_147_cast)[name = tensor<string, []>("hidden_states_55_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480902144)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(484179008)))];
            tensor<fp16, [1, 77, 1280]> var_913_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16, x = hidden_states_55_cast)[name = tensor<string, []>("op_913_cast")];
            tensor<fp16, []> var_914_to_fp16 = const()[name = tensor<string, []>("op_914_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_59_cast = mul(x = var_913_cast, y = var_914_to_fp16)[name = tensor<string, []>("tensor_59_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(484181632)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(487458496)))];
            tensor<fp16, [1, 77, 1280]> tensor_55_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16, x = hidden_states_55_cast)[name = tensor<string, []>("tensor_55_cast")];
            tensor<int32, [4]> var_919 = const()[name = tensor<string, []>("op_919"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_920_cast = reshape(shape = var_919, x = tensor_55_cast)[name = tensor<string, []>("op_920_cast")];
            tensor<int32, [4]> var_921_perm_0 = const()[name = tensor<string, []>("op_921_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(487461120)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490737984)))];
            tensor<fp16, [1, 77, 1280]> tensor_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16, x = hidden_states_55_cast)[name = tensor<string, []>("tensor_57_cast")];
            tensor<int32, [4]> var_926 = const()[name = tensor<string, []>("op_926"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_927_cast = reshape(shape = var_926, x = tensor_57_cast)[name = tensor<string, []>("op_927_cast")];
            tensor<int32, [4]> var_928_perm_0 = const()[name = tensor<string, []>("op_928_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_935 = const()[name = tensor<string, []>("op_935"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_936_cast = reshape(shape = var_935, x = tensor_59_cast)[name = tensor<string, []>("op_936_cast")];
            tensor<int32, [4]> var_937_perm_0 = const()[name = tensor<string, []>("op_937_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_939 = const()[name = tensor<string, []>("op_939"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_113 = transpose(perm = var_937_perm_0, x = var_936_cast)[name = tensor<string, []>("transpose_113")];
            tensor<fp16, [20, 77, 64]> query_states_19_cast = reshape(shape = var_939, x = transpose_113)[name = tensor<string, []>("query_states_19_cast")];
            tensor<int32, [3]> var_941 = const()[name = tensor<string, []>("op_941"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_115 = transpose(perm = var_921_perm_0, x = var_920_cast)[name = tensor<string, []>("transpose_115")];
            tensor<fp16, [20, 77, 64]> key_states_39_cast = reshape(shape = var_941, x = transpose_115)[name = tensor<string, []>("key_states_39_cast")];
            tensor<int32, [3]> var_943 = const()[name = tensor<string, []>("op_943"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_114 = transpose(perm = var_928_perm_0, x = var_927_cast)[name = tensor<string, []>("transpose_114")];
            tensor<fp16, [20, 77, 64]> value_states_39_cast = reshape(shape = var_943, x = transpose_114)[name = tensor<string, []>("value_states_39_cast")];
            tensor<int32, [3]> var_946_perm_0 = const()[name = tensor<string, []>("op_946_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_55_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_55_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_55_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_55_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_112 = transpose(perm = var_946_perm_0, x = key_states_39_cast)[name = tensor<string, []>("transpose_112")];
            tensor<fp16, [20, 77, 77]> attn_weights_55_cast = matmul(transpose_x = attn_weights_55_transpose_x_0, transpose_y = attn_weights_55_transpose_y_0, x = query_states_19_cast, y = transpose_112)[name = tensor<string, []>("attn_weights_55_cast")];
            tensor<int32, [4]> var_948 = const()[name = tensor<string, []>("op_948"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_949_cast = reshape(shape = var_948, x = attn_weights_55_cast)[name = tensor<string, []>("op_949_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_57_cast = add(x = var_949_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_57_cast")];
            tensor<int32, [3]> var_954 = const()[name = tensor<string, []>("op_954"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_149_cast = reshape(shape = var_954, x = attn_weights_57_cast)[name = tensor<string, []>("input_149_cast")];
            tensor<fp16, [20, 77, 77]> input_151_cast = softmax(axis = var_5, x = input_149_cast)[name = tensor<string, []>("input_151_cast")];
            tensor<bool, []> attn_output_55_transpose_x_0 = const()[name = tensor<string, []>("attn_output_55_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_55_transpose_y_0 = const()[name = tensor<string, []>("attn_output_55_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_55_cast = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151_cast, y = value_states_39_cast)[name = tensor<string, []>("attn_output_55_cast")];
            tensor<int32, [4]> var_959 = const()[name = tensor<string, []>("op_959"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_57_cast = reshape(shape = var_959, x = attn_output_55_cast)[name = tensor<string, []>("attn_output_57_cast")];
            tensor<int32, [4]> attn_output_59_perm_0 = const()[name = tensor<string, []>("attn_output_59_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_962 = const()[name = tensor<string, []>("op_962"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_111 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast)[name = tensor<string, []>("transpose_111")];
            tensor<fp16, [1, 77, 1280]> input_153_cast = reshape(shape = var_962, x = transpose_111)[name = tensor<string, []>("input_153_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490740608)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494017472)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16, x = input_153_cast)[name = tensor<string, []>("hidden_states_57_cast")];
            tensor<fp16, [1, 77, 1280]> input_155_cast = add(x = input_147_cast, y = hidden_states_57_cast)[name = tensor<string, []>("input_155_cast")];
            tensor<int32, [1]> input_157_axes_0 = const()[name = tensor<string, []>("input_157_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494020096)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494022720)))];
            tensor<fp16, [1, 77, 1280]> input_157_cast = layer_norm(axes = input_157_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_155_cast)[name = tensor<string, []>("input_157_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494025344)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(507132608)))];
            tensor<fp16, [1, 77, 5120]> input_159_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16, x = input_157_cast)[name = tensor<string, []>("input_159_cast")];
            tensor<string, []> input_161_mode_0 = const()[name = tensor<string, []>("input_161_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_161_cast = gelu(mode = input_161_mode_0, x = input_159_cast)[name = tensor<string, []>("input_161_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(507142912)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520250176)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_59_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16, x = input_161_cast)[name = tensor<string, []>("hidden_states_59_cast")];
            tensor<fp16, [1, 77, 1280]> input_163_cast = add(x = input_155_cast, y = hidden_states_59_cast)[name = tensor<string, []>("input_163_cast")];
            tensor<int32, [1]> hidden_states_61_axes_0 = const()[name = tensor<string, []>("hidden_states_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520252800)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520255424)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_61_cast = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_163_cast)[name = tensor<string, []>("hidden_states_61_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520258048)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(523534912)))];
            tensor<fp16, [1, 77, 1280]> var_1000_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16, x = hidden_states_61_cast)[name = tensor<string, []>("op_1000_cast")];
            tensor<fp16, []> var_1001_to_fp16 = const()[name = tensor<string, []>("op_1001_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_65_cast = mul(x = var_1000_cast, y = var_1001_to_fp16)[name = tensor<string, []>("tensor_65_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(523537536)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526814400)))];
            tensor<fp16, [1, 77, 1280]> tensor_61_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16, x = hidden_states_61_cast)[name = tensor<string, []>("tensor_61_cast")];
            tensor<int32, [4]> var_1006 = const()[name = tensor<string, []>("op_1006"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1007_cast = reshape(shape = var_1006, x = tensor_61_cast)[name = tensor<string, []>("op_1007_cast")];
            tensor<int32, [4]> var_1008_perm_0 = const()[name = tensor<string, []>("op_1008_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526817024)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530093888)))];
            tensor<fp16, [1, 77, 1280]> tensor_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16, x = hidden_states_61_cast)[name = tensor<string, []>("tensor_63_cast")];
            tensor<int32, [4]> var_1013 = const()[name = tensor<string, []>("op_1013"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1014_cast = reshape(shape = var_1013, x = tensor_63_cast)[name = tensor<string, []>("op_1014_cast")];
            tensor<int32, [4]> var_1015_perm_0 = const()[name = tensor<string, []>("op_1015_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1022 = const()[name = tensor<string, []>("op_1022"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1023_cast = reshape(shape = var_1022, x = tensor_65_cast)[name = tensor<string, []>("op_1023_cast")];
            tensor<int32, [4]> var_1024_perm_0 = const()[name = tensor<string, []>("op_1024_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1026 = const()[name = tensor<string, []>("op_1026"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_108 = transpose(perm = var_1024_perm_0, x = var_1023_cast)[name = tensor<string, []>("transpose_108")];
            tensor<fp16, [20, 77, 64]> query_states_21_cast = reshape(shape = var_1026, x = transpose_108)[name = tensor<string, []>("query_states_21_cast")];
            tensor<int32, [3]> var_1028 = const()[name = tensor<string, []>("op_1028"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_110 = transpose(perm = var_1008_perm_0, x = var_1007_cast)[name = tensor<string, []>("transpose_110")];
            tensor<fp16, [20, 77, 64]> key_states_43_cast = reshape(shape = var_1028, x = transpose_110)[name = tensor<string, []>("key_states_43_cast")];
            tensor<int32, [3]> var_1030 = const()[name = tensor<string, []>("op_1030"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_109 = transpose(perm = var_1015_perm_0, x = var_1014_cast)[name = tensor<string, []>("transpose_109")];
            tensor<fp16, [20, 77, 64]> value_states_43_cast = reshape(shape = var_1030, x = transpose_109)[name = tensor<string, []>("value_states_43_cast")];
            tensor<int32, [3]> var_1033_perm_0 = const()[name = tensor<string, []>("op_1033_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_61_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_61_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_61_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_61_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_107 = transpose(perm = var_1033_perm_0, x = key_states_43_cast)[name = tensor<string, []>("transpose_107")];
            tensor<fp16, [20, 77, 77]> attn_weights_61_cast = matmul(transpose_x = attn_weights_61_transpose_x_0, transpose_y = attn_weights_61_transpose_y_0, x = query_states_21_cast, y = transpose_107)[name = tensor<string, []>("attn_weights_61_cast")];
            tensor<int32, [4]> var_1035 = const()[name = tensor<string, []>("op_1035"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1036_cast = reshape(shape = var_1035, x = attn_weights_61_cast)[name = tensor<string, []>("op_1036_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_63_cast = add(x = var_1036_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_63_cast")];
            tensor<int32, [3]> var_1041 = const()[name = tensor<string, []>("op_1041"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_165_cast = reshape(shape = var_1041, x = attn_weights_63_cast)[name = tensor<string, []>("input_165_cast")];
            tensor<fp16, [20, 77, 77]> input_167_cast = softmax(axis = var_5, x = input_165_cast)[name = tensor<string, []>("input_167_cast")];
            tensor<bool, []> attn_output_61_transpose_x_0 = const()[name = tensor<string, []>("attn_output_61_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_61_transpose_y_0 = const()[name = tensor<string, []>("attn_output_61_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_61_cast = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167_cast, y = value_states_43_cast)[name = tensor<string, []>("attn_output_61_cast")];
            tensor<int32, [4]> var_1046 = const()[name = tensor<string, []>("op_1046"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_63_cast = reshape(shape = var_1046, x = attn_output_61_cast)[name = tensor<string, []>("attn_output_63_cast")];
            tensor<int32, [4]> attn_output_65_perm_0 = const()[name = tensor<string, []>("attn_output_65_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1049 = const()[name = tensor<string, []>("op_1049"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_106 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast)[name = tensor<string, []>("transpose_106")];
            tensor<fp16, [1, 77, 1280]> input_169_cast = reshape(shape = var_1049, x = transpose_106)[name = tensor<string, []>("input_169_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530096512)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533373376)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16, x = input_169_cast)[name = tensor<string, []>("hidden_states_63_cast")];
            tensor<fp16, [1, 77, 1280]> input_171_cast = add(x = input_163_cast, y = hidden_states_63_cast)[name = tensor<string, []>("input_171_cast")];
            tensor<int32, [1]> input_173_axes_0 = const()[name = tensor<string, []>("input_173_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533376000)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533378624)))];
            tensor<fp16, [1, 77, 1280]> input_173_cast = layer_norm(axes = input_173_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_171_cast)[name = tensor<string, []>("input_173_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533381248)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(546488512)))];
            tensor<fp16, [1, 77, 5120]> input_175_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16, x = input_173_cast)[name = tensor<string, []>("input_175_cast")];
            tensor<string, []> input_177_mode_0 = const()[name = tensor<string, []>("input_177_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_177_cast = gelu(mode = input_177_mode_0, x = input_175_cast)[name = tensor<string, []>("input_177_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(546498816)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559606080)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_65_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16, x = input_177_cast)[name = tensor<string, []>("hidden_states_65_cast")];
            tensor<fp16, [1, 77, 1280]> input_179_cast = add(x = input_171_cast, y = hidden_states_65_cast)[name = tensor<string, []>("input_179_cast")];
            tensor<int32, [1]> hidden_states_67_axes_0 = const()[name = tensor<string, []>("hidden_states_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559608704)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559611328)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_67_cast = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_179_cast)[name = tensor<string, []>("hidden_states_67_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559613952)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(562890816)))];
            tensor<fp16, [1, 77, 1280]> var_1087_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16, x = hidden_states_67_cast)[name = tensor<string, []>("op_1087_cast")];
            tensor<fp16, []> var_1088_to_fp16 = const()[name = tensor<string, []>("op_1088_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_71_cast = mul(x = var_1087_cast, y = var_1088_to_fp16)[name = tensor<string, []>("tensor_71_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(562893440)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(566170304)))];
            tensor<fp16, [1, 77, 1280]> tensor_67_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16, x = hidden_states_67_cast)[name = tensor<string, []>("tensor_67_cast")];
            tensor<int32, [4]> var_1093 = const()[name = tensor<string, []>("op_1093"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1094_cast = reshape(shape = var_1093, x = tensor_67_cast)[name = tensor<string, []>("op_1094_cast")];
            tensor<int32, [4]> var_1095_perm_0 = const()[name = tensor<string, []>("op_1095_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(566172928)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569449792)))];
            tensor<fp16, [1, 77, 1280]> tensor_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16, x = hidden_states_67_cast)[name = tensor<string, []>("tensor_69_cast")];
            tensor<int32, [4]> var_1100 = const()[name = tensor<string, []>("op_1100"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1101_cast = reshape(shape = var_1100, x = tensor_69_cast)[name = tensor<string, []>("op_1101_cast")];
            tensor<int32, [4]> var_1102_perm_0 = const()[name = tensor<string, []>("op_1102_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1109 = const()[name = tensor<string, []>("op_1109"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1110_cast = reshape(shape = var_1109, x = tensor_71_cast)[name = tensor<string, []>("op_1110_cast")];
            tensor<int32, [4]> var_1111_perm_0 = const()[name = tensor<string, []>("op_1111_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1113 = const()[name = tensor<string, []>("op_1113"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_103 = transpose(perm = var_1111_perm_0, x = var_1110_cast)[name = tensor<string, []>("transpose_103")];
            tensor<fp16, [20, 77, 64]> query_states_23_cast = reshape(shape = var_1113, x = transpose_103)[name = tensor<string, []>("query_states_23_cast")];
            tensor<int32, [3]> var_1115 = const()[name = tensor<string, []>("op_1115"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_105 = transpose(perm = var_1095_perm_0, x = var_1094_cast)[name = tensor<string, []>("transpose_105")];
            tensor<fp16, [20, 77, 64]> key_states_47_cast = reshape(shape = var_1115, x = transpose_105)[name = tensor<string, []>("key_states_47_cast")];
            tensor<int32, [3]> var_1117 = const()[name = tensor<string, []>("op_1117"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_104 = transpose(perm = var_1102_perm_0, x = var_1101_cast)[name = tensor<string, []>("transpose_104")];
            tensor<fp16, [20, 77, 64]> value_states_47_cast = reshape(shape = var_1117, x = transpose_104)[name = tensor<string, []>("value_states_47_cast")];
            tensor<int32, [3]> var_1120_perm_0 = const()[name = tensor<string, []>("op_1120_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_67_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_67_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_67_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_67_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_102 = transpose(perm = var_1120_perm_0, x = key_states_47_cast)[name = tensor<string, []>("transpose_102")];
            tensor<fp16, [20, 77, 77]> attn_weights_67_cast = matmul(transpose_x = attn_weights_67_transpose_x_0, transpose_y = attn_weights_67_transpose_y_0, x = query_states_23_cast, y = transpose_102)[name = tensor<string, []>("attn_weights_67_cast")];
            tensor<int32, [4]> var_1122 = const()[name = tensor<string, []>("op_1122"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1123_cast = reshape(shape = var_1122, x = attn_weights_67_cast)[name = tensor<string, []>("op_1123_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_69_cast = add(x = var_1123_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_69_cast")];
            tensor<int32, [3]> var_1128 = const()[name = tensor<string, []>("op_1128"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_181_cast = reshape(shape = var_1128, x = attn_weights_69_cast)[name = tensor<string, []>("input_181_cast")];
            tensor<fp16, [20, 77, 77]> input_183_cast = softmax(axis = var_5, x = input_181_cast)[name = tensor<string, []>("input_183_cast")];
            tensor<bool, []> attn_output_67_transpose_x_0 = const()[name = tensor<string, []>("attn_output_67_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_67_transpose_y_0 = const()[name = tensor<string, []>("attn_output_67_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_67_cast = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183_cast, y = value_states_47_cast)[name = tensor<string, []>("attn_output_67_cast")];
            tensor<int32, [4]> var_1133 = const()[name = tensor<string, []>("op_1133"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_69_cast = reshape(shape = var_1133, x = attn_output_67_cast)[name = tensor<string, []>("attn_output_69_cast")];
            tensor<int32, [4]> attn_output_71_perm_0 = const()[name = tensor<string, []>("attn_output_71_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1136 = const()[name = tensor<string, []>("op_1136"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_101 = transpose(perm = attn_output_71_perm_0, x = attn_output_69_cast)[name = tensor<string, []>("transpose_101")];
            tensor<fp16, [1, 77, 1280]> input_185_cast = reshape(shape = var_1136, x = transpose_101)[name = tensor<string, []>("input_185_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569452416)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572729280)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16, x = input_185_cast)[name = tensor<string, []>("hidden_states_69_cast")];
            tensor<fp16, [1, 77, 1280]> input_187_cast = add(x = input_179_cast, y = hidden_states_69_cast)[name = tensor<string, []>("input_187_cast")];
            tensor<int32, [1]> input_189_axes_0 = const()[name = tensor<string, []>("input_189_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572731904)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572734528)))];
            tensor<fp16, [1, 77, 1280]> input_189_cast = layer_norm(axes = input_189_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_187_cast)[name = tensor<string, []>("input_189_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572737152)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(585844416)))];
            tensor<fp16, [1, 77, 5120]> input_191_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16, x = input_189_cast)[name = tensor<string, []>("input_191_cast")];
            tensor<string, []> input_193_mode_0 = const()[name = tensor<string, []>("input_193_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_193_cast = gelu(mode = input_193_mode_0, x = input_191_cast)[name = tensor<string, []>("input_193_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(585854720)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598961984)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_71_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16, x = input_193_cast)[name = tensor<string, []>("hidden_states_71_cast")];
            tensor<fp16, [1, 77, 1280]> input_195_cast = add(x = input_187_cast, y = hidden_states_71_cast)[name = tensor<string, []>("input_195_cast")];
