diff --git "a/original/compiled/TextEncoder.mlmodelc/model.mil" "b/original/compiled/TextEncoder.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/original/compiled/TextEncoder.mlmodelc/model.mil" @@ -0,0 +1,883 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.4"}, {"coremlc-version", "1436.100.10"}, {"coremltools-component-torch", "2.1.0.dev20230718"}, {"coremltools-version", "7.0b1"}})] +{ + func main(tensor input_ids) { + tensor text_encoder_text_model_embeddings_token_embedding_weight = const()[name = tensor("text_encoder_text_model_embeddings_token_embedding_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151781504)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151784640)))]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151787776)))]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151790912)))]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154150272)))]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154153408)))]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156512768)))]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156515904)))]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158875264)))]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158878400)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161237760)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161240896)))]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161244032)))]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161256384)))]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170693632)))]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170696768)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180134016)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180137152)))]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180140288)))]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180143424)))]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(182502784)))]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(182505920)))]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184865280)))]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184868416)))]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187227776)))]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187230912)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189590272)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189593408)))]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189596544)))]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189608896)))]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199046144)))]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199049280)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208486528)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208489664)))]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208492800)))]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208495936)))]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210855296)))]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210858432)))]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213217792)))]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213220928)))]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215580288)))]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215583424)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217942784)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217945920)))]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217949056)))]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217961408)))]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227398656)))]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227401792)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236839040)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236842176)))]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236845312)))]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236848448)))]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239207808)))]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239210944)))]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241570304)))]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241573440)))]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243932800)))]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243935936)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246295296)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246298432)))]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246301568)))]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246313920)))]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255751168)))]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255754304)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265191552)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265194688)))]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265197824)))]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265200960)))]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267560320)))]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267563456)))]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269922816)))]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269925952)))]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272285312)))]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272288448)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274647808)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274650944)))]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274654080)))]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274666432)))]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284103680)))]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284106816)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293544064)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293547200)))]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293550336)))]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293553472)))]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295912832)))]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295915968)))]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298275328)))]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298278464)))]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300637824)))]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300640960)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303000320)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303003456)))]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303006592)))]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303018944)))]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312456192)))]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312459328)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321896576)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321899712)))]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321902848)))]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(321905984)))]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(324265344)))]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(324268480)))]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(326627840)))]