diff --git "a/original/compiled/TextEncoder2.mlmodelc/model.mil" "b/original/compiled/TextEncoder2.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/original/compiled/TextEncoder2.mlmodelc/model.mil" @@ -0,0 +1,2273 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.4"}, {"coremlc-version", "1436.100.10"}})] +{ + func main(tensor input_ids) { + tensor var_5 = const()[name = tensor("op_5"), val = tensor(-1)]; + tensor var_6 = const()[name = tensor("op_6"), val = tensor(false)]; + tensor inputs_embeds_axis_0 = const()[name = tensor("inputs_embeds_axis_0"), val = tensor(0)]; + tensor inputs_embeds_batch_dims_0 = const()[name = tensor("inputs_embeds_batch_dims_0"), val = tensor(0)]; + tensor text_encoder_text_model_embeddings_token_embedding_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor 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("inputs_embeds_cast")]; + tensor position_embeddings_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126484608))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126558592))), name = tensor("position_embeddings_to_fp16_palettized"), shape = tensor([1, 77, 1280])]; + tensor input_3_cast = add(x = inputs_embeds_cast, y = position_embeddings_to_fp16_palettized)[name = tensor("input_3_cast")]; + tensor hidden_states_1_axes_0 = const()[name = tensor("hidden_states_1_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126558784)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126561408)))]; + tensor var_13_to_fp16 = const()[name = tensor("op_13_to_fp16"), val = tensor(0x1.5p-17)]; + tensor 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("hidden_states_1_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126564032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127792896))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127793088)))]; + tensor 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_palettized, x = hidden_states_1_cast)[name = tensor("op_130_cast")]; + tensor var_131_to_fp16 = const()[name = tensor("op_131_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_5_cast = mul(x = var_130_cast, y = var_131_to_fp16)[name = tensor("tensor_5_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127795712))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129024576))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129024768)))]; + tensor 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_palettized, x = hidden_states_1_cast)[name = tensor("tensor_1_cast")]; + tensor var_136 = const()[name = tensor("op_136"), val = tensor([1, -1, 20, 64])]; + tensor var_137_cast = reshape(shape = var_136, x = tensor_1_cast)[name = tensor("op_137_cast")]; + tensor var_138_perm_0 = const()[name = tensor("op_138_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129027392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130256256))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130256448)))]; + tensor 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_palettized, x = hidden_states_1_cast)[name = tensor("tensor_3_cast")]; + tensor var_143 = const()[name = tensor("op_143"), val = tensor([1, -1, 20, 64])]; + tensor var_144_cast = reshape(shape = var_143, x = tensor_3_cast)[name = tensor("op_144_cast")]; + tensor var_145_perm_0 = const()[name = tensor("op_145_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_152 = const()[name = tensor("op_152"), val = tensor([1, 77, 20, 64])]; + tensor var_153_cast = reshape(shape = var_152, x = tensor_5_cast)[name = tensor("op_153_cast")]; + tensor var_154_perm_0 = const()[name = tensor("op_154_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_156 = const()[name = tensor("op_156"), val = tensor([20, -1, 64])]; + tensor transpose_159 = transpose(perm = var_154_perm_0, x = var_153_cast)[name = tensor("transpose_159")]; + tensor query_states_1_cast = reshape(shape = var_156, x = transpose_159)[name = tensor("query_states_1_cast")]; + tensor var_158 = const()[name = tensor("op_158"), val = tensor([20, -1, 64])]; + tensor transpose_158 = transpose(perm = var_138_perm_0, x = var_137_cast)[name = tensor("transpose_158")]; + tensor key_states_3_cast = reshape(shape = var_158, x = transpose_158)[name = tensor("key_states_3_cast")]; + tensor var_160 = const()[name = tensor("op_160"), val = tensor([20, -1, 64])]; + tensor transpose_157 = transpose(perm = var_145_perm_0, x = var_144_cast)[name = tensor("transpose_157")]; + tensor value_states_3_cast = reshape(shape = var_160, x = transpose_157)[name = tensor("value_states_3_cast")]; + tensor var_163_perm_0 = const()[name = tensor("op_163_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_1_transpose_x_0 = const()[name = tensor("attn_weights_1_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_1_transpose_y_0 = const()[name = tensor("attn_weights_1_transpose_y_0"), val = tensor(false)]; + tensor transpose_156 = transpose(perm = var_163_perm_0, x = key_states_3_cast)[name = tensor("transpose_156")]; + tensor 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_156)[name = tensor("attn_weights_1_cast")]; + tensor var_165 = const()[name = tensor("op_165"), val = tensor([1, 20, 77, 77])]; + tensor var_166_cast = reshape(shape = var_165, x = attn_weights_1_cast)[name = tensor("op_166_cast")]; + tensor causal_attention_mask_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130259072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130263616))), name = tensor("causal_attention_mask_to_fp16_palettized"), shape = tensor([1, 1, 77, 77])]; + tensor attn_weights_3_cast = add(x = var_166_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_3_cast")]; + tensor var_171 = const()[name = tensor("op_171"), val = tensor([20, 77, 77])]; + tensor input_5_cast = reshape(shape = var_171, x = attn_weights_3_cast)[name = tensor("input_5_cast")]; + tensor input_7_cast = softmax(axis = var_5, x = input_5_cast)[name = tensor("input_7_cast")]; + tensor attn_output_1_transpose_x_0 = const()[name = tensor("attn_output_1_transpose_x_0"), val = tensor(false)]; + tensor attn_output_1_transpose_y_0 = const()[name = tensor("attn_output_1_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_1_cast")]; + tensor var_176 = const()[name = tensor("op_176"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_3_cast = reshape(shape = var_176, x = attn_output_1_cast)[name = tensor("attn_output_3_cast")]; + tensor attn_output_5_perm_0 = const()[name = tensor("attn_output_5_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_179 = const()[name = tensor("op_179"), val = tensor([1, 77, 1280])]; + tensor transpose_155 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast)[name = tensor("transpose_155")]; + tensor input_9_cast = reshape(shape = var_179, x = transpose_155)[name = tensor("input_9_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130263808))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131492672))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131492864)))]; + tensor 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_palettized, x = input_9_cast)[name = tensor("hidden_states_3_cast")]; + tensor input_11_cast = add(x = input_3_cast, y = hidden_states_3_cast)[name = tensor("input_11_cast")]; + tensor input_13_axes_0 = const()[name = tensor("input_13_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131495488)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131498112)))]; + tensor 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("input_13_cast")]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131500736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136416000))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136416192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136420096))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_15_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized, x = input_13_cast)[name = tensor("input_15_cast")]; + tensor input_17_mode_0 = const()[name = tensor("input_17_mode_0"), val = tensor("EXACT")]; + tensor input_17_cast = gelu(mode = input_17_mode_0, x = input_15_cast)[name = tensor("input_17_cast")]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136420288))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141335552))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141335744)))]; + tensor 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_palettized, x = input_17_cast)[name = tensor("hidden_states_5_cast")]; + tensor input_19_cast = add(x = input_11_cast, y = hidden_states_5_cast)[name = tensor("input_19_cast")]; + tensor hidden_states_7_axes_0 = const()[name = tensor("hidden_states_7_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141338368)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141340992)))]; + tensor 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("hidden_states_7_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141343616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142572480))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142572672)))]; + tensor 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_palettized, x = hidden_states_7_cast)[name = tensor("op_217_cast")]; + tensor var_218_to_fp16 = const()[name = tensor("op_218_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_11_cast = mul(x = var_217_cast, y = var_218_to_fp16)[name = tensor("tensor_11_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142575296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143804160))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143804352)))]; + tensor 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_palettized, x = hidden_states_7_cast)[name = tensor("tensor_7_cast")]; + tensor var_223 = const()[name = tensor("op_223"), val = tensor([1, -1, 20, 64])]; + tensor var_224_cast = reshape(shape = var_223, x = tensor_7_cast)[name = tensor("op_224_cast")]; + tensor var_225_perm_0 = const()[name = tensor("op_225_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143806976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145035840))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145036032)))]; + tensor 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_palettized, x = hidden_states_7_cast)[name = tensor("tensor_9_cast")]; + tensor var_230 = const()[name = tensor("op_230"), val = tensor([1, -1, 20, 64])]; + tensor var_231_cast = reshape(shape = var_230, x = tensor_9_cast)[name = tensor("op_231_cast")]; + tensor var_232_perm_0 = const()[name = tensor("op_232_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_239 = const()[name = tensor("op_239"), val = tensor([1, 77, 20, 64])]; + tensor var_240_cast = reshape(shape = var_239, x = tensor_11_cast)[name = tensor("op_240_cast")]; + tensor var_241_perm_0 = const()[name = tensor("op_241_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_243 = const()[name = tensor("op_243"), val = tensor([20, -1, 64])]; + tensor transpose_154 = transpose(perm = var_241_perm_0, x = var_240_cast)[name = tensor("transpose_154")]; + tensor query_states_3_cast = reshape(shape = var_243, x = transpose_154)[name = tensor("query_states_3_cast")]; + tensor var_245 = const()[name = tensor("op_245"), val = tensor([20, -1, 64])]; + tensor transpose_153 = transpose(perm = var_225_perm_0, x = var_224_cast)[name = tensor("transpose_153")]; + tensor key_states_7_cast = reshape(shape = var_245, x = transpose_153)[name = tensor("key_states_7_cast")]; + tensor var_247 = const()[name = tensor("op_247"), val = tensor([20, -1, 64])]; + tensor transpose_152 = transpose(perm = var_232_perm_0, x = var_231_cast)[name = tensor("transpose_152")]; + tensor value_states_7_cast = reshape(shape = var_247, x = transpose_152)[name = tensor("value_states_7_cast")]; + tensor var_250_perm_0 = const()[name = tensor("op_250_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_7_transpose_x_0 = const()[name = tensor("attn_weights_7_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_7_transpose_y_0 = const()[name = tensor("attn_weights_7_transpose_y_0"), val = tensor(false)]; + tensor transpose_151 = transpose(perm = var_250_perm_0, x = key_states_7_cast)[name = tensor("transpose_151")]; + tensor 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_151)[name = tensor("attn_weights_7_cast")]; + tensor var_252 = const()[name = tensor("op_252"), val = tensor([1, 20, 77, 77])]; + tensor var_253_cast = reshape(shape = var_252, x = attn_weights_7_cast)[name = tensor("op_253_cast")]; + tensor attn_weights_9_cast = add(x = var_253_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_9_cast")]; + tensor var_258 = const()[name = tensor("op_258"), val = tensor([20, 77, 77])]; + tensor input_21_cast = reshape(shape = var_258, x = attn_weights_9_cast)[name = tensor("input_21_cast")]; + tensor input_23_cast = softmax(axis = var_5, x = input_21_cast)[name = tensor("input_23_cast")]; + tensor attn_output_7_transpose_x_0 = const()[name = tensor("attn_output_7_transpose_x_0"), val = tensor(false)]; + tensor attn_output_7_transpose_y_0 = const()[name = tensor("attn_output_7_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_7_cast")]; + tensor var_263 = const()[name = tensor("op_263"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_9_cast = reshape(shape = var_263, x = attn_output_7_cast)[name = tensor("attn_output_9_cast")]; + tensor attn_output_11_perm_0 = const()[name = tensor("attn_output_11_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_266 = const()[name = tensor("op_266"), val = tensor([1, 77, 1280])]; + tensor transpose_150 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast)[name = tensor("transpose_150")]; + tensor input_25_cast = reshape(shape = var_266, x = transpose_150)[name = tensor("input_25_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145038656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146267520))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146267712)))]; + tensor 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_palettized, x = input_25_cast)[name = tensor("hidden_states_9_cast")]; + tensor input_27_cast = add(x = input_19_cast, y = hidden_states_9_cast)[name = tensor("input_27_cast")]; + tensor input_29_axes_0 = const()[name = tensor("input_29_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146270336)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146272960)))]; + tensor 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("input_29_cast")]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146275584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151190848))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151191040))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151194944))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_31_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized, x = input_29_cast)[name = tensor("input_31_cast")]; + tensor input_33_mode_0 = const()[name = tensor("input_33_mode_0"), val = tensor("EXACT")]; + tensor input_33_cast = gelu(mode = input_33_mode_0, x = input_31_cast)[name = tensor("input_33_cast")]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151195136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156110400))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156110592)))]; + tensor 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_palettized, x = input_33_cast)[name = tensor("hidden_states_11_cast")]; + tensor input_35_cast = add(x = input_27_cast, y = hidden_states_11_cast)[name = tensor("input_35_cast")]; + tensor hidden_states_13_axes_0 = const()[name = tensor("hidden_states_13_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156113216)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156115840)))]; + tensor 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("hidden_states_13_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156118464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157347328))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157347520)))]; + tensor 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_palettized, x = hidden_states_13_cast)[name = tensor("op_304_cast")]; + tensor var_305_to_fp16 = const()[name = tensor("op_305_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_17_cast = mul(x = var_304_cast, y = var_305_to_fp16)[name = tensor("tensor_17_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157350144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158579008))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158579200)))]; + tensor 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_palettized, x = hidden_states_13_cast)[name = tensor("tensor_13_cast")]; + tensor var_310 = const()[name = tensor("op_310"), val = tensor([1, -1, 20, 64])]; + tensor var_311_cast = reshape(shape = var_310, x = tensor_13_cast)[name = tensor("op_311_cast")]; + tensor var_312_perm_0 = const()[name = tensor("op_312_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158581824))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159810688))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159810880)))]; + tensor 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_palettized, x = hidden_states_13_cast)[name = tensor("tensor_15_cast")]; + tensor var_317 = const()[name = tensor("op_317"), val = tensor([1, -1, 20, 64])]; + tensor var_318_cast = reshape(shape = var_317, x = tensor_15_cast)[name = tensor("op_318_cast")]; + tensor var_319_perm_0 = const()[name = tensor("op_319_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_326 = const()[name = tensor("op_326"), val = tensor([1, 77, 20, 64])]; + tensor var_327_cast = reshape(shape = var_326, x = tensor_17_cast)[name = tensor("op_327_cast")]; + tensor var_328_perm_0 = const()[name = tensor("op_328_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_330 = const()[name = tensor("op_330"), val = tensor([20, -1, 64])]; + tensor transpose_149 = transpose(perm = var_328_perm_0, x = var_327_cast)[name = tensor("transpose_149")]; + tensor query_states_5_cast = reshape(shape = var_330, x = transpose_149)[name = tensor("query_states_5_cast")]; + tensor var_332 = const()[name = tensor("op_332"), val = tensor([20, -1, 64])]; + tensor transpose_148 = transpose(perm = var_312_perm_0, x = var_311_cast)[name = tensor("transpose_148")]; + tensor key_states_11_cast = reshape(shape = var_332, x = transpose_148)[name = tensor("key_states_11_cast")]; + tensor var_334 = const()[name = tensor("op_334"), val = tensor([20, -1, 64])]; + tensor transpose_147 = transpose(perm = var_319_perm_0, x = var_318_cast)[name = tensor("transpose_147")]; + tensor value_states_11_cast = reshape(shape = var_334, x = transpose_147)[name = tensor("value_states_11_cast")]; + tensor var_337_perm_0 = const()[name = tensor("op_337_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_13_transpose_x_0 = const()[name = tensor("attn_weights_13_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_13_transpose_y_0 = const()[name = tensor("attn_weights_13_transpose_y_0"), val = tensor(false)]; + tensor transpose_146 = transpose(perm = var_337_perm_0, x = key_states_11_cast)[name = tensor("transpose_146")]; + tensor 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_146)[name = tensor("attn_weights_13_cast")]; + tensor var_339 = const()[name = tensor("op_339"), val = tensor([1, 20, 77, 77])]; + tensor var_340_cast = reshape(shape = var_339, x = attn_weights_13_cast)[name = tensor("op_340_cast")]; + tensor attn_weights_15_cast = add(x = var_340_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_15_cast")]; + tensor var_345 = const()[name = tensor("op_345"), val = tensor([20, 77, 77])]; + tensor input_37_cast = reshape(shape = var_345, x = attn_weights_15_cast)[name = tensor("input_37_cast")]; + tensor input_39_cast = softmax(axis = var_5, x = input_37_cast)[name = tensor("input_39_cast")]; + tensor attn_output_13_transpose_x_0 = const()[name = tensor("attn_output_13_transpose_x_0"), val = tensor(false)]; + tensor attn_output_13_transpose_y_0 = const()[name = tensor("attn_output_13_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_13_cast")]; + tensor var_350 = const()[name = tensor("op_350"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_15_cast = reshape(shape = var_350, x = attn_output_13_cast)[name = tensor("attn_output_15_cast")]; + tensor attn_output_17_perm_0 = const()[name = tensor("attn_output_17_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_353 = const()[name = tensor("op_353"), val = tensor([1, 77, 1280])]; + tensor transpose_145 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast)[name = tensor("transpose_145")]; + tensor input_41_cast = reshape(shape = var_353, x = transpose_145)[name = tensor("input_41_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159813504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161042368))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161042560)))]; + tensor 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_palettized, x = input_41_cast)[name = tensor("hidden_states_15_cast")]; + tensor input_43_cast = add(x = input_35_cast, y = hidden_states_15_cast)[name = tensor("input_43_cast")]; + tensor input_45_axes_0 = const()[name = tensor("input_45_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161045184)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161047808)))]; + tensor 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("input_45_cast")]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161050432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165965696))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165965888))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165969792))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_47_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized, x = input_45_cast)[name = tensor("input_47_cast")]; + tensor input_49_mode_0 = const()[name = tensor("input_49_mode_0"), val = tensor("EXACT")]; + tensor input_49_cast = gelu(mode = input_49_mode_0, x = input_47_cast)[name = tensor("input_49_cast")]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165969984))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170885248))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170885440)))]; + tensor 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_palettized, x = input_49_cast)[name = tensor("hidden_states_17_cast")]; + tensor input_51_cast = add(x = input_43_cast, y = hidden_states_17_cast)[name = tensor("input_51_cast")]; + tensor hidden_states_19_axes_0 = const()[name = tensor("hidden_states_19_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170888064)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170890688)))]; + tensor 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("hidden_states_19_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170893312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172122176))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172122368)))]; + tensor 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_palettized, x = hidden_states_19_cast)[name = tensor("op_391_cast")]; + tensor var_392_to_fp16 = const()[name = tensor("op_392_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_23_cast = mul(x = var_391_cast, y = var_392_to_fp16)[name = tensor("tensor_23_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172124992))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173353856))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173354048)))]; + tensor 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_palettized, x = hidden_states_19_cast)[name = tensor("tensor_19_cast")]; + tensor var_397 = const()[name = tensor("op_397"), val = tensor([1, -1, 20, 64])]; + tensor var_398_cast = reshape(shape = var_397, x = tensor_19_cast)[name = tensor("op_398_cast")]; + tensor var_399_perm_0 = const()[name = tensor("op_399_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173356672))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174585536))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174585728)))]; + tensor 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_palettized, x = hidden_states_19_cast)[name = tensor("tensor_21_cast")]; + tensor var_404 = const()[name = tensor("op_404"), val = tensor([1, -1, 20, 64])]; + tensor var_405_cast = reshape(shape = var_404, x = tensor_21_cast)[name = tensor("op_405_cast")]; + tensor var_406_perm_0 = const()[name = tensor("op_406_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_413 = const()[name = tensor("op_413"), val = tensor([1, 77, 20, 64])]; + tensor var_414_cast = reshape(shape = var_413, x = tensor_23_cast)[name = tensor("op_414_cast")]; + tensor var_415_perm_0 = const()[name = tensor("op_415_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_417 = const()[name = tensor("op_417"), val = tensor([20, -1, 64])]; + tensor transpose_144 = transpose(perm = var_415_perm_0, x = var_414_cast)[name = tensor("transpose_144")]; + tensor query_states_7_cast = reshape(shape = var_417, x = transpose_144)[name = tensor("query_states_7_cast")]; + tensor var_419 = const()[name = tensor("op_419"), val = tensor([20, -1, 64])]; + tensor transpose_143 = transpose(perm = var_399_perm_0, x = var_398_cast)[name = tensor("transpose_143")]; + tensor key_states_15_cast = reshape(shape = var_419, x = transpose_143)[name = tensor("key_states_15_cast")]; + tensor var_421 = const()[name = tensor("op_421"), val = tensor([20, -1, 64])]; + tensor transpose_142 = transpose(perm = var_406_perm_0, x = var_405_cast)[name = tensor("transpose_142")]; + tensor value_states_15_cast = reshape(shape = var_421, x = transpose_142)[name = tensor("value_states_15_cast")]; + tensor var_424_perm_0 = const()[name = tensor("op_424_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_19_transpose_x_0 = const()[name = tensor("attn_weights_19_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_19_transpose_y_0 = const()[name = tensor("attn_weights_19_transpose_y_0"), val = tensor(false)]; + tensor transpose_141 = transpose(perm = var_424_perm_0, x = key_states_15_cast)[name = tensor("transpose_141")]; + tensor 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_141)[name = tensor("attn_weights_19_cast")]; + tensor var_426 = const()[name = tensor("op_426"), val = tensor([1, 20, 77, 77])]; + tensor var_427_cast = reshape(shape = var_426, x = attn_weights_19_cast)[name = tensor("op_427_cast")]; + tensor attn_weights_21_cast = add(x = var_427_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_21_cast")]; + tensor var_432 = const()[name = tensor("op_432"), val = tensor([20, 77, 77])]; + tensor input_53_cast = reshape(shape = var_432, x = attn_weights_21_cast)[name = tensor("input_53_cast")]; + tensor input_55_cast = softmax(axis = var_5, x = input_53_cast)[name = tensor("input_55_cast")]; + tensor attn_output_19_transpose_x_0 = const()[name = tensor("attn_output_19_transpose_x_0"), val = tensor(false)]; + tensor attn_output_19_transpose_y_0 = const()[name = tensor("attn_output_19_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_19_cast")]; + tensor var_437 = const()[name = tensor("op_437"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_21_cast = reshape(shape = var_437, x = attn_output_19_cast)[name = tensor("attn_output_21_cast")]; + tensor attn_output_23_perm_0 = const()[name = tensor("attn_output_23_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_440 = const()[name = tensor("op_440"), val = tensor([1, 77, 1280])]; + tensor transpose_140 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast)[name = tensor("transpose_140")]; + tensor input_57_cast = reshape(shape = var_440, x = transpose_140)[name = tensor("input_57_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174588352))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175817216))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175817408)))]; + tensor 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_palettized, x = input_57_cast)[name = tensor("hidden_states_21_cast")]; + tensor input_59_cast = add(x = input_51_cast, y = hidden_states_21_cast)[name = tensor("input_59_cast")]; + tensor input_61_axes_0 = const()[name = tensor("input_61_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175820032)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175822656)))]; + tensor 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("input_61_cast")]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175825280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180740544))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180740736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180744640))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_63_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized, x = input_61_cast)[name = tensor("input_63_cast")]; + tensor input_65_mode_0 = const()[name = tensor("input_65_mode_0"), val = tensor("EXACT")]; + tensor input_65_cast = gelu(mode = input_65_mode_0, x = input_63_cast)[name = tensor("input_65_cast")]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180744832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185660096))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185660288)))]; + tensor 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_palettized, x = input_65_cast)[name = tensor("hidden_states_23_cast")]; + tensor input_67_cast = add(x = input_59_cast, y = hidden_states_23_cast)[name = tensor("input_67_cast")]; + tensor hidden_states_25_axes_0 = const()[name = tensor("hidden_states_25_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185662912)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185665536)))]; + tensor 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("hidden_states_25_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185668160))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186897024))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186897216)))]; + tensor 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_palettized, x = hidden_states_25_cast)[name = tensor("op_478_cast")]; + tensor var_479_to_fp16 = const()[name = tensor("op_479_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_29_cast = mul(x = var_478_cast, y = var_479_to_fp16)[name = tensor("tensor_29_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186899840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188128704))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188128896)))]; + tensor 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_palettized, x = hidden_states_25_cast)[name = tensor("tensor_25_cast")]; + tensor var_484 = const()[name = tensor("op_484"), val = tensor([1, -1, 20, 64])]; + tensor var_485_cast = reshape(shape = var_484, x = tensor_25_cast)[name = tensor("op_485_cast")]; + tensor var_486_perm_0 = const()[name = tensor("op_486_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188131520))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189360384))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189360576)))]; + tensor 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_palettized, x = hidden_states_25_cast)[name = tensor("tensor_27_cast")]; + tensor var_491 = const()[name = tensor("op_491"), val = tensor([1, -1, 20, 64])]; + tensor var_492_cast = reshape(shape = var_491, x = tensor_27_cast)[name = tensor("op_492_cast")]; + tensor var_493_perm_0 = const()[name = tensor("op_493_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_500 = const()[name = tensor("op_500"), val = tensor([1, 77, 20, 64])]; + tensor var_501_cast = reshape(shape = var_500, x = tensor_29_cast)[name = tensor("op_501_cast")]; + tensor var_502_perm_0 = const()[name = tensor("op_502_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_504 = const()[name = tensor("op_504"), val = tensor([20, -1, 64])]; + tensor transpose_139 = transpose(perm = var_502_perm_0, x = var_501_cast)[name = tensor("transpose_139")]; + tensor query_states_9_cast = reshape(shape = var_504, x = transpose_139)[name = tensor("query_states_9_cast")]; + tensor var_506 = const()[name = tensor("op_506"), val = tensor([20, -1, 64])]; + tensor transpose_138 = transpose(perm = var_486_perm_0, x = var_485_cast)[name = tensor("transpose_138")]; + tensor key_states_19_cast = reshape(shape = var_506, x = transpose_138)[name = tensor("key_states_19_cast")]; + tensor var_508 = const()[name = tensor("op_508"), val = tensor([20, -1, 64])]; + tensor transpose_137 = transpose(perm = var_493_perm_0, x = var_492_cast)[name = tensor("transpose_137")]; + tensor value_states_19_cast = reshape(shape = var_508, x = transpose_137)[name = tensor("value_states_19_cast")]; + tensor var_511_perm_0 = const()[name = tensor("op_511_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_25_transpose_x_0 = const()[name = tensor("attn_weights_25_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_25_transpose_y_0 = const()[name = tensor("attn_weights_25_transpose_y_0"), val = tensor(false)]; + tensor transpose_136 = transpose(perm = var_511_perm_0, x = key_states_19_cast)[name = tensor("transpose_136")]; + tensor 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_136)[name = tensor("attn_weights_25_cast")]; + tensor var_513 = const()[name = tensor("op_513"), val = tensor([1, 20, 77, 77])]; + tensor var_514_cast = reshape(shape = var_513, x = attn_weights_25_cast)[name = tensor("op_514_cast")]; + tensor attn_weights_27_cast = add(x = var_514_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_27_cast")]; + tensor var_519 = const()[name = tensor("op_519"), val = tensor([20, 77, 77])]; + tensor input_69_cast = reshape(shape = var_519, x = attn_weights_27_cast)[name = tensor("input_69_cast")]; + tensor input_71_cast = softmax(axis = var_5, x = input_69_cast)[name = tensor("input_71_cast")]; + tensor attn_output_25_transpose_x_0 = const()[name = tensor("attn_output_25_transpose_x_0"), val = tensor(false)]; + tensor attn_output_25_transpose_y_0 = const()[name = tensor("attn_output_25_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_25_cast")]; + tensor var_524 = const()[name = tensor("op_524"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_27_cast = reshape(shape = var_524, x = attn_output_25_cast)[name = tensor("attn_output_27_cast")]; + tensor attn_output_29_perm_0 = const()[name = tensor("attn_output_29_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_527 = const()[name = tensor("op_527"), val = tensor([1, 77, 1280])]; + tensor transpose_135 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast)[name = tensor("transpose_135")]; + tensor input_73_cast = reshape(shape = var_527, x = transpose_135)[name = tensor("input_73_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189363200))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190592064))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190592256)))]; + tensor 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_palettized, x = input_73_cast)[name = tensor("hidden_states_27_cast")]; + tensor input_75_cast = add(x = input_67_cast, y = hidden_states_27_cast)[name = tensor("input_75_cast")]; + tensor input_77_axes_0 = const()[name = tensor("input_77_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190594880)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190597504)))]; + tensor 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("input_77_cast")]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190600128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195515392))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195515584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195519488))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_79_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized, x = input_77_cast)[name = tensor("input_79_cast")]; + tensor input_81_mode_0 = const()[name = tensor("input_81_mode_0"), val = tensor("EXACT")]; + tensor input_81_cast = gelu(mode = input_81_mode_0, x = input_79_cast)[name = tensor("input_81_cast")]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195519680))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200434944))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200435136)))]; + tensor 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_palettized, x = input_81_cast)[name = tensor("hidden_states_29_cast")]; + tensor input_83_cast = add(x = input_75_cast, y = hidden_states_29_cast)[name = tensor("input_83_cast")]; + tensor hidden_states_31_axes_0 = const()[name = tensor("hidden_states_31_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200437760)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200440384)))]; + tensor 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("hidden_states_31_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200443008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(201671872))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(201672064)))]; + tensor 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_palettized, x = hidden_states_31_cast)[name = tensor("op_565_cast")]; + tensor var_566_to_fp16 = const()[name = tensor("op_566_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_35_cast = mul(x = var_565_cast, y = var_566_to_fp16)[name = tensor("tensor_35_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(201674688))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202903552))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202903744)))]; + tensor 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_palettized, x = hidden_states_31_cast)[name = tensor("tensor_31_cast")]; + tensor var_571 = const()[name = tensor("op_571"), val = tensor([1, -1, 20, 64])]; + tensor var_572_cast = reshape(shape = var_571, x = tensor_31_cast)[name = tensor("op_572_cast")]; + tensor var_573_perm_0 = const()[name = tensor("op_573_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202906368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204135232))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204135424)))]; + tensor 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_palettized, x = hidden_states_31_cast)[name = tensor("tensor_33_cast")]; + tensor var_578 = const()[name = tensor("op_578"), val = tensor([1, -1, 20, 64])]; + tensor var_579_cast = reshape(shape = var_578, x = tensor_33_cast)[name = tensor("op_579_cast")]; + tensor var_580_perm_0 = const()[name = tensor("op_580_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_587 = const()[name = tensor("op_587"), val = tensor([1, 77, 20, 64])]; + tensor var_588_cast = reshape(shape = var_587, x = tensor_35_cast)[name = tensor("op_588_cast")]; + tensor var_589_perm_0 = const()[name = tensor("op_589_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_591 = const()[name = tensor("op_591"), val = tensor([20, -1, 64])]; + tensor transpose_134 = transpose(perm = var_589_perm_0, x = var_588_cast)[name = tensor("transpose_134")]; + tensor query_states_11_cast = reshape(shape = var_591, x = transpose_134)[name = tensor("query_states_11_cast")]; + tensor var_593 = const()[name = tensor("op_593"), val = tensor([20, -1, 64])]; + tensor transpose_133 = transpose(perm = var_573_perm_0, x = var_572_cast)[name = tensor("transpose_133")]; + tensor key_states_23_cast = reshape(shape = var_593, x = transpose_133)[name = tensor("key_states_23_cast")]; + tensor var_595 = const()[name = tensor("op_595"), val = tensor([20, -1, 64])]; + tensor transpose_132 = transpose(perm = var_580_perm_0, x = var_579_cast)[name = tensor("transpose_132")]; + tensor value_states_23_cast = reshape(shape = var_595, x = transpose_132)[name = tensor("value_states_23_cast")]; + tensor var_598_perm_0 = const()[name = tensor("op_598_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_31_transpose_x_0 = const()[name = tensor("attn_weights_31_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_31_transpose_y_0 = const()[name = tensor("attn_weights_31_transpose_y_0"), val = tensor(false)]; + tensor transpose_131 = transpose(perm = var_598_perm_0, x = key_states_23_cast)[name = tensor("transpose_131")]; + tensor 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_131)[name = tensor("attn_weights_31_cast")]; + tensor var_600 = const()[name = tensor("op_600"), val = tensor([1, 20, 77, 77])]; + tensor var_601_cast = reshape(shape = var_600, x = attn_weights_31_cast)[name = tensor("op_601_cast")]; + tensor attn_weights_33_cast = add(x = var_601_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_33_cast")]; + tensor var_606 = const()[name = tensor("op_606"), val = tensor([20, 77, 77])]; + tensor input_85_cast = reshape(shape = var_606, x = attn_weights_33_cast)[name = tensor("input_85_cast")]; + tensor input_87_cast = softmax(axis = var_5, x = input_85_cast)[name = tensor("input_87_cast")]; + tensor attn_output_31_transpose_x_0 = const()[name = tensor("attn_output_31_transpose_x_0"), val = tensor(false)]; + tensor attn_output_31_transpose_y_0 = const()[name = tensor("attn_output_31_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_31_cast")]; + tensor var_611 = const()[name = tensor("op_611"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_33_cast = reshape(shape = var_611, x = attn_output_31_cast)[name = tensor("attn_output_33_cast")]; + tensor attn_output_35_perm_0 = const()[name = tensor("attn_output_35_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_614 = const()[name = tensor("op_614"), val = tensor([1, 77, 1280])]; + tensor transpose_130 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast)[name = tensor("transpose_130")]; + tensor input_89_cast = reshape(shape = var_614, x = transpose_130)[name = tensor("input_89_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204138048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205366912))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205367104)))]; + tensor 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_palettized, x = input_89_cast)[name = tensor("hidden_states_33_cast")]; + tensor input_91_cast = add(x = input_83_cast, y = hidden_states_33_cast)[name = tensor("input_91_cast")]; + tensor input_93_axes_0 = const()[name = tensor("input_93_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205369728)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205372352)))]; + tensor 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("input_93_cast")]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205374976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210290240))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210290432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210294336))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_95_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized, x = input_93_cast)[name = tensor("input_95_cast")]; + tensor input_97_mode_0 = const()[name = tensor("input_97_mode_0"), val = tensor("EXACT")]; + tensor input_97_cast = gelu(mode = input_97_mode_0, x = input_95_cast)[name = tensor("input_97_cast")]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210294528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215209792))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215209984)))]; + tensor 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_palettized, x = input_97_cast)[name = tensor("hidden_states_35_cast")]; + tensor input_99_cast = add(x = input_91_cast, y = hidden_states_35_cast)[name = tensor("input_99_cast")]; + tensor hidden_states_37_axes_0 = const()[name = tensor("hidden_states_37_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215212608)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215215232)))]; + tensor 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("hidden_states_37_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215217856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216446720))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216446912)))]; + tensor 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_palettized, x = hidden_states_37_cast)[name = tensor("op_652_cast")]; + tensor var_653_to_fp16 = const()[name = tensor("op_653_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_41_cast = mul(x = var_652_cast, y = var_653_to_fp16)[name = tensor("tensor_41_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216449536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217678400))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217678592)))]; + tensor 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_palettized, x = hidden_states_37_cast)[name = tensor("tensor_37_cast")]; + tensor var_658 = const()[name = tensor("op_658"), val = tensor([1, -1, 20, 64])]; + tensor var_659_cast = reshape(shape = var_658, x = tensor_37_cast)[name = tensor("op_659_cast")]; + tensor var_660_perm_0 = const()[name = tensor("op_660_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217681216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218910080))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218910272)))]; + tensor 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_palettized, x = hidden_states_37_cast)[name = tensor("tensor_39_cast")]; + tensor var_665 = const()[name = tensor("op_665"), val = tensor([1, -1, 20, 64])]; + tensor var_666_cast = reshape(shape = var_665, x = tensor_39_cast)[name = tensor("op_666_cast")]; + tensor var_667_perm_0 = const()[name = tensor("op_667_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_674 = const()[name = tensor("op_674"), val = tensor([1, 77, 20, 64])]; + tensor var_675_cast = reshape(shape = var_674, x = tensor_41_cast)[name = tensor("op_675_cast")]; + tensor var_676_perm_0 = const()[name = tensor("op_676_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_678 = const()[name = tensor("op_678"), val = tensor([20, -1, 64])]; + tensor transpose_129 = transpose(perm = var_676_perm_0, x = var_675_cast)[name = tensor("transpose_129")]; + tensor query_states_13_cast = reshape(shape = var_678, x = transpose_129)[name = tensor("query_states_13_cast")]; + tensor var_680 = const()[name = tensor("op_680"), val = tensor([20, -1, 64])]; + tensor transpose_128 = transpose(perm = var_660_perm_0, x = var_659_cast)[name = tensor("transpose_128")]; + tensor key_states_27_cast = reshape(shape = var_680, x = transpose_128)[name = tensor("key_states_27_cast")]; + tensor var_682 = const()[name = tensor("op_682"), val = tensor([20, -1, 64])]; + tensor transpose_127 = transpose(perm = var_667_perm_0, x = var_666_cast)[name = tensor("transpose_127")]; + tensor value_states_27_cast = reshape(shape = var_682, x = transpose_127)[name = tensor("value_states_27_cast")]; + tensor var_685_perm_0 = const()[name = tensor("op_685_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_37_transpose_x_0 = const()[name = tensor("attn_weights_37_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_37_transpose_y_0 = const()[name = tensor("attn_weights_37_transpose_y_0"), val = tensor(false)]; + tensor transpose_126 = transpose(perm = var_685_perm_0, x = key_states_27_cast)[name = tensor("transpose_126")]; + tensor 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_126)[name = tensor("attn_weights_37_cast")]; + tensor var_687 = const()[name = tensor("op_687"), val = tensor([1, 20, 77, 77])]; + tensor var_688_cast = reshape(shape = var_687, x = attn_weights_37_cast)[name = tensor("op_688_cast")]; + tensor attn_weights_39_cast = add(x = var_688_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_39_cast")]; + tensor var_693 = const()[name = tensor("op_693"), val = tensor([20, 77, 77])]; + tensor input_101_cast = reshape(shape = var_693, x = attn_weights_39_cast)[name = tensor("input_101_cast")]; + tensor input_103_cast = softmax(axis = var_5, x = input_101_cast)[name = tensor("input_103_cast")]; + tensor attn_output_37_transpose_x_0 = const()[name = tensor("attn_output_37_transpose_x_0"), val = tensor(false)]; + tensor attn_output_37_transpose_y_0 = const()[name = tensor("attn_output_37_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_37_cast")]; + tensor var_698 = const()[name = tensor("op_698"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_39_cast = reshape(shape = var_698, x = attn_output_37_cast)[name = tensor("attn_output_39_cast")]; + tensor attn_output_41_perm_0 = const()[name = tensor("attn_output_41_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_701 = const()[name = tensor("op_701"), val = tensor([1, 77, 1280])]; + tensor transpose_125 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast)[name = tensor("transpose_125")]; + tensor input_105_cast = reshape(shape = var_701, x = transpose_125)[name = tensor("input_105_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218912896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220141760))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220141952)))]; + tensor 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_palettized, x = input_105_cast)[name = tensor("hidden_states_39_cast")]; + tensor input_107_cast = add(x = input_99_cast, y = hidden_states_39_cast)[name = tensor("input_107_cast")]; + tensor input_109_axes_0 = const()[name = tensor("input_109_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220144576)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220147200)))]; + tensor 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("input_109_cast")]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220149824))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225065088))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225065280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225069184))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_111_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized, x = input_109_cast)[name = tensor("input_111_cast")]; + tensor input_113_mode_0 = const()[name = tensor("input_113_mode_0"), val = tensor("EXACT")]; + tensor input_113_cast = gelu(mode = input_113_mode_0, x = input_111_cast)[name = tensor("input_113_cast")]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225069376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229984640))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229984832)))]; + tensor 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_palettized, x = input_113_cast)[name = tensor("hidden_states_41_cast")]; + tensor input_115_cast = add(x = input_107_cast, y = hidden_states_41_cast)[name = tensor("input_115_cast")]; + tensor hidden_states_43_axes_0 = const()[name = tensor("hidden_states_43_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229987456)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229990080)))]; + tensor 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("hidden_states_43_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229992704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231221568))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231221760)))]; + tensor 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_palettized, x = hidden_states_43_cast)[name = tensor("op_739_cast")]; + tensor var_740_to_fp16 = const()[name = tensor("op_740_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_47_cast = mul(x = var_739_cast, y = var_740_to_fp16)[name = tensor("tensor_47_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231224384))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232453248))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232453440)))]; + tensor 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_palettized, x = hidden_states_43_cast)[name = tensor("tensor_43_cast")]; + tensor var_745 = const()[name = tensor("op_745"), val = tensor([1, -1, 20, 64])]; + tensor var_746_cast = reshape(shape = var_745, x = tensor_43_cast)[name = tensor("op_746_cast")]; + tensor var_747_perm_0 = const()[name = tensor("op_747_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232456064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233684928))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233685120)))]; + tensor 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_palettized, x = hidden_states_43_cast)[name = tensor("tensor_45_cast")]; + tensor var_752 = const()[name = tensor("op_752"), val = tensor([1, -1, 20, 64])]; + tensor var_753_cast = reshape(shape = var_752, x = tensor_45_cast)[name = tensor("op_753_cast")]; + tensor var_754_perm_0 = const()[name = tensor("op_754_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_761 = const()[name = tensor("op_761"), val = tensor([1, 77, 20, 64])]; + tensor var_762_cast = reshape(shape = var_761, x = tensor_47_cast)[name = tensor("op_762_cast")]; + tensor var_763_perm_0 = const()[name = tensor("op_763_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_765 = const()[name = tensor("op_765"), val = tensor([20, -1, 64])]; + tensor transpose_124 = transpose(perm = var_763_perm_0, x = var_762_cast)[name = tensor("transpose_124")]; + tensor query_states_15_cast = reshape(shape = var_765, x = transpose_124)[name = tensor("query_states_15_cast")]; + tensor var_767 = const()[name = tensor("op_767"), val = tensor([20, -1, 64])]; + tensor transpose_123 = transpose(perm = var_747_perm_0, x = var_746_cast)[name = tensor("transpose_123")]; + tensor key_states_31_cast = reshape(shape = var_767, x = transpose_123)[name = tensor("key_states_31_cast")]; + tensor var_769 = const()[name = tensor("op_769"), val = tensor([20, -1, 64])]; + tensor transpose_122 = transpose(perm = var_754_perm_0, x = var_753_cast)[name = tensor("transpose_122")]; + tensor value_states_31_cast = reshape(shape = var_769, x = transpose_122)[name = tensor("value_states_31_cast")]; + tensor var_772_perm_0 = const()[name = tensor("op_772_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_43_transpose_x_0 = const()[name = tensor("attn_weights_43_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_43_transpose_y_0 = const()[name = tensor("attn_weights_43_transpose_y_0"), val = tensor(false)]; + tensor transpose_121 = transpose(perm = var_772_perm_0, x = key_states_31_cast)[name = tensor("transpose_121")]; + tensor 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_121)[name = tensor("attn_weights_43_cast")]; + tensor var_774 = const()[name = tensor("op_774"), val = tensor([1, 20, 77, 77])]; + tensor var_775_cast = reshape(shape = var_774, x = attn_weights_43_cast)[name = tensor("op_775_cast")]; + tensor attn_weights_45_cast = add(x = var_775_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_45_cast")]; + tensor var_780 = const()[name = tensor("op_780"), val = tensor([20, 77, 77])]; + tensor input_117_cast = reshape(shape = var_780, x = attn_weights_45_cast)[name = tensor("input_117_cast")]; + tensor input_119_cast = softmax(axis = var_5, x = input_117_cast)[name = tensor("input_119_cast")]; + tensor attn_output_43_transpose_x_0 = const()[name = tensor("attn_output_43_transpose_x_0"), val = tensor(false)]; + tensor attn_output_43_transpose_y_0 = const()[name = tensor("attn_output_43_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_43_cast")]; + tensor var_785 = const()[name = tensor("op_785"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_45_cast = reshape(shape = var_785, x = attn_output_43_cast)[name = tensor("attn_output_45_cast")]; + tensor attn_output_47_perm_0 = const()[name = tensor("attn_output_47_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_788 = const()[name = tensor("op_788"), val = tensor([1, 77, 1280])]; + tensor transpose_120 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast)[name = tensor("transpose_120")]; + tensor input_121_cast = reshape(shape = var_788, x = transpose_120)[name = tensor("input_121_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233687744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234916608))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234916800)))]; + tensor 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_palettized, x = input_121_cast)[name = tensor("hidden_states_45_cast")]; + tensor input_123_cast = add(x = input_115_cast, y = hidden_states_45_cast)[name = tensor("input_123_cast")]; + tensor input_125_axes_0 = const()[name = tensor("input_125_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234919424)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234922048)))]; + tensor 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("input_125_cast")]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234924672))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239839936))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239840128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239844032))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_127_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized, x = input_125_cast)[name = tensor("input_127_cast")]; + tensor input_129_mode_0 = const()[name = tensor("input_129_mode_0"), val = tensor("EXACT")]; + tensor input_129_cast = gelu(mode = input_129_mode_0, x = input_127_cast)[name = tensor("input_129_cast")]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239844224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244759488))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244759680)))]; + tensor 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_palettized, x = input_129_cast)[name = tensor("hidden_states_47_cast")]; + tensor input_131_cast = add(x = input_123_cast, y = hidden_states_47_cast)[name = tensor("input_131_cast")]; + tensor hidden_states_49_axes_0 = const()[name = tensor("hidden_states_49_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244762304)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244764928)))]; + tensor 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("hidden_states_49_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244767552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245996416))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245996608)))]; + tensor 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_palettized, x = hidden_states_49_cast)[name = tensor("op_826_cast")]; + tensor var_827_to_fp16 = const()[name = tensor("op_827_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_53_cast = mul(x = var_826_cast, y = var_827_to_fp16)[name = tensor("tensor_53_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245999232))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247228096))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247228288)))]; + tensor 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_palettized, x = hidden_states_49_cast)[name = tensor("tensor_49_cast")]; + tensor var_832 = const()[name = tensor("op_832"), val = tensor([1, -1, 