            tensor<int32, [1]> hidden_states_73_axes_0 = const()[name = tensor<string, []>("hidden_states_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598964608)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598967232)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_73_cast = layer_norm(axes = hidden_states_73_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16, x = input_195_cast)[name = tensor<string, []>("hidden_states_73_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598969856)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(602246720)))];
            tensor<fp16, [1, 77, 1280]> var_1174_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16, x = hidden_states_73_cast)[name = tensor<string, []>("op_1174_cast")];
            tensor<fp16, []> var_1175_to_fp16 = const()[name = tensor<string, []>("op_1175_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_77_cast = mul(x = var_1174_cast, y = var_1175_to_fp16)[name = tensor<string, []>("tensor_77_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(602249344)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(605526208)))];
            tensor<fp16, [1, 77, 1280]> tensor_73_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16, x = hidden_states_73_cast)[name = tensor<string, []>("tensor_73_cast")];
            tensor<int32, [4]> var_1180 = const()[name = tensor<string, []>("op_1180"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1181_cast = reshape(shape = var_1180, x = tensor_73_cast)[name = tensor<string, []>("op_1181_cast")];
            tensor<int32, [4]> var_1182_perm_0 = const()[name = tensor<string, []>("op_1182_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(605528832)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(608805696)))];
            tensor<fp16, [1, 77, 1280]> tensor_75_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16, x = hidden_states_73_cast)[name = tensor<string, []>("tensor_75_cast")];
            tensor<int32, [4]> var_1187 = const()[name = tensor<string, []>("op_1187"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1188_cast = reshape(shape = var_1187, x = tensor_75_cast)[name = tensor<string, []>("op_1188_cast")];
            tensor<int32, [4]> var_1189_perm_0 = const()[name = tensor<string, []>("op_1189_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1196 = const()[name = tensor<string, []>("op_1196"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1197_cast = reshape(shape = var_1196, x = tensor_77_cast)[name = tensor<string, []>("op_1197_cast")];
            tensor<int32, [4]> var_1198_perm_0 = const()[name = tensor<string, []>("op_1198_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1200 = const()[name = tensor<string, []>("op_1200"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_98 = transpose(perm = var_1198_perm_0, x = var_1197_cast)[name = tensor<string, []>("transpose_98")];
            tensor<fp16, [20, 77, 64]> query_states_25_cast = reshape(shape = var_1200, x = transpose_98)[name = tensor<string, []>("query_states_25_cast")];
            tensor<int32, [3]> var_1202 = const()[name = tensor<string, []>("op_1202"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_100 = transpose(perm = var_1182_perm_0, x = var_1181_cast)[name = tensor<string, []>("transpose_100")];
            tensor<fp16, [20, 77, 64]> key_states_51_cast = reshape(shape = var_1202, x = transpose_100)[name = tensor<string, []>("key_states_51_cast")];
            tensor<int32, [3]> var_1204 = const()[name = tensor<string, []>("op_1204"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_99 = transpose(perm = var_1189_perm_0, x = var_1188_cast)[name = tensor<string, []>("transpose_99")];
            tensor<fp16, [20, 77, 64]> value_states_51_cast = reshape(shape = var_1204, x = transpose_99)[name = tensor<string, []>("value_states_51_cast")];
            tensor<int32, [3]> var_1207_perm_0 = const()[name = tensor<string, []>("op_1207_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_73_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_73_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_73_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_73_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_97 = transpose(perm = var_1207_perm_0, x = key_states_51_cast)[name = tensor<string, []>("transpose_97")];
            tensor<fp16, [20, 77, 77]> attn_weights_73_cast = matmul(transpose_x = attn_weights_73_transpose_x_0, transpose_y = attn_weights_73_transpose_y_0, x = query_states_25_cast, y = transpose_97)[name = tensor<string, []>("attn_weights_73_cast")];
            tensor<int32, [4]> var_1209 = const()[name = tensor<string, []>("op_1209"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1210_cast = reshape(shape = var_1209, x = attn_weights_73_cast)[name = tensor<string, []>("op_1210_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_75_cast = add(x = var_1210_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_75_cast")];
            tensor<int32, [3]> var_1215 = const()[name = tensor<string, []>("op_1215"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_197_cast = reshape(shape = var_1215, x = attn_weights_75_cast)[name = tensor<string, []>("input_197_cast")];
            tensor<fp16, [20, 77, 77]> input_199_cast = softmax(axis = var_5, x = input_197_cast)[name = tensor<string, []>("input_199_cast")];
            tensor<bool, []> attn_output_73_transpose_x_0 = const()[name = tensor<string, []>("attn_output_73_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_73_transpose_y_0 = const()[name = tensor<string, []>("attn_output_73_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_73_cast = matmul(transpose_x = attn_output_73_transpose_x_0, transpose_y = attn_output_73_transpose_y_0, x = input_199_cast, y = value_states_51_cast)[name = tensor<string, []>("attn_output_73_cast")];
            tensor<int32, [4]> var_1220 = const()[name = tensor<string, []>("op_1220"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_75_cast = reshape(shape = var_1220, x = attn_output_73_cast)[name = tensor<string, []>("attn_output_75_cast")];
            tensor<int32, [4]> attn_output_77_perm_0 = const()[name = tensor<string, []>("attn_output_77_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1223 = const()[name = tensor<string, []>("op_1223"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_96 = transpose(perm = attn_output_77_perm_0, x = attn_output_75_cast)[name = tensor<string, []>("transpose_96")];
            tensor<fp16, [1, 77, 1280]> input_201_cast = reshape(shape = var_1223, x = transpose_96)[name = tensor<string, []>("input_201_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(608808320)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612085184)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_75_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16, x = input_201_cast)[name = tensor<string, []>("hidden_states_75_cast")];
            tensor<fp16, [1, 77, 1280]> input_203_cast = add(x = input_195_cast, y = hidden_states_75_cast)[name = tensor<string, []>("input_203_cast")];
            tensor<int32, [1]> input_205_axes_0 = const()[name = tensor<string, []>("input_205_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612087808)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612090432)))];
            tensor<fp16, [1, 77, 1280]> input_205_cast = layer_norm(axes = input_205_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16, x = input_203_cast)[name = tensor<string, []>("input_205_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612093056)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(625200320)))];
            tensor<fp16, [1, 77, 5120]> input_207_cast = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16, x = input_205_cast)[name = tensor<string, []>("input_207_cast")];
            tensor<string, []> input_209_mode_0 = const()[name = tensor<string, []>("input_209_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_209_cast = gelu(mode = input_209_mode_0, x = input_207_cast)[name = tensor<string, []>("input_209_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(625210624)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638317888)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_77_cast = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16, x = input_209_cast)[name = tensor<string, []>("hidden_states_77_cast")];
            tensor<fp16, [1, 77, 1280]> input_211_cast = add(x = input_203_cast, y = hidden_states_77_cast)[name = tensor<string, []>("input_211_cast")];
            tensor<int32, [1]> hidden_states_79_axes_0 = const()[name = tensor<string, []>("hidden_states_79_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638320512)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638323136)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_79_cast = layer_norm(axes = hidden_states_79_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16, x = input_211_cast)[name = tensor<string, []>("hidden_states_79_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638325760)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(641602624)))];
            tensor<fp16, [1, 77, 1280]> var_1261_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16, x = hidden_states_79_cast)[name = tensor<string, []>("op_1261_cast")];
            tensor<fp16, []> var_1262_to_fp16 = const()[name = tensor<string, []>("op_1262_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_83_cast = mul(x = var_1261_cast, y = var_1262_to_fp16)[name = tensor<string, []>("tensor_83_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(641605248)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(644882112)))];
            tensor<fp16, [1, 77, 1280]> tensor_79_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16, x = hidden_states_79_cast)[name = tensor<string, []>("tensor_79_cast")];
            tensor<int32, [4]> var_1267 = const()[name = tensor<string, []>("op_1267"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1268_cast = reshape(shape = var_1267, x = tensor_79_cast)[name = tensor<string, []>("op_1268_cast")];
            tensor<int32, [4]> var_1269_perm_0 = const()[name = tensor<string, []>("op_1269_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(644884736)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(648161600)))];
            tensor<fp16, [1, 77, 1280]> tensor_81_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16, x = hidden_states_79_cast)[name = tensor<string, []>("tensor_81_cast")];
            tensor<int32, [4]> var_1274 = const()[name = tensor<string, []>("op_1274"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1275_cast = reshape(shape = var_1274, x = tensor_81_cast)[name = tensor<string, []>("op_1275_cast")];
            tensor<int32, [4]> var_1276_perm_0 = const()[name = tensor<string, []>("op_1276_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1283 = const()[name = tensor<string, []>("op_1283"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1284_cast = reshape(shape = var_1283, x = tensor_83_cast)[name = tensor<string, []>("op_1284_cast")];
            tensor<int32, [4]> var_1285_perm_0 = const()[name = tensor<string, []>("op_1285_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1287 = const()[name = tensor<string, []>("op_1287"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_93 = transpose(perm = var_1285_perm_0, x = var_1284_cast)[name = tensor<string, []>("transpose_93")];
            tensor<fp16, [20, 77, 64]> query_states_27_cast = reshape(shape = var_1287, x = transpose_93)[name = tensor<string, []>("query_states_27_cast")];
            tensor<int32, [3]> var_1289 = const()[name = tensor<string, []>("op_1289"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_95 = transpose(perm = var_1269_perm_0, x = var_1268_cast)[name = tensor<string, []>("transpose_95")];
            tensor<fp16, [20, 77, 64]> key_states_55_cast = reshape(shape = var_1289, x = transpose_95)[name = tensor<string, []>("key_states_55_cast")];
            tensor<int32, [3]> var_1291 = const()[name = tensor<string, []>("op_1291"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_94 = transpose(perm = var_1276_perm_0, x = var_1275_cast)[name = tensor<string, []>("transpose_94")];
            tensor<fp16, [20, 77, 64]> value_states_55_cast = reshape(shape = var_1291, x = transpose_94)[name = tensor<string, []>("value_states_55_cast")];
            tensor<int32, [3]> var_1294_perm_0 = const()[name = tensor<string, []>("op_1294_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_79_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_79_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_79_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_79_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_92 = transpose(perm = var_1294_perm_0, x = key_states_55_cast)[name = tensor<string, []>("transpose_92")];
            tensor<fp16, [20, 77, 77]> attn_weights_79_cast = matmul(transpose_x = attn_weights_79_transpose_x_0, transpose_y = attn_weights_79_transpose_y_0, x = query_states_27_cast, y = transpose_92)[name = tensor<string, []>("attn_weights_79_cast")];
            tensor<int32, [4]> var_1296 = const()[name = tensor<string, []>("op_1296"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1297_cast = reshape(shape = var_1296, x = attn_weights_79_cast)[name = tensor<string, []>("op_1297_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_81_cast = add(x = var_1297_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_81_cast")];
            tensor<int32, [3]> var_1302 = const()[name = tensor<string, []>("op_1302"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_213_cast = reshape(shape = var_1302, x = attn_weights_81_cast)[name = tensor<string, []>("input_213_cast")];
            tensor<fp16, [20, 77, 77]> input_215_cast = softmax(axis = var_5, x = input_213_cast)[name = tensor<string, []>("input_215_cast")];
            tensor<bool, []> attn_output_79_transpose_x_0 = const()[name = tensor<string, []>("attn_output_79_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_79_transpose_y_0 = const()[name = tensor<string, []>("attn_output_79_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_79_cast = matmul(transpose_x = attn_output_79_transpose_x_0, transpose_y = attn_output_79_transpose_y_0, x = input_215_cast, y = value_states_55_cast)[name = tensor<string, []>("attn_output_79_cast")];
            tensor<int32, [4]> var_1307 = const()[name = tensor<string, []>("op_1307"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_81_cast = reshape(shape = var_1307, x = attn_output_79_cast)[name = tensor<string, []>("attn_output_81_cast")];
            tensor<int32, [4]> attn_output_83_perm_0 = const()[name = tensor<string, []>("attn_output_83_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1310 = const()[name = tensor<string, []>("op_1310"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_91 = transpose(perm = attn_output_83_perm_0, x = attn_output_81_cast)[name = tensor<string, []>("transpose_91")];
            tensor<fp16, [1, 77, 1280]> input_217_cast = reshape(shape = var_1310, x = transpose_91)[name = tensor<string, []>("input_217_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(648164224)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651441088)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_81_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16, x = input_217_cast)[name = tensor<string, []>("hidden_states_81_cast")];
            tensor<fp16, [1, 77, 1280]> input_219_cast = add(x = input_211_cast, y = hidden_states_81_cast)[name = tensor<string, []>("input_219_cast")];
            tensor<int32, [1]> input_221_axes_0 = const()[name = tensor<string, []>("input_221_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651443712)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651446336)))];
            tensor<fp16, [1, 77, 1280]> input_221_cast = layer_norm(axes = input_221_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16, x = input_219_cast)[name = tensor<string, []>("input_221_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651448960)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(664556224)))];
            tensor<fp16, [1, 77, 5120]> input_223_cast = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16, x = input_221_cast)[name = tensor<string, []>("input_223_cast")];
            tensor<string, []> input_225_mode_0 = const()[name = tensor<string, []>("input_225_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_225_cast = gelu(mode = input_225_mode_0, x = input_223_cast)[name = tensor<string, []>("input_225_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(664566528)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677673792)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_83_cast = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16, x = input_225_cast)[name = tensor<string, []>("hidden_states_83_cast")];
            tensor<fp16, [1, 77, 1280]> input_227_cast = add(x = input_219_cast, y = hidden_states_83_cast)[name = tensor<string, []>("input_227_cast")];
            tensor<int32, [1]> hidden_states_85_axes_0 = const()[name = tensor<string, []>("hidden_states_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677676416)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677679040)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_85_cast = layer_norm(axes = hidden_states_85_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16, x = input_227_cast)[name = tensor<string, []>("hidden_states_85_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677681664)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(680958528)))];
            tensor<fp16, [1, 77, 1280]> var_1348_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16, x = hidden_states_85_cast)[name = tensor<string, []>("op_1348_cast")];
            tensor<fp16, []> var_1349_to_fp16 = const()[name = tensor<string, []>("op_1349_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_89_cast = mul(x = var_1348_cast, y = var_1349_to_fp16)[name = tensor<string, []>("tensor_89_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(680961152)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(684238016)))];
            tensor<fp16, [1, 77, 1280]> tensor_85_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16, x = hidden_states_85_cast)[name = tensor<string, []>("tensor_85_cast")];
            tensor<int32, [4]> var_1354 = const()[name = tensor<string, []>("op_1354"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1355_cast = reshape(shape = var_1354, x = tensor_85_cast)[name = tensor<string, []>("op_1355_cast")];
            tensor<int32, [4]> var_1356_perm_0 = const()[name = tensor<string, []>("op_1356_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(684240640)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(687517504)))];
            tensor<fp16, [1, 77, 1280]> tensor_87_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16, x = hidden_states_85_cast)[name = tensor<string, []>("tensor_87_cast")];
            tensor<int32, [4]> var_1361 = const()[name = tensor<string, []>("op_1361"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1362_cast = reshape(shape = var_1361, x = tensor_87_cast)[name = tensor<string, []>("op_1362_cast")];
            tensor<int32, [4]> var_1363_perm_0 = const()[name = tensor<string, []>("op_1363_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1370 = const()[name = tensor<string, []>("op_1370"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1371_cast = reshape(shape = var_1370, x = tensor_89_cast)[name = tensor<string, []>("op_1371_cast")];
            tensor<int32, [4]> var_1372_perm_0 = const()[name = tensor<string, []>("op_1372_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1374 = const()[name = tensor<string, []>("op_1374"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_88 = transpose(perm = var_1372_perm_0, x = var_1371_cast)[name = tensor<string, []>("transpose_88")];
            tensor<fp16, [20, 77, 64]> query_states_29_cast = reshape(shape = var_1374, x = transpose_88)[name = tensor<string, []>("query_states_29_cast")];
            tensor<int32, [3]> var_1376 = const()[name = tensor<string, []>("op_1376"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_90 = transpose(perm = var_1356_perm_0, x = var_1355_cast)[name = tensor<string, []>("transpose_90")];
            tensor<fp16, [20, 77, 64]> key_states_59_cast = reshape(shape = var_1376, x = transpose_90)[name = tensor<string, []>("key_states_59_cast")];
            tensor<int32, [3]> var_1378 = const()[name = tensor<string, []>("op_1378"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_89 = transpose(perm = var_1363_perm_0, x = var_1362_cast)[name = tensor<string, []>("transpose_89")];
            tensor<fp16, [20, 77, 64]> value_states_59_cast = reshape(shape = var_1378, x = transpose_89)[name = tensor<string, []>("value_states_59_cast")];
            tensor<int32, [3]> var_1381_perm_0 = const()[name = tensor<string, []>("op_1381_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_85_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_85_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_85_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_85_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_87 = transpose(perm = var_1381_perm_0, x = key_states_59_cast)[name = tensor<string, []>("transpose_87")];
            tensor<fp16, [20, 77, 77]> attn_weights_85_cast = matmul(transpose_x = attn_weights_85_transpose_x_0, transpose_y = attn_weights_85_transpose_y_0, x = query_states_29_cast, y = transpose_87)[name = tensor<string, []>("attn_weights_85_cast")];
            tensor<int32, [4]> var_1383 = const()[name = tensor<string, []>("op_1383"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1384_cast = reshape(shape = var_1383, x = attn_weights_85_cast)[name = tensor<string, []>("op_1384_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_87_cast = add(x = var_1384_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_87_cast")];
            tensor<int32, [3]> var_1389 = const()[name = tensor<string, []>("op_1389"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_229_cast = reshape(shape = var_1389, x = attn_weights_87_cast)[name = tensor<string, []>("input_229_cast")];
            tensor<fp16, [20, 77, 77]> input_231_cast = softmax(axis = var_5, x = input_229_cast)[name = tensor<string, []>("input_231_cast")];
            tensor<bool, []> attn_output_85_transpose_x_0 = const()[name = tensor<string, []>("attn_output_85_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_85_transpose_y_0 = const()[name = tensor<string, []>("attn_output_85_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_85_cast = matmul(transpose_x = attn_output_85_transpose_x_0, transpose_y = attn_output_85_transpose_y_0, x = input_231_cast, y = value_states_59_cast)[name = tensor<string, []>("attn_output_85_cast")];
            tensor<int32, [4]> var_1394 = const()[name = tensor<string, []>("op_1394"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_87_cast = reshape(shape = var_1394, x = attn_output_85_cast)[name = tensor<string, []>("attn_output_87_cast")];
            tensor<int32, [4]> attn_output_89_perm_0 = const()[name = tensor<string, []>("attn_output_89_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1397 = const()[name = tensor<string, []>("op_1397"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_86 = transpose(perm = attn_output_89_perm_0, x = attn_output_87_cast)[name = tensor<string, []>("transpose_86")];
            tensor<fp16, [1, 77, 1280]> input_233_cast = reshape(shape = var_1397, x = transpose_86)[name = tensor<string, []>("input_233_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(687520128)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690796992)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_87_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16, x = input_233_cast)[name = tensor<string, []>("hidden_states_87_cast")];
            tensor<fp16, [1, 77, 1280]> input_235_cast = add(x = input_227_cast, y = hidden_states_87_cast)[name = tensor<string, []>("input_235_cast")];
            tensor<int32, [1]> input_237_axes_0 = const()[name = tensor<string, []>("input_237_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690799616)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690802240)))];
            tensor<fp16, [1, 77, 1280]> input_237_cast = layer_norm(axes = input_237_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16, x = input_235_cast)[name = tensor<string, []>("input_237_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690804864)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(703912128)))];
            tensor<fp16, [1, 77, 5120]> input_239_cast = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16, x = input_237_cast)[name = tensor<string, []>("input_239_cast")];
            tensor<string, []> input_241_mode_0 = const()[name = tensor<string, []>("input_241_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_241_cast = gelu(mode = input_241_mode_0, x = input_239_cast)[name = tensor<string, []>("input_241_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(703922432)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717029696)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_89_cast = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16, x = input_241_cast)[name = tensor<string, []>("hidden_states_89_cast")];
            tensor<fp16, [1, 77, 1280]> input_243_cast = add(x = input_235_cast, y = hidden_states_89_cast)[name = tensor<string, []>("input_243_cast")];
            tensor<int32, [1]> hidden_states_91_axes_0 = const()[name = tensor<string, []>("hidden_states_91_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717032320)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717034944)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_91_cast = layer_norm(axes = hidden_states_91_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16, x = input_243_cast)[name = tensor<string, []>("hidden_states_91_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717037568)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(720314432)))];
            tensor<fp16, [1, 77, 1280]> var_1435_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16, x = hidden_states_91_cast)[name = tensor<string, []>("op_1435_cast")];
            tensor<fp16, []> var_1436_to_fp16 = const()[name = tensor<string, []>("op_1436_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_95_cast = mul(x = var_1435_cast, y = var_1436_to_fp16)[name = tensor<string, []>("tensor_95_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(720317056)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(723593920)))];
            tensor<fp16, [1, 77, 1280]> tensor_91_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16, x = hidden_states_91_cast)[name = tensor<string, []>("tensor_91_cast")];
            tensor<int32, [4]> var_1441 = const()[name = tensor<string, []>("op_1441"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1442_cast = reshape(shape = var_1441, x = tensor_91_cast)[name = tensor<string, []>("op_1442_cast")];
            tensor<int32, [4]> var_1443_perm_0 = const()[name = tensor<string, []>("op_1443_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(723596544)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726873408)))];
            tensor<fp16, [1, 77, 1280]> tensor_93_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16, x = hidden_states_91_cast)[name = tensor<string, []>("tensor_93_cast")];
            tensor<int32, [4]> var_1448 = const()[name = tensor<string, []>("op_1448"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1449_cast = reshape(shape = var_1448, x = tensor_93_cast)[name = tensor<string, []>("op_1449_cast")];
            tensor<int32, [4]> var_1450_perm_0 = const()[name = tensor<string, []>("op_1450_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1457 = const()[name = tensor<string, []>("op_1457"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1458_cast = reshape(shape = var_1457, x = tensor_95_cast)[name = tensor<string, []>("op_1458_cast")];
            tensor<int32, [4]> var_1459_perm_0 = const()[name = tensor<string, []>("op_1459_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1461 = const()[name = tensor<string, []>("op_1461"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_83 = transpose(perm = var_1459_perm_0, x = var_1458_cast)[name = tensor<string, []>("transpose_83")];
            tensor<fp16, [20, 77, 64]> query_states_31_cast = reshape(shape = var_1461, x = transpose_83)[name = tensor<string, []>("query_states_31_cast")];
            tensor<int32, [3]> var_1463 = const()[name = tensor<string, []>("op_1463"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_85 = transpose(perm = var_1443_perm_0, x = var_1442_cast)[name = tensor<string, []>("transpose_85")];
            tensor<fp16, [20, 77, 64]> key_states_63_cast = reshape(shape = var_1463, x = transpose_85)[name = tensor<string, []>("key_states_63_cast")];
            tensor<int32, [3]> var_1465 = const()[name = tensor<string, []>("op_1465"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_84 = transpose(perm = var_1450_perm_0, x = var_1449_cast)[name = tensor<string, []>("transpose_84")];
            tensor<fp16, [20, 77, 64]> value_states_63_cast = reshape(shape = var_1465, x = transpose_84)[name = tensor<string, []>("value_states_63_cast")];
            tensor<int32, [3]> var_1468_perm_0 = const()[name = tensor<string, []>("op_1468_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_91_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_91_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_91_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_91_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_82 = transpose(perm = var_1468_perm_0, x = key_states_63_cast)[name = tensor<string, []>("transpose_82")];
            tensor<fp16, [20, 77, 77]> attn_weights_91_cast = matmul(transpose_x = attn_weights_91_transpose_x_0, transpose_y = attn_weights_91_transpose_y_0, x = query_states_31_cast, y = transpose_82)[name = tensor<string, []>("attn_weights_91_cast")];
            tensor<int32, [4]> var_1470 = const()[name = tensor<string, []>("op_1470"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1471_cast = reshape(shape = var_1470, x = attn_weights_91_cast)[name = tensor<string, []>("op_1471_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_93_cast = add(x = var_1471_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_93_cast")];
            tensor<int32, [3]> var_1476 = const()[name = tensor<string, []>("op_1476"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_245_cast = reshape(shape = var_1476, x = attn_weights_93_cast)[name = tensor<string, []>("input_245_cast")];
            tensor<fp16, [20, 77, 77]> input_247_cast = softmax(axis = var_5, x = input_245_cast)[name = tensor<string, []>("input_247_cast")];
            tensor<bool, []> attn_output_91_transpose_x_0 = const()[name = tensor<string, []>("attn_output_91_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_91_transpose_y_0 = const()[name = tensor<string, []>("attn_output_91_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_91_cast = matmul(transpose_x = attn_output_91_transpose_x_0, transpose_y = attn_output_91_transpose_y_0, x = input_247_cast, y = value_states_63_cast)[name = tensor<string, []>("attn_output_91_cast")];
            tensor<int32, [4]> var_1481 = const()[name = tensor<string, []>("op_1481"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_93_cast = reshape(shape = var_1481, x = attn_output_91_cast)[name = tensor<string, []>("attn_output_93_cast")];
            tensor<int32, [4]> attn_output_95_perm_0 = const()[name = tensor<string, []>("attn_output_95_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1484 = const()[name = tensor<string, []>("op_1484"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_81 = transpose(perm = attn_output_95_perm_0, x = attn_output_93_cast)[name = tensor<string, []>("transpose_81")];
            tensor<fp16, [1, 77, 1280]> input_249_cast = reshape(shape = var_1484, x = transpose_81)[name = tensor<string, []>("input_249_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726876032)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730152896)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_93_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16, x = input_249_cast)[name = tensor<string, []>("hidden_states_93_cast")];
            tensor<fp16, [1, 77, 1280]> input_251_cast = add(x = input_243_cast, y = hidden_states_93_cast)[name = tensor<string, []>("input_251_cast")];
            tensor<int32, [1]> input_253_axes_0 = const()[name = tensor<string, []>("input_253_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730155520)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730158144)))];
            tensor<fp16, [1, 77, 1280]> input_253_cast = layer_norm(axes = input_253_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16, x = input_251_cast)[name = tensor<string, []>("input_253_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730160768)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(743268032)))];
            tensor<fp16, [1, 77, 5120]> input_255_cast = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16, x = input_253_cast)[name = tensor<string, []>("input_255_cast")];
            tensor<string, []> input_257_mode_0 = const()[name = tensor<string, []>("input_257_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_257_cast = gelu(mode = input_257_mode_0, x = input_255_cast)[name = tensor<string, []>("input_257_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(743278336)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756385600)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_95_cast = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16, x = input_257_cast)[name = tensor<string, []>("hidden_states_95_cast")];
            tensor<fp16, [1, 77, 1280]> input_259_cast = add(x = input_251_cast, y = hidden_states_95_cast)[name = tensor<string, []>("input_259_cast")];
            tensor<int32, [1]> hidden_states_97_axes_0 = const()[name = tensor<string, []>("hidden_states_97_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756388224)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756390848)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_97_cast = layer_norm(axes = hidden_states_97_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16, x = input_259_cast)[name = tensor<string, []>("hidden_states_97_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756393472)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(759670336)))];
            tensor<fp16, [1, 77, 1280]> var_1522_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16, x = hidden_states_97_cast)[name = tensor<string, []>("op_1522_cast")];
            tensor<fp16, []> var_1523_to_fp16 = const()[name = tensor<string, []>("op_1523_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_101_cast = mul(x = var_1522_cast, y = var_1523_to_fp16)[name = tensor<string, []>("tensor_101_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(759672960)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(762949824)))];
            tensor<fp16, [1, 77, 1280]> tensor_97_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16, x = hidden_states_97_cast)[name = tensor<string, []>("tensor_97_cast")];
            tensor<int32, [4]> var_1528 = const()[name = tensor<string, []>("op_1528"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1529_cast = reshape(shape = var_1528, x = tensor_97_cast)[name = tensor<string, []>("op_1529_cast")];
            tensor<int32, [4]> var_1530_perm_0 = const()[name = tensor<string, []>("op_1530_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(762952448)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766229312)))];
            tensor<fp16, [1, 77, 1280]> tensor_99_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16, x = hidden_states_97_cast)[name = tensor<string, []>("tensor_99_cast")];
            tensor<int32, [4]> var_1535 = const()[name = tensor<string, []>("op_1535"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1536_cast = reshape(shape = var_1535, x = tensor_99_cast)[name = tensor<string, []>("op_1536_cast")];
            tensor<int32, [4]> var_1537_perm_0 = const()[name = tensor<string, []>("op_1537_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1544 = const()[name = tensor<string, []>("op_1544"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1545_cast = reshape(shape = var_1544, x = tensor_101_cast)[name = tensor<string, []>("op_1545_cast")];
            tensor<int32, [4]> var_1546_perm_0 = const()[name = tensor<string, []>("op_1546_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1548 = const()[name = tensor<string, []>("op_1548"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_78 = transpose(perm = var_1546_perm_0, x = var_1545_cast)[name = tensor<string, []>("transpose_78")];
            tensor<fp16, [20, 77, 64]> query_states_33_cast = reshape(shape = var_1548, x = transpose_78)[name = tensor<string, []>("query_states_33_cast")];
            tensor<int32, [3]> var_1550 = const()[name = tensor<string, []>("op_1550"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_80 = transpose(perm = var_1530_perm_0, x = var_1529_cast)[name = tensor<string, []>("transpose_80")];
            tensor<fp16, [20, 77, 64]> key_states_67_cast = reshape(shape = var_1550, x = transpose_80)[name = tensor<string, []>("key_states_67_cast")];
            tensor<int32, [3]> var_1552 = const()[name = tensor<string, []>("op_1552"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_79 = transpose(perm = var_1537_perm_0, x = var_1536_cast)[name = tensor<string, []>("transpose_79")];
            tensor<fp16, [20, 77, 64]> value_states_67_cast = reshape(shape = var_1552, x = transpose_79)[name = tensor<string, []>("value_states_67_cast")];
            tensor<int32, [3]> var_1555_perm_0 = const()[name = tensor<string, []>("op_1555_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_97_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_97_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_97_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_97_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_77 = transpose(perm = var_1555_perm_0, x = key_states_67_cast)[name = tensor<string, []>("transpose_77")];
            tensor<fp16, [20, 77, 77]> attn_weights_97_cast = matmul(transpose_x = attn_weights_97_transpose_x_0, transpose_y = attn_weights_97_transpose_y_0, x = query_states_33_cast, y = transpose_77)[name = tensor<string, []>("attn_weights_97_cast")];
            tensor<int32, [4]> var_1557 = const()[name = tensor<string, []>("op_1557"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1558_cast = reshape(shape = var_1557, x = attn_weights_97_cast)[name = tensor<string, []>("op_1558_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_99_cast = add(x = var_1558_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_99_cast")];
            tensor<int32, [3]> var_1563 = const()[name = tensor<string, []>("op_1563"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_261_cast = reshape(shape = var_1563, x = attn_weights_99_cast)[name = tensor<string, []>("input_261_cast")];
            tensor<fp16, [20, 77, 77]> input_263_cast = softmax(axis = var_5, x = input_261_cast)[name = tensor<string, []>("input_263_cast")];
            tensor<bool, []> attn_output_97_transpose_x_0 = const()[name = tensor<string, []>("attn_output_97_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_97_transpose_y_0 = const()[name = tensor<string, []>("attn_output_97_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_97_cast = matmul(transpose_x = attn_output_97_transpose_x_0, transpose_y = attn_output_97_transpose_y_0, x = input_263_cast, y = value_states_67_cast)[name = tensor<string, []>("attn_output_97_cast")];
            tensor<int32, [4]> var_1568 = const()[name = tensor<string, []>("op_1568"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_99_cast = reshape(shape = var_1568, x = attn_output_97_cast)[name = tensor<string, []>("attn_output_99_cast")];
            tensor<int32, [4]> attn_output_101_perm_0 = const()[name = tensor<string, []>("attn_output_101_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1571 = const()[name = tensor<string, []>("op_1571"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_76 = transpose(perm = attn_output_101_perm_0, x = attn_output_99_cast)[name = tensor<string, []>("transpose_76")];
            tensor<fp16, [1, 77, 1280]> input_265_cast = reshape(shape = var_1571, x = transpose_76)[name = tensor<string, []>("input_265_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766231936)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769508800)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_99_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16, x = input_265_cast)[name = tensor<string, []>("hidden_states_99_cast")];
            tensor<fp16, [1, 77, 1280]> input_267_cast = add(x = input_259_cast, y = hidden_states_99_cast)[name = tensor<string, []>("input_267_cast")];
            tensor<int32, [1]> input_269_axes_0 = const()[name = tensor<string, []>("input_269_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769511424)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769514048)))];
            tensor<fp16, [1, 77, 1280]> input_269_cast = layer_norm(axes = input_269_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16, x = input_267_cast)[name = tensor<string, []>("input_269_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769516672)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(782623936)))];
            tensor<fp16, [1, 77, 5120]> input_271_cast = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16, x = input_269_cast)[name = tensor<string, []>("input_271_cast")];
            tensor<string, []> input_273_mode_0 = const()[name = tensor<string, []>("input_273_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_273_cast = gelu(mode = input_273_mode_0, x = input_271_cast)[name = tensor<string, []>("input_273_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(782634240)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795741504)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_101_cast = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16, x = input_273_cast)[name = tensor<string, []>("hidden_states_101_cast")];
            tensor<fp16, [1, 77, 1280]> input_275_cast = add(x = input_267_cast, y = hidden_states_101_cast)[name = tensor<string, []>("input_275_cast")];
            tensor<int32, [1]> hidden_states_103_axes_0 = const()[name = tensor<string, []>("hidden_states_103_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795744128)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795746752)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_103_cast = layer_norm(axes = hidden_states_103_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16, x = input_275_cast)[name = tensor<string, []>("hidden_states_103_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795749376)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(799026240)))];
            tensor<fp16, [1, 77, 1280]> var_1609_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16, x = hidden_states_103_cast)[name = tensor<string, []>("op_1609_cast")];
            tensor<fp16, []> var_1610_to_fp16 = const()[name = tensor<string, []>("op_1610_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_107_cast = mul(x = var_1609_cast, y = var_1610_to_fp16)[name = tensor<string, []>("tensor_107_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(799028864)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802305728)))];
            tensor<fp16, [1, 77, 1280]> tensor_103_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16, x = hidden_states_103_cast)[name = tensor<string, []>("tensor_103_cast")];
            tensor<int32, [4]> var_1615 = const()[name = tensor<string, []>("op_1615"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1616_cast = reshape(shape = var_1615, x = tensor_103_cast)[name = tensor<string, []>("op_1616_cast")];
            tensor<int32, [4]> var_1617_perm_0 = const()[name = tensor<string, []>("op_1617_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802308352)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(805585216)))];
            tensor<fp16, [1, 77, 1280]> tensor_105_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16, x = hidden_states_103_cast)[name = tensor<string, []>("tensor_105_cast")];
            tensor<int32, [4]> var_1622 = const()[name = tensor<string, []>("op_1622"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1623_cast = reshape(shape = var_1622, x = tensor_105_cast)[name = tensor<string, []>("op_1623_cast")];
            tensor<int32, [4]> var_1624_perm_0 = const()[name = tensor<string, []>("op_1624_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1631 = const()[name = tensor<string, []>("op_1631"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1632_cast = reshape(shape = var_1631, x = tensor_107_cast)[name = tensor<string, []>("op_1632_cast")];
            tensor<int32, [4]> var_1633_perm_0 = const()[name = tensor<string, []>("op_1633_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1635 = const()[name = tensor<string, []>("op_1635"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_73 = transpose(perm = var_1633_perm_0, x = var_1632_cast)[name = tensor<string, []>("transpose_73")];
            tensor<fp16, [20, 77, 64]> query_states_35_cast = reshape(shape = var_1635, x = transpose_73)[name = tensor<string, []>("query_states_35_cast")];
            tensor<int32, [3]> var_1637 = const()[name = tensor<string, []>("op_1637"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_75 = transpose(perm = var_1617_perm_0, x = var_1616_cast)[name = tensor<string, []>("transpose_75")];
            tensor<fp16, [20, 77, 64]> key_states_71_cast = reshape(shape = var_1637, x = transpose_75)[name = tensor<string, []>("key_states_71_cast")];
            tensor<int32, [3]> var_1639 = const()[name = tensor<string, []>("op_1639"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_74 = transpose(perm = var_1624_perm_0, x = var_1623_cast)[name = tensor<string, []>("transpose_74")];
            tensor<fp16, [20, 77, 64]> value_states_71_cast = reshape(shape = var_1639, x = transpose_74)[name = tensor<string, []>("value_states_71_cast")];
            tensor<int32, [3]> var_1642_perm_0 = const()[name = tensor<string, []>("op_1642_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_103_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_103_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_103_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_103_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_72 = transpose(perm = var_1642_perm_0, x = key_states_71_cast)[name = tensor<string, []>("transpose_72")];
            tensor<fp16, [20, 77, 77]> attn_weights_103_cast = matmul(transpose_x = attn_weights_103_transpose_x_0, transpose_y = attn_weights_103_transpose_y_0, x = query_states_35_cast, y = transpose_72)[name = tensor<string, []>("attn_weights_103_cast")];
            tensor<int32, [4]> var_1644 = const()[name = tensor<string, []>("op_1644"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1645_cast = reshape(shape = var_1644, x = attn_weights_103_cast)[name = tensor<string, []>("op_1645_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_105_cast = add(x = var_1645_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_105_cast")];
            tensor<int32, [3]> var_1650 = const()[name = tensor<string, []>("op_1650"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_277_cast = reshape(shape = var_1650, x = attn_weights_105_cast)[name = tensor<string, []>("input_277_cast")];
            tensor<fp16, [20, 77, 77]> input_279_cast = softmax(axis = var_5, x = input_277_cast)[name = tensor<string, []>("input_279_cast")];
            tensor<bool, []> attn_output_103_transpose_x_0 = const()[name = tensor<string, []>("attn_output_103_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_103_transpose_y_0 = const()[name = tensor<string, []>("attn_output_103_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_103_cast = matmul(transpose_x = attn_output_103_transpose_x_0, transpose_y = attn_output_103_transpose_y_0, x = input_279_cast, y = value_states_71_cast)[name = tensor<string, []>("attn_output_103_cast")];
            tensor<int32, [4]> var_1655 = const()[name = tensor<string, []>("op_1655"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_105_cast = reshape(shape = var_1655, x = attn_output_103_cast)[name = tensor<string, []>("attn_output_105_cast")];
            tensor<int32, [4]> attn_output_107_perm_0 = const()[name = tensor<string, []>("attn_output_107_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1658 = const()[name = tensor<string, []>("op_1658"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_71 = transpose(perm = attn_output_107_perm_0, x = attn_output_105_cast)[name = tensor<string, []>("transpose_71")];
            tensor<fp16, [1, 77, 1280]> input_281_cast = reshape(shape = var_1658, x = transpose_71)[name = tensor<string, []>("input_281_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(805587840)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808864704)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_105_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16, x = input_281_cast)[name = tensor<string, []>("hidden_states_105_cast")];
            tensor<fp16, [1, 77, 1280]> input_283_cast = add(x = input_275_cast, y = hidden_states_105_cast)[name = tensor<string, []>("input_283_cast")];
            tensor<int32, [1]> input_285_axes_0 = const()[name = tensor<string, []>("input_285_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808867328)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808869952)))];