20, 64])]; + tensor var_833_cast = reshape(shape = var_832, x = tensor_49_cast)[name = tensor("op_833_cast")]; + tensor var_834_perm_0 = const()[name = tensor("op_834_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247230912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248459776))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248459968)))]; + tensor 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_palettized, x = hidden_states_49_cast)[name = tensor("tensor_51_cast")]; + tensor var_839 = const()[name = tensor("op_839"), val = tensor([1, -1, 20, 64])]; + tensor var_840_cast = reshape(shape = var_839, x = tensor_51_cast)[name = tensor("op_840_cast")]; + tensor var_841_perm_0 = const()[name = tensor("op_841_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_848 = const()[name = tensor("op_848"), val = tensor([1, 77, 20, 64])]; + tensor var_849_cast = reshape(shape = var_848, x = tensor_53_cast)[name = tensor("op_849_cast")]; + tensor var_850_perm_0 = const()[name = tensor("op_850_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_852 = const()[name = tensor("op_852"), val = tensor([20, -1, 64])]; + tensor transpose_119 = transpose(perm = var_850_perm_0, x = var_849_cast)[name = tensor("transpose_119")]; + tensor query_states_17_cast = reshape(shape = var_852, x = transpose_119)[name = tensor("query_states_17_cast")]; + tensor var_854 = const()[name = tensor("op_854"), val = tensor([20, -1, 64])]; + tensor transpose_118 = transpose(perm = var_834_perm_0, x = var_833_cast)[name = tensor("transpose_118")]; + tensor key_states_35_cast = reshape(shape = var_854, x = transpose_118)[name = tensor("key_states_35_cast")]; + tensor var_856 = const()[name = tensor("op_856"), val = tensor([20, -1, 64])]; + tensor transpose_117 = transpose(perm = var_841_perm_0, x = var_840_cast)[name = tensor("transpose_117")]; + tensor value_states_35_cast = reshape(shape = var_856, x = transpose_117)[name = tensor("value_states_35_cast")]; + tensor var_859_perm_0 = const()[name = tensor("op_859_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_49_transpose_x_0 = const()[name = tensor("attn_weights_49_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_49_transpose_y_0 = const()[name = tensor("attn_weights_49_transpose_y_0"), val = tensor(false)]; + tensor transpose_116 = transpose(perm = var_859_perm_0, x = key_states_35_cast)[name = tensor("transpose_116")]; + tensor 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_116)[name = tensor("attn_weights_49_cast")]; + tensor var_861 = const()[name = tensor("op_861"), val = tensor([1, 20, 77, 77])]; + tensor var_862_cast = reshape(shape = var_861, x = attn_weights_49_cast)[name = tensor("op_862_cast")]; + tensor attn_weights_51_cast = add(x = var_862_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_51_cast")]; + tensor var_867 = const()[name = tensor("op_867"), val = tensor([20, 77, 77])]; + tensor input_133_cast = reshape(shape = var_867, x = attn_weights_51_cast)[name = tensor("input_133_cast")]; + tensor input_135_cast = softmax(axis = var_5, x = input_133_cast)[name = tensor("input_135_cast")]; + tensor attn_output_49_transpose_x_0 = const()[name = tensor("attn_output_49_transpose_x_0"), val = tensor(false)]; + tensor attn_output_49_transpose_y_0 = const()[name = tensor("attn_output_49_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_49_cast")]; + tensor var_872 = const()[name = tensor("op_872"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_51_cast = reshape(shape = var_872, x = attn_output_49_cast)[name = tensor("attn_output_51_cast")]; + tensor attn_output_53_perm_0 = const()[name = tensor("attn_output_53_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_875 = const()[name = tensor("op_875"), val = tensor([1, 77, 1280])]; + tensor transpose_115 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast)[name = tensor("transpose_115")]; + tensor input_137_cast = reshape(shape = var_875, x = transpose_115)[name = tensor("input_137_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248462592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249691456))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249691648)))]; + tensor 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_palettized, x = input_137_cast)[name = tensor("hidden_states_51_cast")]; + tensor input_139_cast = add(x = input_131_cast, y = hidden_states_51_cast)[name = tensor("input_139_cast")]; + tensor input_141_axes_0 = const()[name = tensor("input_141_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249694272)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249696896)))]; + tensor 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("input_141_cast")]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249699520))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254614784))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254614976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254618880))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_143_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized, x = input_141_cast)[name = tensor("input_143_cast")]; + tensor input_145_mode_0 = const()[name = tensor("input_145_mode_0"), val = tensor("EXACT")]; + tensor input_145_cast = gelu(mode = input_145_mode_0, x = input_143_cast)[name = tensor("input_145_cast")]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254619072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259534336))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259534528)))]; + tensor 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_palettized, x = input_145_cast)[name = tensor("hidden_states_53_cast")]; + tensor input_147_cast = add(x = input_139_cast, y = hidden_states_53_cast)[name = tensor("input_147_cast")]; + tensor hidden_states_55_axes_0 = const()[name = tensor("hidden_states_55_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259537152)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259539776)))]; + tensor 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("hidden_states_55_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259542400))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260771264))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260771456)))]; + tensor 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_palettized, x = hidden_states_55_cast)[name = tensor("op_913_cast")]; + tensor var_914_to_fp16 = const()[name = tensor("op_914_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_59_cast = mul(x = var_913_cast, y = var_914_to_fp16)[name = tensor("tensor_59_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260774080))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262002944))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262003136)))]; + tensor 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_palettized, x = hidden_states_55_cast)[name = tensor("tensor_55_cast")]; + tensor var_919 = const()[name = tensor("op_919"), val = tensor([1, -1, 20, 64])]; + tensor var_920_cast = reshape(shape = var_919, x = tensor_55_cast)[name = tensor("op_920_cast")]; + tensor var_921_perm_0 = const()[name = tensor("op_921_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262005760))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263234624))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263234816)))]; + tensor 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_palettized, x = hidden_states_55_cast)[name = tensor("tensor_57_cast")]; + tensor var_926 = const()[name = tensor("op_926"), val = tensor([1, -1, 20, 64])]; + tensor var_927_cast = reshape(shape = var_926, x = tensor_57_cast)[name = tensor("op_927_cast")]; + tensor var_928_perm_0 = const()[name = tensor("op_928_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_935 = const()[name = tensor("op_935"), val = tensor([1, 77, 20, 64])]; + tensor var_936_cast = reshape(shape = var_935, x = tensor_59_cast)[name = tensor("op_936_cast")]; + tensor var_937_perm_0 = const()[name = tensor("op_937_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_939 = const()[name = tensor("op_939"), val = tensor([20, -1, 64])]; + tensor transpose_114 = transpose(perm = var_937_perm_0, x = var_936_cast)[name = tensor("transpose_114")]; + tensor query_states_19_cast = reshape(shape = var_939, x = transpose_114)[name = tensor("query_states_19_cast")]; + tensor var_941 = const()[name = tensor("op_941"), val = tensor([20, -1, 64])]; + tensor transpose_113 = transpose(perm = var_921_perm_0, x = var_920_cast)[name = tensor("transpose_113")]; + tensor key_states_39_cast = reshape(shape = var_941, x = transpose_113)[name = tensor("key_states_39_cast")]; + tensor var_943 = const()[name = tensor("op_943"), val = tensor([20, -1, 64])]; + tensor transpose_112 = transpose(perm = var_928_perm_0, x = var_927_cast)[name = tensor("transpose_112")]; + tensor value_states_39_cast = reshape(shape = var_943, x = transpose_112)[name = tensor("value_states_39_cast")]; + tensor var_946_perm_0 = const()[name = tensor("op_946_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_55_transpose_x_0 = const()[name = tensor("attn_weights_55_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_55_transpose_y_0 = const()[name = tensor("attn_weights_55_transpose_y_0"), val = tensor(false)]; + tensor transpose_111 = transpose(perm = var_946_perm_0, x = key_states_39_cast)[name = tensor("transpose_111")]; + tensor 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_111)[name = tensor("attn_weights_55_cast")]; + tensor var_948 = const()[name = tensor("op_948"), val = tensor([1, 20, 77, 77])]; + tensor var_949_cast = reshape(shape = var_948, x = attn_weights_55_cast)[name = tensor("op_949_cast")]; + tensor attn_weights_57_cast = add(x = var_949_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_57_cast")]; + tensor var_954 = const()[name = tensor("op_954"), val = tensor([20, 77, 77])]; + tensor input_149_cast = reshape(shape = var_954, x = attn_weights_57_cast)[name = tensor("input_149_cast")]; + tensor input_151_cast = softmax(axis = var_5, x = input_149_cast)[name = tensor("input_151_cast")]; + tensor attn_output_55_transpose_x_0 = const()[name = tensor("attn_output_55_transpose_x_0"), val = tensor(false)]; + tensor attn_output_55_transpose_y_0 = const()[name = tensor("attn_output_55_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_55_cast")]; + tensor var_959 = const()[name = tensor("op_959"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_57_cast = reshape(shape = var_959, x = attn_output_55_cast)[name = tensor("attn_output_57_cast")]; + tensor attn_output_59_perm_0 = const()[name = tensor("attn_output_59_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_962 = const()[name = tensor("op_962"), val = tensor([1, 77, 1280])]; + tensor transpose_110 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast)[name = tensor("transpose_110")]; + tensor input_153_cast = reshape(shape = var_962, x = transpose_110)[name = tensor("input_153_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263237440))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264466304))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264466496)))]; + tensor 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_palettized, x = input_153_cast)[name = tensor("hidden_states_57_cast")]; + tensor input_155_cast = add(x = input_147_cast, y = hidden_states_57_cast)[name = tensor("input_155_cast")]; + tensor input_157_axes_0 = const()[name = tensor("input_157_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264469120)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264471744)))]; + tensor 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("input_157_cast")]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264474368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269389632))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269389824))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269393728))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_159_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized, x = input_157_cast)[name = tensor("input_159_cast")]; + tensor input_161_mode_0 = const()[name = tensor("input_161_mode_0"), val = tensor("EXACT")]; + tensor input_161_cast = gelu(mode = input_161_mode_0, x = input_159_cast)[name = tensor("input_161_cast")]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269393920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274309184))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274309376)))]; + tensor 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_palettized, x = input_161_cast)[name = tensor("hidden_states_59_cast")]; + tensor input_163_cast = add(x = input_155_cast, y = hidden_states_59_cast)[name = tensor("input_163_cast")]; + tensor hidden_states_61_axes_0 = const()[name = tensor("hidden_states_61_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274312000)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274314624)))]; + tensor 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("hidden_states_61_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274317248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275546112))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275546304)))]; + tensor 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_palettized, x = hidden_states_61_cast)[name = tensor("op_1000_cast")]; + tensor var_1001_to_fp16 = const()[name = tensor("op_1001_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_65_cast = mul(x = var_1000_cast, y = var_1001_to_fp16)[name = tensor("tensor_65_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275548928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276777792))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276777984)))]; + tensor 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_palettized, x = hidden_states_61_cast)[name = tensor("tensor_61_cast")]; + tensor var_1006 = const()[name = tensor("op_1006"), val = tensor([1, -1, 20, 64])]; + tensor var_1007_cast = reshape(shape = var_1006, x = tensor_61_cast)[name = tensor("op_1007_cast")]; + tensor var_1008_perm_0 = const()[name = tensor("op_1008_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276780608))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278009472))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278009664)))]; + tensor 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_palettized, x = hidden_states_61_cast)[name = tensor("tensor_63_cast")]; + tensor var_1013 = const()[name = tensor("op_1013"), val = tensor([1, -1, 20, 64])]; + tensor var_1014_cast = reshape(shape = var_1013, x = tensor_63_cast)[name = tensor("op_1014_cast")]; + tensor var_1015_perm_0 = const()[name = tensor("op_1015_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1022 = const()[name = tensor("op_1022"), val = tensor([1, 77, 20, 64])]; + tensor var_1023_cast = reshape(shape = var_1022, x = tensor_65_cast)[name = tensor("op_1023_cast")]; + tensor var_1024_perm_0 = const()[name = tensor("op_1024_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1026 = const()[name = tensor("op_1026"), val = tensor([20, -1, 64])]; + tensor transpose_109 = transpose(perm = var_1024_perm_0, x = var_1023_cast)[name = tensor("transpose_109")]; + tensor query_states_21_cast = reshape(shape = var_1026, x = transpose_109)[name = tensor("query_states_21_cast")]; + tensor var_1028 = const()[name = tensor("op_1028"), val = tensor([20, -1, 64])]; + tensor transpose_108 = transpose(perm = var_1008_perm_0, x = var_1007_cast)[name = tensor("transpose_108")]; + tensor key_states_43_cast = reshape(shape = var_1028, x = transpose_108)[name = tensor("key_states_43_cast")]; + tensor var_1030 = const()[name = tensor("op_1030"), val = tensor([20, -1, 64])]; + tensor transpose_107 = transpose(perm = var_1015_perm_0, x = var_1014_cast)[name = tensor("transpose_107")]; + tensor value_states_43_cast = reshape(shape = var_1030, x = transpose_107)[name = tensor("value_states_43_cast")]; + tensor var_1033_perm_0 = const()[name = tensor("op_1033_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_61_transpose_x_0 = const()[name = tensor("attn_weights_61_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_61_transpose_y_0 = const()[name = tensor("attn_weights_61_transpose_y_0"), val = tensor(false)]; + tensor transpose_106 = transpose(perm = var_1033_perm_0, x = key_states_43_cast)[name = tensor("transpose_106")]; + tensor 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_106)[name = tensor("attn_weights_61_cast")]; + tensor var_1035 = const()[name = tensor("op_1035"), val = tensor([1, 20, 77, 77])]; + tensor var_1036_cast = reshape(shape = var_1035, x = attn_weights_61_cast)[name = tensor("op_1036_cast")]; + tensor attn_weights_63_cast = add(x = var_1036_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_63_cast")]; + tensor var_1041 = const()[name = tensor("op_1041"), val = tensor([20, 77, 77])]; + tensor input_165_cast = reshape(shape = var_1041, x = attn_weights_63_cast)[name = tensor("input_165_cast")]; + tensor input_167_cast = softmax(axis = var_5, x = input_165_cast)[name = tensor("input_167_cast")]; + tensor attn_output_61_transpose_x_0 = const()[name = tensor("attn_output_61_transpose_x_0"), val = tensor(false)]; + tensor attn_output_61_transpose_y_0 = const()[name = tensor("attn_output_61_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_61_cast")]; + tensor var_1046 = const()[name = tensor("op_1046"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_63_cast = reshape(shape = var_1046, x = attn_output_61_cast)[name = tensor("attn_output_63_cast")]; + tensor attn_output_65_perm_0 = const()[name = tensor("attn_output_65_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1049 = const()[name = tensor("op_1049"), val = tensor([1, 77, 1280])]; + tensor transpose_105 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast)[name = tensor("transpose_105")]; + tensor input_169_cast = reshape(shape = var_1049, x = transpose_105)[name = tensor("input_169_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278012288))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279241152))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279241344)))]; + tensor 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_palettized, x = input_169_cast)[name = tensor("hidden_states_63_cast")]; + tensor input_171_cast = add(x = input_163_cast, y = hidden_states_63_cast)[name = tensor("input_171_cast")]; + tensor input_173_axes_0 = const()[name = tensor("input_173_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279243968)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279246592)))]; + tensor 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("input_173_cast")]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279249216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284164480))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284164672))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284168576))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_175_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized, x = input_173_cast)[name = tensor("input_175_cast")]; + tensor input_177_mode_0 = const()[name = tensor("input_177_mode_0"), val = tensor("EXACT")]; + tensor input_177_cast = gelu(mode = input_177_mode_0, x = input_175_cast)[name = tensor("input_177_cast")]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284168768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289084032))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289084224)))]; + tensor 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_palettized, x = input_177_cast)[name = tensor("hidden_states_65_cast")]; + tensor input_179_cast = add(x = input_171_cast, y = hidden_states_65_cast)[name = tensor("input_179_cast")]; + tensor hidden_states_67_axes_0 = const()[name = tensor("hidden_states_67_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289086848)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289089472)))]; + tensor 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("hidden_states_67_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289092096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290320960))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290321152)))]; + tensor 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_palettized, x = hidden_states_67_cast)[name = tensor("op_1087_cast")]; + tensor var_1088_to_fp16 = const()[name = tensor("op_1088_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_71_cast = mul(x = var_1087_cast, y = var_1088_to_fp16)[name = tensor("tensor_71_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290323776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291552640))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291552832)))]; + tensor 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_palettized, x = hidden_states_67_cast)[name = tensor("tensor_67_cast")]; + tensor var_1093 = const()[name = tensor("op_1093"), val = tensor([1, -1, 20, 64])]; + tensor var_1094_cast = reshape(shape = var_1093, x = tensor_67_cast)[name = tensor("op_1094_cast")]; + tensor var_1095_perm_0 = const()[name = tensor("op_1095_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291555456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292784320))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292784512)))]; + tensor 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_palettized, x = hidden_states_67_cast)[name = tensor("tensor_69_cast")]; + tensor var_1100 = const()[name = tensor("op_1100"), val = tensor([1, -1, 20, 64])]; + tensor var_1101_cast = reshape(shape = var_1100, x = tensor_69_cast)[name = tensor("op_1101_cast")]; + tensor var_1102_perm_0 = const()[name = tensor("op_1102_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1109 = const()[name = tensor("op_1109"), val = tensor([1, 77, 20, 64])]; + tensor var_1110_cast = reshape(shape = var_1109, x = tensor_71_cast)[name = tensor("op_1110_cast")]; + tensor var_1111_perm_0 = const()[name = tensor("op_1111_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1113 = const()[name = tensor("op_1113"), val = tensor([20, -1, 64])]; + tensor transpose_104 = transpose(perm = var_1111_perm_0, x = var_1110_cast)[name = tensor("transpose_104")]; + tensor query_states_23_cast = reshape(shape = var_1113, x = transpose_104)[name = tensor("query_states_23_cast")]; + tensor var_1115 = const()[name = tensor("op_1115"), val = tensor([20, -1, 64])]; + tensor transpose_103 = transpose(perm = var_1095_perm_0, x = var_1094_cast)[name = tensor("transpose_103")]; + tensor key_states_47_cast = reshape(shape = var_1115, x = transpose_103)[name = tensor("key_states_47_cast")]; + tensor var_1117 = const()[name = tensor("op_1117"), val = tensor([20, -1, 64])]; + tensor transpose_102 = transpose(perm = var_1102_perm_0, x = var_1101_cast)[name = tensor("transpose_102")]; + tensor value_states_47_cast = reshape(shape = var_1117, x = transpose_102)[name = tensor("value_states_47_cast")]; + tensor var_1120_perm_0 = const()[name = tensor("op_1120_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_67_transpose_x_0 = const()[name = tensor("attn_weights_67_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_67_transpose_y_0 = const()[name = tensor("attn_weights_67_transpose_y_0"), val = tensor(false)]; + tensor transpose_101 = transpose(perm = var_1120_perm_0, x = key_states_47_cast)[name = tensor("transpose_101")]; + tensor 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_101)[name = tensor("attn_weights_67_cast")]; + tensor var_1122 = const()[name = tensor("op_1122"), val = tensor([1, 20, 77, 77])]; + tensor var_1123_cast = reshape(shape = var_1122, x = attn_weights_67_cast)[name = tensor("op_1123_cast")]; + tensor attn_weights_69_cast = add(x = var_1123_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_69_cast")]; + tensor var_1128 = const()[name = tensor("op_1128"), val = tensor([20, 77, 77])]; + tensor input_181_cast = reshape(shape = var_1128, x = attn_weights_69_cast)[name = tensor("input_181_cast")]; + tensor input_183_cast = softmax(axis = var_5, x = input_181_cast)[name = tensor("input_183_cast")]; + tensor attn_output_67_transpose_x_0 = const()[name = tensor("attn_output_67_transpose_x_0"), val = tensor(false)]; + tensor attn_output_67_transpose_y_0 = const()[name = tensor("attn_output_67_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_67_cast")]; + tensor var_1133 = const()[name = tensor("op_1133"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_69_cast = reshape(shape = var_1133, x = attn_output_67_cast)[name = tensor("attn_output_69_cast")]; + tensor attn_output_71_perm_0 = const()[name = tensor("attn_output_71_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1136 = const()[name = tensor("op_1136"), val = tensor([1, 77, 1280])]; + tensor transpose_100 = transpose(perm = attn_output_71_perm_0, x = attn_output_69_cast)[name = tensor("transpose_100")]; + tensor input_185_cast = reshape(shape = var_1136, x = transpose_100)[name = tensor("input_185_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292787136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294016000))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294016192)))]; + tensor 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_palettized, x = input_185_cast)[name = tensor("hidden_states_69_cast")]; + tensor input_187_cast = add(x = input_179_cast, y = hidden_states_69_cast)[name = tensor("input_187_cast")]; + tensor input_189_axes_0 = const()[name = tensor("input_189_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294018816)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294021440)))]; + tensor 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("input_189_cast")]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294024064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298939328))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298939520))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298943424))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_191_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized, x = input_189_cast)[name = tensor("input_191_cast")]; + tensor input_193_mode_0 = const()[name = tensor("input_193_mode_0"), val = tensor("EXACT")]; + tensor input_193_cast = gelu(mode = input_193_mode_0, x = input_191_cast)[name = tensor("input_193_cast")]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298943616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303858880))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303859072)))]; + tensor 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_palettized, x = input_193_cast)[name = tensor("hidden_states_71_cast")]; + tensor input_195_cast = add(x = input_187_cast, y = hidden_states_71_cast)[name = tensor("input_195_cast")]; + tensor hidden_states_73_axes_0 = const()[name = tensor("hidden_states_73_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303861696)))]; + tensor text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303864320)))]; + tensor 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("hidden_states_73_cast")]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303866944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305095808))), name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305096000)))]; + tensor 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_palettized, x = hidden_states_73_cast)[name = tensor("op_1174_cast")]; + tensor var_1175_to_fp16 = const()[name = tensor("op_1175_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_77_cast = mul(x = var_1174_cast, y = var_1175_to_fp16)[name = tensor("tensor_77_cast")]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305098624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(306327488))), name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(306327680)))]; + tensor 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_palettized, x = hidden_states_73_cast)[name = tensor("tensor_73_cast")]; + tensor var_1180 = const()[name = tensor("op_1180"), val = tensor([1, -1, 20, 64])]; + tensor var_1181_cast = reshape(shape = var_1180, x = tensor_73_cast)[name = tensor("op_1181_cast")]; + tensor var_1182_perm_0 = const()[name = tensor("op_1182_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(306330304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307559168))), name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307559360)))]; + tensor 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_palettized, x = hidden_states_73_cast)[name = tensor("tensor_75_cast")]; + tensor var_1187 = const()[name = tensor("op_1187"), val = tensor([1, -1, 20, 64])]; + tensor var_1188_cast = reshape(shape = var_1187, x = tensor_75_cast)[name = tensor("op_1188_cast")]; + tensor var_1189_perm_0 = const()[name = tensor("op_1189_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1196 = const()[name = tensor("op_1196"), val = tensor([1, 77, 20, 64])]; + tensor var_1197_cast = reshape(shape = var_1196, x = tensor_77_cast)[name = tensor("op_1197_cast")]; + tensor var_1198_perm_0 = const()[name = tensor("op_1198_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1200 = const()[name = tensor("op_1200"), val = tensor([20, -1, 64])]; + tensor transpose_99 = transpose(perm = var_1198_perm_0, x = var_1197_cast)[name = tensor("transpose_99")]; + tensor query_states_25_cast = reshape(shape = var_1200, x = transpose_99)[name = tensor("query_states_25_cast")]; + tensor var_1202 = const()[name = tensor("op_1202"), val = tensor([20, -1, 64])]; + tensor transpose_98 = transpose(perm = var_1182_perm_0, x = var_1181_cast)[name = tensor("transpose_98")]; + tensor key_states_51_cast = reshape(shape = var_1202, x = transpose_98)[name = tensor("key_states_51_cast")]; + tensor var_1204 = const()[name = tensor("op_1204"), val = tensor([20, -1, 64])]; + tensor transpose_97 = transpose(perm = var_1189_perm_0, x = var_1188_cast)[name = tensor("transpose_97")]; + tensor value_states_51_cast = reshape(shape = var_1204, x = transpose_97)[name = tensor("value_states_51_cast")]; + tensor var_1207_perm_0 = const()[name = tensor("op_1207_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_73_transpose_x_0 = const()[name = tensor("attn_weights_73_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_73_transpose_y_0 = const()[name = tensor("attn_weights_73_transpose_y_0"), val = tensor(false)]; + tensor transpose_96 = transpose(perm = var_1207_perm_0, x = key_states_51_cast)[name = tensor("transpose_96")]; + tensor 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_96)[name = tensor("attn_weights_73_cast")]; + tensor var_1209 = const()[name = tensor("op_1209"), val = tensor([1, 20, 77, 77])]; + tensor var_1210_cast = reshape(shape = var_1209, x = attn_weights_73_cast)[name = tensor("op_1210_cast")]; + tensor attn_weights_75_cast = add(x = var_1210_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_75_cast")]; + tensor var_1215 = const()[name = tensor("op_1215"), val = tensor([20, 77, 77])]; + tensor input_197_cast = reshape(shape = var_1215, x = attn_weights_75_cast)[name = tensor("input_197_cast")]; + tensor input_199_cast = softmax(axis = var_5, x = input_197_cast)[name = tensor("input_199_cast")]; + tensor attn_output_73_transpose_x_0 = const()[name = tensor("attn_output_73_transpose_x_0"), val = tensor(false)]; + tensor attn_output_73_transpose_y_0 = const()[name = tensor("attn_output_73_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_73_cast")]; + tensor var_1220 = const()[name = tensor("op_1220"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_75_cast = reshape(shape = var_1220, x = attn_output_73_cast)[name = tensor("attn_output_75_cast")]; + tensor attn_output_77_perm_0 = const()[name = tensor("attn_output_77_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1223 = const()[name = tensor("op_1223"), val = tensor([1, 77, 1280])]; + tensor transpose_95 = transpose(perm = attn_output_77_perm_0, x = attn_output_75_cast)[name = tensor("transpose_95")]; + tensor input_201_cast = reshape(shape = var_1223, x = transpose_95)[name = tensor("input_201_cast")]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307561984))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308790848))), name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308791040)))]; + tensor 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_palettized, x = input_201_cast)[name = tensor("hidden_states_75_cast")]; + tensor input_203_cast = add(x = input_195_cast, y = hidden_states_75_cast)[name = tensor("input_203_cast")]; + tensor input_205_axes_0 = const()[name = tensor("input_205_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308793664)))]; + tensor text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308796288)))]; + tensor 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("input_205_cast")]; + tensor text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308798912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(313714176))), name = tensor("text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(313714368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(313718272))), name = tensor("text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_207_cast = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized, x = input_205_cast)[name = tensor("input_207_cast")]; + tensor input_209_mode_0 = const()[name = tensor("input_209_mode_0"), val = tensor("EXACT")]; + tensor input_209_cast = gelu(mode = input_209_mode_0, x = input_207_cast)[name = tensor("input_209_cast")]; + tensor text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(313718464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318633728))), name = tensor("text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318633920)))]; + tensor 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_palettized, x = input_209_cast)[name = tensor("hidden_states_77_cast")]; + tensor input_211_cast = add(x = input_203_cast, y = hidden_states_77_cast)[name = tensor("input_211_cast")]; + tensor hidden_states_79_axes_0 = const()[name = tensor("hidden_states_79_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318636544)))]; + tensor text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318639168)))]; + tensor 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("hidden_states_79_cast")]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318641792))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(319870656))), name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(319870848)))]; + tensor 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_palettized, x = hidden_states_79_cast)[name = tensor("op_1261_cast")]; + tensor var_1262_to_fp16 = const()[name = tensor("op_1262_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_83_cast = mul(x = var_1261_cast, y = var_1262_to_fp16)[name = tensor("tensor_83_cast")]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(319873472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321102336))), name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321102528)))]; + tensor 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_palettized, x = hidden_states_79_cast)[name = tensor("tensor_79_cast")]; + tensor var_1267 = const()[name = tensor("op_1267"), val = tensor([1, -1, 20, 64])]; + tensor var_1268_cast = reshape(shape = var_1267, x = tensor_79_cast)[name = tensor("op_1268_cast")]; + tensor var_1269_perm_0 = const()[name = tensor("op_1269_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321105152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(322334016))), name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(322334208)))]; + tensor 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_palettized, x = hidden_states_79_cast)[name = tensor("tensor_81_cast")]; + tensor var_1274 = const()[name = tensor("op_1274"), val = tensor([1, -1, 20, 64])]; + tensor var_1275_cast = reshape(shape = var_1274, x = tensor_81_cast)[name = tensor("op_1275_cast")]; + tensor var_1276_perm_0 = const()[name = tensor("op_1276_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1283 = const()[name = tensor("op_1283"), val = tensor([1, 77, 20, 64])]; + tensor var_1284_cast = reshape(shape = var_1283, x = tensor_83_cast)[name = tensor("op_1284_cast")]; + tensor var_1285_perm_0 = const()[name = tensor("op_1285_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1287 = const()[name = tensor("op_1287"), val = tensor([20, -1, 64])]; + tensor transpose_94 = transpose(perm = var_1285_perm_0, x = var_1284_cast)[name = tensor("transpose_94")]; + tensor query_states_27_cast = reshape(shape = var_1287, x = transpose_94)[name = tensor("query_states_27_cast")]; + tensor var_1289 = const()[name = tensor("op_1289"), val = tensor([20, -1, 64])]; + tensor transpose_93 = transpose(perm = var_1269_perm_0, x = var_1268_cast)[name = tensor("transpose_93")]; + tensor key_states_55_cast = reshape(shape = var_1289, x = transpose_93)[name = tensor("key_states_55_cast")]; + tensor var_1291 = const()[name = tensor("op_1291"), val = tensor([20, -1, 64])]; + tensor transpose_92 = transpose(perm = var_1276_perm_0, x = var_1275_cast)[name = tensor("transpose_92")]; + tensor value_states_55_cast = reshape(shape = var_1291, x = transpose_92)[name = tensor("value_states_55_cast")]; + tensor var_1294_perm_0 = const()[name = tensor("op_1294_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_79_transpose_x_0 = const()[name = tensor("attn_weights_79_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_79_transpose_y_0 = const()[name = tensor("attn_weights_79_transpose_y_0"), val = tensor(false)]; + tensor transpose_91 = transpose(perm = var_1294_perm_0, x = key_states_55_cast)[name = tensor("transpose_91")]; + tensor 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_91)[name = tensor("attn_weights_79_cast")]; + tensor var_1296 = const()[name = tensor("op_1296"), val = tensor([1, 20, 77, 77])]; + tensor var_1297_cast = reshape(shape = var_1296, x = attn_weights_79_cast)[name = tensor("op_1297_cast")]; + tensor attn_weights_81_cast = add(x = var_1297_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_81_cast")]; + tensor var_1302 = const()[name = tensor("op_1302"), val = tensor([20, 77, 77])]; + tensor input_213_cast = reshape(shape = var_1302, x = attn_weights_81_cast)[name = tensor("input_213_cast")]; + tensor input_215_cast = softmax(axis = var_5, x = input_213_cast)[name = tensor("input_215_cast")]; + tensor attn_output_79_transpose_x_0 = const()[name = tensor("attn_output_79_transpose_x_0"), val = tensor(false)]; + tensor attn_output_79_transpose_y_0 = const()[name = tensor("attn_output_79_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_79_cast")]; + tensor var_1307 = const()[name = tensor("op_1307"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_81_cast = reshape(shape = var_1307, x = attn_output_79_cast)[name = tensor("attn_output_81_cast")]; + tensor attn_output_83_perm_0 = const()[name = tensor("attn_output_83_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1310 = const()[name = tensor("op_1310"), val = tensor([1, 77, 1280])]; + tensor transpose_90 = transpose(perm = attn_output_83_perm_0, x = attn_output_81_cast)[name = tensor("transpose_90")]; + tensor input_217_cast = reshape(shape = var_1310, x = transpose_90)[name = tensor("input_217_cast")]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(322336832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323565696))), name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323565888)))]; + tensor 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_palettized, x = input_217_cast)[name = tensor("hidden_states_81_cast")]; + tensor input_219_cast = add(x = input_211_cast, y = hidden_states_81_cast)[name = tensor("input_219_cast")]; + tensor input_221_axes_0 = const()[name = tensor("input_221_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323568512)))]; + tensor text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323571136)))]; + tensor 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("input_221_cast")]; + tensor text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323573760))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328489024))), name = tensor("text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328489216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328493120))), name = tensor("text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_223_cast = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized, x = input_221_cast)[name = tensor("input_223_cast")]; + tensor input_225_mode_0 = const()[name = tensor("input_225_mode_0"), val = tensor("EXACT")]; + tensor input_225_cast = gelu(mode = input_225_mode_0, x = input_223_cast)[name = tensor("input_225_cast")]; + tensor text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328493312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(333408576))), name = tensor("text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(333408768)))]; + tensor 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_palettized, x = input_225_cast)[name = tensor("hidden_states_83_cast")]; + tensor input_227_cast = add(x = input_219_cast, y = hidden_states_83_cast)[name = tensor("input_227_cast")]; + tensor hidden_states_85_axes_0 = const()[name = tensor("hidden_states_85_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(333411392)))]; + tensor text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(333414016)))]; + tensor 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("hidden_states_85_cast")]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(333416640))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334645504))), name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334645696)))]; + tensor 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_palettized, x = hidden_states_85_cast)[name = tensor("op_1348_cast")]; + tensor var_1349_to_fp16 = const()[name = tensor("op_1349_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_89_cast = mul(x = var_1348_cast, y = var_1349_to_fp16)[name = tensor("tensor_89_cast")]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334648320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(335877184))), name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(335877376)))]; + tensor 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_palettized, x = hidden_states_85_cast)[name = tensor("tensor_85_cast")]; + tensor var_1354 = const()[name = tensor("op_1354"), val = tensor([1, -1, 20, 64])]; + tensor var_1355_cast = reshape(shape = var_1354, x = tensor_85_cast)[name = tensor("op_1355_cast")]; + tensor var_1356_perm_0 = const()[name = tensor("op_1356_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(335880000))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337108864))), name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337109056)))]; + tensor 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_palettized, x = hidden_states_85_cast)[name = tensor("tensor_87_cast")]; + tensor var_1361 = const()[name = tensor("op_1361"), val = tensor([1, -1, 20, 64])]; + tensor var_1362_cast = reshape(shape = var_1361, x = tensor_87_cast)[name = tensor("op_1362_cast")]; + tensor var_1363_perm_0 = const()[name = tensor("op_1363_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1370 = const()[name = tensor("op_1370"), val = tensor([1, 77, 20, 64])]; + tensor var_1371_cast = reshape(shape = var_1370, x = tensor_89_cast)[name = tensor("op_1371_cast")]; + tensor var_1372_perm_0 = const()[name = tensor("op_1372_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1374 = const()[name = tensor("op_1374"), val = tensor([20, -1, 64])]; + tensor transpose_89 = transpose(perm = var_1372_perm_0, x = var_1371_cast)[name = tensor("transpose_89")]; + tensor query_states_29_cast = reshape(shape = var_1374, x = transpose_89)[name = tensor("query_states_29_cast")]; + tensor var_1376 = const()[name = tensor("op_1376"), val = tensor([20, -1, 64])]; + tensor transpose_88 = transpose(perm = var_1356_perm_0, x = var_1355_cast)[name = tensor("transpose_88")]; + tensor key_states_59_cast = reshape(shape = var_1376, x = transpose_88)[name = tensor("key_states_59_cast")]; + tensor var_1378 = const()[name = tensor("op_1378"), val = tensor([20, -1, 64])]; + tensor transpose_87 = transpose(perm = var_1363_perm_0, x = var_1362_cast)[name = tensor("transpose_87")]; + tensor value_states_59_cast = reshape(shape = var_1378, x = transpose_87)[name = tensor("value_states_59_cast")]; + tensor var_1381_perm_0 = const()[name = tensor("op_1381_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_85_transpose_x_0 = const()[name = tensor("attn_weights_85_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_85_transpose_y_0 = const()[name = tensor("attn_weights_85_transpose_y_0"), val = tensor(false)]; + tensor transpose_86 = transpose(perm = var_1381_perm_0, x = key_states_59_cast)[name = tensor("transpose_86")]; + tensor 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_86)[name = tensor("attn_weights_85_cast")]; + tensor var_1383 = const()[name = tensor("op_1383"), val = tensor([1, 20, 77, 77])]; + tensor var_1384_cast = reshape(shape = var_1383, x = attn_weights_85_cast)[name = tensor("op_1384_cast")]; + tensor attn_weights_87_cast = add(x = var_1384_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_87_cast")]; + tensor var_1389 = const()[name = tensor("op_1389"), val = tensor([20, 77, 77])]; + tensor input_229_cast = reshape(shape = var_1389, x = attn_weights_87_cast)[name = tensor("input_229_cast")]; + tensor input_231_cast = softmax(axis = var_5, x = input_229_cast)[name = tensor("input_231_cast")]; + tensor attn_output_85_transpose_x_0 = const()[name = tensor("attn_output_85_transpose_x_0"), val = tensor(false)]; + tensor attn_output_85_transpose_y_0 = const()[name = tensor("attn_output_85_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_85_cast")]; + tensor var_1394 = const()[name = tensor("op_1394"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_87_cast = reshape(shape = var_1394, x = attn_output_85_cast)[name = tensor("attn_output_87_cast")]; + tensor attn_output_89_perm_0 = const()[name = tensor("attn_output_89_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1397 = const()[name = tensor("op_1397"), val = tensor([1, 77, 1280])]; + tensor transpose_85 = transpose(perm = attn_output_89_perm_0, x = attn_output_87_cast)[name = tensor("transpose_85")]; + tensor input_233_cast = reshape(shape = var_1397, x = transpose_85)[name = tensor("input_233_cast")]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337111680))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(338340544))), name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(338340736)))]; + tensor 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_palettized, x = input_233_cast)[name = tensor("hidden_states_87_cast")]; + tensor input_235_cast = add(x = input_227_cast, y = hidden_states_87_cast)[name = tensor("input_235_cast")]; + tensor input_237_axes_0 = const()[name = tensor("input_237_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(338343360)))]; + tensor text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(338345984)))]; + tensor 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("input_237_cast")]; + tensor text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(338348608))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343263872))), name = tensor("text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343264064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343267968))), name = tensor("text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_239_cast = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized, x = input_237_cast)[name = tensor("input_239_cast")]; + tensor input_241_mode_0 = const()[name = tensor("input_241_mode_0"), val = tensor("EXACT")]; + tensor input_241_cast = gelu(mode = input_241_mode_0, x = input_239_cast)[name = tensor("input_241_cast")]; + tensor text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343268160))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(348183424))), name = tensor("text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(348183616)))]; + tensor 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_palettized, x = input_241_cast)[name = tensor("hidden_states_89_cast")]; + tensor input_243_cast = add(x = input_235_cast, y = hidden_states_89_cast)[name = tensor("input_243_cast")]; + tensor hidden_states_91_axes_0 = const()[name = tensor("hidden_states_91_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(348186240)))]; + tensor text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(348188864)))]; + tensor 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("hidden_states_91_cast")]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(348191488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349420352))), name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349420544)))]; + tensor 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_palettized, x = hidden_states_91_cast)[name = tensor("op_1435_cast")]; + tensor var_1436_to_fp16 = const()[name = tensor("op_1436_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_95_cast = mul(x = var_1435_cast, y = var_1436_to_fp16)[name = tensor("tensor_95_cast")]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349423168))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350652032))), name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350652224)))]; + tensor 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_palettized, x = hidden_states_91_cast)[name = tensor("tensor_91_cast")]; + tensor var_1441 = const()[name = tensor("op_1441"), val = tensor([1, -1, 20, 64])]; + tensor var_1442_cast = reshape(shape = var_1441, x = tensor_91_cast)[name = tensor("op_1442_cast")]; + tensor var_1443_perm_0 = const()[name = tensor("op_1443_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350654848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(351883712))), name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(351883904)))]; + tensor 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_palettized, x = hidden_states_91_cast)[name = tensor("tensor_93_cast")]; + tensor var_1448 = const()[name = tensor("op_1448"), val = tensor([1, -1, 20, 64])]; + tensor var_1449_cast = reshape(shape = var_1448, x = tensor_93_cast)[name = tensor("op_1449_cast")]; + tensor var_1450_perm_0 = const()[name = tensor("op_1450_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1457 = const()[name = tensor("op_1457"), val = tensor([1, 77, 20, 64])]; + tensor var_1458_cast = reshape(shape = var_1457, x = tensor_95_cast)[name = tensor("op_1458_cast")]; + tensor var_1459_perm_0 = const()[name = tensor("op_1459_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1461 = const()[name = tensor("op_1461"), val = tensor([20, -1, 64])]; + tensor transpose_84 = transpose(perm = var_1459_perm_0, x = var_1458_cast)[name = tensor("transpose_84")]; + tensor query_states_31_cast = reshape(shape = var_1461, x = transpose_84)[name = tensor("query_states_31_cast")]; + tensor var_1463 = const()[name = tensor("op_1463"), val = tensor([20, -1, 64])]; + tensor transpose_83 = transpose(perm = var_1443_perm_0, x = var_1442_cast)[name = tensor("transpose_83")]; + tensor key_states_63_cast = reshape(shape = var_1463, x = transpose_83)[name = tensor("key_states_63_cast")]; + tensor var_1465 = const()[name = tensor("op_1465"), val = tensor([20, -1, 64])]; + tensor transpose_82 = transpose(perm = var_1450_perm_0, x = var_1449_cast)[name = tensor("transpose_82")]; + tensor value_states_63_cast = reshape(shape = var_1465, x = transpose_82)[name = tensor("value_states_63_cast")]; + tensor var_1468_perm_0 = const()[name = tensor("op_1468_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_91_transpose_x_0 = const()[name = tensor("attn_weights_91_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_91_transpose_y_0 = const()[name = tensor("attn_weights_91_transpose_y_0"), val = tensor(false)]; + tensor transpose_81 = transpose(perm = var_1468_perm_0, x = key_states_63_cast)[name = tensor("transpose_81")]; + tensor 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_81)[name = tensor("attn_weights_91_cast")]; + tensor var_1470 = const()[name = tensor("op_1470"), val = tensor([1, 20, 77, 77])]; + tensor var_1471_cast = reshape(shape = var_1470, x = attn_weights_91_cast)[name = tensor("op_1471_cast")]; + tensor attn_weights_93_cast = add(x = var_1471_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_93_cast")]; + tensor var_1476 = const()[name = tensor("op_1476"), val = tensor([20, 77, 77])]; + tensor input_245_cast = reshape(shape = var_1476, x = attn_weights_93_cast)[name = tensor("input_245_cast")]; + tensor input_247_cast = softmax(axis = var_5, x = input_245_cast)[name = tensor("input_247_cast")]; + tensor attn_output_91_transpose_x_0 = const()[name = tensor("attn_output_91_transpose_x_0"), val = tensor(false)]; + tensor attn_output_91_transpose_y_0 = const()[name = tensor("attn_output_91_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_91_cast")]; + tensor var_1481 = const()[name = tensor("op_1481"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_93_cast = reshape(shape = var_1481, x = attn_output_91_cast)[name = tensor("attn_output_93_cast")]; + tensor attn_output_95_perm_0 = const()[name = tensor("attn_output_95_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1484 = const()[name = tensor("op_1484"), val = tensor([1, 77, 1280])]; + tensor transpose_80 = transpose(perm = attn_output_95_perm_0, x = attn_output_93_cast)[name = tensor("transpose_80")]; + tensor input_249_cast = reshape(shape = var_1484, x = transpose_80)[name = tensor("input_249_cast")]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(351886528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353115392))), name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353115584)))]; + tensor 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_palettized, x = input_249_cast)[name = tensor("hidden_states_93_cast")]; + tensor input_251_cast = add(x = input_243_cast, y = hidden_states_93_cast)[name = tensor("input_251_cast")]; + tensor input_253_axes_0 = const()[name = tensor("input_253_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353118208)))]; + tensor text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353120832)))]; + tensor 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("input_253_cast")]; + tensor text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353123456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(358038720))), name = tensor("text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(358038912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(358042816))), name = tensor("text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_255_cast = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized, x = input_253_cast)[name = tensor("input_255_cast")]; + tensor input_257_mode_0 = const()[name = tensor("input_257_mode_0"), val = tensor("EXACT")]; + tensor input_257_cast = gelu(mode = input_257_mode_0, x = input_255_cast)[name = tensor("input_257_cast")]; + tensor text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(358043008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362958272))), name = tensor("text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362958464)))]; + tensor 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_palettized, x = input_257_cast)[name = tensor("hidden_states_95_cast")]; + tensor input_259_cast = add(x = input_251_cast, y = hidden_states_95_cast)[name = tensor("input_259_cast")]; + tensor hidden_states_97_axes_0 = const()[name = tensor("hidden_states_97_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362961088)))]; + tensor text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362963712)))]; + tensor 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("hidden_states_97_cast")]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362966336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(364195200))), name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(364195392)))]; + tensor 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_palettized, x = hidden_states_97_cast)[name = tensor("op_1522_cast")]; + tensor var_1523_to_fp16 = const()[name = tensor("op_1523_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_101_cast = mul(x = var_1522_cast, y = var_1523_to_fp16)[name = tensor("tensor_101_cast")]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(364198016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(365426880))), name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(365427072)))]; + tensor 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_palettized, x = hidden_states_97_cast)[name = tensor("tensor_97_cast")]; + tensor var_1528 = const()[name = tensor("op_1528"), val = tensor([1, -1, 20, 64])]; + tensor var_1529_cast = reshape(shape = var_1528, x = tensor_97_cast)[name = tensor("op_1529_cast")]; + tensor var_1530_perm_0 = const()[name = tensor("op_1530_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(365429696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(366658560))), name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(366658752)))]; + tensor 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_palettized, x = hidden_states_97_cast)[name = tensor("tensor_99_cast")]; + tensor var_1535 = const()[name = tensor("op_1535"), val = tensor([1, -1, 20, 64])]; + tensor var_1536_cast = reshape(shape = var_1535, x = tensor_99_cast)[name = tensor("op_1536_cast")]; + tensor var_1537_perm_0 = const()[name = tensor("op_1537_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1544 = const()[name = tensor("op_1544"), val = tensor([1, 77, 20, 64])]; + tensor var_1545_cast = reshape(shape = var_1544, x = tensor_101_cast)[name = tensor("op_1545_cast")]; + tensor var_1546_perm_0 = const()[name = tensor("op_1546_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1548 = const()[name = tensor("op_1548"), val = tensor([20, -1, 64])]; + tensor transpose_79 = transpose(perm = var_1546_perm_0, x = var_1545_cast)[name = tensor("transpose_79")]; + tensor query_states_33_cast = reshape(shape = var_1548, x = transpose_79)[name = tensor("query_states_33_cast")]; + tensor var_1550 = const()[name = tensor("op_1550"), val = tensor([20, -1, 64])]; + tensor transpose_78 = transpose(perm = var_1530_perm_0, x = var_1529_cast)[name = tensor("transpose_78")]; + tensor key_states_67_cast = reshape(shape = var_1550, x = transpose_78)[name = tensor("key_states_67_cast")]; + tensor var_1552 = const()[name = tensor("op_1552"), val = tensor([20, -1, 64])]; + tensor transpose_77 = transpose(perm = var_1537_perm_0, x = var_1536_cast)[name = tensor("transpose_77")]; + tensor value_states_67_cast = reshape(shape = var_1552, x = transpose_77)[name = tensor("value_states_67_cast")]; + tensor var_1555_perm_0 = const()[name = tensor("op_1555_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_97_transpose_x_0 = const()[name = tensor("attn_weights_97_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_97_transpose_y_0 = const()[name = tensor("attn_weights_97_transpose_y_0"), val = tensor(false)]; + tensor transpose_76 = transpose(perm = var_1555_perm_0, x = key_states_67_cast)[name = tensor("transpose_76")]; + tensor 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_76)[name = tensor("attn_weights_97_cast")]; + tensor var_1557 = const()[name = tensor("op_1557"), val = tensor([1, 20, 77, 77])]; + tensor var_1558_cast = reshape(shape = var_1557, x = attn_weights_97_cast)[name = tensor("op_1558_cast")]; + tensor attn_weights_99_cast = add(x = var_1558_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_99_cast")]; + tensor var_1563 = const()[name = tensor("op_1563"), val = tensor([20, 77, 77])]; + tensor input_261_cast = reshape(shape = var_1563, x = attn_weights_99_cast)[name = tensor("input_261_cast")]; + tensor input_263_cast = softmax(axis = var_5, x = input_261_cast)[name = tensor("input_263_cast")]; + tensor attn_output_97_transpose_x_0 = const()[name = tensor("attn_output_97_transpose_x_0"), val = tensor(false)]; + tensor attn_output_97_transpose_y_0 = const()[name = tensor("attn_output_97_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_97_cast")]; + tensor var_1568 = const()[name = tensor("op_1568"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_99_cast = reshape(shape = var_1568, x = attn_output_97_cast)[name = tensor("attn_output_99_cast")]; + tensor attn_output_101_perm_0 = const()[name = tensor("attn_output_101_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1571 = const()[name = tensor("op_1571"), val = tensor([1, 77, 1280])]; + tensor transpose_75 = transpose(perm = attn_output_101_perm_0, x = attn_output_99_cast)[name = tensor("transpose_75")]; + tensor input_265_cast = reshape(shape = var_1571, x = transpose_75)[name = tensor("input_265_cast")]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(366661376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(367890240))), name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(367890432)))]; + tensor 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_palettized, x = input_265_cast)[name = tensor("hidden_states_99_cast")]; + tensor input_267_cast = add(x = input_259_cast, y = hidden_states_99_cast)[name = tensor("input_267_cast")]; + tensor input_269_axes_0 = const()[name = tensor("input_269_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(367893056)))]; + tensor text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(367895680)))]; + tensor 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("input_269_cast")]; + tensor text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(367898304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(372813568))), name = tensor("text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(372813760))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(372817664))), name = tensor("text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_271_cast = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized, x = input_269_cast)[name = tensor("input_271_cast")]; + tensor input_273_mode_0 = const()[name = tensor("input_273_mode_0"), val = tensor("EXACT")]; + tensor input_273_cast = gelu(mode = input_273_mode_0, x = input_271_cast)[name = tensor("input_273_cast")]; + tensor text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(372817856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377733120))), name = tensor("text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377733312)))]; + tensor 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_palettized, x = input_273_cast)[name = tensor("hidden_states_101_cast")]; + tensor input_275_cast = add(x = input_267_cast, y = hidden_states_101_cast)[name = tensor("input_275_cast")]; + tensor hidden_states_103_axes_0 = const()[name = tensor("hidden_states_103_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377735936)))]; + tensor text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377738560)))]; + tensor 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("hidden_states_103_cast")]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377741184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(378970048))), name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(378970240)))]; + tensor 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_palettized, x = hidden_states_103_cast)[name = tensor("op_1609_cast")]; + tensor var_1610_to_fp16 = const()[name = tensor("op_1610_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_107_cast = mul(x = var_1609_cast, y = var_1610_to_fp16)[name = tensor("tensor_107_cast")]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(378972864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380201728))), name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380201920)))]; + tensor 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_palettized, x = hidden_states_103_cast)[name = tensor("tensor_103_cast")]; + tensor var_1615 = const()[name = tensor("op_1615"), val = tensor([1, -1, 20, 64])]; + tensor var_1616_cast = reshape(shape = var_1615, x = tensor_103_cast)[name = tensor("op_1616_cast")]; + tensor var_1617_perm_0 = const()[name = tensor("op_1617_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380204544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(381433408))), name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(381433600)))]; + tensor 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_palettized, x = hidden_states_103_cast)[name = tensor("tensor_105_cast")]; + tensor var_1622 = const()[name = tensor("op_1622"), val = tensor([1, -1, 20, 64])]; + tensor var_1623_cast = reshape(shape = var_1622, x = tensor_105_cast)[name = tensor("op_1623_cast")]; + tensor var_1624_perm_0 = const()[name = tensor("op_1624_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1631 = const()[name = tensor("op_1631"), val = tensor([1, 77, 20, 64])]; + tensor var_1632_cast = reshape(shape = var_1631, x = tensor_107_cast)[name = tensor("op_1632_cast")]; + tensor var_1633_perm_0 = const()[name = tensor("op_1633_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1635 = const()[name = tensor("op_1635"), val = tensor([20, -1, 64])]; + tensor transpose_74 = transpose(perm = var_1633_perm_0, x = var_1632_cast)[name = tensor("transpose_74")]; + tensor query_states_35_cast = reshape(shape = var_1635, x = transpose_74)[name = tensor("query_states_35_cast")]; + tensor var_1637 = const()[name = tensor("op_1637"), val = tensor([20, -1, 64])]; + tensor transpose_73 = transpose(perm = var_1617_perm_0, x = var_1616_cast)[name = tensor("transpose_73")]; + tensor key_states_71_cast = reshape(shape = var_1637, x = transpose_73)[name = tensor("key_states_71_cast")]; + tensor var_1639 = const()[name = tensor("op_1639"), val = tensor([20, -1, 64])]; + tensor transpose_72 = transpose(perm = var_1624_perm_0, x = var_1623_cast)[name = tensor("transpose_72")]; + tensor value_states_71_cast = reshape(shape = var_1639, x = transpose_72)[name = tensor("value_states_71_cast")]; + tensor var_1642_perm_0 = const()[name = tensor("op_1642_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_103_transpose_x_0 = const()[name = tensor("attn_weights_103_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_103_transpose_y_0 = const()[name = tensor("attn_weights_103_transpose_y_0"), val = tensor(false)]; + tensor transpose_71 = transpose(perm = var_1642_perm_0, x = key_states_71_cast)[name = tensor("transpose_71")]; + tensor 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_71)[name = tensor("attn_weights_103_cast")]; + tensor var_1644 = const()[name = tensor("op_1644"), val = tensor([1, 20, 77, 77])]; + tensor var_1645_cast = reshape(shape = var_1644, x = attn_weights_103_cast)[name = tensor("op_1645_cast")]; + tensor attn_weights_105_cast = add(x = var_1645_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_105_cast")]; + tensor var_1650 = const()[name = tensor("op_1650"), val = tensor([20, 77, 77])]; + tensor input_277_cast = reshape(shape = var_1650, x = attn_weights_105_cast)[name = tensor("input_277_cast")]; + tensor input_279_cast = softmax(axis = var_5, x = input_277_cast)[name = tensor("input_279_cast")]; + tensor attn_output_103_transpose_x_0 = const()[name = tensor("attn_output_103_transpose_x_0"), val = tensor(false)]; + tensor attn_output_103_transpose_y_0 = const()[name = tensor("attn_output_103_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_103_cast")]; + tensor var_1655 = const()[name = tensor("op_1655"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_105_cast = reshape(shape = var_1655, x = attn_output_103_cast)[name = tensor("attn_output_105_cast")]; + tensor attn_output_107_perm_0 = const()[name = tensor("attn_output_107_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1658 = const()[name = tensor("op_1658"), val = tensor([1, 77, 1280])]; + tensor transpose_70 = transpose(perm = attn_output_107_perm_0, x = attn_output_105_cast)[name = tensor("transpose_70")]; + tensor input_281_cast = reshape(shape = var_1658, x = transpose_70)[name = tensor("input_281_cast")]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(381436224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(382665088))), name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(382665280)))]; + tensor 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_palettized, x = input_281_cast)[name = tensor("hidden_states_105_cast")]; + tensor input_283_cast = add(x = input_275_cast, y = hidden_states_105_cast)[name = tensor("input_283_cast")]; + tensor input_285_axes_0 = const()[name = tensor("input_285_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(382667904)))]; + tensor text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(382670528)))]; + tensor 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("input_285_cast")]; + tensor text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(382673152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387588416))), name = tensor("text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387588608))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387592512))), name = tensor("text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_287_cast = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized, x = input_285_cast)[name = tensor("input_287_cast")]; + tensor input_289_mode_0 = const()[name = tensor("input_289_mode_0"), val = tensor("EXACT")]; + tensor input_289_cast = gelu(mode = input_289_mode_0, x = input_287_cast)[name = tensor("input_289_cast")]; + tensor text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387592704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392507968))), name = tensor("text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392508160)))]; + tensor 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_palettized, x = input_289_cast)[name = tensor("hidden_states_107_cast")]; + tensor input_291_cast = add(x = input_283_cast, y = hidden_states_107_cast)[name = tensor("input_291_cast")]; + tensor hidden_states_109_axes_0 = const()[name = tensor("hidden_states_109_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392510784)))]; + tensor text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392513408)))]; + tensor 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("hidden_states_109_cast")]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(392516032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393744896))), name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393745088)))]; + tensor 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_palettized, x = hidden_states_109_cast)[name = tensor("op_1696_cast")]; + tensor var_1697_to_fp16 = const()[name = tensor("op_1697_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_113_cast = mul(x = var_1696_cast, y = var_1697_to_fp16)[name = tensor("tensor_113_cast")]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393747712))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(394976576))), name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(394976768)))]; + tensor 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_palettized, x = hidden_states_109_cast)[name = tensor("tensor_109_cast")]; + tensor var_1702 = const()[name = tensor("op_1702"), val = tensor([1, -1, 20, 64])]; + tensor var_1703_cast = reshape(shape = var_1702, x = tensor_109_cast)[name = tensor("op_1703_cast")]; + tensor var_1704_perm_0 = const()[name = tensor("op_1704_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(394979392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396208256))), name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396208448)))]; + tensor 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_palettized, x = hidden_states_109_cast)[name = tensor("tensor_111_cast")]; + tensor var_1709 = const()[name = tensor("op_1709"), val = tensor([1, -1, 20, 64])]; + tensor var_1710_cast = reshape(shape = var_1709, x = tensor_111_cast)[name = tensor("op_1710_cast")]; + tensor var_1711_perm_0 = const()[name = tensor("op_1711_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1718 = const()[name = tensor("op_1718"), val = tensor([1, 77, 20, 64])]; + tensor var_1719_cast = reshape(shape = var_1718, x = tensor_113_cast)[name = tensor("op_1719_cast")]; + tensor var_1720_perm_0 = const()[name = tensor("op_1720_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1722 = const()[name = tensor("op_1722"), val = tensor([20, -1, 64])]; + tensor transpose_69 = transpose(perm = var_1720_perm_0, x = var_1719_cast)[name = tensor("transpose_69")]; + tensor query_states_37_cast = reshape(shape = var_1722, x = transpose_69)[name = tensor("query_states_37_cast")]; + tensor var_1724 = const()[name = tensor("op_1724"), val = tensor([20, -1, 64])]; + tensor transpose_68 = transpose(perm = var_1704_perm_0, x = var_1703_cast)[name = tensor("transpose_68")]; + tensor key_states_75_cast = reshape(shape = var_1724, x = transpose_68)[name = tensor("key_states_75_cast")]; + tensor var_1726 = const()[name = tensor("op_1726"), val = tensor([20, -1, 64])]; + tensor transpose_67 = transpose(perm = var_1711_perm_0, x = var_1710_cast)[name = tensor("transpose_67")]; + tensor value_states_75_cast = reshape(shape = var_1726, x = transpose_67)[name = tensor("value_states_75_cast")]; + tensor var_1729_perm_0 = const()[name = tensor("op_1729_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_109_transpose_x_0 = const()[name = tensor("attn_weights_109_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_109_transpose_y_0 = const()[name = tensor("attn_weights_109_transpose_y_0"), val = tensor(false)]; + tensor transpose_66 = transpose(perm = var_1729_perm_0, x = key_states_75_cast)[name = tensor("transpose_66")]; + tensor 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_66)[name = tensor("attn_weights_109_cast")]; + tensor var_1731 = const()[name = tensor("op_1731"), val = tensor([1, 20, 77, 77])]; + tensor var_1732_cast = reshape(shape = var_1731, x = attn_weights_109_cast)[name = tensor("op_1732_cast")]; + tensor attn_weights_111_cast = add(x = var_1732_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_111_cast")]; + tensor var_1737 = const()[name = tensor("op_1737"), val = tensor([20, 77, 77])]; + tensor input_293_cast = reshape(shape = var_1737, x = attn_weights_111_cast)[name = tensor("input_293_cast")]; + tensor input_295_cast = softmax(axis = var_5, x = input_293_cast)[name = tensor("input_295_cast")]; + tensor attn_output_109_transpose_x_0 = const()[name = tensor("attn_output_109_transpose_x_0"), val = tensor(false)]; + tensor attn_output_109_transpose_y_0 = const()[name = tensor("attn_output_109_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_109_cast")]; + tensor var_1742 = const()[name = tensor("op_1742"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_111_cast = reshape(shape = var_1742, x = attn_output_109_cast)[name = tensor("attn_output_111_cast")]; + tensor attn_output_113_perm_0 = const()[name = tensor("attn_output_113_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1745 = const()[name = tensor("op_1745"), val = tensor([1, 77, 1280])]; + tensor transpose_65 = transpose(perm = attn_output_113_perm_0, x = attn_output_111_cast)[name = tensor("transpose_65")]; + tensor input_297_cast = reshape(shape = var_1745, x = transpose_65)[name = tensor("input_297_cast")]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396211072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397439936))), name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397440128)))]; + tensor 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_palettized, x = input_297_cast)[name = tensor("hidden_states_111_cast")]; + tensor input_299_cast = add(x = input_291_cast, y = hidden_states_111_cast)[name = tensor("input_299_cast")]; + tensor input_301_axes_0 = const()[name = tensor("input_301_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397442752)))]; + tensor text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397445376)))]; + tensor 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("input_301_cast")]; + tensor text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397448000))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(402363264))), name = tensor("text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(402363456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(402367360))), name = tensor("text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_303_cast = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized, x = input_301_cast)[name = tensor("input_303_cast")]; + tensor input_305_mode_0 = const()[name = tensor("input_305_mode_0"), val = tensor("EXACT")]; + tensor input_305_cast = gelu(mode = input_305_mode_0, x = input_303_cast)[name = tensor("input_305_cast")]; + tensor text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(402367552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(407282816))), name = tensor("text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(407283008)))]; + tensor 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_palettized, x = input_305_cast)[name = tensor("hidden_states_113_cast")]; + tensor input_307_cast = add(x = input_299_cast, y = hidden_states_113_cast)[name = tensor("input_307_cast")]; + tensor hidden_states_115_axes_0 = const()[name = tensor("hidden_states_115_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(407285632)))]; + tensor text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(407288256)))]; + tensor 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("hidden_states_115_cast")]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(407290880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(408519744))), name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(408519936)))]; + tensor 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_palettized, x = hidden_states_115_cast)[name = tensor("op_1783_cast")]; + tensor var_1784_to_fp16 = const()[name = tensor("op_1784_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_119_cast = mul(x = var_1783_cast, y = var_1784_to_fp16)[name = tensor("tensor_119_cast")]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(408522560))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409751424))), name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409751616)))]; + tensor 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_palettized, x = hidden_states_115_cast)[name = tensor("tensor_115_cast")]; + tensor var_1789 = const()[name = tensor("op_1789"), val = tensor([1, -1, 20, 64])]; + tensor var_1790_cast = reshape(shape = var_1789, x = tensor_115_cast)[name = tensor("op_1790_cast")]; + tensor var_1791_perm_0 = const()[name = tensor("op_1791_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409754240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(410983104))), name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(410983296)))]; + tensor 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_palettized, x = hidden_states_115_cast)[name = tensor("tensor_117_cast")]; + tensor var_1796 = const()[name = tensor("op_1796"), val = tensor([1, -1, 20, 64])]; + tensor var_1797_cast = reshape(shape = var_1796, x = tensor_117_cast)[name = tensor("op_1797_cast")]; + tensor var_1798_perm_0 = const()[name = tensor("op_1798_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1805 = const()[name = tensor("op_1805"), val = tensor([1, 77, 20, 64])]; + tensor var_1806_cast = reshape(shape = var_1805, x = tensor_119_cast)[name = tensor("op_1806_cast")]; + tensor var_1807_perm_0 = const()[name = tensor("op_1807_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1809 = const()[name = tensor("op_1809"), val = tensor([20, -1, 64])]; + tensor transpose_64 = transpose(perm = var_1807_perm_0, x = var_1806_cast)[name = tensor("transpose_64")]; + tensor query_states_39_cast = reshape(shape = var_1809, x = transpose_64)[name = tensor("query_states_39_cast")]; + tensor var_1811 = const()[name = tensor("op_1811"), val = tensor([20, -1, 64])]; + tensor transpose_63 = transpose(perm = var_1791_perm_0, x = var_1790_cast)[name = tensor("transpose_63")]; + tensor key_states_79_cast = reshape(shape = var_1811, x = transpose_63)[name = tensor("key_states_79_cast")]; + tensor var_1813 = const()[name = tensor("op_1813"), val = tensor([20, -1, 64])]; + tensor transpose_62 = transpose(perm = var_1798_perm_0, x = var_1797_cast)[name = tensor("transpose_62")]; + tensor value_states_79_cast = reshape(shape = var_1813, x = transpose_62)[name = tensor("value_states_79_cast")]; + tensor var_1816_perm_0 = const()[name = tensor("op_1816_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_115_transpose_x_0 = const()[name = tensor("attn_weights_115_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_115_transpose_y_0 = const()[name = tensor("attn_weights_115_transpose_y_0"), val = tensor(false)]; + tensor transpose_61 = transpose(perm = var_1816_perm_0, x = key_states_79_cast)[name = tensor("transpose_61")]; + tensor 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_61)[name = tensor("attn_weights_115_cast")]; + tensor var_1818 = const()[name = tensor("op_1818"), val = tensor([1, 20, 77, 77])]; + tensor var_1819_cast = reshape(shape = var_1818, x = attn_weights_115_cast)[name = tensor("op_1819_cast")]; + tensor attn_weights_117_cast = add(x = var_1819_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_117_cast")]; + tensor var_1824 = const()[name = tensor("op_1824"), val = tensor([20, 77, 77])]; + tensor input_309_cast = reshape(shape = var_1824, x = attn_weights_117_cast)[name = tensor("input_309_cast")]; + tensor input_311_cast = softmax(axis = var_5, x = input_309_cast)[name = tensor("input_311_cast")]; + tensor attn_output_115_transpose_x_0 = const()[name = tensor("attn_output_115_transpose_x_0"), val = tensor(false)]; + tensor attn_output_115_transpose_y_0 = const()[name = tensor("attn_output_115_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_115_cast")]; + tensor var_1829 = const()[name = tensor("op_1829"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_117_cast = reshape(shape = var_1829, x = attn_output_115_cast)[name = tensor("attn_output_117_cast")]; + tensor attn_output_119_perm_0 = const()[name = tensor("attn_output_119_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1832 = const()[name = tensor("op_1832"), val = tensor([1, 77, 1280])]; + tensor transpose_60 = transpose(perm = attn_output_119_perm_0, x = attn_output_117_cast)[name = tensor("transpose_60")]; + tensor input_313_cast = reshape(shape = var_1832, x = transpose_60)[name = tensor("input_313_cast")]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(410985920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412214784))), name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412214976)))]; + tensor 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_palettized, x = input_313_cast)[name = tensor("hidden_states_117_cast")]; + tensor input_315_cast = add(x = input_307_cast, y = hidden_states_117_cast)[name = tensor("input_315_cast")]; + tensor input_317_axes_0 = const()[name = tensor("input_317_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412217600)))]; + tensor text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412220224)))]; + tensor 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("input_317_cast")]; + tensor text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412222848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417138112))), name = tensor("text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417138304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417142208))), name = tensor("text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_319_cast = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized, x = input_317_cast)[name = tensor("input_319_cast")]; + tensor input_321_mode_0 = const()[name = tensor("input_321_mode_0"), val = tensor("EXACT")]; + tensor input_321_cast = gelu(mode = input_321_mode_0, x = input_319_cast)[name = tensor("input_321_cast")]; + tensor text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417142400))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422057664))), name = tensor("text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422057856)))]; + tensor 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_palettized, x = input_321_cast)[name = tensor("hidden_states_119_cast")]; + tensor input_323_cast = add(x = input_315_cast, y = hidden_states_119_cast)[name = tensor("input_323_cast")]; + tensor hidden_states_121_axes_0 = const()[name = tensor("hidden_states_121_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422060480)))]; + tensor text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422063104)))]; + tensor 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("hidden_states_121_cast")]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(422065728))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(423294592))), name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(423294784)))]; + tensor 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_palettized, x = hidden_states_121_cast)[name = tensor("op_1870_cast")]; + tensor var_1871_to_fp16 = const()[name = tensor("op_1871_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_125_cast = mul(x = var_1870_cast, y = var_1871_to_fp16)[name = tensor("tensor_125_cast")]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(423297408))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(424526272))), name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(424526464)))]; + tensor 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_palettized, x = hidden_states_121_cast)[name = tensor("tensor_121_cast")]; + tensor var_1876 = const()[name = tensor("op_1876"), val = tensor([1, -1, 20, 64])]; + tensor var_1877_cast = reshape(shape = var_1876, x = tensor_121_cast)[name = tensor("op_1877_cast")]; + tensor var_1878_perm_0 = const()[name = tensor("op_1878_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(424529088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425757952))), name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425758144)))]; + tensor 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_palettized, x = hidden_states_121_cast)[name = tensor("tensor_123_cast")]; + tensor var_1883 = const()[name = tensor("op_1883"), val = tensor([1, -1, 20, 64])]; + tensor var_1884_cast = reshape(shape = var_1883, x = tensor_123_cast)[name = tensor("op_1884_cast")]; + tensor var_1885_perm_0 = const()[name = tensor("op_1885_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1892 = const()[name = tensor("op_1892"), val = tensor([1, 77, 20, 64])]; + tensor var_1893_cast = reshape(shape = var_1892, x = tensor_125_cast)[name = tensor("op_1893_cast")]; + tensor var_1894_perm_0 = const()[name = tensor("op_1894_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1896 = const()[name = tensor("op_1896"), val = tensor([20, -1, 64])]; + tensor transpose_59 = transpose(perm = var_1894_perm_0, x = var_1893_cast)[name = tensor("transpose_59")]; + tensor query_states_41_cast = reshape(shape = var_1896, x = transpose_59)[name = tensor("query_states_41_cast")]; + tensor var_1898 = const()[name = tensor("op_1898"), val = tensor([20, -1, 64])]; + tensor transpose_58 = transpose(perm = var_1878_perm_0, x = var_1877_cast)[name = tensor("transpose_58")]; + tensor key_states_83_cast = reshape(shape = var_1898, x = transpose_58)[name = tensor("key_states_83_cast")]; + tensor var_1900 = const()[name = tensor("op_1900"), val = tensor([20, -1, 64])]; + tensor transpose_57 = transpose(perm = var_1885_perm_0, x = var_1884_cast)[name = tensor("transpose_57")]; + tensor value_states_83_cast = reshape(shape = var_1900, x = transpose_57)[name = tensor("value_states_83_cast")]; + tensor var_1903_perm_0 = const()[name = tensor("op_1903_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_121_transpose_x_0 = const()[name = tensor("attn_weights_121_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_121_transpose_y_0 = const()[name = tensor("attn_weights_121_transpose_y_0"), val = tensor(false)]; + tensor transpose_56 = transpose(perm = var_1903_perm_0, x = key_states_83_cast)[name = tensor("transpose_56")]; + tensor 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_56)[name = tensor("attn_weights_121_cast")]; + tensor var_1905 = const()[name = tensor("op_1905"), val = tensor([1, 20, 77, 77])]; + tensor var_1906_cast = reshape(shape = var_1905, x = attn_weights_121_cast)[name = tensor("op_1906_cast")]; + tensor attn_weights_123_cast = add(x = var_1906_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_123_cast")]; + tensor var_1911 = const()[name = tensor("op_1911"), val = tensor([20, 77, 77])]; + tensor input_325_cast = reshape(shape = var_1911, x = attn_weights_123_cast)[name = tensor("input_325_cast")]; + tensor input_327_cast = softmax(axis = var_5, x = input_325_cast)[name = tensor("input_327_cast")]; + tensor attn_output_121_transpose_x_0 = const()[name = tensor("attn_output_121_transpose_x_0"), val = tensor(false)]; + tensor attn_output_121_transpose_y_0 = const()[name = tensor("attn_output_121_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_121_cast")]; + tensor var_1916 = const()[name = tensor("op_1916"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_123_cast = reshape(shape = var_1916, x = attn_output_121_cast)[name = tensor("attn_output_123_cast")]; + tensor attn_output_125_perm_0 = const()[name = tensor("attn_output_125_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1919 = const()[name = tensor("op_1919"), val = tensor([1, 77, 1280])]; + tensor transpose_55 = transpose(perm = attn_output_125_perm_0, x = attn_output_123_cast)[name = tensor("transpose_55")]; + tensor input_329_cast = reshape(shape = var_1919, x = transpose_55)[name = tensor("input_329_cast")]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425760768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426989632))), name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426989824)))]; + tensor 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_palettized, x = input_329_cast)[name = tensor("hidden_states_123_cast")]; + tensor input_331_cast = add(x = input_323_cast, y = hidden_states_123_cast)[name = tensor("input_331_cast")]; + tensor input_333_axes_0 = const()[name = tensor("input_333_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426992448)))]; + tensor text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426995072)))]; + tensor 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("input_333_cast")]; + tensor text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(426997696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431912960))), name = tensor("text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431913152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431917056))), name = tensor("text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_335_cast = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized, x = input_333_cast)[name = tensor("input_335_cast")]; + tensor input_337_mode_0 = const()[name = tensor("input_337_mode_0"), val = tensor("EXACT")]; + tensor input_337_cast = gelu(mode = input_337_mode_0, x = input_335_cast)[name = tensor("input_337_cast")]; + tensor text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431917248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436832512))), name = tensor("text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436832704)))]; + tensor 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_palettized, x = input_337_cast)[name = tensor("hidden_states_125_cast")]; + tensor input_339_cast = add(x = input_331_cast, y = hidden_states_125_cast)[name = tensor("input_339_cast")]; + tensor hidden_states_127_axes_0 = const()[name = tensor("hidden_states_127_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436835328)))]; + tensor text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436837952)))]; + tensor 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("hidden_states_127_cast")]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436840576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438069440))), name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438069632)))]; + tensor 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_palettized, x = hidden_states_127_cast)[name = tensor("op_1957_cast")]; + tensor var_1958_to_fp16 = const()[name = tensor("op_1958_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_131_cast = mul(x = var_1957_cast, y = var_1958_to_fp16)[name = tensor("tensor_131_cast")]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438072256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(439301120))), name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(439301312)))]; + tensor 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_palettized, x = hidden_states_127_cast)[name = tensor("tensor_127_cast")]; + tensor var_1963 = const()[name = tensor("op_1963"), val = tensor([1, -1, 20, 64])]; + tensor var_1964_cast = reshape(shape = var_1963, x = tensor_127_cast)[name = tensor("op_1964_cast")]; + tensor var_1965_perm_0 = const()[name = tensor("op_1965_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(439303936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440532800))), name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440532992)))]; + tensor 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_palettized, x = hidden_states_127_cast)[name = tensor("tensor_129_cast")]; + tensor var_1970 = const()[name = tensor("op_1970"), val = tensor([1, -1, 20, 64])]; + tensor var_1971_cast = reshape(shape = var_1970, x = tensor_129_cast)[name = tensor("op_1971_cast")]; + tensor var_1972_perm_0 = const()[name = tensor("op_1972_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1979 = const()[name = tensor("op_1979"), val = tensor([1, 77, 20, 64])]; + tensor var_1980_cast = reshape(shape = var_1979, x = tensor_131_cast)[name = tensor("op_1980_cast")]; + tensor var_1981_perm_0 = const()[name = tensor("op_1981_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1983 = const()[name = tensor("op_1983"), val = tensor([20, -1, 64])]; + tensor transpose_54 = transpose(perm = var_1981_perm_0, x = var_1980_cast)[name = tensor("transpose_54")]; + tensor query_states_43_cast = reshape(shape = var_1983, x = transpose_54)[name = tensor("query_states_43_cast")]; + tensor var_1985 = const()[name = tensor("op_1985"), val = tensor([20, -1, 64])]; + tensor transpose_53 = transpose(perm = var_1965_perm_0, x = var_1964_cast)[name = tensor("transpose_53")]; + tensor key_states_87_cast = reshape(shape = var_1985, x = transpose_53)[name = tensor("key_states_87_cast")]; + tensor var_1987 = const()[name = tensor("op_1987"), val = tensor([20, -1, 64])]; + tensor transpose_52 = transpose(perm = var_1972_perm_0, x = var_1971_cast)[name = tensor("transpose_52")]; + tensor value_states_87_cast = reshape(shape = var_1987, x = transpose_52)[name = tensor("value_states_87_cast")]; + tensor var_1990_perm_0 = const()[name = tensor("op_1990_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_127_transpose_x_0 = const()[name = tensor("attn_weights_127_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_127_transpose_y_0 = const()[name = tensor("attn_weights_127_transpose_y_0"), val = tensor(false)]; + tensor transpose_51 = transpose(perm = var_1990_perm_0, x = key_states_87_cast)[name = tensor("transpose_51")]; + tensor 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_51)[name = tensor("attn_weights_127_cast")]; + tensor var_1992 = const()[name = tensor("op_1992"), val = tensor([1, 20, 77, 77])]; + tensor var_1993_cast = reshape(shape = var_1992, x = attn_weights_127_cast)[name = tensor("op_1993_cast")]; + tensor attn_weights_129_cast = add(x = var_1993_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_129_cast")]; + tensor var_1998 = const()[name = tensor("op_1998"), val = tensor([20, 77, 77])]; + tensor input_341_cast = reshape(shape = var_1998, x = attn_weights_129_cast)[name = tensor("input_341_cast")]; + tensor input_343_cast = softmax(axis = var_5, x = input_341_cast)[name = tensor("input_343_cast")]; + tensor attn_output_127_transpose_x_0 = const()[name = tensor("attn_output_127_transpose_x_0"), val = tensor(false)]; + tensor attn_output_127_transpose_y_0 = const()[name = tensor("attn_output_127_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_127_cast")]; + tensor var_2003 = const()[name = tensor("op_2003"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_129_cast = reshape(shape = var_2003, x = attn_output_127_cast)[name = tensor("attn_output_129_cast")]; + tensor attn_output_131_perm_0 = const()[name = tensor("attn_output_131_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2006 = const()[name = tensor("op_2006"), val = tensor([1, 77, 1280])]; + tensor transpose_50 = transpose(perm = attn_output_131_perm_0, x = attn_output_129_cast)[name = tensor("transpose_50")]; + tensor input_345_cast = reshape(shape = var_2006, x = transpose_50)[name = tensor("input_345_cast")]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440535616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(441764480))), name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(441764672)))]; + tensor 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_palettized, x = input_345_cast)[name = tensor("hidden_states_129_cast")]; + tensor input_347_cast = add(x = input_339_cast, y = hidden_states_129_cast)[name = tensor("input_347_cast")]; + tensor input_349_axes_0 = const()[name = tensor("input_349_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(441767296)))]; + tensor text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(441769920)))]; + tensor 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("input_349_cast")]; + tensor text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(441772544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(446687808))), name = tensor("text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(446688000))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(446691904))), name = tensor("text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_351_cast = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized, x = input_349_cast)[name = tensor("input_351_cast")]; + tensor input_353_mode_0 = const()[name = tensor("input_353_mode_0"), val = tensor("EXACT")]; + tensor input_353_cast = gelu(mode = input_353_mode_0, x = input_351_cast)[name = tensor("input_353_cast")]; + tensor text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(446692096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451607360))), name = tensor("text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451607552)))]; + tensor 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_palettized, x = input_353_cast)[name = tensor("hidden_states_131_cast")]; + tensor input_355_cast = add(x = input_347_cast, y = hidden_states_131_cast)[name = tensor("input_355_cast")]; + tensor hidden_states_133_axes_0 = const()[name = tensor("hidden_states_133_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451610176)))]; + tensor text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451612800)))]; + tensor 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("hidden_states_133_cast")]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(451615424))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(452844288))), name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(452844480)))]; + tensor 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_palettized, x = hidden_states_133_cast)[name = tensor("op_2044_cast")]; + tensor var_2045_to_fp16 = const()[name = tensor("op_2045_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_137_cast = mul(x = var_2044_cast, y = var_2045_to_fp16)[name = tensor("tensor_137_cast")]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(452847104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(454075968))), name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(454076160)))]; + tensor 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_palettized, x = hidden_states_133_cast)[name = tensor("tensor_133_cast")]; + tensor var_2050 = const()[name = tensor("op_2050"), val = tensor([1, -1, 20, 64])]; + tensor var_2051_cast = reshape(shape = var_2050, x = tensor_133_cast)[name = tensor("op_2051_cast")]; + tensor var_2052_perm_0 = const()[name = tensor("op_2052_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(454078784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(455307648))), name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(455307840)))]; + tensor 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_palettized, x = hidden_states_133_cast)[name = tensor("tensor_135_cast")]; + tensor var_2057 = const()[name = tensor("op_2057"), val = tensor([1, -1, 20, 64])]; + tensor var_2058_cast = reshape(shape = var_2057, x = tensor_135_cast)[name = tensor("op_2058_cast")]; + tensor var_2059_perm_0 = const()[name = tensor("op_2059_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2066 = const()[name = tensor("op_2066"), val = tensor([1, 77, 20, 64])]; + tensor var_2067_cast = reshape(shape = var_2066, x = tensor_137_cast)[name = tensor("op_2067_cast")]; + tensor var_2068_perm_0 = const()[name = tensor("op_2068_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2070 = const()[name = tensor("op_2070"), val = tensor([20, -1, 64])]; + tensor transpose_49 = transpose(perm = var_2068_perm_0, x = var_2067_cast)[name = tensor("transpose_49")]; + tensor query_states_45_cast = reshape(shape = var_2070, x = transpose_49)[name = tensor("query_states_45_cast")]; + tensor var_2072 = const()[name = tensor("op_2072"), val = tensor([20, -1, 64])]; + tensor transpose_48 = transpose(perm = var_2052_perm_0, x = var_2051_cast)[name = tensor("transpose_48")]; + tensor key_states_91_cast = reshape(shape = var_2072, x = transpose_48)[name = tensor("key_states_91_cast")]; + tensor var_2074 = const()[name = tensor("op_2074"), val = tensor([20, -1, 64])]; + tensor transpose_47 = transpose(perm = var_2059_perm_0, x = var_2058_cast)[name = tensor("transpose_47")]; + tensor value_states_91_cast = reshape(shape = var_2074, x = transpose_47)[name = tensor("value_states_91_cast")]; + tensor var_2077_perm_0 = const()[name = tensor("op_2077_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_133_transpose_x_0 = const()[name = tensor("attn_weights_133_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_133_transpose_y_0 = const()[name = tensor("attn_weights_133_transpose_y_0"), val = tensor(false)]; + tensor transpose_46 = transpose(perm = var_2077_perm_0, x = key_states_91_cast)[name = tensor("transpose_46")]; + tensor 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_46)[name = tensor("attn_weights_133_cast")]; + tensor var_2079 = const()[name = tensor("op_2079"), val = tensor([1, 20, 77, 77])]; + tensor var_2080_cast = reshape(shape = var_2079, x = attn_weights_133_cast)[name = tensor("op_2080_cast")]; + tensor attn_weights_135_cast = add(x = var_2080_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_135_cast")]; + tensor var_2085 = const()[name = tensor("op_2085"), val = tensor([20, 77, 77])]; + tensor input_357_cast = reshape(shape = var_2085, x = attn_weights_135_cast)[name = tensor("input_357_cast")]; + tensor input_359_cast = softmax(axis = var_5, x = input_357_cast)[name = tensor("input_359_cast")]; + tensor attn_output_133_transpose_x_0 = const()[name = tensor("attn_output_133_transpose_x_0"), val = tensor(false)]; + tensor attn_output_133_transpose_y_0 = const()[name = tensor("attn_output_133_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_133_cast")]; + tensor var_2090 = const()[name = tensor("op_2090"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_135_cast = reshape(shape = var_2090, x = attn_output_133_cast)[name = tensor("attn_output_135_cast")]; + tensor attn_output_137_perm_0 = const()[name = tensor("attn_output_137_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2093 = const()[name = tensor("op_2093"), val = tensor([1, 77, 1280])]; + tensor transpose_45 = transpose(perm = attn_output_137_perm_0, x = attn_output_135_cast)[name = tensor("transpose_45")]; + tensor input_361_cast = reshape(shape = var_2093, x = transpose_45)[name = tensor("input_361_cast")]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(455310464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(456539328))), name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(456539520)))]; + tensor 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_palettized, x = input_361_cast)[name = tensor("hidden_states_135_cast")]; + tensor input_363_cast = add(x = input_355_cast, y = hidden_states_135_cast)[name = tensor("input_363_cast")]; + tensor input_365_axes_0 = const()[name = tensor("input_365_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(456542144)))]; + tensor text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(456544768)))]; + tensor 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("input_365_cast")]; + tensor text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(456547392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(461462656))), name = tensor("text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(461462848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(461466752))), name = tensor("text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_367_cast = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized, x = input_365_cast)[name = tensor("input_367_cast")]; + tensor input_369_mode_0 = const()[name = tensor("input_369_mode_0"), val = tensor("EXACT")]; + tensor input_369_cast = gelu(mode = input_369_mode_0, x = input_367_cast)[name = tensor("input_369_cast")]; + tensor text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(461466944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(466382208))), name = tensor("text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(466382400)))]; + tensor 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_palettized, x = input_369_cast)[name = tensor("hidden_states_137_cast")]; + tensor input_371_cast = add(x = input_363_cast, y = hidden_states_137_cast)[name = tensor("input_371_cast")]; + tensor hidden_states_139_axes_0 = const()[name = tensor("hidden_states_139_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(466385024)))]; + tensor text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(466387648)))]; + tensor 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("hidden_states_139_cast")]; + tensor text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(466390272))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(467619136))), name = tensor("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(467619328)))]; + tensor 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_palettized, x = hidden_states_139_cast)[name = tensor("op_2131_cast")]; + tensor var_2132_to_fp16 = const()[name = tensor("op_2132_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_143_cast = mul(x = var_2131_cast, y = var_2132_to_fp16)[name = tensor("tensor_143_cast")]; + tensor text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(467621952))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(468850816))), name = tensor("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(468851008)))]; + tensor 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_palettized, x = hidden_states_139_cast)[name = tensor("tensor_139_cast")]; + tensor var_2137 = const()[name = tensor("op_2137"), val = tensor([1, -1, 20, 64])]; + tensor var_2138_cast = reshape(shape = var_2137, x = tensor_139_cast)[name = tensor("op_2138_cast")]; + tensor var_2139_perm_0 = const()[name = tensor("op_2139_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(468853632))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(470082496))), name = tensor("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(470082688)))]; + tensor 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_palettized, x = hidden_states_139_cast)[name = tensor("tensor_141_cast")]; + tensor var_2144 = const()[name = tensor("op_2144"), val = tensor([1, -1, 20, 64])]; + tensor var_2145_cast = reshape(shape = var_2144, x = tensor_141_cast)[name = tensor("op_2145_cast")]; + tensor var_2146_perm_0 = const()[name = tensor("op_2146_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2153 = const()[name = tensor("op_2153"), val = tensor([1, 77, 20, 64])]; + tensor var_2154_cast = reshape(shape = var_2153, x = tensor_143_cast)[name = tensor("op_2154_cast")]; + tensor var_2155_perm_0 = const()[name = tensor("op_2155_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2157 = const()[name = tensor("op_2157"), val = tensor([20, -1, 64])]; + tensor transpose_44 = transpose(perm = var_2155_perm_0, x = var_2154_cast)[name = tensor("transpose_44")]; + tensor query_states_47_cast = reshape(shape = var_2157, x = transpose_44)[name = tensor("query_states_47_cast")]; + tensor var_2159 = const()[name = tensor("op_2159"), val = tensor([20, -1, 64])]; + tensor transpose_43 = transpose(perm = var_2139_perm_0, x = var_2138_cast)[name = tensor("transpose_43")]; + tensor key_states_95_cast = reshape(shape = var_2159, x = transpose_43)[name = tensor("key_states_95_cast")]; + tensor var_2161 = const()[name = tensor("op_2161"), val = tensor([20, -1, 64])]; + tensor transpose_42 = transpose(perm = var_2146_perm_0, x = var_2145_cast)[name = tensor("transpose_42")]; + tensor value_states_95_cast = reshape(shape = var_2161, x = transpose_42)[name = tensor("value_states_95_cast")]; + tensor var_2164_perm_0 = const()[name = tensor("op_2164_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_139_transpose_x_0 = const()[name = tensor("attn_weights_139_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_139_transpose_y_0 = const()[name = tensor("attn_weights_139_transpose_y_0"), val = tensor(false)]; + tensor transpose_41 = transpose(perm = var_2164_perm_0, x = key_states_95_cast)[name = tensor("transpose_41")]; + tensor 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_41)[name = tensor("attn_weights_139_cast")]; + tensor var_2166 = const()[name = tensor("op_2166"), val = tensor([1, 20, 77, 77])]; + tensor var_2167_cast = reshape(shape = var_2166, x = attn_weights_139_cast)[name = tensor("op_2167_cast")]; + tensor attn_weights_141_cast = add(x = var_2167_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_141_cast")]; + tensor var_2172 = const()[name = tensor("op_2172"), val = tensor([20, 77, 77])]; + tensor input_373_cast = reshape(shape = var_2172, x = attn_weights_141_cast)[name = tensor("input_373_cast")]; + tensor input_375_cast = softmax(axis = var_5, x = input_373_cast)[name = tensor("input_375_cast")]; + tensor attn_output_139_transpose_x_0 = const()[name = tensor("attn_output_139_transpose_x_0"), val = tensor(false)]; + tensor attn_output_139_transpose_y_0 = const()[name = tensor("attn_output_139_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_139_cast")]; + tensor var_2177 = const()[name = tensor("op_2177"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_141_cast = reshape(shape = var_2177, x = attn_output_139_cast)[name = tensor("attn_output_141_cast")]; + tensor attn_output_143_perm_0 = const()[name = tensor("attn_output_143_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2180 = const()[name = tensor("op_2180"), val = tensor([1, 77, 1280])]; + tensor transpose_40 = transpose(perm = attn_output_143_perm_0, x = attn_output_141_cast)[name = tensor("transpose_40")]; + tensor input_377_cast = reshape(shape = var_2180, x = transpose_40)[name = tensor("input_377_cast")]; + tensor text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(470085312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471314176))), name = tensor("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471314368)))]; + tensor 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_palettized, x = input_377_cast)[name = tensor("hidden_states_141_cast")]; + tensor input_379_cast = add(x = input_371_cast, y = hidden_states_141_cast)[name = tensor("input_379_cast")]; + tensor input_381_axes_0 = const()[name = tensor("input_381_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471316992)))]; + tensor text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471319616)))]; + tensor 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("input_381_cast")]; + tensor text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(471322240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(476237504))), name = tensor("text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(476237696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(476241600))), name = tensor("text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_383_cast = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized, x = input_381_cast)[name = tensor("input_383_cast")]; + tensor input_385_mode_0 = const()[name = tensor("input_385_mode_0"), val = tensor("EXACT")]; + tensor input_385_cast = gelu(mode = input_385_mode_0, x = input_383_cast)[name = tensor("input_385_cast")]; + tensor text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(476241792))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(481157056))), name = tensor("text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(481157248)))]; + tensor 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_palettized, x = input_385_cast)[name = tensor("hidden_states_143_cast")]; + tensor input_387_cast = add(x = input_379_cast, y = hidden_states_143_cast)[name = tensor("input_387_cast")]; + tensor hidden_states_145_axes_0 = const()[name = tensor("hidden_states_145_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(481159872)))]; + tensor text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(481162496)))]; + tensor 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("hidden_states_145_cast")]; + tensor text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(481165120))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(482393984))), name = tensor("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(482394176)))]; + tensor 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_palettized, x = hidden_states_145_cast)[name = tensor("op_2218_cast")]; + tensor var_2219_to_fp16 = const()[name = tensor("op_2219_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_149_cast = mul(x = var_2218_cast, y = var_2219_to_fp16)[name = tensor("tensor_149_cast")]; + tensor text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(482396800))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(483625664))), name = tensor("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(483625856)))]; + tensor 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_palettized, x = hidden_states_145_cast)[name = tensor("tensor_145_cast")]; + tensor var_2224 = const()[name = tensor("op_2224"), val = tensor([1, -1, 20, 64])]; + tensor var_2225_cast = reshape(shape = var_2224, x = tensor_145_cast)[name = tensor("op_2225_cast")]; + tensor var_2226_perm_0 = const()[name = tensor("op_2226_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(483628480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(484857344))), name = tensor("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(484857536)))]; + tensor 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_palettized, x = hidden_states_145_cast)[name = tensor("tensor_147_cast")]; + tensor var_2231 = const()[name = tensor("op_2231"), val = tensor([1, -1, 20, 64])]; + tensor var_2232_cast = reshape(shape = var_2231, x = tensor_147_cast)[name = tensor("op_2232_cast")]; + tensor var_2233_perm_0 = const()[name = tensor("op_2233_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2240 = const()[name = tensor("op_2240"), val = tensor([1, 77, 20, 64])]; + tensor var_2241_cast = reshape(shape = var_2240, x = tensor_149_cast)[name = tensor("op_2241_cast")]; + tensor var_2242_perm_0 = const()[name = tensor("op_2242_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2244 = const()[name = tensor("op_2244"), val = tensor([20, -1, 64])]; + tensor transpose_39 = transpose(perm = var_2242_perm_0, x = var_2241_cast)[name = tensor("transpose_39")]; + tensor query_states_49_cast = reshape(shape = var_2244, x = transpose_39)[name = tensor("query_states_49_cast")]; + tensor var_2246 = const()[name = tensor("op_2246"), val = tensor([20, -1, 64])]; + tensor transpose_38 = transpose(perm = var_2226_perm_0, x = var_2225_cast)[name = tensor("transpose_38")]; + tensor key_states_99_cast = reshape(shape = var_2246, x = transpose_38)[name = tensor("key_states_99_cast")]; + tensor var_2248 = const()[name = tensor("op_2248"), val = tensor([20, -1, 64])]; + tensor transpose_37 = transpose(perm = var_2233_perm_0, x = var_2232_cast)[name = tensor("transpose_37")]; + tensor value_states_99_cast = reshape(shape = var_2248, x = transpose_37)[name = tensor("value_states_99_cast")]; + tensor var_2251_perm_0 = const()[name = tensor("op_2251_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_145_transpose_x_0 = const()[name = tensor("attn_weights_145_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_145_transpose_y_0 = const()[name = tensor("attn_weights_145_transpose_y_0"), val = tensor(false)]; + tensor transpose_36 = transpose(perm = var_2251_perm_0, x = key_states_99_cast)[name = tensor("transpose_36")]; + tensor 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_36)[name = tensor("attn_weights_145_cast")]; + tensor var_2253 = const()[name = tensor("op_2253"), val = tensor([1, 20, 77, 77])]; + tensor var_2254_cast = reshape(shape = var_2253, x = attn_weights_145_cast)[name = tensor("op_2254_cast")]; + tensor attn_weights_147_cast = add(x = var_2254_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_147_cast")]; + tensor var_2259 = const()[name = tensor("op_2259"), val = tensor([20, 77, 77])]; + tensor input_389_cast = reshape(shape = var_2259, x = attn_weights_147_cast)[name = tensor("input_389_cast")]; + tensor input_391_cast = softmax(axis = var_5, x = input_389_cast)[name = tensor("input_391_cast")]; + tensor attn_output_145_transpose_x_0 = const()[name = tensor("attn_output_145_transpose_x_0"), val = tensor(false)]; + tensor attn_output_145_transpose_y_0 = const()[name = tensor("attn_output_145_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_145_cast")]; + tensor var_2264 = const()[name = tensor("op_2264"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_147_cast = reshape(shape = var_2264, x = attn_output_145_cast)[name = tensor("attn_output_147_cast")]; + tensor attn_output_149_perm_0 = const()[name = tensor("attn_output_149_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2267 = const()[name = tensor("op_2267"), val = tensor([1, 77, 1280])]; + tensor transpose_35 = transpose(perm = attn_output_149_perm_0, x = attn_output_147_cast)[name = tensor("transpose_35")]; + tensor input_393_cast = reshape(shape = var_2267, x = transpose_35)[name = tensor("input_393_cast")]; + tensor text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(484860160))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(486089024))), name = tensor("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(486089216)))]; + tensor 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_palettized, x = input_393_cast)[name = tensor("hidden_states_147_cast")]; + tensor input_395_cast = add(x = input_387_cast, y = hidden_states_147_cast)[name = tensor("input_395_cast")]; + tensor input_397_axes_0 = const()[name = tensor("input_397_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(486091840)))]; + tensor text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(486094464)))]; + tensor 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("input_397_cast")]; + tensor text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(486097088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(491012352))), name = tensor("text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(491012544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(491016448))), name = tensor("text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_399_cast = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized, x = input_397_cast)[name = tensor("input_399_cast")]; + tensor input_401_mode_0 = const()[name = tensor("input_401_mode_0"), val = tensor("EXACT")]; + tensor input_401_cast = gelu(mode = input_401_mode_0, x = input_399_cast)[name = tensor("input_401_cast")]; + tensor text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(491016640))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(495931904))), name = tensor("text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(495932096)))]; + tensor 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_palettized, x = input_401_cast)[name = tensor("hidden_states_149_cast")]; + tensor input_403_cast = add(x = input_395_cast, y = hidden_states_149_cast)[name = tensor("input_403_cast")]; + tensor hidden_states_151_axes_0 = const()[name = tensor("hidden_states_151_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(495934720)))]; + tensor text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(495937344)))]; + tensor 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("hidden_states_151_cast")]; + tensor text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(495939968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(497168832))), name = tensor("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(497169024)))]; + tensor 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_palettized, x = hidden_states_151_cast)[name = tensor("op_2305_cast")]; + tensor var_2306_to_fp16 = const()[name = tensor("op_2306_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_155_cast = mul(x = var_2305_cast, y = var_2306_to_fp16)[name = tensor("tensor_155_cast")]; + tensor text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(497171648))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(498400512))), name = tensor("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(498400704)))]; + tensor 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_palettized, x = hidden_states_151_cast)[name = tensor("tensor_151_cast")]; + tensor var_2311 = const()[name = tensor("op_2311"), val = tensor([1, -1, 20, 64])]; + tensor var_2312_cast = reshape(shape = var_2311, x = tensor_151_cast)[name = tensor("op_2312_cast")]; + tensor var_2313_perm_0 = const()[name = tensor("op_2313_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(498403328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(499632192))), name = tensor("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(499632384)))]; + tensor 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_palettized, x = hidden_states_151_cast)[name = tensor("tensor_153_cast")]; + tensor var_2318 = const()[name = tensor("op_2318"), val = tensor([1, -1, 20, 64])]; + tensor var_2319_cast = reshape(shape = var_2318, x = tensor_153_cast)[name = tensor("op_2319_cast")]; + tensor var_2320_perm_0 = const()[name = tensor("op_2320_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2327 = const()[name = tensor("op_2327"), val = tensor([1, 77, 20, 64])]; + tensor var_2328_cast = reshape(shape = var_2327, x = tensor_155_cast)[name = tensor("op_2328_cast")]; + tensor var_2329_perm_0 = const()[name = tensor("op_2329_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2331 = const()[name = tensor("op_2331"), val = tensor([20, -1, 64])]; + tensor transpose_34 = transpose(perm = var_2329_perm_0, x = var_2328_cast)[name = tensor("transpose_34")]; + tensor query_states_51_cast = reshape(shape = var_2331, x = transpose_34)[name = tensor("query_states_51_cast")]; + tensor var_2333 = const()[name = tensor("op_2333"), val = tensor([20, -1, 64])]; + tensor transpose_33 = transpose(perm = var_2313_perm_0, x = var_2312_cast)[name = tensor("transpose_33")]; + tensor key_states_103_cast = reshape(shape = var_2333, x = transpose_33)[name = tensor("key_states_103_cast")]; + tensor var_2335 = const()[name = tensor("op_2335"), val = tensor([20, -1, 64])]; + tensor transpose_32 = transpose(perm = var_2320_perm_0, x = var_2319_cast)[name = tensor("transpose_32")]; + tensor value_states_103_cast = reshape(shape = var_2335, x = transpose_32)[name = tensor("value_states_103_cast")]; + tensor var_2338_perm_0 = const()[name = tensor("op_2338_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_151_transpose_x_0 = const()[name = tensor("attn_weights_151_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_151_transpose_y_0 = const()[name = tensor("attn_weights_151_transpose_y_0"), val = tensor(false)]; + tensor transpose_31 = transpose(perm = var_2338_perm_0, x = key_states_103_cast)[name = tensor("transpose_31")]; + tensor 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_31)[name = tensor("attn_weights_151_cast")]; + tensor var_2340 = const()[name = tensor("op_2340"), val = tensor([1, 20, 77, 77])]; + tensor var_2341_cast = reshape(shape = var_2340, x = attn_weights_151_cast)[name = tensor("op_2341_cast")]; + tensor attn_weights_153_cast = add(x = var_2341_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_153_cast")]; + tensor var_2346 = const()[name = tensor("op_2346"), val = tensor([20, 77, 77])]; + tensor input_405_cast = reshape(shape = var_2346, x = attn_weights_153_cast)[name = tensor("input_405_cast")]; + tensor input_407_cast = softmax(axis = var_5, x = input_405_cast)[name = tensor("input_407_cast")]; + tensor attn_output_151_transpose_x_0 = const()[name = tensor("attn_output_151_transpose_x_0"), val = tensor(false)]; + tensor attn_output_151_transpose_y_0 = const()[name = tensor("attn_output_151_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_151_cast")]; + tensor var_2351 = const()[name = tensor("op_2351"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_153_cast = reshape(shape = var_2351, x = attn_output_151_cast)[name = tensor("attn_output_153_cast")]; + tensor attn_output_155_perm_0 = const()[name = tensor("attn_output_155_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2354 = const()[name = tensor("op_2354"), val = tensor([1, 77, 1280])]; + tensor transpose_30 = transpose(perm = attn_output_155_perm_0, x = attn_output_153_cast)[name = tensor("transpose_30")]; + tensor input_409_cast = reshape(shape = var_2354, x = transpose_30)[name = tensor("input_409_cast")]; + tensor text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(499635008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(500863872))), name = tensor("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(500864064)))]; + tensor 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_palettized, x = input_409_cast)[name = tensor("hidden_states_153_cast")]; + tensor input_411_cast = add(x = input_403_cast, y = hidden_states_153_cast)[name = tensor("input_411_cast")]; + tensor input_413_axes_0 = const()[name = tensor("input_413_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(500866688)))]; + tensor text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(500869312)))]; + tensor 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("input_413_cast")]; + tensor text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(500871936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(505787200))), name = tensor("text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(505787392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(505791296))), name = tensor("text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_415_cast = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized, x = input_413_cast)[name = tensor("input_415_cast")]; + tensor input_417_mode_0 = const()[name = tensor("input_417_mode_0"), val = tensor("EXACT")]; + tensor input_417_cast = gelu(mode = input_417_mode_0, x = input_415_cast)[name = tensor("input_417_cast")]; + tensor text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(505791488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510706752))), name = tensor("text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510706944)))]; + tensor 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_palettized, x = input_417_cast)[name = tensor("hidden_states_155_cast")]; + tensor input_419_cast = add(x = input_411_cast, y = hidden_states_155_cast)[name = tensor("input_419_cast")]; + tensor hidden_states_157_axes_0 = const()[name = tensor("hidden_states_157_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510709568)))]; + tensor text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510712192)))]; + tensor 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("hidden_states_157_cast")]; + tensor text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(510714816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(511943680))), name = tensor("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(511943872)))]; + tensor 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_palettized, x = hidden_states_157_cast)[name = tensor("op_2392_cast")]; + tensor var_2393_to_fp16 = const()[name = tensor("op_2393_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_161_cast = mul(x = var_2392_cast, y = var_2393_to_fp16)[name = tensor("tensor_161_cast")]; + tensor text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(511946496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(513175360))), name = tensor("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(513175552)))]; + tensor 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_palettized, x = hidden_states_157_cast)[name = tensor("tensor_157_cast")]; + tensor var_2398 = const()[name = tensor("op_2398"), val = tensor([1, -1, 20, 64])]; + tensor var_2399_cast = reshape(shape = var_2398, x = tensor_157_cast)[name = tensor("op_2399_cast")]; + tensor var_2400_perm_0 = const()[name = tensor("op_2400_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(513178176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(514407040))), name = tensor("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(514407232)))]; + tensor 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_palettized, x = hidden_states_157_cast)[name = tensor("tensor_159_cast")]; + tensor var_2405 = const()[name = tensor("op_2405"), val = tensor([1, -1, 20, 64])]; + tensor var_2406_cast = reshape(shape = var_2405, x = tensor_159_cast)[name = tensor("op_2406_cast")]; + tensor var_2407_perm_0 = const()[name = tensor("op_2407_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2414 = const()[name = tensor("op_2414"), val = tensor([1, 77, 20, 64])]; + tensor var_2415_cast = reshape(shape = var_2414, x = tensor_161_cast)[name = tensor("op_2415_cast")]; + tensor var_2416_perm_0 = const()[name = tensor("op_2416_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2418 = const()[name = tensor("op_2418"), val = tensor([20, -1, 64])]; + tensor transpose_29 = transpose(perm = var_2416_perm_0, x = var_2415_cast)[name = tensor("transpose_29")]; + tensor query_states_53_cast = reshape(shape = var_2418, x = transpose_29)[name = tensor("query_states_53_cast")]; + tensor var_2420 = const()[name = tensor("op_2420"), val = tensor([20, -1, 64])]; + tensor transpose_28 = transpose(perm = var_2400_perm_0, x = var_2399_cast)[name = tensor("transpose_28")]; + tensor key_states_107_cast = reshape(shape = var_2420, x = transpose_28)[name = tensor("key_states_107_cast")]; + tensor var_2422 = const()[name = tensor("op_2422"), val = tensor([20, -1, 64])]; + tensor transpose_27 = transpose(perm = var_2407_perm_0, x = var_2406_cast)[name = tensor("transpose_27")]; + tensor value_states_107_cast = reshape(shape = var_2422, x = transpose_27)[name = tensor("value_states_107_cast")]; + tensor var_2425_perm_0 = const()[name = tensor("op_2425_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_157_transpose_x_0 = const()[name = tensor("attn_weights_157_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_157_transpose_y_0 = const()[name = tensor("attn_weights_157_transpose_y_0"), val = tensor(false)]; + tensor transpose_26 = transpose(perm = var_2425_perm_0, x = key_states_107_cast)[name = tensor("transpose_26")]; + tensor 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_26)[name = tensor("attn_weights_157_cast")]; + tensor var_2427 = const()[name = tensor("op_2427"), val = tensor([1, 20, 77, 77])]; + tensor var_2428_cast = reshape(shape = var_2427, x = attn_weights_157_cast)[name = tensor("op_2428_cast")]; + tensor attn_weights_159_cast = add(x = var_2428_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_159_cast")]; + tensor var_2433 = const()[name = tensor("op_2433"), val = tensor([20, 77, 77])]; + tensor input_421_cast = reshape(shape = var_2433, x = attn_weights_159_cast)[name = tensor("input_421_cast")]; + tensor input_423_cast = softmax(axis = var_5, x = input_421_cast)[name = tensor("input_423_cast")]; + tensor attn_output_157_transpose_x_0 = const()[name = tensor("attn_output_157_transpose_x_0"), val = tensor(false)]; + tensor attn_output_157_transpose_y_0 = const()[name = tensor("attn_output_157_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_157_cast")]; + tensor var_2438 = const()[name = tensor("op_2438"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_159_cast = reshape(shape = var_2438, x = attn_output_157_cast)[name = tensor("attn_output_159_cast")]; + tensor attn_output_161_perm_0 = const()[name = tensor("attn_output_161_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2441 = const()[name = tensor("op_2441"), val = tensor([1, 77, 1280])]; + tensor transpose_25 = transpose(perm = attn_output_161_perm_0, x = attn_output_159_cast)[name = tensor("transpose_25")]; + tensor input_425_cast = reshape(shape = var_2441, x = transpose_25)[name = tensor("input_425_cast")]; + tensor text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(514409856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(515638720))), name = tensor("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(515638912)))]; + tensor 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_palettized, x = input_425_cast)[name = tensor("hidden_states_159_cast")]; + tensor input_427_cast = add(x = input_419_cast, y = hidden_states_159_cast)[name = tensor("input_427_cast")]; + tensor input_429_axes_0 = const()[name = tensor("input_429_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(515641536)))]; + tensor text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(515644160)))]; + tensor 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("input_429_cast")]; + tensor text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(515646784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(520562048))), name = tensor("text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(520562240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(520566144))), name = tensor("text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_431_cast = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized, x = input_429_cast)[name = tensor("input_431_cast")]; + tensor input_433_mode_0 = const()[name = tensor("input_433_mode_0"), val = tensor("EXACT")]; + tensor input_433_cast = gelu(mode = input_433_mode_0, x = input_431_cast)[name = tensor("input_433_cast")]; + tensor text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(520566336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(525481600))), name = tensor("text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(525481792)))]; + tensor 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_palettized, x = input_433_cast)[name = tensor("hidden_states_161_cast")]; + tensor input_435_cast = add(x = input_427_cast, y = hidden_states_161_cast)[name = tensor("input_435_cast")]; + tensor hidden_states_163_axes_0 = const()[name = tensor("hidden_states_163_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(525484416)))]; + tensor text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(525487040)))]; + tensor 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("hidden_states_163_cast")]; + tensor text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(525489664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(526718528))), name = tensor("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(526718720)))]; + tensor 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_palettized, x = hidden_states_163_cast)[name = tensor("op_2479_cast")]; + tensor var_2480_to_fp16 = const()[name = tensor("op_2480_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_167_cast = mul(x = var_2479_cast, y = var_2480_to_fp16)[name = tensor("tensor_167_cast")]; + tensor text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(526721344))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(527950208))), name = tensor("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(527950400)))]; + tensor 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_palettized, x = hidden_states_163_cast)[name = tensor("tensor_163_cast")]; + tensor var_2485 = const()[name = tensor("op_2485"), val = tensor([1, -1, 20, 64])]; + tensor var_2486_cast = reshape(shape = var_2485, x = tensor_163_cast)[name = tensor("op_2486_cast")]; + tensor var_2487_perm_0 = const()[name = tensor("op_2487_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(527953024))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(529181888))), name = tensor("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(529182080)))]; + tensor 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_palettized, x = hidden_states_163_cast)[name = tensor("tensor_165_cast")]; + tensor var_2492 = const()[name = tensor("op_2492"), val = tensor([1, -1, 20, 64])]; + tensor var_2493_cast = reshape(shape = var_2492, x = tensor_165_cast)[name = tensor("op_2493_cast")]; + tensor var_2494_perm_0 = const()[name = tensor("op_2494_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2501 = const()[name = tensor("op_2501"), val = tensor([1, 77, 20, 64])]; + tensor var_2502_cast = reshape(shape = var_2501, x = tensor_167_cast)[name = tensor("op_2502_cast")]; + tensor var_2503_perm_0 = const()[name = tensor("op_2503_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2505 = const()[name = tensor("op_2505"), val = tensor([20, -1, 64])]; + tensor transpose_24 = transpose(perm = var_2503_perm_0, x = var_2502_cast)[name = tensor("transpose_24")]; + tensor query_states_55_cast = reshape(shape = var_2505, x = transpose_24)[name = tensor("query_states_55_cast")]; + tensor var_2507 = const()[name = tensor("op_2507"), val = tensor([20, -1, 64])]; + tensor transpose_23 = transpose(perm = var_2487_perm_0, x = var_2486_cast)[name = tensor("transpose_23")]; + tensor key_states_111_cast = reshape(shape = var_2507, x = transpose_23)[name = tensor("key_states_111_cast")]; + tensor var_2509 = const()[name = tensor("op_2509"), val = tensor([20, -1, 64])]; + tensor transpose_22 = transpose(perm = var_2494_perm_0, x = var_2493_cast)[name = tensor("transpose_22")]; + tensor value_states_111_cast = reshape(shape = var_2509, x = transpose_22)[name = tensor("value_states_111_cast")]; + tensor var_2512_perm_0 = const()[name = tensor("op_2512_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_163_transpose_x_0 = const()[name = tensor("attn_weights_163_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_163_transpose_y_0 = const()[name = tensor("attn_weights_163_transpose_y_0"), val = tensor(false)]; + tensor transpose_21 = transpose(perm = var_2512_perm_0, x = key_states_111_cast)[name = tensor("transpose_21")]; + tensor 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_21)[name = tensor("attn_weights_163_cast")]; + tensor var_2514 = const()[name = tensor("op_2514"), val = tensor([1, 20, 77, 77])]; + tensor var_2515_cast = reshape(shape = var_2514, x = attn_weights_163_cast)[name = tensor("op_2515_cast")]; + tensor attn_weights_165_cast = add(x = var_2515_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_165_cast")]; + tensor var_2520 = const()[name = tensor("op_2520"), val = tensor([20, 77, 77])]; + tensor input_437_cast = reshape(shape = var_2520, x = attn_weights_165_cast)[name = tensor("input_437_cast")]; + tensor input_439_cast = softmax(axis = var_5, x = input_437_cast)[name = tensor("input_439_cast")]; + tensor attn_output_163_transpose_x_0 = const()[name = tensor("attn_output_163_transpose_x_0"), val = tensor(false)]; + tensor attn_output_163_transpose_y_0 = const()[name = tensor("attn_output_163_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_163_cast")]; + tensor var_2525 = const()[name = tensor("op_2525"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_165_cast = reshape(shape = var_2525, x = attn_output_163_cast)[name = tensor("attn_output_165_cast")]; + tensor attn_output_167_perm_0 = const()[name = tensor("attn_output_167_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2528 = const()[name = tensor("op_2528"), val = tensor([1, 77, 1280])]; + tensor transpose_20 = transpose(perm = attn_output_167_perm_0, x = attn_output_165_cast)[name = tensor("transpose_20")]; + tensor input_441_cast = reshape(shape = var_2528, x = transpose_20)[name = tensor("input_441_cast")]; + tensor text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(529184704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(530413568))), name = tensor("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(530413760)))]; + tensor 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_palettized, x = input_441_cast)[name = tensor("hidden_states_165_cast")]; + tensor input_443_cast = add(x = input_435_cast, y = hidden_states_165_cast)[name = tensor("input_443_cast")]; + tensor input_445_axes_0 = const()[name = tensor("input_445_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(530416384)))]; + tensor text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(530419008)))]; + tensor 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("input_445_cast")]; + tensor text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(530421632))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(535336896))), name = tensor("text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(535337088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(535340992))), name = tensor("text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_447_cast = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized, x = input_445_cast)[name = tensor("input_447_cast")]; + tensor input_449_mode_0 = const()[name = tensor("input_449_mode_0"), val = tensor("EXACT")]; + tensor input_449_cast = gelu(mode = input_449_mode_0, x = input_447_cast)[name = tensor("input_449_cast")]; + tensor text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(535341184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(540256448))), name = tensor("text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(540256640)))]; + tensor 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_palettized, x = input_449_cast)[name = tensor("hidden_states_167_cast")]; + tensor input_451_cast = add(x = input_443_cast, y = hidden_states_167_cast)[name = tensor("input_451_cast")]; + tensor hidden_states_169_axes_0 = const()[name = tensor("hidden_states_169_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(540259264)))]; + tensor text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(540261888)))]; + tensor 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("hidden_states_169_cast")]; + tensor text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(540264512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(541493376))), name = tensor("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(541493568)))]; + tensor 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_palettized, x = hidden_states_169_cast)[name = tensor("op_2566_cast")]; + tensor var_2567_to_fp16 = const()[name = tensor("op_2567_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_173_cast = mul(x = var_2566_cast, y = var_2567_to_fp16)[name = tensor("tensor_173_cast")]; + tensor text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(541496192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(542725056))), name = tensor("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(542725248)))]; + tensor 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_palettized, x = hidden_states_169_cast)[name = tensor("tensor_169_cast")]; + tensor var_2572 = const()[name = tensor("op_2572"), val = tensor([1, -1, 20, 64])]; + tensor var_2573_cast = reshape(shape = var_2572, x = tensor_169_cast)[name = tensor("op_2573_cast")]; + tensor var_2574_perm_0 = const()[name = tensor("op_2574_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(542727872))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(543956736))), name = tensor("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(543956928)))]; + tensor 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_palettized, x = hidden_states_169_cast)[name = tensor("tensor_171_cast")]; + tensor var_2579 = const()[name = tensor("op_2579"), val = tensor([1, -1, 20, 64])]; + tensor var_2580_cast = reshape(shape = var_2579, x = tensor_171_cast)[name = tensor("op_2580_cast")]; + tensor var_2581_perm_0 = const()[name = tensor("op_2581_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2588 = const()[name = tensor("op_2588"), val = tensor([1, 77, 20, 64])]; + tensor var_2589_cast = reshape(shape = var_2588, x = tensor_173_cast)[name = tensor("op_2589_cast")]; + tensor var_2590_perm_0 = const()[name = tensor("op_2590_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2592 = const()[name = tensor("op_2592"), val = tensor([20, -1, 64])]; + tensor transpose_19 = transpose(perm = var_2590_perm_0, x = var_2589_cast)[name = tensor("transpose_19")]; + tensor query_states_57_cast = reshape(shape = var_2592, x = transpose_19)[name = tensor("query_states_57_cast")]; + tensor var_2594 = const()[name = tensor("op_2594"), val = tensor([20, -1, 64])]; + tensor transpose_18 = transpose(perm = var_2574_perm_0, x = var_2573_cast)[name = tensor("transpose_18")]; + tensor key_states_115_cast = reshape(shape = var_2594, x = transpose_18)[name = tensor("key_states_115_cast")]; + tensor var_2596 = const()[name = tensor("op_2596"), val = tensor([20, -1, 64])]; + tensor transpose_17 = transpose(perm = var_2581_perm_0, x = var_2580_cast)[name = tensor("transpose_17")]; + tensor value_states_115_cast = reshape(shape = var_2596, x = transpose_17)[name = tensor("value_states_115_cast")]; + tensor var_2599_perm_0 = const()[name = tensor("op_2599_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_169_transpose_x_0 = const()[name = tensor("attn_weights_169_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_169_transpose_y_0 = const()[name = tensor("attn_weights_169_transpose_y_0"), val = tensor(false)]; + tensor transpose_16 = transpose(perm = var_2599_perm_0, x = key_states_115_cast)[name = tensor("transpose_16")]; + tensor 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_16)[name = tensor("attn_weights_169_cast")]; + tensor var_2601 = const()[name = tensor("op_2601"), val = tensor([1, 20, 77, 77])]; + tensor var_2602_cast = reshape(shape = var_2601, x = attn_weights_169_cast)[name = tensor("op_2602_cast")]; + tensor attn_weights_171_cast = add(x = var_2602_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_171_cast")]; + tensor var_2607 = const()[name = tensor("op_2607"), val = tensor([20, 77, 77])]; + tensor input_453_cast = reshape(shape = var_2607, x = attn_weights_171_cast)[name = tensor("input_453_cast")]; + tensor input_455_cast = softmax(axis = var_5, x = input_453_cast)[name = tensor("input_455_cast")]; + tensor attn_output_169_transpose_x_0 = const()[name = tensor("attn_output_169_transpose_x_0"), val = tensor(false)]; + tensor attn_output_169_transpose_y_0 = const()[name = tensor("attn_output_169_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_169_cast")]; + tensor var_2612 = const()[name = tensor("op_2612"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_171_cast = reshape(shape = var_2612, x = attn_output_169_cast)[name = tensor("attn_output_171_cast")]; + tensor attn_output_173_perm_0 = const()[name = tensor("attn_output_173_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2615 = const()[name = tensor("op_2615"), val = tensor([1, 77, 1280])]; + tensor transpose_15 = transpose(perm = attn_output_173_perm_0, x = attn_output_171_cast)[name = tensor("transpose_15")]; + tensor input_457_cast = reshape(shape = var_2615, x = transpose_15)[name = tensor("input_457_cast")]; + tensor text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(543959552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545188416))), name = tensor("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545188608)))]; + tensor 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_palettized, x = input_457_cast)[name = tensor("hidden_states_171_cast")]; + tensor input_459_cast = add(x = input_451_cast, y = hidden_states_171_cast)[name = tensor("input_459_cast")]; + tensor input_461_axes_0 = const()[name = tensor("input_461_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545191232)))]; + tensor text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545193856)))]; + tensor 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("input_461_cast")]; + tensor text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(545196480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(550111744))), name = tensor("text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(550111936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(550115840))), name = tensor("text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_463_cast = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized, x = input_461_cast)[name = tensor("input_463_cast")]; + tensor input_465_mode_0 = const()[name = tensor("input_465_mode_0"), val = tensor("EXACT")]; + tensor input_465_cast = gelu(mode = input_465_mode_0, x = input_463_cast)[name = tensor("input_465_cast")]; + tensor text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(550116032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(555031296))), name = tensor("text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(555031488)))]; + tensor 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_palettized, x = input_465_cast)[name = tensor("hidden_states_173_cast")]; + tensor input_467_cast = add(x = input_459_cast, y = hidden_states_173_cast)[name = tensor("input_467_cast")]; + tensor hidden_states_175_axes_0 = const()[name = tensor("hidden_states_175_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(555034112)))]; + tensor text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(555036736)))]; + tensor 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("hidden_states_175_cast")]; + tensor text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(555039360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(556268224))), name = tensor("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(556268416)))]; + tensor 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_palettized, x = hidden_states_175_cast)[name = tensor("op_2653_cast")]; + tensor var_2654_to_fp16 = const()[name = tensor("op_2654_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_179_cast = mul(x = var_2653_cast, y = var_2654_to_fp16)[name = tensor("tensor_179_cast")]; + tensor text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(556271040))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(557499904))), name = tensor("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(557500096)))]; + tensor 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_palettized, x = hidden_states_175_cast)[name = tensor("tensor_175_cast")]; + tensor var_2659 = const()[name = tensor("op_2659"), val = tensor([1, -1, 20, 64])]; + tensor var_2660_cast = reshape(shape = var_2659, x = tensor_175_cast)[name = tensor("op_2660_cast")]; + tensor var_2661_perm_0 = const()[name = tensor("op_2661_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(557502720))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(558731584))), name = tensor("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(558731776)))]; + tensor 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_palettized, x = hidden_states_175_cast)[name = tensor("tensor_177_cast")]; + tensor var_2666 = const()[name = tensor("op_2666"), val = tensor([1, -1, 20, 64])]; + tensor var_2667_cast = reshape(shape = var_2666, x = tensor_177_cast)[name = tensor("op_2667_cast")]; + tensor var_2668_perm_0 = const()[name = tensor("op_2668_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2675 = const()[name = tensor("op_2675"), val = tensor([1, 77, 20, 64])]; + tensor var_2676_cast = reshape(shape = var_2675, x = tensor_179_cast)[name = tensor("op_2676_cast")]; + tensor var_2677_perm_0 = const()[name = tensor("op_2677_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2679 = const()[name = tensor("op_2679"), val = tensor([20, -1, 64])]; + tensor transpose_14 = transpose(perm = var_2677_perm_0, x = var_2676_cast)[name = tensor("transpose_14")]; + tensor query_states_59_cast = reshape(shape = var_2679, x = transpose_14)[name = tensor("query_states_59_cast")]; + tensor var_2681 = const()[name = tensor("op_2681"), val = tensor([20, -1, 64])]; + tensor transpose_13 = transpose(perm = var_2661_perm_0, x = var_2660_cast)[name = tensor("transpose_13")]; + tensor key_states_119_cast = reshape(shape = var_2681, x = transpose_13)[name = tensor("key_states_119_cast")]; + tensor var_2683 = const()[name = tensor("op_2683"), val = tensor([20, -1, 64])]; + tensor transpose_12 = transpose(perm = var_2668_perm_0, x = var_2667_cast)[name = tensor("transpose_12")]; + tensor value_states_119_cast = reshape(shape = var_2683, x = transpose_12)[name = tensor("value_states_119_cast")]; + tensor var_2686_perm_0 = const()[name = tensor("op_2686_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_175_transpose_x_0 = const()[name = tensor("attn_weights_175_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_175_transpose_y_0 = const()[name = tensor("attn_weights_175_transpose_y_0"), val = tensor(false)]; + tensor transpose_11 = transpose(perm = var_2686_perm_0, x = key_states_119_cast)[name = tensor("transpose_11")]; + tensor 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_11)[name = tensor("attn_weights_175_cast")]; + tensor var_2688 = const()[name = tensor("op_2688"), val = tensor([1, 20, 77, 77])]; + tensor var_2689_cast = reshape(shape = var_2688, x = attn_weights_175_cast)[name = tensor("op_2689_cast")]; + tensor attn_weights_177_cast = add(x = var_2689_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_177_cast")]; + tensor var_2694 = const()[name = tensor("op_2694"), val = tensor([20, 77, 77])]; + tensor input_469_cast = reshape(shape = var_2694, x = attn_weights_177_cast)[name = tensor("input_469_cast")]; + tensor input_471_cast = softmax(axis = var_5, x = input_469_cast)[name = tensor("input_471_cast")]; + tensor attn_output_175_transpose_x_0 = const()[name = tensor("attn_output_175_transpose_x_0"), val = tensor(false)]; + tensor attn_output_175_transpose_y_0 = const()[name = tensor("attn_output_175_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_175_cast")]; + tensor var_2699 = const()[name = tensor("op_2699"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_177_cast = reshape(shape = var_2699, x = attn_output_175_cast)[name = tensor("attn_output_177_cast")]; + tensor attn_output_179_perm_0 = const()[name = tensor("attn_output_179_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2702 = const()[name = tensor("op_2702"), val = tensor([1, 77, 1280])]; + tensor transpose_10 = transpose(perm = attn_output_179_perm_0, x = attn_output_177_cast)[name = tensor("transpose_10")]; + tensor input_473_cast = reshape(shape = var_2702, x = transpose_10)[name = tensor("input_473_cast")]; + tensor text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(558734400))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(559963264))), name = tensor("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(559963456)))]; + tensor 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_palettized, x = input_473_cast)[name = tensor("hidden_states_177_cast")]; + tensor input_475_cast = add(x = input_467_cast, y = hidden_states_177_cast)[name = tensor("input_475_cast")]; + tensor input_477_axes_0 = const()[name = tensor("input_477_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(559966080)))]; + tensor text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(559968704)))]; + tensor 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("input_477_cast")]; + tensor text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(559971328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(564886592))), name = tensor("text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(564886784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(564890688))), name = tensor("text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_479_cast = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized, x = input_477_cast)[name = tensor("input_479_cast")]; + tensor input_481_mode_0 = const()[name = tensor("input_481_mode_0"), val = tensor("EXACT")]; + tensor input_481_cast = gelu(mode = input_481_mode_0, x = input_479_cast)[name = tensor("input_481_cast")]; + tensor text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(564890880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(569806144))), name = tensor("text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(569806336)))]; + tensor 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_palettized, x = input_481_cast)[name = tensor("hidden_states_179_cast")]; + tensor input_483_cast = add(x = input_475_cast, y = hidden_states_179_cast)[name = tensor("input_483_cast")]; + tensor hidden_states_181_axes_0 = const()[name = tensor("hidden_states_181_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(569808960)))]; + tensor text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(569811584)))]; + tensor 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("hidden_states_181_cast")]; + tensor text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(569814208))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(571043072))), name = tensor("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(571043264)))]; + tensor 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_palettized, x = hidden_states_181_cast)[name = tensor("op_2740_cast")]; + tensor var_2741_to_fp16 = const()[name = tensor("op_2741_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_185_cast = mul(x = var_2740_cast, y = var_2741_to_fp16)[name = tensor("tensor_185_cast")]; + tensor text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(571045888))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(572274752))), name = tensor("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(572274944)))]; + tensor 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_palettized, x = hidden_states_181_cast)[name = tensor("tensor_181_cast")]; + tensor var_2746 = const()[name = tensor("op_2746"), val = tensor([1, -1, 20, 64])]; + tensor var_2747_cast = reshape(shape = var_2746, x = tensor_181_cast)[name = tensor("op_2747_cast")]; + tensor var_2748_perm_0 = const()[name = tensor("op_2748_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(572277568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(573506432))), name = tensor("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(573506624)))]; + tensor 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_palettized, x = hidden_states_181_cast)[name = tensor("tensor_183_cast")]; + tensor var_2753 = const()[name = tensor("op_2753"), val = tensor([1, -1, 20, 64])]; + tensor var_2754_cast = reshape(shape = var_2753, x = tensor_183_cast)[name = tensor("op_2754_cast")]; + tensor var_2755_perm_0 = const()[name = tensor("op_2755_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2762 = const()[name = tensor("op_2762"), val = tensor([1, 77, 20, 64])]; + tensor var_2763_cast = reshape(shape = var_2762, x = tensor_185_cast)[name = tensor("op_2763_cast")]; + tensor var_2764_perm_0 = const()[name = tensor("op_2764_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2766 = const()[name = tensor("op_2766"), val = tensor([20, -1, 64])]; + tensor transpose_9 = transpose(perm = var_2764_perm_0, x = var_2763_cast)[name = tensor("transpose_9")]; + tensor query_states_61_cast = reshape(shape = var_2766, x = transpose_9)[name = tensor("query_states_61_cast")]; + tensor var_2768 = const()[name = tensor("op_2768"), val = tensor([20, -1, 64])]; + tensor transpose_8 = transpose(perm = var_2748_perm_0, x = var_2747_cast)[name = tensor("transpose_8")]; + tensor key_states_123_cast = reshape(shape = var_2768, x = transpose_8)[name = tensor("key_states_123_cast")]; + tensor var_2770 = const()[name = tensor("op_2770"), val = tensor([20, -1, 64])]; + tensor transpose_7 = transpose(perm = var_2755_perm_0, x = var_2754_cast)[name = tensor("transpose_7")]; + tensor value_states_123_cast = reshape(shape = var_2770, x = transpose_7)[name = tensor("value_states_123_cast")]; + tensor var_2773_perm_0 = const()[name = tensor("op_2773_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_181_transpose_x_0 = const()[name = tensor("attn_weights_181_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_181_transpose_y_0 = const()[name = tensor("attn_weights_181_transpose_y_0"), val = tensor(false)]; + tensor transpose_6 = transpose(perm = var_2773_perm_0, x = key_states_123_cast)[name = tensor("transpose_6")]; + tensor 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_6)[name = tensor("attn_weights_181_cast")]; + tensor var_2775 = const()[name = tensor("op_2775"), val = tensor([1, 20, 77, 77])]; + tensor var_2776_cast = reshape(shape = var_2775, x = attn_weights_181_cast)[name = tensor("op_2776_cast")]; + tensor attn_weights_183_cast = add(x = var_2776_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_183_cast")]; + tensor var_2781 = const()[name = tensor("op_2781"), val = tensor([20, 77, 77])]; + tensor input_485_cast = reshape(shape = var_2781, x = attn_weights_183_cast)[name = tensor("input_485_cast")]; + tensor input_487_cast = softmax(axis = var_5, x = input_485_cast)[name = tensor("input_487_cast")]; + tensor attn_output_181_transpose_x_0 = const()[name = tensor("attn_output_181_transpose_x_0"), val = tensor(false)]; + tensor attn_output_181_transpose_y_0 = const()[name = tensor("attn_output_181_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_181_cast")]; + tensor var_2786 = const()[name = tensor("op_2786"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_183_cast = reshape(shape = var_2786, x = attn_output_181_cast)[name = tensor("attn_output_183_cast")]; + tensor attn_output_185_perm_0 = const()[name = tensor("attn_output_185_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2789 = const()[name = tensor("op_2789"), val = tensor([1, 77, 1280])]; + tensor transpose_5 = transpose(perm = attn_output_185_perm_0, x = attn_output_183_cast)[name = tensor("transpose_5")]; + tensor input_489_cast = reshape(shape = var_2789, x = transpose_5)[name = tensor("input_489_cast")]; + tensor text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(573509248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(574738112))), name = tensor("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(574738304)))]; + tensor 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_palettized, x = input_489_cast)[name = tensor("hidden_states_183_cast")]; + tensor input_491_cast = add(x = input_483_cast, y = hidden_states_183_cast)[name = tensor("input_491_cast")]; + tensor input_493_axes_0 = const()[name = tensor("input_493_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(574740928)))]; + tensor text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(574743552)))]; + tensor 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("input_493_cast")]; + tensor text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(574746176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(579661440))), name = tensor("text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(579661632))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(579665536))), name = tensor("text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_495_cast = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized, x = input_493_cast)[name = tensor("input_495_cast")]; + tensor input_497_mode_0 = const()[name = tensor("input_497_mode_0"), val = tensor("EXACT")]; + tensor input_497_cast = gelu(mode = input_497_mode_0, x = input_495_cast)[name = tensor("input_497_cast")]; + tensor text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(579665728))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(584580992))), name = tensor("text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(584581184)))]; + tensor 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_palettized, x = input_497_cast)[name = tensor("hidden_states_185_cast")]; + tensor input_499_cast = add(x = input_491_cast, y = hidden_states_185_cast)[name = tensor("input_499_cast")]; + tensor input_499_cast_to_fp32_dtype_0 = const()[name = tensor("input_499_cast_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor hidden_states_187_axes_0 = const()[name = tensor("hidden_states_187_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(584583808)))]; + tensor text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(584586432)))]; + tensor 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("hidden_states_187_cast")]; + tensor text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(584589056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(585817920))), name = tensor("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(585818112)))]; + tensor 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_palettized, x = hidden_states_187_cast)[name = tensor("op_2827_cast")]; + tensor var_2828_to_fp16 = const()[name = tensor("op_2828_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_cast = mul(x = var_2827_cast, y = var_2828_to_fp16)[name = tensor("tensor_cast")]; + tensor text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(585820736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(587049600))), name = tensor("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(587049792)))]; + tensor 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_palettized, x = hidden_states_187_cast)[name = tensor("tensor_187_cast")]; + tensor var_2833 = const()[name = tensor("op_2833"), val = tensor([1, -1, 20, 64])]; + tensor var_2834_cast = reshape(shape = var_2833, x = tensor_187_cast)[name = tensor("op_2834_cast")]; + tensor var_2835_perm_0 = const()[name = tensor("op_2835_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(587052416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(588281280))), name = tensor("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(588281472)))]; + tensor 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_palettized, x = hidden_states_187_cast)[name = tensor("tensor_189_cast")]; + tensor var_2840 = const()[name = tensor("op_2840"), val = tensor([1, -1, 20, 64])]; + tensor var_2841_cast = reshape(shape = var_2840, x = tensor_189_cast)[name = tensor("op_2841_cast")]; + tensor var_2842_perm_0 = const()[name = tensor("op_2842_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2849 = const()[name = tensor("op_2849"), val = tensor([1, 77, 20, 64])]; + tensor var_2850_cast = reshape(shape = var_2849, x = tensor_cast)[name = tensor("op_2850_cast")]; + tensor var_2851_perm_0 = const()[name = tensor("op_2851_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2853 = const()[name = tensor("op_2853"), val = tensor([20, -1, 64])]; + tensor transpose_4 = transpose(perm = var_2851_perm_0, x = var_2850_cast)[name = tensor("transpose_4")]; + tensor query_states_cast = reshape(shape = var_2853, x = transpose_4)[name = tensor("query_states_cast")]; + tensor var_2855 = const()[name = tensor("op_2855"), val = tensor([20, -1, 64])]; + tensor transpose_3 = transpose(perm = var_2835_perm_0, x = var_2834_cast)[name = tensor("transpose_3")]; + tensor key_states_cast = reshape(shape = var_2855, x = transpose_3)[name = tensor("key_states_cast")]; + tensor var_2857 = const()[name = tensor("op_2857"), val = tensor([20, -1, 64])]; + tensor transpose_2 = transpose(perm = var_2842_perm_0, x = var_2841_cast)[name = tensor("transpose_2")]; + tensor value_states_cast = reshape(shape = var_2857, x = transpose_2)[name = tensor("value_states_cast")]; + tensor var_2860_perm_0 = const()[name = tensor("op_2860_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_187_transpose_x_0 = const()[name = tensor("attn_weights_187_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_187_transpose_y_0 = const()[name = tensor("attn_weights_187_transpose_y_0"), val = tensor(false)]; + tensor transpose_1 = transpose(perm = var_2860_perm_0, x = key_states_cast)[name = tensor("transpose_1")]; + tensor 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_1)[name = tensor("attn_weights_187_cast")]; + tensor var_2862 = const()[name = tensor("op_2862"), val = tensor([1, 20, 77, 77])]; + tensor var_2863_cast = reshape(shape = var_2862, x = attn_weights_187_cast)[name = tensor("op_2863_cast")]; + tensor attn_weights_189_cast = add(x = var_2863_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_189_cast")]; + tensor var_2868 = const()[name = tensor("op_2868"), val = tensor([20, 77, 77])]; + tensor input_501_cast = reshape(shape = var_2868, x = attn_weights_189_cast)[name = tensor("input_501_cast")]; + tensor input_503_cast = softmax(axis = var_5, x = input_501_cast)[name = tensor("input_503_cast")]; + tensor attn_output_187_transpose_x_0 = const()[name = tensor("attn_output_187_transpose_x_0"), val = tensor(false)]; + tensor attn_output_187_transpose_y_0 = const()[name = tensor("attn_output_187_transpose_y_0"), val = tensor(false)]; + tensor 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("attn_output_187_cast")]; + tensor var_2873 = const()[name = tensor("op_2873"), val = tensor([1, 20, 77, 64])]; + tensor attn_output_189_cast = reshape(shape = var_2873, x = attn_output_187_cast)[name = tensor("attn_output_189_cast")]; + tensor attn_output_perm_0 = const()[name = tensor("attn_output_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2876 = const()[name = tensor("op_2876"), val = tensor([1, 77, 1280])]; + tensor transpose_0 = transpose(perm = attn_output_perm_0, x = attn_output_189_cast)[name = tensor("transpose_0")]; + tensor input_505_cast = reshape(shape = var_2876, x = transpose_0)[name = tensor("input_505_cast")]; + tensor text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(588284096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589512960))), name = tensor("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589513152)))]; + tensor 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_palettized, x = input_505_cast)[name = tensor("hidden_states_189_cast")]; + tensor input_507_cast = add(x = input_499_cast, y = hidden_states_189_cast)[name = tensor("input_507_cast")]; + tensor input_509_axes_0 = const()[name = tensor("input_509_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589515776)))]; + tensor text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589518400)))]; + tensor 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("input_509_cast")]; + tensor text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(589521024))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(594436288))), name = tensor("text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([5120, 1280])]; + tensor text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(594436480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(594440384))), name = tensor("text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([5120])]; + tensor input_511_cast = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized, x = input_509_cast)[name = tensor("input_511_cast")]; + tensor input_513_mode_0 = const()[name = tensor("input_513_mode_0"), val = tensor("EXACT")]; + tensor input_513_cast = gelu(mode = input_513_mode_0, x = input_511_cast)[name = tensor("input_513_cast")]; + tensor text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(594440576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(599355840))), name = tensor("text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1280, 5120])]; + tensor text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(599356032)))]; + tensor 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_palettized, x = input_513_cast)[name = tensor("hidden_states_cast")]; + tensor input_515_cast = add(x = input_507_cast, y = hidden_states_cast)[name = tensor("input_515_cast")]; + tensor last_hidden_state_axes_0 = const()[name = tensor("last_hidden_state_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(599358656)))]; + tensor text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(599361280)))]; + tensor 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("last_hidden_state_cast")]; + tensor var_2904 = const()[name = tensor("op_2904"), val = tensor([0])]; + tensor var_2906 = reduce_argmax(axis = var_5, keep_dims = var_6, x = input_ids)[name = tensor("op_2906")]; + tensor stack_0_axis_0 = const()[name = tensor("stack_0_axis_0"), val = tensor(1)]; + tensor stack_0 = stack(axis = stack_0_axis_0, values = (var_2904, var_2906))[name = tensor("stack_0")]; + tensor input_transpose_batch_dims_0 = const()[name = tensor("input_transpose_batch_dims_0"), val = tensor(0)]; + tensor input_transpose_cast = gather_nd(batch_dims = input_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast)[name = tensor("input_transpose_cast")]; + tensor text_encoder_text_projection_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(599363904))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(600592768))), name = tensor("text_encoder_text_projection_weight_to_fp16_palettized"), shape = tensor([1280, 1280])]; + tensor var_2913_bias_0_to_fp16 = const()[name = tensor("op_2913_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(600592960)))]; + tensor var_2913_cast = linear(bias = var_2913_bias_0_to_fp16, weight = text_encoder_text_projection_weight_to_fp16_palettized, x = input_transpose_cast)[name = tensor("op_2913_cast")]; + tensor var_2913_cast_to_fp32_dtype_0 = const()[name = tensor("op_2913_cast_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor last_hidden_state = cast(dtype = input_499_cast_to_fp32_dtype_0, x = input_499_cast)[name = tensor("cast_0")]; + tensor pooled_outputs = cast(dtype = var_2913_cast_to_fp32_dtype_0, x = var_2913_cast)[name = tensor("cast_1")]; + } -> (last_hidden_state, pooled_outputs); +} \ No newline at end of file