            tensor<fp16, [1, 77, 1280]> input_285_cast = layer_norm(axes = input_285_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16, x = input_283_cast)[name = tensor<string, []>("input_285_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808872576)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(821979840)))];
            tensor<fp16, [1, 77, 5120]> input_287_cast = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16, x = input_285_cast)[name = tensor<string, []>("input_287_cast")];
            tensor<string, []> input_289_mode_0 = const()[name = tensor<string, []>("input_289_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_289_cast = gelu(mode = input_289_mode_0, x = input_287_cast)[name = tensor<string, []>("input_289_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(821990144)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835097408)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_107_cast = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16, x = input_289_cast)[name = tensor<string, []>("hidden_states_107_cast")];
            tensor<fp16, [1, 77, 1280]> input_291_cast = add(x = input_283_cast, y = hidden_states_107_cast)[name = tensor<string, []>("input_291_cast")];
            tensor<int32, [1]> hidden_states_109_axes_0 = const()[name = tensor<string, []>("hidden_states_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835100032)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835102656)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_109_cast = layer_norm(axes = hidden_states_109_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16, x = input_291_cast)[name = tensor<string, []>("hidden_states_109_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835105280)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(838382144)))];
            tensor<fp16, [1, 77, 1280]> var_1696_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16, x = hidden_states_109_cast)[name = tensor<string, []>("op_1696_cast")];
            tensor<fp16, []> var_1697_to_fp16 = const()[name = tensor<string, []>("op_1697_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_113_cast = mul(x = var_1696_cast, y = var_1697_to_fp16)[name = tensor<string, []>("tensor_113_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(838384768)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(841661632)))];
            tensor<fp16, [1, 77, 1280]> tensor_109_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16, x = hidden_states_109_cast)[name = tensor<string, []>("tensor_109_cast")];
            tensor<int32, [4]> var_1702 = const()[name = tensor<string, []>("op_1702"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1703_cast = reshape(shape = var_1702, x = tensor_109_cast)[name = tensor<string, []>("op_1703_cast")];
            tensor<int32, [4]> var_1704_perm_0 = const()[name = tensor<string, []>("op_1704_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(841664256)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(844941120)))];
            tensor<fp16, [1, 77, 1280]> tensor_111_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16, x = hidden_states_109_cast)[name = tensor<string, []>("tensor_111_cast")];
            tensor<int32, [4]> var_1709 = const()[name = tensor<string, []>("op_1709"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1710_cast = reshape(shape = var_1709, x = tensor_111_cast)[name = tensor<string, []>("op_1710_cast")];
            tensor<int32, [4]> var_1711_perm_0 = const()[name = tensor<string, []>("op_1711_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1718 = const()[name = tensor<string, []>("op_1718"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1719_cast = reshape(shape = var_1718, x = tensor_113_cast)[name = tensor<string, []>("op_1719_cast")];
            tensor<int32, [4]> var_1720_perm_0 = const()[name = tensor<string, []>("op_1720_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1722 = const()[name = tensor<string, []>("op_1722"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_68 = transpose(perm = var_1720_perm_0, x = var_1719_cast)[name = tensor<string, []>("transpose_68")];
            tensor<fp16, [20, 77, 64]> query_states_37_cast = reshape(shape = var_1722, x = transpose_68)[name = tensor<string, []>("query_states_37_cast")];
            tensor<int32, [3]> var_1724 = const()[name = tensor<string, []>("op_1724"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_70 = transpose(perm = var_1704_perm_0, x = var_1703_cast)[name = tensor<string, []>("transpose_70")];
            tensor<fp16, [20, 77, 64]> key_states_75_cast = reshape(shape = var_1724, x = transpose_70)[name = tensor<string, []>("key_states_75_cast")];
            tensor<int32, [3]> var_1726 = const()[name = tensor<string, []>("op_1726"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_69 = transpose(perm = var_1711_perm_0, x = var_1710_cast)[name = tensor<string, []>("transpose_69")];
            tensor<fp16, [20, 77, 64]> value_states_75_cast = reshape(shape = var_1726, x = transpose_69)[name = tensor<string, []>("value_states_75_cast")];
            tensor<int32, [3]> var_1729_perm_0 = const()[name = tensor<string, []>("op_1729_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_109_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_109_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_109_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_109_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_67 = transpose(perm = var_1729_perm_0, x = key_states_75_cast)[name = tensor<string, []>("transpose_67")];
            tensor<fp16, [20, 77, 77]> attn_weights_109_cast = matmul(transpose_x = attn_weights_109_transpose_x_0, transpose_y = attn_weights_109_transpose_y_0, x = query_states_37_cast, y = transpose_67)[name = tensor<string, []>("attn_weights_109_cast")];
            tensor<int32, [4]> var_1731 = const()[name = tensor<string, []>("op_1731"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1732_cast = reshape(shape = var_1731, x = attn_weights_109_cast)[name = tensor<string, []>("op_1732_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_111_cast = add(x = var_1732_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_111_cast")];
            tensor<int32, [3]> var_1737 = const()[name = tensor<string, []>("op_1737"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_293_cast = reshape(shape = var_1737, x = attn_weights_111_cast)[name = tensor<string, []>("input_293_cast")];
            tensor<fp16, [20, 77, 77]> input_295_cast = softmax(axis = var_5, x = input_293_cast)[name = tensor<string, []>("input_295_cast")];
            tensor<bool, []> attn_output_109_transpose_x_0 = const()[name = tensor<string, []>("attn_output_109_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_109_transpose_y_0 = const()[name = tensor<string, []>("attn_output_109_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_109_cast = matmul(transpose_x = attn_output_109_transpose_x_0, transpose_y = attn_output_109_transpose_y_0, x = input_295_cast, y = value_states_75_cast)[name = tensor<string, []>("attn_output_109_cast")];
            tensor<int32, [4]> var_1742 = const()[name = tensor<string, []>("op_1742"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_111_cast = reshape(shape = var_1742, x = attn_output_109_cast)[name = tensor<string, []>("attn_output_111_cast")];
            tensor<int32, [4]> attn_output_113_perm_0 = const()[name = tensor<string, []>("attn_output_113_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1745 = const()[name = tensor<string, []>("op_1745"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_66 = transpose(perm = attn_output_113_perm_0, x = attn_output_111_cast)[name = tensor<string, []>("transpose_66")];
            tensor<fp16, [1, 77, 1280]> input_297_cast = reshape(shape = var_1745, x = transpose_66)[name = tensor<string, []>("input_297_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(844943744)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848220608)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_111_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16, x = input_297_cast)[name = tensor<string, []>("hidden_states_111_cast")];
            tensor<fp16, [1, 77, 1280]> input_299_cast = add(x = input_291_cast, y = hidden_states_111_cast)[name = tensor<string, []>("input_299_cast")];
            tensor<int32, [1]> input_301_axes_0 = const()[name = tensor<string, []>("input_301_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848223232)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848225856)))];
            tensor<fp16, [1, 77, 1280]> input_301_cast = layer_norm(axes = input_301_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16, x = input_299_cast)[name = tensor<string, []>("input_301_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848228480)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(861335744)))];
            tensor<fp16, [1, 77, 5120]> input_303_cast = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16, x = input_301_cast)[name = tensor<string, []>("input_303_cast")];
            tensor<string, []> input_305_mode_0 = const()[name = tensor<string, []>("input_305_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_305_cast = gelu(mode = input_305_mode_0, x = input_303_cast)[name = tensor<string, []>("input_305_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(861346048)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874453312)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_113_cast = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16, x = input_305_cast)[name = tensor<string, []>("hidden_states_113_cast")];
            tensor<fp16, [1, 77, 1280]> input_307_cast = add(x = input_299_cast, y = hidden_states_113_cast)[name = tensor<string, []>("input_307_cast")];
            tensor<int32, [1]> hidden_states_115_axes_0 = const()[name = tensor<string, []>("hidden_states_115_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874455936)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874458560)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_115_cast = layer_norm(axes = hidden_states_115_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16, x = input_307_cast)[name = tensor<string, []>("hidden_states_115_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874461184)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(877738048)))];
            tensor<fp16, [1, 77, 1280]> var_1783_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16, x = hidden_states_115_cast)[name = tensor<string, []>("op_1783_cast")];
            tensor<fp16, []> var_1784_to_fp16 = const()[name = tensor<string, []>("op_1784_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_119_cast = mul(x = var_1783_cast, y = var_1784_to_fp16)[name = tensor<string, []>("tensor_119_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(877740672)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(881017536)))];
            tensor<fp16, [1, 77, 1280]> tensor_115_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16, x = hidden_states_115_cast)[name = tensor<string, []>("tensor_115_cast")];
            tensor<int32, [4]> var_1789 = const()[name = tensor<string, []>("op_1789"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1790_cast = reshape(shape = var_1789, x = tensor_115_cast)[name = tensor<string, []>("op_1790_cast")];
            tensor<int32, [4]> var_1791_perm_0 = const()[name = tensor<string, []>("op_1791_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(881020160)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(884297024)))];
            tensor<fp16, [1, 77, 1280]> tensor_117_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16, x = hidden_states_115_cast)[name = tensor<string, []>("tensor_117_cast")];
            tensor<int32, [4]> var_1796 = const()[name = tensor<string, []>("op_1796"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1797_cast = reshape(shape = var_1796, x = tensor_117_cast)[name = tensor<string, []>("op_1797_cast")];
            tensor<int32, [4]> var_1798_perm_0 = const()[name = tensor<string, []>("op_1798_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1805 = const()[name = tensor<string, []>("op_1805"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1806_cast = reshape(shape = var_1805, x = tensor_119_cast)[name = tensor<string, []>("op_1806_cast")];
            tensor<int32, [4]> var_1807_perm_0 = const()[name = tensor<string, []>("op_1807_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1809 = const()[name = tensor<string, []>("op_1809"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_63 = transpose(perm = var_1807_perm_0, x = var_1806_cast)[name = tensor<string, []>("transpose_63")];
            tensor<fp16, [20, 77, 64]> query_states_39_cast = reshape(shape = var_1809, x = transpose_63)[name = tensor<string, []>("query_states_39_cast")];
            tensor<int32, [3]> var_1811 = const()[name = tensor<string, []>("op_1811"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_65 = transpose(perm = var_1791_perm_0, x = var_1790_cast)[name = tensor<string, []>("transpose_65")];
            tensor<fp16, [20, 77, 64]> key_states_79_cast = reshape(shape = var_1811, x = transpose_65)[name = tensor<string, []>("key_states_79_cast")];
            tensor<int32, [3]> var_1813 = const()[name = tensor<string, []>("op_1813"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_64 = transpose(perm = var_1798_perm_0, x = var_1797_cast)[name = tensor<string, []>("transpose_64")];
            tensor<fp16, [20, 77, 64]> value_states_79_cast = reshape(shape = var_1813, x = transpose_64)[name = tensor<string, []>("value_states_79_cast")];
            tensor<int32, [3]> var_1816_perm_0 = const()[name = tensor<string, []>("op_1816_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_115_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_115_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_115_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_115_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_62 = transpose(perm = var_1816_perm_0, x = key_states_79_cast)[name = tensor<string, []>("transpose_62")];
            tensor<fp16, [20, 77, 77]> attn_weights_115_cast = matmul(transpose_x = attn_weights_115_transpose_x_0, transpose_y = attn_weights_115_transpose_y_0, x = query_states_39_cast, y = transpose_62)[name = tensor<string, []>("attn_weights_115_cast")];
            tensor<int32, [4]> var_1818 = const()[name = tensor<string, []>("op_1818"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1819_cast = reshape(shape = var_1818, x = attn_weights_115_cast)[name = tensor<string, []>("op_1819_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_117_cast = add(x = var_1819_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_117_cast")];
            tensor<int32, [3]> var_1824 = const()[name = tensor<string, []>("op_1824"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_309_cast = reshape(shape = var_1824, x = attn_weights_117_cast)[name = tensor<string, []>("input_309_cast")];
            tensor<fp16, [20, 77, 77]> input_311_cast = softmax(axis = var_5, x = input_309_cast)[name = tensor<string, []>("input_311_cast")];
            tensor<bool, []> attn_output_115_transpose_x_0 = const()[name = tensor<string, []>("attn_output_115_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_115_transpose_y_0 = const()[name = tensor<string, []>("attn_output_115_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_115_cast = matmul(transpose_x = attn_output_115_transpose_x_0, transpose_y = attn_output_115_transpose_y_0, x = input_311_cast, y = value_states_79_cast)[name = tensor<string, []>("attn_output_115_cast")];
            tensor<int32, [4]> var_1829 = const()[name = tensor<string, []>("op_1829"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_117_cast = reshape(shape = var_1829, x = attn_output_115_cast)[name = tensor<string, []>("attn_output_117_cast")];
            tensor<int32, [4]> attn_output_119_perm_0 = const()[name = tensor<string, []>("attn_output_119_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1832 = const()[name = tensor<string, []>("op_1832"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_61 = transpose(perm = attn_output_119_perm_0, x = attn_output_117_cast)[name = tensor<string, []>("transpose_61")];
            tensor<fp16, [1, 77, 1280]> input_313_cast = reshape(shape = var_1832, x = transpose_61)[name = tensor<string, []>("input_313_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(884299648)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887576512)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_117_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16, x = input_313_cast)[name = tensor<string, []>("hidden_states_117_cast")];
            tensor<fp16, [1, 77, 1280]> input_315_cast = add(x = input_307_cast, y = hidden_states_117_cast)[name = tensor<string, []>("input_315_cast")];
            tensor<int32, [1]> input_317_axes_0 = const()[name = tensor<string, []>("input_317_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887579136)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887581760)))];
            tensor<fp16, [1, 77, 1280]> input_317_cast = layer_norm(axes = input_317_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16, x = input_315_cast)[name = tensor<string, []>("input_317_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887584384)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900691648)))];
            tensor<fp16, [1, 77, 5120]> input_319_cast = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16, x = input_317_cast)[name = tensor<string, []>("input_319_cast")];
            tensor<string, []> input_321_mode_0 = const()[name = tensor<string, []>("input_321_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_321_cast = gelu(mode = input_321_mode_0, x = input_319_cast)[name = tensor<string, []>("input_321_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900701952)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913809216)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_119_cast = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16, x = input_321_cast)[name = tensor<string, []>("hidden_states_119_cast")];
            tensor<fp16, [1, 77, 1280]> input_323_cast = add(x = input_315_cast, y = hidden_states_119_cast)[name = tensor<string, []>("input_323_cast")];
            tensor<int32, [1]> hidden_states_121_axes_0 = const()[name = tensor<string, []>("hidden_states_121_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913811840)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913814464)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_121_cast = layer_norm(axes = hidden_states_121_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16, x = input_323_cast)[name = tensor<string, []>("hidden_states_121_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913817088)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(917093952)))];
            tensor<fp16, [1, 77, 1280]> var_1870_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16, x = hidden_states_121_cast)[name = tensor<string, []>("op_1870_cast")];
            tensor<fp16, []> var_1871_to_fp16 = const()[name = tensor<string, []>("op_1871_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_125_cast = mul(x = var_1870_cast, y = var_1871_to_fp16)[name = tensor<string, []>("tensor_125_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(917096576)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(920373440)))];
            tensor<fp16, [1, 77, 1280]> tensor_121_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16, x = hidden_states_121_cast)[name = tensor<string, []>("tensor_121_cast")];
            tensor<int32, [4]> var_1876 = const()[name = tensor<string, []>("op_1876"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1877_cast = reshape(shape = var_1876, x = tensor_121_cast)[name = tensor<string, []>("op_1877_cast")];
            tensor<int32, [4]> var_1878_perm_0 = const()[name = tensor<string, []>("op_1878_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(920376064)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(923652928)))];
            tensor<fp16, [1, 77, 1280]> tensor_123_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16, x = hidden_states_121_cast)[name = tensor<string, []>("tensor_123_cast")];
            tensor<int32, [4]> var_1883 = const()[name = tensor<string, []>("op_1883"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1884_cast = reshape(shape = var_1883, x = tensor_123_cast)[name = tensor<string, []>("op_1884_cast")];
            tensor<int32, [4]> var_1885_perm_0 = const()[name = tensor<string, []>("op_1885_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1892 = const()[name = tensor<string, []>("op_1892"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1893_cast = reshape(shape = var_1892, x = tensor_125_cast)[name = tensor<string, []>("op_1893_cast")];
            tensor<int32, [4]> var_1894_perm_0 = const()[name = tensor<string, []>("op_1894_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1896 = const()[name = tensor<string, []>("op_1896"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_58 = transpose(perm = var_1894_perm_0, x = var_1893_cast)[name = tensor<string, []>("transpose_58")];
            tensor<fp16, [20, 77, 64]> query_states_41_cast = reshape(shape = var_1896, x = transpose_58)[name = tensor<string, []>("query_states_41_cast")];
            tensor<int32, [3]> var_1898 = const()[name = tensor<string, []>("op_1898"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_60 = transpose(perm = var_1878_perm_0, x = var_1877_cast)[name = tensor<string, []>("transpose_60")];
            tensor<fp16, [20, 77, 64]> key_states_83_cast = reshape(shape = var_1898, x = transpose_60)[name = tensor<string, []>("key_states_83_cast")];
            tensor<int32, [3]> var_1900 = const()[name = tensor<string, []>("op_1900"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_59 = transpose(perm = var_1885_perm_0, x = var_1884_cast)[name = tensor<string, []>("transpose_59")];
            tensor<fp16, [20, 77, 64]> value_states_83_cast = reshape(shape = var_1900, x = transpose_59)[name = tensor<string, []>("value_states_83_cast")];
            tensor<int32, [3]> var_1903_perm_0 = const()[name = tensor<string, []>("op_1903_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_121_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_121_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_121_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_121_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_57 = transpose(perm = var_1903_perm_0, x = key_states_83_cast)[name = tensor<string, []>("transpose_57")];
            tensor<fp16, [20, 77, 77]> attn_weights_121_cast = matmul(transpose_x = attn_weights_121_transpose_x_0, transpose_y = attn_weights_121_transpose_y_0, x = query_states_41_cast, y = transpose_57)[name = tensor<string, []>("attn_weights_121_cast")];
            tensor<int32, [4]> var_1905 = const()[name = tensor<string, []>("op_1905"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1906_cast = reshape(shape = var_1905, x = attn_weights_121_cast)[name = tensor<string, []>("op_1906_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_123_cast = add(x = var_1906_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_123_cast")];
            tensor<int32, [3]> var_1911 = const()[name = tensor<string, []>("op_1911"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_325_cast = reshape(shape = var_1911, x = attn_weights_123_cast)[name = tensor<string, []>("input_325_cast")];
            tensor<fp16, [20, 77, 77]> input_327_cast = softmax(axis = var_5, x = input_325_cast)[name = tensor<string, []>("input_327_cast")];
            tensor<bool, []> attn_output_121_transpose_x_0 = const()[name = tensor<string, []>("attn_output_121_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_121_transpose_y_0 = const()[name = tensor<string, []>("attn_output_121_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_121_cast = matmul(transpose_x = attn_output_121_transpose_x_0, transpose_y = attn_output_121_transpose_y_0, x = input_327_cast, y = value_states_83_cast)[name = tensor<string, []>("attn_output_121_cast")];
            tensor<int32, [4]> var_1916 = const()[name = tensor<string, []>("op_1916"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_123_cast = reshape(shape = var_1916, x = attn_output_121_cast)[name = tensor<string, []>("attn_output_123_cast")];
            tensor<int32, [4]> attn_output_125_perm_0 = const()[name = tensor<string, []>("attn_output_125_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1919 = const()[name = tensor<string, []>("op_1919"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_56 = transpose(perm = attn_output_125_perm_0, x = attn_output_123_cast)[name = tensor<string, []>("transpose_56")];
            tensor<fp16, [1, 77, 1280]> input_329_cast = reshape(shape = var_1919, x = transpose_56)[name = tensor<string, []>("input_329_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(923655552)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926932416)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_123_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16, x = input_329_cast)[name = tensor<string, []>("hidden_states_123_cast")];
            tensor<fp16, [1, 77, 1280]> input_331_cast = add(x = input_323_cast, y = hidden_states_123_cast)[name = tensor<string, []>("input_331_cast")];
            tensor<int32, [1]> input_333_axes_0 = const()[name = tensor<string, []>("input_333_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926935040)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926937664)))];
            tensor<fp16, [1, 77, 1280]> input_333_cast = layer_norm(axes = input_333_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16, x = input_331_cast)[name = tensor<string, []>("input_333_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926940288)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(940047552)))];
            tensor<fp16, [1, 77, 5120]> input_335_cast = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16, x = input_333_cast)[name = tensor<string, []>("input_335_cast")];
            tensor<string, []> input_337_mode_0 = const()[name = tensor<string, []>("input_337_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_337_cast = gelu(mode = input_337_mode_0, x = input_335_cast)[name = tensor<string, []>("input_337_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(940057856)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953165120)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_125_cast = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16, x = input_337_cast)[name = tensor<string, []>("hidden_states_125_cast")];
            tensor<fp16, [1, 77, 1280]> input_339_cast = add(x = input_331_cast, y = hidden_states_125_cast)[name = tensor<string, []>("input_339_cast")];
            tensor<int32, [1]> hidden_states_127_axes_0 = const()[name = tensor<string, []>("hidden_states_127_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953167744)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953170368)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_127_cast = layer_norm(axes = hidden_states_127_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16, x = input_339_cast)[name = tensor<string, []>("hidden_states_127_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953172992)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(956449856)))];
            tensor<fp16, [1, 77, 1280]> var_1957_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16, x = hidden_states_127_cast)[name = tensor<string, []>("op_1957_cast")];
            tensor<fp16, []> var_1958_to_fp16 = const()[name = tensor<string, []>("op_1958_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_131_cast = mul(x = var_1957_cast, y = var_1958_to_fp16)[name = tensor<string, []>("tensor_131_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(956452480)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(959729344)))];
            tensor<fp16, [1, 77, 1280]> tensor_127_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16, x = hidden_states_127_cast)[name = tensor<string, []>("tensor_127_cast")];
            tensor<int32, [4]> var_1963 = const()[name = tensor<string, []>("op_1963"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1964_cast = reshape(shape = var_1963, x = tensor_127_cast)[name = tensor<string, []>("op_1964_cast")];
            tensor<int32, [4]> var_1965_perm_0 = const()[name = tensor<string, []>("op_1965_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(959731968)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(963008832)))];
            tensor<fp16, [1, 77, 1280]> tensor_129_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16, x = hidden_states_127_cast)[name = tensor<string, []>("tensor_129_cast")];
            tensor<int32, [4]> var_1970 = const()[name = tensor<string, []>("op_1970"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1971_cast = reshape(shape = var_1970, x = tensor_129_cast)[name = tensor<string, []>("op_1971_cast")];
            tensor<int32, [4]> var_1972_perm_0 = const()[name = tensor<string, []>("op_1972_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1979 = const()[name = tensor<string, []>("op_1979"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1980_cast = reshape(shape = var_1979, x = tensor_131_cast)[name = tensor<string, []>("op_1980_cast")];
            tensor<int32, [4]> var_1981_perm_0 = const()[name = tensor<string, []>("op_1981_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1983 = const()[name = tensor<string, []>("op_1983"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_53 = transpose(perm = var_1981_perm_0, x = var_1980_cast)[name = tensor<string, []>("transpose_53")];
            tensor<fp16, [20, 77, 64]> query_states_43_cast = reshape(shape = var_1983, x = transpose_53)[name = tensor<string, []>("query_states_43_cast")];
            tensor<int32, [3]> var_1985 = const()[name = tensor<string, []>("op_1985"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_55 = transpose(perm = var_1965_perm_0, x = var_1964_cast)[name = tensor<string, []>("transpose_55")];
            tensor<fp16, [20, 77, 64]> key_states_87_cast = reshape(shape = var_1985, x = transpose_55)[name = tensor<string, []>("key_states_87_cast")];
            tensor<int32, [3]> var_1987 = const()[name = tensor<string, []>("op_1987"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_54 = transpose(perm = var_1972_perm_0, x = var_1971_cast)[name = tensor<string, []>("transpose_54")];
            tensor<fp16, [20, 77, 64]> value_states_87_cast = reshape(shape = var_1987, x = transpose_54)[name = tensor<string, []>("value_states_87_cast")];
            tensor<int32, [3]> var_1990_perm_0 = const()[name = tensor<string, []>("op_1990_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_127_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_127_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_127_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_127_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_52 = transpose(perm = var_1990_perm_0, x = key_states_87_cast)[name = tensor<string, []>("transpose_52")];
            tensor<fp16, [20, 77, 77]> attn_weights_127_cast = matmul(transpose_x = attn_weights_127_transpose_x_0, transpose_y = attn_weights_127_transpose_y_0, x = query_states_43_cast, y = transpose_52)[name = tensor<string, []>("attn_weights_127_cast")];
            tensor<int32, [4]> var_1992 = const()[name = tensor<string, []>("op_1992"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1993_cast = reshape(shape = var_1992, x = attn_weights_127_cast)[name = tensor<string, []>("op_1993_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_129_cast = add(x = var_1993_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_129_cast")];
            tensor<int32, [3]> var_1998 = const()[name = tensor<string, []>("op_1998"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_341_cast = reshape(shape = var_1998, x = attn_weights_129_cast)[name = tensor<string, []>("input_341_cast")];
            tensor<fp16, [20, 77, 77]> input_343_cast = softmax(axis = var_5, x = input_341_cast)[name = tensor<string, []>("input_343_cast")];
            tensor<bool, []> attn_output_127_transpose_x_0 = const()[name = tensor<string, []>("attn_output_127_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_127_transpose_y_0 = const()[name = tensor<string, []>("attn_output_127_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_127_cast = matmul(transpose_x = attn_output_127_transpose_x_0, transpose_y = attn_output_127_transpose_y_0, x = input_343_cast, y = value_states_87_cast)[name = tensor<string, []>("attn_output_127_cast")];
            tensor<int32, [4]> var_2003 = const()[name = tensor<string, []>("op_2003"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_129_cast = reshape(shape = var_2003, x = attn_output_127_cast)[name = tensor<string, []>("attn_output_129_cast")];
            tensor<int32, [4]> attn_output_131_perm_0 = const()[name = tensor<string, []>("attn_output_131_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2006 = const()[name = tensor<string, []>("op_2006"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_51 = transpose(perm = attn_output_131_perm_0, x = attn_output_129_cast)[name = tensor<string, []>("transpose_51")];
            tensor<fp16, [1, 77, 1280]> input_345_cast = reshape(shape = var_2006, x = transpose_51)[name = tensor<string, []>("input_345_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(963011456)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966288320)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_129_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16, x = input_345_cast)[name = tensor<string, []>("hidden_states_129_cast")];
            tensor<fp16, [1, 77, 1280]> input_347_cast = add(x = input_339_cast, y = hidden_states_129_cast)[name = tensor<string, []>("input_347_cast")];
            tensor<int32, [1]> input_349_axes_0 = const()[name = tensor<string, []>("input_349_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966290944)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966293568)))];
            tensor<fp16, [1, 77, 1280]> input_349_cast = layer_norm(axes = input_349_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16, x = input_347_cast)[name = tensor<string, []>("input_349_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966296192)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(979403456)))];
            tensor<fp16, [1, 77, 5120]> input_351_cast = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16, x = input_349_cast)[name = tensor<string, []>("input_351_cast")];
            tensor<string, []> input_353_mode_0 = const()[name = tensor<string, []>("input_353_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_353_cast = gelu(mode = input_353_mode_0, x = input_351_cast)[name = tensor<string, []>("input_353_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(979413760)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992521024)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_131_cast = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16, x = input_353_cast)[name = tensor<string, []>("hidden_states_131_cast")];
            tensor<fp16, [1, 77, 1280]> input_355_cast = add(x = input_347_cast, y = hidden_states_131_cast)[name = tensor<string, []>("input_355_cast")];
            tensor<int32, [1]> hidden_states_133_axes_0 = const()[name = tensor<string, []>("hidden_states_133_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992523648)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992526272)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_133_cast = layer_norm(axes = hidden_states_133_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16, x = input_355_cast)[name = tensor<string, []>("hidden_states_133_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992528896)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(995805760)))];
            tensor<fp16, [1, 77, 1280]> var_2044_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16, x = hidden_states_133_cast)[name = tensor<string, []>("op_2044_cast")];
            tensor<fp16, []> var_2045_to_fp16 = const()[name = tensor<string, []>("op_2045_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_137_cast = mul(x = var_2044_cast, y = var_2045_to_fp16)[name = tensor<string, []>("tensor_137_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(995808384)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(999085248)))];
            tensor<fp16, [1, 77, 1280]> tensor_133_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16, x = hidden_states_133_cast)[name = tensor<string, []>("tensor_133_cast")];
            tensor<int32, [4]> var_2050 = const()[name = tensor<string, []>("op_2050"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2051_cast = reshape(shape = var_2050, x = tensor_133_cast)[name = tensor<string, []>("op_2051_cast")];
            tensor<int32, [4]> var_2052_perm_0 = const()[name = tensor<string, []>("op_2052_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(999087872)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1002364736)))];
            tensor<fp16, [1, 77, 1280]> tensor_135_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16, x = hidden_states_133_cast)[name = tensor<string, []>("tensor_135_cast")];
            tensor<int32, [4]> var_2057 = const()[name = tensor<string, []>("op_2057"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2058_cast = reshape(shape = var_2057, x = tensor_135_cast)[name = tensor<string, []>("op_2058_cast")];
            tensor<int32, [4]> var_2059_perm_0 = const()[name = tensor<string, []>("op_2059_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2066 = const()[name = tensor<string, []>("op_2066"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2067_cast = reshape(shape = var_2066, x = tensor_137_cast)[name = tensor<string, []>("op_2067_cast")];
            tensor<int32, [4]> var_2068_perm_0 = const()[name = tensor<string, []>("op_2068_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2070 = const()[name = tensor<string, []>("op_2070"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_48 = transpose(perm = var_2068_perm_0, x = var_2067_cast)[name = tensor<string, []>("transpose_48")];
            tensor<fp16, [20, 77, 64]> query_states_45_cast = reshape(shape = var_2070, x = transpose_48)[name = tensor<string, []>("query_states_45_cast")];
            tensor<int32, [3]> var_2072 = const()[name = tensor<string, []>("op_2072"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_50 = transpose(perm = var_2052_perm_0, x = var_2051_cast)[name = tensor<string, []>("transpose_50")];
            tensor<fp16, [20, 77, 64]> key_states_91_cast = reshape(shape = var_2072, x = transpose_50)[name = tensor<string, []>("key_states_91_cast")];
            tensor<int32, [3]> var_2074 = const()[name = tensor<string, []>("op_2074"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_49 = transpose(perm = var_2059_perm_0, x = var_2058_cast)[name = tensor<string, []>("transpose_49")];
            tensor<fp16, [20, 77, 64]> value_states_91_cast = reshape(shape = var_2074, x = transpose_49)[name = tensor<string, []>("value_states_91_cast")];
            tensor<int32, [3]> var_2077_perm_0 = const()[name = tensor<string, []>("op_2077_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_133_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_133_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_133_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_133_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_47 = transpose(perm = var_2077_perm_0, x = key_states_91_cast)[name = tensor<string, []>("transpose_47")];
            tensor<fp16, [20, 77, 77]> attn_weights_133_cast = matmul(transpose_x = attn_weights_133_transpose_x_0, transpose_y = attn_weights_133_transpose_y_0, x = query_states_45_cast, y = transpose_47)[name = tensor<string, []>("attn_weights_133_cast")];
            tensor<int32, [4]> var_2079 = const()[name = tensor<string, []>("op_2079"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2080_cast = reshape(shape = var_2079, x = attn_weights_133_cast)[name = tensor<string, []>("op_2080_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_135_cast = add(x = var_2080_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_135_cast")];
            tensor<int32, [3]> var_2085 = const()[name = tensor<string, []>("op_2085"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_357_cast = reshape(shape = var_2085, x = attn_weights_135_cast)[name = tensor<string, []>("input_357_cast")];
            tensor<fp16, [20, 77, 77]> input_359_cast = softmax(axis = var_5, x = input_357_cast)[name = tensor<string, []>("input_359_cast")];
            tensor<bool, []> attn_output_133_transpose_x_0 = const()[name = tensor<string, []>("attn_output_133_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_133_transpose_y_0 = const()[name = tensor<string, []>("attn_output_133_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_133_cast = matmul(transpose_x = attn_output_133_transpose_x_0, transpose_y = attn_output_133_transpose_y_0, x = input_359_cast, y = value_states_91_cast)[name = tensor<string, []>("attn_output_133_cast")];
            tensor<int32, [4]> var_2090 = const()[name = tensor<string, []>("op_2090"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_135_cast = reshape(shape = var_2090, x = attn_output_133_cast)[name = tensor<string, []>("attn_output_135_cast")];
            tensor<int32, [4]> attn_output_137_perm_0 = const()[name = tensor<string, []>("attn_output_137_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2093 = const()[name = tensor<string, []>("op_2093"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_46 = transpose(perm = attn_output_137_perm_0, x = attn_output_135_cast)[name = tensor<string, []>("transpose_46")];
            tensor<fp16, [1, 77, 1280]> input_361_cast = reshape(shape = var_2093, x = transpose_46)[name = tensor<string, []>("input_361_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1002367360)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005644224)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_135_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16, x = input_361_cast)[name = tensor<string, []>("hidden_states_135_cast")];
            tensor<fp16, [1, 77, 1280]> input_363_cast = add(x = input_355_cast, y = hidden_states_135_cast)[name = tensor<string, []>("input_363_cast")];
            tensor<int32, [1]> input_365_axes_0 = const()[name = tensor<string, []>("input_365_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005646848)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005649472)))];
            tensor<fp16, [1, 77, 1280]> input_365_cast = layer_norm(axes = input_365_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16, x = input_363_cast)[name = tensor<string, []>("input_365_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005652096)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1018759360)))];
            tensor<fp16, [1, 77, 5120]> input_367_cast = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16, x = input_365_cast)[name = tensor<string, []>("input_367_cast")];
            tensor<string, []> input_369_mode_0 = const()[name = tensor<string, []>("input_369_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_369_cast = gelu(mode = input_369_mode_0, x = input_367_cast)[name = tensor<string, []>("input_369_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1018769664)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031876928)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_137_cast = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16, x = input_369_cast)[name = tensor<string, []>("hidden_states_137_cast")];
            tensor<fp16, [1, 77, 1280]> input_371_cast = add(x = input_363_cast, y = hidden_states_137_cast)[name = tensor<string, []>("input_371_cast")];
            tensor<int32, [1]> hidden_states_139_axes_0 = const()[name = tensor<string, []>("hidden_states_139_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031879552)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031882176)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_139_cast = layer_norm(axes = hidden_states_139_axes_0, beta = text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16, x = input_371_cast)[name = tensor<string, []>("hidden_states_139_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031884800)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1035161664)))];
            tensor<fp16, [1, 77, 1280]> var_2131_cast = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16, x = hidden_states_139_cast)[name = tensor<string, []>("op_2131_cast")];
            tensor<fp16, []> var_2132_to_fp16 = const()[name = tensor<string, []>("op_2132_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_143_cast = mul(x = var_2131_cast, y = var_2132_to_fp16)[name = tensor<string, []>("tensor_143_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1035164288)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1038441152)))];
            tensor<fp16, [1, 77, 1280]> tensor_139_cast = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16, x = hidden_states_139_cast)[name = tensor<string, []>("tensor_139_cast")];
            tensor<int32, [4]> var_2137 = const()[name = tensor<string, []>("op_2137"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2138_cast = reshape(shape = var_2137, x = tensor_139_cast)[name = tensor<string, []>("op_2138_cast")];
            tensor<int32, [4]> var_2139_perm_0 = const()[name = tensor<string, []>("op_2139_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1038443776)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1041720640)))];
            tensor<fp16, [1, 77, 1280]> tensor_141_cast = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16, x = hidden_states_139_cast)[name = tensor<string, []>("tensor_141_cast")];
            tensor<int32, [4]> var_2144 = const()[name = tensor<string, []>("op_2144"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2145_cast = reshape(shape = var_2144, x = tensor_141_cast)[name = tensor<string, []>("op_2145_cast")];
            tensor<int32, [4]> var_2146_perm_0 = const()[name = tensor<string, []>("op_2146_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2153 = const()[name = tensor<string, []>("op_2153"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2154_cast = reshape(shape = var_2153, x = tensor_143_cast)[name = tensor<string, []>("op_2154_cast")];
            tensor<int32, [4]> var_2155_perm_0 = const()[name = tensor<string, []>("op_2155_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2157 = const()[name = tensor<string, []>("op_2157"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_43 = transpose(perm = var_2155_perm_0, x = var_2154_cast)[name = tensor<string, []>("transpose_43")];
            tensor<fp16, [20, 77, 64]> query_states_47_cast = reshape(shape = var_2157, x = transpose_43)[name = tensor<string, []>("query_states_47_cast")];
            tensor<int32, [3]> var_2159 = const()[name = tensor<string, []>("op_2159"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_45 = transpose(perm = var_2139_perm_0, x = var_2138_cast)[name = tensor<string, []>("transpose_45")];
            tensor<fp16, [20, 77, 64]> key_states_95_cast = reshape(shape = var_2159, x = transpose_45)[name = tensor<string, []>("key_states_95_cast")];
            tensor<int32, [3]> var_2161 = const()[name = tensor<string, []>("op_2161"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_44 = transpose(perm = var_2146_perm_0, x = var_2145_cast)[name = tensor<string, []>("transpose_44")];
            tensor<fp16, [20, 77, 64]> value_states_95_cast = reshape(shape = var_2161, x = transpose_44)[name = tensor<string, []>("value_states_95_cast")];
            tensor<int32, [3]> var_2164_perm_0 = const()[name = tensor<string, []>("op_2164_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_139_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_139_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_139_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_139_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_42 = transpose(perm = var_2164_perm_0, x = key_states_95_cast)[name = tensor<string, []>("transpose_42")];
            tensor<fp16, [20, 77, 77]> attn_weights_139_cast = matmul(transpose_x = attn_weights_139_transpose_x_0, transpose_y = attn_weights_139_transpose_y_0, x = query_states_47_cast, y = transpose_42)[name = tensor<string, []>("attn_weights_139_cast")];
            tensor<int32, [4]> var_2166 = const()[name = tensor<string, []>("op_2166"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2167_cast = reshape(shape = var_2166, x = attn_weights_139_cast)[name = tensor<string, []>("op_2167_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_141_cast = add(x = var_2167_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_141_cast")];
            tensor<int32, [3]> var_2172 = const()[name = tensor<string, []>("op_2172"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_373_cast = reshape(shape = var_2172, x = attn_weights_141_cast)[name = tensor<string, []>("input_373_cast")];
            tensor<fp16, [20, 77, 77]> input_375_cast = softmax(axis = var_5, x = input_373_cast)[name = tensor<string, []>("input_375_cast")];
            tensor<bool, []> attn_output_139_transpose_x_0 = const()[name = tensor<string, []>("attn_output_139_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_139_transpose_y_0 = const()[name = tensor<string, []>("attn_output_139_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_139_cast = matmul(transpose_x = attn_output_139_transpose_x_0, transpose_y = attn_output_139_transpose_y_0, x = input_375_cast, y = value_states_95_cast)[name = tensor<string, []>("attn_output_139_cast")];
            tensor<int32, [4]> var_2177 = const()[name = tensor<string, []>("op_2177"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_141_cast = reshape(shape = var_2177, x = attn_output_139_cast)[name = tensor<string, []>("attn_output_141_cast")];
            tensor<int32, [4]> attn_output_143_perm_0 = const()[name = tensor<string, []>("attn_output_143_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2180 = const()[name = tensor<string, []>("op_2180"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_41 = transpose(perm = attn_output_143_perm_0, x = attn_output_141_cast)[name = tensor<string, []>("transpose_41")];
            tensor<fp16, [1, 77, 1280]> input_377_cast = reshape(shape = var_2180, x = transpose_41)[name = tensor<string, []>("input_377_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1041723264)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045000128)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_141_cast = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16, x = input_377_cast)[name = tensor<string, []>("hidden_states_141_cast")];
            tensor<fp16, [1, 77, 1280]> input_379_cast = add(x = input_371_cast, y = hidden_states_141_cast)[name = tensor<string, []>("input_379_cast")];
            tensor<int32, [1]> input_381_axes_0 = const()[name = tensor<string, []>("input_381_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045002752)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045005376)))];
            tensor<fp16, [1, 77, 1280]> input_381_cast = layer_norm(axes = input_381_axes_0, beta = text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16, x = input_379_cast)[name = tensor<string, []>("input_381_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045008000)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1058115264)))];
            tensor<fp16, [1, 77, 5120]> input_383_cast = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16, x = input_381_cast)[name = tensor<string, []>("input_383_cast")];
            tensor<string, []> input_385_mode_0 = const()[name = tensor<string, []>("input_385_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_385_cast = gelu(mode = input_385_mode_0, x = input_383_cast)[name = tensor<string, []>("input_385_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1058125568)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071232832)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_143_cast = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16, x = input_385_cast)[name = tensor<string, []>("hidden_states_143_cast")];
            tensor<fp16, [1, 77, 1280]> input_387_cast = add(x = input_379_cast, y = hidden_states_143_cast)[name = tensor<string, []>("input_387_cast")];
            tensor<int32, [1]> hidden_states_145_axes_0 = const()[name = tensor<string, []>("hidden_states_145_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071235456)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071238080)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_145_cast = layer_norm(axes = hidden_states_145_axes_0, beta = text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16, x = input_387_cast)[name = tensor<string, []>("hidden_states_145_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071240704)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1074517568)))];
            tensor<fp16, [1, 77, 1280]> var_2218_cast = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16, x = hidden_states_145_cast)[name = tensor<string, []>("op_2218_cast")];
            tensor<fp16, []> var_2219_to_fp16 = const()[name = tensor<string, []>("op_2219_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_149_cast = mul(x = var_2218_cast, y = var_2219_to_fp16)[name = tensor<string, []>("tensor_149_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1074520192)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1077797056)))];
            tensor<fp16, [1, 77, 1280]> tensor_145_cast = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16, x = hidden_states_145_cast)[name = tensor<string, []>("tensor_145_cast")];
            tensor<int32, [4]> var_2224 = const()[name = tensor<string, []>("op_2224"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2225_cast = reshape(shape = var_2224, x = tensor_145_cast)[name = tensor<string, []>("op_2225_cast")];
            tensor<int32, [4]> var_2226_perm_0 = const()[name = tensor<string, []>("op_2226_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1077799680)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1081076544)))];
            tensor<fp16, [1, 77, 1280]> tensor_147_cast = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16, x = hidden_states_145_cast)[name = tensor<string, []>("tensor_147_cast")];
            tensor<int32, [4]> var_2231 = const()[name = tensor<string, []>("op_2231"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2232_cast = reshape(shape = var_2231, x = tensor_147_cast)[name = tensor<string, []>("op_2232_cast")];
            tensor<int32, [4]> var_2233_perm_0 = const()[name = tensor<string, []>("op_2233_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2240 = const()[name = tensor<string, []>("op_2240"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2241_cast = reshape(shape = var_2240, x = tensor_149_cast)[name = tensor<string, []>("op_2241_cast")];
            tensor<int32, [4]> var_2242_perm_0 = const()[name = tensor<string, []>("op_2242_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2244 = const()[name = tensor<string, []>("op_2244"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_38 = transpose(perm = var_2242_perm_0, x = var_2241_cast)[name = tensor<string, []>("transpose_38")];
            tensor<fp16, [20, 77, 64]> query_states_49_cast = reshape(shape = var_2244, x = transpose_38)[name = tensor<string, []>("query_states_49_cast")];
            tensor<int32, [3]> var_2246 = const()[name = tensor<string, []>("op_2246"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_40 = transpose(perm = var_2226_perm_0, x = var_2225_cast)[name = tensor<string, []>("transpose_40")];
            tensor<fp16, [20, 77, 64]> key_states_99_cast = reshape(shape = var_2246, x = transpose_40)[name = tensor<string, []>("key_states_99_cast")];
            tensor<int32, [3]> var_2248 = const()[name = tensor<string, []>("op_2248"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_39 = transpose(perm = var_2233_perm_0, x = var_2232_cast)[name = tensor<string, []>("transpose_39")];
            tensor<fp16, [20, 77, 64]> value_states_99_cast = reshape(shape = var_2248, x = transpose_39)[name = tensor<string, []>("value_states_99_cast")];
            tensor<int32, [3]> var_2251_perm_0 = const()[name = tensor<string, []>("op_2251_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_145_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_145_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_145_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_145_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_37 = transpose(perm = var_2251_perm_0, x = key_states_99_cast)[name = tensor<string, []>("transpose_37")];
            tensor<fp16, [20, 77, 77]> attn_weights_145_cast = matmul(transpose_x = attn_weights_145_transpose_x_0, transpose_y = attn_weights_145_transpose_y_0, x = query_states_49_cast, y = transpose_37)[name = tensor<string, []>("attn_weights_145_cast")];
            tensor<int32, [4]> var_2253 = const()[name = tensor<string, []>("op_2253"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2254_cast = reshape(shape = var_2253, x = attn_weights_145_cast)[name = tensor<string, []>("op_2254_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_147_cast = add(x = var_2254_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_147_cast")];
            tensor<int32, [3]> var_2259 = const()[name = tensor<string, []>("op_2259"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_389_cast = reshape(shape = var_2259, x = attn_weights_147_cast)[name = tensor<string, []>("input_389_cast")];
            tensor<fp16, [20, 77, 77]> input_391_cast = softmax(axis = var_5, x = input_389_cast)[name = tensor<string, []>("input_391_cast")];
            tensor<bool, []> attn_output_145_transpose_x_0 = const()[name = tensor<string, []>("attn_output_145_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_145_transpose_y_0 = const()[name = tensor<string, []>("attn_output_145_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_145_cast = matmul(transpose_x = attn_output_145_transpose_x_0, transpose_y = attn_output_145_transpose_y_0, x = input_391_cast, y = value_states_99_cast)[name = tensor<string, []>("attn_output_145_cast")];
            tensor<int32, [4]> var_2264 = const()[name = tensor<string, []>("op_2264"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_147_cast = reshape(shape = var_2264, x = attn_output_145_cast)[name = tensor<string, []>("attn_output_147_cast")];
            tensor<int32, [4]> attn_output_149_perm_0 = const()[name = tensor<string, []>("attn_output_149_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2267 = const()[name = tensor<string, []>("op_2267"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_36 = transpose(perm = attn_output_149_perm_0, x = attn_output_147_cast)[name = tensor<string, []>("transpose_36")];
            tensor<fp16, [1, 77, 1280]> input_393_cast = reshape(shape = var_2267, x = transpose_36)[name = tensor<string, []>("input_393_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1081079168)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084356032)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_147_cast = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16, x = input_393_cast)[name = tensor<string, []>("hidden_states_147_cast")];
            tensor<fp16, [1, 77, 1280]> input_395_cast = add(x = input_387_cast, y = hidden_states_147_cast)[name = tensor<string, []>("input_395_cast")];
            tensor<int32, [1]> input_397_axes_0 = const()[name = tensor<string, []>("input_397_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084358656)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084361280)))];
            tensor<fp16, [1, 77, 1280]> input_397_cast = layer_norm(axes = input_397_axes_0, beta = text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16, x = input_395_cast)[name = tensor<string, []>("input_397_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084363904)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1097471168)))];
            tensor<fp16, [1, 77, 5120]> input_399_cast = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16, x = input_397_cast)[name = tensor<string, []>("input_399_cast")];
            tensor<string, []> input_401_mode_0 = const()[name = tensor<string, []>("input_401_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_401_cast = gelu(mode = input_401_mode_0, x = input_399_cast)[name = tensor<string, []>("input_401_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1097481472)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110588736)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_149_cast = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16, x = input_401_cast)[name = tensor<string, []>("hidden_states_149_cast")];
            tensor<fp16, [1, 77, 1280]> input_403_cast = add(x = input_395_cast, y = hidden_states_149_cast)[name = tensor<string, []>("input_403_cast")];
            tensor<int32, [1]> hidden_states_151_axes_0 = const()[name = tensor<string, []>("hidden_states_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110591360)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110593984)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_151_cast = layer_norm(axes = hidden_states_151_axes_0, beta = text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16, x = input_403_cast)[name = tensor<string, []>("hidden_states_151_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110596608)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1113873472)))];
            tensor<fp16, [1, 77, 1280]> var_2305_cast = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16, x = hidden_states_151_cast)[name = tensor<string, []>("op_2305_cast")];
            tensor<fp16, []> var_2306_to_fp16 = const()[name = tensor<string, []>("op_2306_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_155_cast = mul(x = var_2305_cast, y = var_2306_to_fp16)[name = tensor<string, []>("tensor_155_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1113876096)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1117152960)))];
            tensor<fp16, [1, 77, 1280]> tensor_151_cast = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16, x = hidden_states_151_cast)[name = tensor<string, []>("tensor_151_cast")];
            tensor<int32, [4]> var_2311 = const()[name = tensor<string, []>("op_2311"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2312_cast = reshape(shape = var_2311, x = tensor_151_cast)[name = tensor<string, []>("op_2312_cast")];
            tensor<int32, [4]> var_2313_perm_0 = const()[name = tensor<string, []>("op_2313_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1117155584)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120432448)))];
            tensor<fp16, [1, 77, 1280]> tensor_153_cast = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16, x = hidden_states_151_cast)[name = tensor<string, []>("tensor_153_cast")];
            tensor<int32, [4]> var_2318 = const()[name = tensor<string, []>("op_2318"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2319_cast = reshape(shape = var_2318, x = tensor_153_cast)[name = tensor<string, []>("op_2319_cast")];
            tensor<int32, [4]> var_2320_perm_0 = const()[name = tensor<string, []>("op_2320_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2327 = const()[name = tensor<string, []>("op_2327"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2328_cast = reshape(shape = var_2327, x = tensor_155_cast)[name = tensor<string, []>("op_2328_cast")];
            tensor<int32, [4]> var_2329_perm_0 = const()[name = tensor<string, []>("op_2329_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2331 = const()[name = tensor<string, []>("op_2331"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_33 = transpose(perm = var_2329_perm_0, x = var_2328_cast)[name = tensor<string, []>("transpose_33")];
            tensor<fp16, [20, 77, 64]> query_states_51_cast = reshape(shape = var_2331, x = transpose_33)[name = tensor<string, []>("query_states_51_cast")];
            tensor<int32, [3]> var_2333 = const()[name = tensor<string, []>("op_2333"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_35 = transpose(perm = var_2313_perm_0, x = var_2312_cast)[name = tensor<string, []>("transpose_35")];
            tensor<fp16, [20, 77, 64]> key_states_103_cast = reshape(shape = var_2333, x = transpose_35)[name = tensor<string, []>("key_states_103_cast")];
            tensor<int32, [3]> var_2335 = const()[name = tensor<string, []>("op_2335"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_34 = transpose(perm = var_2320_perm_0, x = var_2319_cast)[name = tensor<string, []>("transpose_34")];
            tensor<fp16, [20, 77, 64]> value_states_103_cast = reshape(shape = var_2335, x = transpose_34)[name = tensor<string, []>("value_states_103_cast")];
            tensor<int32, [3]> var_2338_perm_0 = const()[name = tensor<string, []>("op_2338_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_151_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_151_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_151_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_151_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_32 = transpose(perm = var_2338_perm_0, x = key_states_103_cast)[name = tensor<string, []>("transpose_32")];
            tensor<fp16, [20, 77, 77]> attn_weights_151_cast = matmul(transpose_x = attn_weights_151_transpose_x_0, transpose_y = attn_weights_151_transpose_y_0, x = query_states_51_cast, y = transpose_32)[name = tensor<string, []>("attn_weights_151_cast")];
            tensor<int32, [4]> var_2340 = const()[name = tensor<string, []>("op_2340"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2341_cast = reshape(shape = var_2340, x = attn_weights_151_cast)[name = tensor<string, []>("op_2341_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_153_cast = add(x = var_2341_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_153_cast")];
            tensor<int32, [3]> var_2346 = const()[name = tensor<string, []>("op_2346"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_405_cast = reshape(shape = var_2346, x = attn_weights_153_cast)[name = tensor<string, []>("input_405_cast")];
            tensor<fp16, [20, 77, 77]> input_407_cast = softmax(axis = var_5, x = input_405_cast)[name = tensor<string, []>("input_407_cast")];
            tensor<bool, []> attn_output_151_transpose_x_0 = const()[name = tensor<string, []>("attn_output_151_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_151_transpose_y_0 = const()[name = tensor<string, []>("attn_output_151_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_151_cast = matmul(transpose_x = attn_output_151_transpose_x_0, transpose_y = attn_output_151_transpose_y_0, x = input_407_cast, y = value_states_103_cast)[name = tensor<string, []>("attn_output_151_cast")];
            tensor<int32, [4]> var_2351 = const()[name = tensor<string, []>("op_2351"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_153_cast = reshape(shape = var_2351, x = attn_output_151_cast)[name = tensor<string, []>("attn_output_153_cast")];
            tensor<int32, [4]> attn_output_155_perm_0 = const()[name = tensor<string, []>("attn_output_155_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2354 = const()[name = tensor<string, []>("op_2354"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_31 = transpose(perm = attn_output_155_perm_0, x = attn_output_153_cast)[name = tensor<string, []>("transpose_31")];
            tensor<fp16, [1, 77, 1280]> input_409_cast = reshape(shape = var_2354, x = transpose_31)[name = tensor<string, []>("input_409_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120435072)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123711936)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_153_cast = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16, x = input_409_cast)[name = tensor<string, []>("hidden_states_153_cast")];
            tensor<fp16, [1, 77, 1280]> input_411_cast = add(x = input_403_cast, y = hidden_states_153_cast)[name = tensor<string, []>("input_411_cast")];
            tensor<int32, [1]> input_413_axes_0 = const()[name = tensor<string, []>("input_413_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123714560)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123717184)))];
            tensor<fp16, [1, 77, 1280]> input_413_cast = layer_norm(axes = input_413_axes_0, beta = text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16, x = input_411_cast)[name = tensor<string, []>("input_413_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123719808)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1136827072)))];
            tensor<fp16, [1, 77, 5120]> input_415_cast = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16, x = input_413_cast)[name = tensor<string, []>("input_415_cast")];
            tensor<string, []> input_417_mode_0 = const()[name = tensor<string, []>("input_417_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_417_cast = gelu(mode = input_417_mode_0, x = input_415_cast)[name = tensor<string, []>("input_417_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1136837376)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149944640)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_155_cast = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16, x = input_417_cast)[name = tensor<string, []>("hidden_states_155_cast")];
            tensor<fp16, [1, 77, 1280]> input_419_cast = add(x = input_411_cast, y = hidden_states_155_cast)[name = tensor<string, []>("input_419_cast")];
            tensor<int32, [1]> hidden_states_157_axes_0 = const()[name = tensor<string, []>("hidden_states_157_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149947264)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149949888)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_157_cast = layer_norm(axes = hidden_states_157_axes_0, beta = text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16, x = input_419_cast)[name = tensor<string, []>("hidden_states_157_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149952512)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1153229376)))];
            tensor<fp16, [1, 77, 1280]> var_2392_cast = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16, x = hidden_states_157_cast)[name = tensor<string, []>("op_2392_cast")];
            tensor<fp16, []> var_2393_to_fp16 = const()[name = tensor<string, []>("op_2393_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_161_cast = mul(x = var_2392_cast, y = var_2393_to_fp16)[name = tensor<string, []>("tensor_161_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1153232000)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1156508864)))];
            tensor<fp16, [1, 77, 1280]> tensor_157_cast = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16, x = hidden_states_157_cast)[name = tensor<string, []>("tensor_157_cast")];
            tensor<int32, [4]> var_2398 = const()[name = tensor<string, []>("op_2398"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2399_cast = reshape(shape = var_2398, x = tensor_157_cast)[name = tensor<string, []>("op_2399_cast")];
            tensor<int32, [4]> var_2400_perm_0 = const()[name = tensor<string, []>("op_2400_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1156511488)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1159788352)))];
            tensor<fp16, [1, 77, 1280]> tensor_159_cast = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16, x = hidden_states_157_cast)[name = tensor<string, []>("tensor_159_cast")];
            tensor<int32, [4]> var_2405 = const()[name = tensor<string, []>("op_2405"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2406_cast = reshape(shape = var_2405, x = tensor_159_cast)[name = tensor<string, []>("op_2406_cast")];
            tensor<int32, [4]> var_2407_perm_0 = const()[name = tensor<string, []>("op_2407_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2414 = const()[name = tensor<string, []>("op_2414"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2415_cast = reshape(shape = var_2414, x = tensor_161_cast)[name = tensor<string, []>("op_2415_cast")];
            tensor<int32, [4]> var_2416_perm_0 = const()[name = tensor<string, []>("op_2416_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2418 = const()[name = tensor<string, []>("op_2418"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_28 = transpose(perm = var_2416_perm_0, x = var_2415_cast)[name = tensor<string, []>("transpose_28")];
            tensor<fp16, [20, 77, 64]> query_states_53_cast = reshape(shape = var_2418, x = transpose_28)[name = tensor<string, []>("query_states_53_cast")];
            tensor<int32, [3]> var_2420 = const()[name = tensor<string, []>("op_2420"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_30 = transpose(perm = var_2400_perm_0, x = var_2399_cast)[name = tensor<string, []>("transpose_30")];
            tensor<fp16, [20, 77, 64]> key_states_107_cast = reshape(shape = var_2420, x = transpose_30)[name = tensor<string, []>("key_states_107_cast")];
            tensor<int32, [3]> var_2422 = const()[name = tensor<string, []>("op_2422"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_29 = transpose(perm = var_2407_perm_0, x = var_2406_cast)[name = tensor<string, []>("transpose_29")];
            tensor<fp16, [20, 77, 64]> value_states_107_cast = reshape(shape = var_2422, x = transpose_29)[name = tensor<string, []>("value_states_107_cast")];
            tensor<int32, [3]> var_2425_perm_0 = const()[name = tensor<string, []>("op_2425_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_157_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_157_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_157_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_157_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_27 = transpose(perm = var_2425_perm_0, x = key_states_107_cast)[name = tensor<string, []>("transpose_27")];
            tensor<fp16, [20, 77, 77]> attn_weights_157_cast = matmul(transpose_x = attn_weights_157_transpose_x_0, transpose_y = attn_weights_157_transpose_y_0, x = query_states_53_cast, y = transpose_27)[name = tensor<string, []>("attn_weights_157_cast")];
            tensor<int32, [4]> var_2427 = const()[name = tensor<string, []>("op_2427"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2428_cast = reshape(shape = var_2427, x = attn_weights_157_cast)[name = tensor<string, []>("op_2428_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_159_cast = add(x = var_2428_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_159_cast")];
            tensor<int32, [3]> var_2433 = const()[name = tensor<string, []>("op_2433"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_421_cast = reshape(shape = var_2433, x = attn_weights_159_cast)[name = tensor<string, []>("input_421_cast")];
            tensor<fp16, [20, 77, 77]> input_423_cast = softmax(axis = var_5, x = input_421_cast)[name = tensor<string, []>("input_423_cast")];
            tensor<bool, []> attn_output_157_transpose_x_0 = const()[name = tensor<string, []>("attn_output_157_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_157_transpose_y_0 = const()[name = tensor<string, []>("attn_output_157_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_157_cast = matmul(transpose_x = attn_output_157_transpose_x_0, transpose_y = attn_output_157_transpose_y_0, x = input_423_cast, y = value_states_107_cast)[name = tensor<string, []>("attn_output_157_cast")];
            tensor<int32, [4]> var_2438 = const()[name = tensor<string, []>("op_2438"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_159_cast = reshape(shape = var_2438, x = attn_output_157_cast)[name = tensor<string, []>("attn_output_159_cast")];
            tensor<int32, [4]> attn_output_161_perm_0 = const()[name = tensor<string, []>("attn_output_161_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2441 = const()[name = tensor<string, []>("op_2441"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_26 = transpose(perm = attn_output_161_perm_0, x = attn_output_159_cast)[name = tensor<string, []>("transpose_26")];
            tensor<fp16, [1, 77, 1280]> input_425_cast = reshape(shape = var_2441, x = transpose_26)[name = tensor<string, []>("input_425_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1159790976)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163067840)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_159_cast = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16, x = input_425_cast)[name = tensor<string, []>("hidden_states_159_cast")];
            tensor<fp16, [1, 77, 1280]> input_427_cast = add(x = input_419_cast, y = hidden_states_159_cast)[name = tensor<string, []>("input_427_cast")];
            tensor<int32, [1]> input_429_axes_0 = const()[name = tensor<string, []>("input_429_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163070464)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163073088)))];
            tensor<fp16, [1, 77, 1280]> input_429_cast = layer_norm(axes = input_429_axes_0, beta = text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16, x = input_427_cast)[name = tensor<string, []>("input_429_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163075712)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1176182976)))];
            tensor<fp16, [1, 77, 5120]> input_431_cast = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16, x = input_429_cast)[name = tensor<string, []>("input_431_cast")];
            tensor<string, []> input_433_mode_0 = const()[name = tensor<string, []>("input_433_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_433_cast = gelu(mode = input_433_mode_0, x = input_431_cast)[name = tensor<string, []>("input_433_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1176193280)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189300544)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_161_cast = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16, x = input_433_cast)[name = tensor<string, []>("hidden_states_161_cast")];
            tensor<fp16, [1, 77, 1280]> input_435_cast = add(x = input_427_cast, y = hidden_states_161_cast)[name = tensor<string, []>("input_435_cast")];
            tensor<int32, [1]> hidden_states_163_axes_0 = const()[name = tensor<string, []>("hidden_states_163_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189303168)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189305792)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_163_cast = layer_norm(axes = hidden_states_163_axes_0, beta = text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16, x = input_435_cast)[name = tensor<string, []>("hidden_states_163_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189308416)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1192585280)))];
            tensor<fp16, [1, 77, 1280]> var_2479_cast = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16, x = hidden_states_163_cast)[name = tensor<string, []>("op_2479_cast")];
            tensor<fp16, []> var_2480_to_fp16 = const()[name = tensor<string, []>("op_2480_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_167_cast = mul(x = var_2479_cast, y = var_2480_to_fp16)[name = tensor<string, []>("tensor_167_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1192587904)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1195864768)))];
            tensor<fp16, [1, 77, 1280]> tensor_163_cast = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16, x = hidden_states_163_cast)[name = tensor<string, []>("tensor_163_cast")];
            tensor<int32, [4]> var_2485 = const()[name = tensor<string, []>("op_2485"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2486_cast = reshape(shape = var_2485, x = tensor_163_cast)[name = tensor<string, []>("op_2486_cast")];
            tensor<int32, [4]> var_2487_perm_0 = const()[name = tensor<string, []>("op_2487_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1195867392)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1199144256)))];
            tensor<fp16, [1, 77, 1280]> tensor_165_cast = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16, x = hidden_states_163_cast)[name = tensor<string, []>("tensor_165_cast")];
            tensor<int32, [4]> var_2492 = const()[name = tensor<string, []>("op_2492"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2493_cast = reshape(shape = var_2492, x = tensor_165_cast)[name = tensor<string, []>("op_2493_cast")];
            tensor<int32, [4]> var_2494_perm_0 = const()[name = tensor<string, []>("op_2494_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2501 = const()[name = tensor<string, []>("op_2501"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2502_cast = reshape(shape = var_2501, x = tensor_167_cast)[name = tensor<string, []>("op_2502_cast")];
            tensor<int32, [4]> var_2503_perm_0 = const()[name = tensor<string, []>("op_2503_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2505 = const()[name = tensor<string, []>("op_2505"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_23 = transpose(perm = var_2503_perm_0, x = var_2502_cast)[name = tensor<string, []>("transpose_23")];
            tensor<fp16, [20, 77, 64]> query_states_55_cast = reshape(shape = var_2505, x = transpose_23)[name = tensor<string, []>("query_states_55_cast")];
            tensor<int32, [3]> var_2507 = const()[name = tensor<string, []>("op_2507"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_25 = transpose(perm = var_2487_perm_0, x = var_2486_cast)[name = tensor<string, []>("transpose_25")];
            tensor<fp16, [20, 77, 64]> key_states_111_cast = reshape(shape = var_2507, x = transpose_25)[name = tensor<string, []>("key_states_111_cast")];
            tensor<int32, [3]> var_2509 = const()[name = tensor<string, []>("op_2509"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_24 = transpose(perm = var_2494_perm_0, x = var_2493_cast)[name = tensor<string, []>("transpose_24")];
            tensor<fp16, [20, 77, 64]> value_states_111_cast = reshape(shape = var_2509, x = transpose_24)[name = tensor<string, []>("value_states_111_cast")];
            tensor<int32, [3]> var_2512_perm_0 = const()[name = tensor<string, []>("op_2512_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_163_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_163_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_163_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_163_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_22 = transpose(perm = var_2512_perm_0, x = key_states_111_cast)[name = tensor<string, []>("transpose_22")];
            tensor<fp16, [20, 77, 77]> attn_weights_163_cast = matmul(transpose_x = attn_weights_163_transpose_x_0, transpose_y = attn_weights_163_transpose_y_0, x = query_states_55_cast, y = transpose_22)[name = tensor<string, []>("attn_weights_163_cast")];
            tensor<int32, [4]> var_2514 = const()[name = tensor<string, []>("op_2514"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2515_cast = reshape(shape = var_2514, x = attn_weights_163_cast)[name = tensor<string, []>("op_2515_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_165_cast = add(x = var_2515_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_165_cast")];
            tensor<int32, [3]> var_2520 = const()[name = tensor<string, []>("op_2520"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_437_cast = reshape(shape = var_2520, x = attn_weights_165_cast)[name = tensor<string, []>("input_437_cast")];
            tensor<fp16, [20, 77, 77]> input_439_cast = softmax(axis = var_5, x = input_437_cast)[name = tensor<string, []>("input_439_cast")];
            tensor<bool, []> attn_output_163_transpose_x_0 = const()[name = tensor<string, []>("attn_output_163_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_163_transpose_y_0 = const()[name = tensor<string, []>("attn_output_163_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_163_cast = matmul(transpose_x = attn_output_163_transpose_x_0, transpose_y = attn_output_163_transpose_y_0, x = input_439_cast, y = value_states_111_cast)[name = tensor<string, []>("attn_output_163_cast")];
            tensor<int32, [4]> var_2525 = const()[name = tensor<string, []>("op_2525"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_165_cast = reshape(shape = var_2525, x = attn_output_163_cast)[name = tensor<string, []>("attn_output_165_cast")];
            tensor<int32, [4]> attn_output_167_perm_0 = const()[name = tensor<string, []>("attn_output_167_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2528 = const()[name = tensor<string, []>("op_2528"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_21 = transpose(perm = attn_output_167_perm_0, x = attn_output_165_cast)[name = tensor<string, []>("transpose_21")];
            tensor<fp16, [1, 77, 1280]> input_441_cast = reshape(shape = var_2528, x = transpose_21)[name = tensor<string, []>("input_441_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1199146880)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202423744)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_165_cast = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16, x = input_441_cast)[name = tensor<string, []>("hidden_states_165_cast")];
            tensor<fp16, [1, 77, 1280]> input_443_cast = add(x = input_435_cast, y = hidden_states_165_cast)[name = tensor<string, []>("input_443_cast")];
            tensor<int32, [1]> input_445_axes_0 = const()[name = tensor<string, []>("input_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202426368)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202428992)))];
            tensor<fp16, [1, 77, 1280]> input_445_cast = layer_norm(axes = input_445_axes_0, beta = text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16, x = input_443_cast)[name = tensor<string, []>("input_445_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202431616)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1215538880)))];
            tensor<fp16, [1, 77, 5120]> input_447_cast = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16, x = input_445_cast)[name = tensor<string, []>("input_447_cast")];
            tensor<string, []> input_449_mode_0 = const()[name = tensor<string, []>("input_449_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_449_cast = gelu(mode = input_449_mode_0, x = input_447_cast)[name = tensor<string, []>("input_449_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1215549184)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228656448)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_167_cast = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16, x = input_449_cast)[name = tensor<string, []>("hidden_states_167_cast")];
            tensor<fp16, [1, 77, 1280]> input_451_cast = add(x = input_443_cast, y = hidden_states_167_cast)[name = tensor<string, []>("input_451_cast")];
            tensor<int32, [1]> hidden_states_169_axes_0 = const()[name = tensor<string, []>("hidden_states_169_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228659072)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228661696)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_169_cast = layer_norm(axes = hidden_states_169_axes_0, beta = text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16, x = input_451_cast)[name = tensor<string, []>("hidden_states_169_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228664320)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1231941184)))];
            tensor<fp16, [1, 77, 1280]> var_2566_cast = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16, x = hidden_states_169_cast)[name = tensor<string, []>("op_2566_cast")];
            tensor<fp16, []> var_2567_to_fp16 = const()[name = tensor<string, []>("op_2567_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_173_cast = mul(x = var_2566_cast, y = var_2567_to_fp16)[name = tensor<string, []>("tensor_173_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1231943808)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235220672)))];
            tensor<fp16, [1, 77, 1280]> tensor_169_cast = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16, x = hidden_states_169_cast)[name = tensor<string, []>("tensor_169_cast")];
            tensor<int32, [4]> var_2572 = const()[name = tensor<string, []>("op_2572"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2573_cast = reshape(shape = var_2572, x = tensor_169_cast)[name = tensor<string, []>("op_2573_cast")];
            tensor<int32, [4]> var_2574_perm_0 = const()[name = tensor<string, []>("op_2574_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235223296)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1238500160)))];
            tensor<fp16, [1, 77, 1280]> tensor_171_cast = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16, x = hidden_states_169_cast)[name = tensor<string, []>("tensor_171_cast")];
            tensor<int32, [4]> var_2579 = const()[name = tensor<string, []>("op_2579"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2580_cast = reshape(shape = var_2579, x = tensor_171_cast)[name = tensor<string, []>("op_2580_cast")];
            tensor<int32, [4]> var_2581_perm_0 = const()[name = tensor<string, []>("op_2581_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2588 = const()[name = tensor<string, []>("op_2588"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2589_cast = reshape(shape = var_2588, x = tensor_173_cast)[name = tensor<string, []>("op_2589_cast")];
            tensor<int32, [4]> var_2590_perm_0 = const()[name = tensor<string, []>("op_2590_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2592 = const()[name = tensor<string, []>("op_2592"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_18 = transpose(perm = var_2590_perm_0, x = var_2589_cast)[name = tensor<string, []>("transpose_18")];
            tensor<fp16, [20, 77, 64]> query_states_57_cast = reshape(shape = var_2592, x = transpose_18)[name = tensor<string, []>("query_states_57_cast")];
            tensor<int32, [3]> var_2594 = const()[name = tensor<string, []>("op_2594"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_20 = transpose(perm = var_2574_perm_0, x = var_2573_cast)[name = tensor<string, []>("transpose_20")];
            tensor<fp16, [20, 77, 64]> key_states_115_cast = reshape(shape = var_2594, x = transpose_20)[name = tensor<string, []>("key_states_115_cast")];
            tensor<int32, [3]> var_2596 = const()[name = tensor<string, []>("op_2596"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_19 = transpose(perm = var_2581_perm_0, x = var_2580_cast)[name = tensor<string, []>("transpose_19")];
            tensor<fp16, [20, 77, 64]> value_states_115_cast = reshape(shape = var_2596, x = transpose_19)[name = tensor<string, []>("value_states_115_cast")];
            tensor<int32, [3]> var_2599_perm_0 = const()[name = tensor<string, []>("op_2599_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_169_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_169_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_169_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_169_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_17 = transpose(perm = var_2599_perm_0, x = key_states_115_cast)[name = tensor<string, []>("transpose_17")];
            tensor<fp16, [20, 77, 77]> attn_weights_169_cast = matmul(transpose_x = attn_weights_169_transpose_x_0, transpose_y = attn_weights_169_transpose_y_0, x = query_states_57_cast, y = transpose_17)[name = tensor<string, []>("attn_weights_169_cast")];
            tensor<int32, [4]> var_2601 = const()[name = tensor<string, []>("op_2601"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2602_cast = reshape(shape = var_2601, x = attn_weights_169_cast)[name = tensor<string, []>("op_2602_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_171_cast = add(x = var_2602_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_171_cast")];
            tensor<int32, [3]> var_2607 = const()[name = tensor<string, []>("op_2607"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_453_cast = reshape(shape = var_2607, x = attn_weights_171_cast)[name = tensor<string, []>("input_453_cast")];
            tensor<fp16, [20, 77, 77]> input_455_cast = softmax(axis = var_5, x = input_453_cast)[name = tensor<string, []>("input_455_cast")];
            tensor<bool, []> attn_output_169_transpose_x_0 = const()[name = tensor<string, []>("attn_output_169_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_169_transpose_y_0 = const()[name = tensor<string, []>("attn_output_169_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_169_cast = matmul(transpose_x = attn_output_169_transpose_x_0, transpose_y = attn_output_169_transpose_y_0, x = input_455_cast, y = value_states_115_cast)[name = tensor<string, []>("attn_output_169_cast")];
            tensor<int32, [4]> var_2612 = const()[name = tensor<string, []>("op_2612"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_171_cast = reshape(shape = var_2612, x = attn_output_169_cast)[name = tensor<string, []>("attn_output_171_cast")];
            tensor<int32, [4]> attn_output_173_perm_0 = const()[name = tensor<string, []>("attn_output_173_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2615 = const()[name = tensor<string, []>("op_2615"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_16 = transpose(perm = attn_output_173_perm_0, x = attn_output_171_cast)[name = tensor<string, []>("transpose_16")];
            tensor<fp16, [1, 77, 1280]> input_457_cast = reshape(shape = var_2615, x = transpose_16)[name = tensor<string, []>("input_457_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1238502784)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241779648)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_171_cast = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16, x = input_457_cast)[name = tensor<string, []>("hidden_states_171_cast")];
            tensor<fp16, [1, 77, 1280]> input_459_cast = add(x = input_451_cast, y = hidden_states_171_cast)[name = tensor<string, []>("input_459_cast")];
            tensor<int32, [1]> input_461_axes_0 = const()[name = tensor<string, []>("input_461_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241782272)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241784896)))];
            tensor<fp16, [1, 77, 1280]> input_461_cast = layer_norm(axes = input_461_axes_0, beta = text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16, x = input_459_cast)[name = tensor<string, []>("input_461_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241787520)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1254894784)))];
            tensor<fp16, [1, 77, 5120]> input_463_cast = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16, x = input_461_cast)[name = tensor<string, []>("input_463_cast")];
            tensor<string, []> input_465_mode_0 = const()[name = tensor<string, []>("input_465_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_465_cast = gelu(mode = input_465_mode_0, x = input_463_cast)[name = tensor<string, []>("input_465_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1254905088)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268012352)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_173_cast = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16, x = input_465_cast)[name = tensor<string, []>("hidden_states_173_cast")];
            tensor<fp16, [1, 77, 1280]> input_467_cast = add(x = input_459_cast, y = hidden_states_173_cast)[name = tensor<string, []>("input_467_cast")];
            tensor<int32, [1]> hidden_states_175_axes_0 = const()[name = tensor<string, []>("hidden_states_175_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268014976)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268017600)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_175_cast = layer_norm(axes = hidden_states_175_axes_0, beta = text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16, x = input_467_cast)[name = tensor<string, []>("hidden_states_175_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268020224)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1271297088)))];
            tensor<fp16, [1, 77, 1280]> var_2653_cast = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16, x = hidden_states_175_cast)[name = tensor<string, []>("op_2653_cast")];
            tensor<fp16, []> var_2654_to_fp16 = const()[name = tensor<string, []>("op_2654_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_179_cast = mul(x = var_2653_cast, y = var_2654_to_fp16)[name = tensor<string, []>("tensor_179_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1271299712)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1274576576)))];
            tensor<fp16, [1, 77, 1280]> tensor_175_cast = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16, x = hidden_states_175_cast)[name = tensor<string, []>("tensor_175_cast")];
            tensor<int32, [4]> var_2659 = const()[name = tensor<string, []>("op_2659"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2660_cast = reshape(shape = var_2659, x = tensor_175_cast)[name = tensor<string, []>("op_2660_cast")];
            tensor<int32, [4]> var_2661_perm_0 = const()[name = tensor<string, []>("op_2661_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1274579200)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1277856064)))];
            tensor<fp16, [1, 77, 1280]> tensor_177_cast = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16, x = hidden_states_175_cast)[name = tensor<string, []>("tensor_177_cast")];
            tensor<int32, [4]> var_2666 = const()[name = tensor<string, []>("op_2666"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2667_cast = reshape(shape = var_2666, x = tensor_177_cast)[name = tensor<string, []>("op_2667_cast")];
            tensor<int32, [4]> var_2668_perm_0 = const()[name = tensor<string, []>("op_2668_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2675 = const()[name = tensor<string, []>("op_2675"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2676_cast = reshape(shape = var_2675, x = tensor_179_cast)[name = tensor<string, []>("op_2676_cast")];
            tensor<int32, [4]> var_2677_perm_0 = const()[name = tensor<string, []>("op_2677_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2679 = const()[name = tensor<string, []>("op_2679"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_13 = transpose(perm = var_2677_perm_0, x = var_2676_cast)[name = tensor<string, []>("transpose_13")];
            tensor<fp16, [20, 77, 64]> query_states_59_cast = reshape(shape = var_2679, x = transpose_13)[name = tensor<string, []>("query_states_59_cast")];
            tensor<int32, [3]> var_2681 = const()[name = tensor<string, []>("op_2681"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_15 = transpose(perm = var_2661_perm_0, x = var_2660_cast)[name = tensor<string, []>("transpose_15")];
            tensor<fp16, [20, 77, 64]> key_states_119_cast = reshape(shape = var_2681, x = transpose_15)[name = tensor<string, []>("key_states_119_cast")];
            tensor<int32, [3]> var_2683 = const()[name = tensor<string, []>("op_2683"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_14 = transpose(perm = var_2668_perm_0, x = var_2667_cast)[name = tensor<string, []>("transpose_14")];
            tensor<fp16, [20, 77, 64]> value_states_119_cast = reshape(shape = var_2683, x = transpose_14)[name = tensor<string, []>("value_states_119_cast")];
            tensor<int32, [3]> var_2686_perm_0 = const()[name = tensor<string, []>("op_2686_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_175_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_175_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_175_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_175_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_12 = transpose(perm = var_2686_perm_0, x = key_states_119_cast)[name = tensor<string, []>("transpose_12")];
            tensor<fp16, [20, 77, 77]> attn_weights_175_cast = matmul(transpose_x = attn_weights_175_transpose_x_0, transpose_y = attn_weights_175_transpose_y_0, x = query_states_59_cast, y = transpose_12)[name = tensor<string, []>("attn_weights_175_cast")];
            tensor<int32, [4]> var_2688 = const()[name = tensor<string, []>("op_2688"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2689_cast = reshape(shape = var_2688, x = attn_weights_175_cast)[name = tensor<string, []>("op_2689_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_177_cast = add(x = var_2689_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_177_cast")];
            tensor<int32, [3]> var_2694 = const()[name = tensor<string, []>("op_2694"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_469_cast = reshape(shape = var_2694, x = attn_weights_177_cast)[name = tensor<string, []>("input_469_cast")];
            tensor<fp16, [20, 77, 77]> input_471_cast = softmax(axis = var_5, x = input_469_cast)[name = tensor<string, []>("input_471_cast")];
            tensor<bool, []> attn_output_175_transpose_x_0 = const()[name = tensor<string, []>("attn_output_175_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_175_transpose_y_0 = const()[name = tensor<string, []>("attn_output_175_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_175_cast = matmul(transpose_x = attn_output_175_transpose_x_0, transpose_y = attn_output_175_transpose_y_0, x = input_471_cast, y = value_states_119_cast)[name = tensor<string, []>("attn_output_175_cast")];
            tensor<int32, [4]> var_2699 = const()[name = tensor<string, []>("op_2699"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_177_cast = reshape(shape = var_2699, x = attn_output_175_cast)[name = tensor<string, []>("attn_output_177_cast")];
            tensor<int32, [4]> attn_output_179_perm_0 = const()[name = tensor<string, []>("attn_output_179_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2702 = const()[name = tensor<string, []>("op_2702"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_11 = transpose(perm = attn_output_179_perm_0, x = attn_output_177_cast)[name = tensor<string, []>("transpose_11")];
            tensor<fp16, [1, 77, 1280]> input_473_cast = reshape(shape = var_2702, x = transpose_11)[name = tensor<string, []>("input_473_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1277858688)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281135552)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_177_cast = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16, x = input_473_cast)[name = tensor<string, []>("hidden_states_177_cast")];
            tensor<fp16, [1, 77, 1280]> input_475_cast = add(x = input_467_cast, y = hidden_states_177_cast)[name = tensor<string, []>("input_475_cast")];
            tensor<int32, [1]> input_477_axes_0 = const()[name = tensor<string, []>("input_477_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281138176)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281140800)))];
            tensor<fp16, [1, 77, 1280]> input_477_cast = layer_norm(axes = input_477_axes_0, beta = text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16, x = input_475_cast)[name = tensor<string, []>("input_477_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281143424)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1294250688)))];
            tensor<fp16, [1, 77, 5120]> input_479_cast = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16, x = input_477_cast)[name = tensor<string, []>("input_479_cast")];
            tensor<string, []> input_481_mode_0 = const()[name = tensor<string, []>("input_481_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_481_cast = gelu(mode = input_481_mode_0, x = input_479_cast)[name = tensor<string, []>("input_481_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1294260992)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307368256)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_179_cast = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16, x = input_481_cast)[name = tensor<string, []>("hidden_states_179_cast")];
            tensor<fp16, [1, 77, 1280]> input_483_cast = add(x = input_475_cast, y = hidden_states_179_cast)[name = tensor<string, []>("input_483_cast")];
            tensor<int32, [1]> hidden_states_181_axes_0 = const()[name = tensor<string, []>("hidden_states_181_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307370880)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307373504)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_181_cast = layer_norm(axes = hidden_states_181_axes_0, beta = text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16, x = input_483_cast)[name = tensor<string, []>("hidden_states_181_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307376128)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310652992)))];
            tensor<fp16, [1, 77, 1280]> var_2740_cast = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16, x = hidden_states_181_cast)[name = tensor<string, []>("op_2740_cast")];
            tensor<fp16, []> var_2741_to_fp16 = const()[name = tensor<string, []>("op_2741_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_185_cast = mul(x = var_2740_cast, y = var_2741_to_fp16)[name = tensor<string, []>("tensor_185_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310655616)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1313932480)))];
            tensor<fp16, [1, 77, 1280]> tensor_181_cast = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16, x = hidden_states_181_cast)[name = tensor<string, []>("tensor_181_cast")];
            tensor<int32, [4]> var_2746 = const()[name = tensor<string, []>("op_2746"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2747_cast = reshape(shape = var_2746, x = tensor_181_cast)[name = tensor<string, []>("op_2747_cast")];
            tensor<int32, [4]> var_2748_perm_0 = const()[name = tensor<string, []>("op_2748_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1313935104)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317211968)))];
            tensor<fp16, [1, 77, 1280]> tensor_183_cast = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16, x = hidden_states_181_cast)[name = tensor<string, []>("tensor_183_cast")];
            tensor<int32, [4]> var_2753 = const()[name = tensor<string, []>("op_2753"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2754_cast = reshape(shape = var_2753, x = tensor_183_cast)[name = tensor<string, []>("op_2754_cast")];
            tensor<int32, [4]> var_2755_perm_0 = const()[name = tensor<string, []>("op_2755_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2762 = const()[name = tensor<string, []>("op_2762"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2763_cast = reshape(shape = var_2762, x = tensor_185_cast)[name = tensor<string, []>("op_2763_cast")];
            tensor<int32, [4]> var_2764_perm_0 = const()[name = tensor<string, []>("op_2764_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2766 = const()[name = tensor<string, []>("op_2766"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_8 = transpose(perm = var_2764_perm_0, x = var_2763_cast)[name = tensor<string, []>("transpose_8")];
            tensor<fp16, [20, 77, 64]> query_states_61_cast = reshape(shape = var_2766, x = transpose_8)[name = tensor<string, []>("query_states_61_cast")];
            tensor<int32, [3]> var_2768 = const()[name = tensor<string, []>("op_2768"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_10 = transpose(perm = var_2748_perm_0, x = var_2747_cast)[name = tensor<string, []>("transpose_10")];
            tensor<fp16, [20, 77, 64]> key_states_123_cast = reshape(shape = var_2768, x = transpose_10)[name = tensor<string, []>("key_states_123_cast")];
            tensor<int32, [3]> var_2770 = const()[name = tensor<string, []>("op_2770"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_9 = transpose(perm = var_2755_perm_0, x = var_2754_cast)[name = tensor<string, []>("transpose_9")];
            tensor<fp16, [20, 77, 64]> value_states_123_cast = reshape(shape = var_2770, x = transpose_9)[name = tensor<string, []>("value_states_123_cast")];
            tensor<int32, [3]> var_2773_perm_0 = const()[name = tensor<string, []>("op_2773_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_181_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_181_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_181_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_181_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_7 = transpose(perm = var_2773_perm_0, x = key_states_123_cast)[name = tensor<string, []>("transpose_7")];
            tensor<fp16, [20, 77, 77]> attn_weights_181_cast = matmul(transpose_x = attn_weights_181_transpose_x_0, transpose_y = attn_weights_181_transpose_y_0, x = query_states_61_cast, y = transpose_7)[name = tensor<string, []>("attn_weights_181_cast")];
            tensor<int32, [4]> var_2775 = const()[name = tensor<string, []>("op_2775"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2776_cast = reshape(shape = var_2775, x = attn_weights_181_cast)[name = tensor<string, []>("op_2776_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_183_cast = add(x = var_2776_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_183_cast")];
            tensor<int32, [3]> var_2781 = const()[name = tensor<string, []>("op_2781"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_485_cast = reshape(shape = var_2781, x = attn_weights_183_cast)[name = tensor<string, []>("input_485_cast")];
            tensor<fp16, [20, 77, 77]> input_487_cast = softmax(axis = var_5, x = input_485_cast)[name = tensor<string, []>("input_487_cast")];
            tensor<bool, []> attn_output_181_transpose_x_0 = const()[name = tensor<string, []>("attn_output_181_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_181_transpose_y_0 = const()[name = tensor<string, []>("attn_output_181_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_181_cast = matmul(transpose_x = attn_output_181_transpose_x_0, transpose_y = attn_output_181_transpose_y_0, x = input_487_cast, y = value_states_123_cast)[name = tensor<string, []>("attn_output_181_cast")];
            tensor<int32, [4]> var_2786 = const()[name = tensor<string, []>("op_2786"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_183_cast = reshape(shape = var_2786, x = attn_output_181_cast)[name = tensor<string, []>("attn_output_183_cast")];
            tensor<int32, [4]> attn_output_185_perm_0 = const()[name = tensor<string, []>("attn_output_185_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2789 = const()[name = tensor<string, []>("op_2789"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_6 = transpose(perm = attn_output_185_perm_0, x = attn_output_183_cast)[name = tensor<string, []>("transpose_6")];
            tensor<fp16, [1, 77, 1280]> input_489_cast = reshape(shape = var_2789, x = transpose_6)[name = tensor<string, []>("input_489_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317214592)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320491456)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_183_cast = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16, x = input_489_cast)[name = tensor<string, []>("hidden_states_183_cast")];
            tensor<fp16, [1, 77, 1280]> input_491_cast = add(x = input_483_cast, y = hidden_states_183_cast)[name = tensor<string, []>("input_491_cast")];
            tensor<int32, [1]> input_493_axes_0 = const()[name = tensor<string, []>("input_493_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320494080)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320496704)))];
            tensor<fp16, [1, 77, 1280]> input_493_cast = layer_norm(axes = input_493_axes_0, beta = text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16, x = input_491_cast)[name = tensor<string, []>("input_493_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320499328)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333606592)))];
            tensor<fp16, [1, 77, 5120]> input_495_cast = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16, x = input_493_cast)[name = tensor<string, []>("input_495_cast")];
            tensor<string, []> input_497_mode_0 = const()[name = tensor<string, []>("input_497_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_497_cast = gelu(mode = input_497_mode_0, x = input_495_cast)[name = tensor<string, []>("input_497_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333616896)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346724160)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_185_cast = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16, x = input_497_cast)[name = tensor<string, []>("hidden_states_185_cast")];
            tensor<fp16, [1, 77, 1280]> input_499_cast = add(x = input_491_cast, y = hidden_states_185_cast)[name = tensor<string, []>("input_499_cast")];
            tensor<string, []> input_499_cast_to_fp32_dtype_0 = const()[name = tensor<string, []>("input_499_cast_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<int32, [1]> hidden_states_187_axes_0 = const()[name = tensor<string, []>("hidden_states_187_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346726784)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346729408)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_187_cast = layer_norm(axes = hidden_states_187_axes_0, beta = text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16, x = input_499_cast)[name = tensor<string, []>("hidden_states_187_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346732032)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350008896)))];
            tensor<fp16, [1, 77, 1280]> var_2827_cast = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16, x = hidden_states_187_cast)[name = tensor<string, []>("op_2827_cast")];
            tensor<fp16, []> var_2828_to_fp16 = const()[name = tensor<string, []>("op_2828_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_cast = mul(x = var_2827_cast, y = var_2828_to_fp16)[name = tensor<string, []>("tensor_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350011520)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1353288384)))];
            tensor<fp16, [1, 77, 1280]> tensor_187_cast = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16, x = hidden_states_187_cast)[name = tensor<string, []>("tensor_187_cast")];
            tensor<int32, [4]> var_2833 = const()[name = tensor<string, []>("op_2833"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2834_cast = reshape(shape = var_2833, x = tensor_187_cast)[name = tensor<string, []>("op_2834_cast")];
            tensor<int32, [4]> var_2835_perm_0 = const()[name = tensor<string, []>("op_2835_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1353291008)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1356567872)))];
            tensor<fp16, [1, 77, 1280]> tensor_189_cast = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16, x = hidden_states_187_cast)[name = tensor<string, []>("tensor_189_cast")];
            tensor<int32, [4]> var_2840 = const()[name = tensor<string, []>("op_2840"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2841_cast = reshape(shape = var_2840, x = tensor_189_cast)[name = tensor<string, []>("op_2841_cast")];
            tensor<int32, [4]> var_2842_perm_0 = const()[name = tensor<string, []>("op_2842_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2849 = const()[name = tensor<string, []>("op_2849"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2850_cast = reshape(shape = var_2849, x = tensor_cast)[name = tensor<string, []>("op_2850_cast")];
            tensor<int32, [4]> var_2851_perm_0 = const()[name = tensor<string, []>("op_2851_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2853 = const()[name = tensor<string, []>("op_2853"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_3 = transpose(perm = var_2851_perm_0, x = var_2850_cast)[name = tensor<string, []>("transpose_3")];
            tensor<fp16, [20, 77, 64]> query_states_cast = reshape(shape = var_2853, x = transpose_3)[name = tensor<string, []>("query_states_cast")];
            tensor<int32, [3]> var_2855 = const()[name = tensor<string, []>("op_2855"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_5 = transpose(perm = var_2835_perm_0, x = var_2834_cast)[name = tensor<string, []>("transpose_5")];
            tensor<fp16, [20, 77, 64]> key_states_cast = reshape(shape = var_2855, x = transpose_5)[name = tensor<string, []>("key_states_cast")];
            tensor<int32, [3]> var_2857 = const()[name = tensor<string, []>("op_2857"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> transpose_4 = transpose(perm = var_2842_perm_0, x = var_2841_cast)[name = tensor<string, []>("transpose_4")];
            tensor<fp16, [20, 77, 64]> value_states_cast = reshape(shape = var_2857, x = transpose_4)[name = tensor<string, []>("value_states_cast")];
            tensor<int32, [3]> var_2860_perm_0 = const()[name = tensor<string, []>("op_2860_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, []> attn_weights_187_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_187_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_187_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_187_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 64, 77]> transpose_2 = transpose(perm = var_2860_perm_0, x = key_states_cast)[name = tensor<string, []>("transpose_2")];
            tensor<fp16, [20, 77, 77]> attn_weights_187_cast = matmul(transpose_x = attn_weights_187_transpose_x_0, transpose_y = attn_weights_187_transpose_y_0, x = query_states_cast, y = transpose_2)[name = tensor<string, []>("attn_weights_187_cast")];
            tensor<int32, [4]> var_2862 = const()[name = tensor<string, []>("op_2862"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2863_cast = reshape(shape = var_2862, x = attn_weights_187_cast)[name = tensor<string, []>("op_2863_cast")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_189_cast = add(x = var_2863_cast, y = causal_attention_mask_to_fp16)[name = tensor<string, []>("attn_weights_189_cast")];
            tensor<int32, [3]> var_2868 = const()[name = tensor<string, []>("op_2868"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_501_cast = reshape(shape = var_2868, x = attn_weights_189_cast)[name = tensor<string, []>("input_501_cast")];
            tensor<fp16, [20, 77, 77]> input_503_cast = softmax(axis = var_5, x = input_501_cast)[name = tensor<string, []>("input_503_cast")];
            tensor<bool, []> attn_output_187_transpose_x_0 = const()[name = tensor<string, []>("attn_output_187_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_187_transpose_y_0 = const()[name = tensor<string, []>("attn_output_187_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_187_cast = matmul(transpose_x = attn_output_187_transpose_x_0, transpose_y = attn_output_187_transpose_y_0, x = input_503_cast, y = value_states_cast)[name = tensor<string, []>("attn_output_187_cast")];
            tensor<int32, [4]> var_2873 = const()[name = tensor<string, []>("op_2873"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_189_cast = reshape(shape = var_2873, x = attn_output_187_cast)[name = tensor<string, []>("attn_output_189_cast")];
            tensor<int32, [4]> attn_output_perm_0 = const()[name = tensor<string, []>("attn_output_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2876 = const()[name = tensor<string, []>("op_2876"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> transpose_1 = transpose(perm = attn_output_perm_0, x = attn_output_189_cast)[name = tensor<string, []>("transpose_1")];
            tensor<fp16, [1, 77, 1280]> input_505_cast = reshape(shape = var_2876, x = transpose_1)[name = tensor<string, []>("input_505_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1356570496)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359847360)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_189_cast = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16, x = input_505_cast)[name = tensor<string, []>("hidden_states_189_cast")];
            tensor<fp16, [1, 77, 1280]> input_507_cast = add(x = input_499_cast, y = hidden_states_189_cast)[name = tensor<string, []>("input_507_cast")];
            tensor<int32, [1]> input_509_axes_0 = const()[name = tensor<string, []>("input_509_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359849984)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359852608)))];
            tensor<fp16, [1, 77, 1280]> input_509_cast = layer_norm(axes = input_509_axes_0, beta = text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16, x = input_507_cast)[name = tensor<string, []>("input_509_cast")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359855232)))];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1372962496)))];
            tensor<fp16, [1, 77, 5120]> input_511_cast = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16, x = input_509_cast)[name = tensor<string, []>("input_511_cast")];
            tensor<string, []> input_513_mode_0 = const()[name = tensor<string, []>("input_513_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_513_cast = gelu(mode = input_513_mode_0, x = input_511_cast)[name = tensor<string, []>("input_513_cast")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1372972800)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386080064)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_cast = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16, x = input_513_cast)[name = tensor<string, []>("hidden_states_cast")];
            tensor<fp16, [1, 77, 1280]> input_515_cast = add(x = input_507_cast, y = hidden_states_cast)[name = tensor<string, []>("input_515_cast")];
            tensor<int32, [1]> last_hidden_state_axes_0 = const()[name = tensor<string, []>("last_hidden_state_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386082688)))];
            tensor<fp16, [1280]> text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386085312)))];
            tensor<fp16, [1, 77, 1280]> last_hidden_state_cast = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_final_layer_norm_weight_to_fp16, x = input_515_cast)[name = tensor<string, []>("last_hidden_state_cast")];
            tensor<int32, [1]> var_2904 = const()[name = tensor<string, []>("op_2904"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> var_2906 = reduce_argmax(axis = var_5, keep_dims = var_6, x = input_ids)[name = tensor<string, []>("op_2906")];
            tensor<int32, []> stack_0_axis_0 = const()[name = tensor<string, []>("stack_0_axis_0"), val = tensor<int32, []>(1)];
            tensor<int32, [1, 2]> stack_0 = stack(axis = stack_0_axis_0, values = (var_2904, var_2906))[name = tensor<string, []>("stack_0")];
            tensor<int32, []> input_transpose_batch_dims_0 = const()[name = tensor<string, []>("input_transpose_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [1, 1280]> input_transpose_cast = gather_nd(batch_dims = input_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast)[name = tensor<string, []>("input_transpose_cast")];
            tensor<fp16, [1280, 1280]> text_encoder_text_projection_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_projection_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386087936)))];
            tensor<fp16, [1280]> var_2913_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2913_bias_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1389364800)))];
            tensor<fp16, [1, 1280]> var_2913_cast = linear(bias = var_2913_bias_0_to_fp16, weight = text_encoder_text_projection_weight_to_fp16, x = input_transpose_cast)[name = tensor<string, []>("op_2913_cast")];
            tensor<string, []> var_2913_cast_to_fp32_dtype_0 = const()[name = tensor<string, []>("op_2913_cast_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp32, [1, 1280]> pooled_outputs = cast(dtype = var_2913_cast_to_fp32_dtype_0, x = var_2913_cast)[name = tensor<string, []>("cast_325")];
            tensor<fp32, [1, 77, 1280]> last_hidden_state = cast(dtype = input_499_cast_to_fp32_dtype_0, x = input_499_cast)[name = tensor<string, []>("cast_359")];
        } -> (last_hidden_state, pooled_outputs);
}