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(326630976)))]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328990336)))]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328993472)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(331352832)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(331355968)))]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(331359104)))]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(331371456)))]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(340808704)))]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(340811840)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350249088)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350252224)))]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350255360)))]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(350258496)))]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352617856)))]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(352620992)))]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(354980352)))]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(354983488)))]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(357342848)))]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(357345984)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(359705344)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(359708480)))]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(359711616)))]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(359723968)))]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(369161216)))]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(369164352)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(378601600)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(378604736)))]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(378607872)))]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(378611008)))]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380970368)))]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380973504)))]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(383332864)))]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(383336000)))]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(385695360)))]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(385698496)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388057856)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388060992)))]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388064128)))]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(388076480)))]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397513728)))]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(397516864)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406954112)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406957248)))]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406960384)))]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406963520)))]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409322880)))]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(409326016)))]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(411685376)))]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(411688512)))]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(414047872)))]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(414051008)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(416410368)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(416413504)))]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(416416640)))]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(416428992)))]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425866240)))]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425869376)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(435306624)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(435309760)))]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(435312896)))]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(435316032)))]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(437675392)))]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(437678528)))]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440037888)))]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440041024)))]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(442400384)))]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(442403520)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(444762880)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(444766016)))]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(444769152)))]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(444781504)))]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(454218752)))]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(454221888)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(463659136)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(463662272)))]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(463665408)))]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(463668544)))]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(466027904)))]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(466031040)))]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(468390400)))]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(468393536)))]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(470752896)))]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(470756032)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(473115392)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(473118528)))]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(473121664)))]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(473134016)))]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_bias = const()[name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(482571264)))]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_weight = const()[name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(482574400)))]; + tensor text_encoder_text_model_final_layer_norm_bias = const()[name = tensor("text_encoder_text_model_final_layer_norm_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(492011648)))]; + tensor text_encoder_text_model_final_layer_norm_weight = const()[name = tensor("text_encoder_text_model_final_layer_norm_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(492014784)))]; + tensor var_5 = const()[name = tensor("op_5"), val = tensor(-1)]; + tensor var_12 = const()[name = tensor("op_12"), val = tensor(0x1.4f8b58p-17)]; + 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 inputs_embeds = 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)[name = tensor("inputs_embeds")]; + tensor position_embeddings = const()[name = tensor("position_embeddings"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(492017920)))]; + tensor input_3 = add(x = inputs_embeds, y = position_embeddings)[name = tensor("input_3")]; + tensor causal_attention_mask = const()[name = tensor("causal_attention_mask"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(492254528)))]; + tensor hidden_states_1_axes_0 = const()[name = tensor("hidden_states_1_axes_0"), val = tensor([-1])]; + tensor hidden_states_1 = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight, x = input_3)[name = tensor("hidden_states_1")]; + tensor var_85 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight, x = hidden_states_1)[name = tensor("op_85")]; + tensor var_86 = const()[name = tensor("op_86"), val = tensor(0x1p-3)]; + tensor tensor_5 = mul(x = var_85, y = var_86)[name = tensor("tensor_5")]; + tensor tensor_1 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight, x = hidden_states_1)[name = tensor("tensor_1")]; + tensor var_91 = const()[name = tensor("op_91"), val = tensor([1, -1, 12, 64])]; + tensor var_92 = reshape(shape = var_91, x = tensor_1)[name = tensor("op_92")]; + tensor var_93_perm_0 = const()[name = tensor("op_93_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_3 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight, x = hidden_states_1)[name = tensor("tensor_3")]; + tensor var_98 = const()[name = tensor("op_98"), val = tensor([1, -1, 12, 64])]; + tensor var_99 = reshape(shape = var_98, x = tensor_3)[name = tensor("op_99")]; + tensor var_100_perm_0 = const()[name = tensor("op_100_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_107 = const()[name = tensor("op_107"), val = tensor([1, 77, 12, 64])]; + tensor var_108 = reshape(shape = var_107, x = tensor_5)[name = tensor("op_108")]; + tensor var_109_perm_0 = const()[name = tensor("op_109_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_111 = const()[name = tensor("op_111"), val = tensor([12, -1, 64])]; + tensor transpose_57 = transpose(perm = var_109_perm_0, x = var_108)[name = tensor("transpose_57")]; + tensor query_states_1 = reshape(shape = var_111, x = transpose_57)[name = tensor("query_states_1")]; + tensor var_113 = const()[name = tensor("op_113"), val = tensor([12, -1, 64])]; + tensor transpose_59 = transpose(perm = var_93_perm_0, x = var_92)[name = tensor("transpose_59")]; + tensor key_states_3 = reshape(shape = var_113, x = transpose_59)[name = tensor("key_states_3")]; + tensor var_115 = const()[name = tensor("op_115"), val = tensor([12, -1, 64])]; + tensor transpose_58 = transpose(perm = var_100_perm_0, x = var_99)[name = tensor("transpose_58")]; + tensor value_states_3 = reshape(shape = var_115, x = transpose_58)[name = tensor("value_states_3")]; + tensor var_118_perm_0 = const()[name = tensor("op_118_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_56 = transpose(perm = var_118_perm_0, x = key_states_3)[name = tensor("transpose_56")]; + tensor attn_weights_1 = matmul(transpose_x = attn_weights_1_transpose_x_0, transpose_y = attn_weights_1_transpose_y_0, x = query_states_1, y = transpose_56)[name = tensor("attn_weights_1")]; + tensor var_120 = const()[name = tensor("op_120"), val = tensor([1, 12, 77, 77])]; + tensor var_121 = reshape(shape = var_120, x = attn_weights_1)[name = tensor("op_121")]; + tensor attn_weights_3 = add(x = var_121, y = causal_attention_mask)[name = tensor("attn_weights_3")]; + tensor var_126 = const()[name = tensor("op_126"), val = tensor([12, 77, 77])]; + tensor input_5 = reshape(shape = var_126, x = attn_weights_3)[name = tensor("input_5")]; + tensor input_7 = softmax(axis = var_5, x = input_5)[name = tensor("input_7")]; + 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 = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7, y = value_states_3)[name = tensor("attn_output_1")]; + tensor var_131 = const()[name = tensor("op_131"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_3 = reshape(shape = var_131, x = attn_output_1)[name = tensor("attn_output_3")]; + tensor attn_output_5_perm_0 = const()[name = tensor("attn_output_5_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_134 = const()[name = tensor("op_134"), val = tensor([1, 77, 768])]; + tensor transpose_55 = transpose(perm = attn_output_5_perm_0, x = attn_output_3)[name = tensor("transpose_55")]; + tensor input_9 = reshape(shape = var_134, x = transpose_55)[name = tensor("input_9")]; + tensor hidden_states_3 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight, x = input_9)[name = tensor("hidden_states_3")]; + tensor input_11 = add(x = input_3, y = hidden_states_3)[name = tensor("input_11")]; + tensor input_13_axes_0 = const()[name = tensor("input_13_axes_0"), val = tensor([-1])]; + tensor input_13 = layer_norm(axes = input_13_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight, x = input_11)[name = tensor("input_13")]; + tensor input_15 = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight, x = input_13)[name = tensor("input_15")]; + tensor var_149 = const()[name = tensor("op_149"), val = tensor(0x1.b3b646p+0)]; + tensor var_150 = mul(x = input_15, y = var_149)[name = tensor("op_150")]; + tensor var_151 = sigmoid(x = var_150)[name = tensor("op_151")]; + tensor input_17 = mul(x = input_15, y = var_151)[name = tensor("input_17")]; + tensor hidden_states_5 = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight, x = input_17)[name = tensor("hidden_states_5")]; + tensor input_19 = add(x = input_11, y = hidden_states_5)[name = tensor("input_19")]; + tensor hidden_states_7_axes_0 = const()[name = tensor("hidden_states_7_axes_0"), val = tensor([-1])]; + tensor hidden_states_7 = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight, x = input_19)[name = tensor("hidden_states_7")]; + tensor var_175 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight, x = hidden_states_7)[name = tensor("op_175")]; + tensor var_176 = const()[name = tensor("op_176"), val = tensor(0x1p-3)]; + tensor tensor_11 = mul(x = var_175, y = var_176)[name = tensor("tensor_11")]; + tensor tensor_7 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight, x = hidden_states_7)[name = tensor("tensor_7")]; + tensor var_181 = const()[name = tensor("op_181"), val = tensor([1, -1, 12, 64])]; + tensor var_182 = reshape(shape = var_181, x = tensor_7)[name = tensor("op_182")]; + tensor var_183_perm_0 = const()[name = tensor("op_183_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_9 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight, x = hidden_states_7)[name = tensor("tensor_9")]; + tensor var_188 = const()[name = tensor("op_188"), val = tensor([1, -1, 12, 64])]; + tensor var_189 = reshape(shape = var_188, x = tensor_9)[name = tensor("op_189")]; + tensor var_190_perm_0 = const()[name = tensor("op_190_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_197 = const()[name = tensor("op_197"), val = tensor([1, 77, 12, 64])]; + tensor var_198 = reshape(shape = var_197, x = tensor_11)[name = tensor("op_198")]; + tensor var_199_perm_0 = const()[name = tensor("op_199_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_201 = const()[name = tensor("op_201"), val = tensor([12, -1, 64])]; + tensor transpose_52 = transpose(perm = var_199_perm_0, x = var_198)[name = tensor("transpose_52")]; + tensor query_states_3 = reshape(shape = var_201, x = transpose_52)[name = tensor("query_states_3")]; + tensor var_203 = const()[name = tensor("op_203"), val = tensor([12, -1, 64])]; + tensor transpose_54 = transpose(perm = var_183_perm_0, x = var_182)[name = tensor("transpose_54")]; + tensor key_states_7 = reshape(shape = var_203, x = transpose_54)[name = tensor("key_states_7")]; + tensor var_205 = const()[name = tensor("op_205"), val = tensor([12, -1, 64])]; + tensor transpose_53 = transpose(perm = var_190_perm_0, x = var_189)[name = tensor("transpose_53")]; + tensor value_states_7 = reshape(shape = var_205, x = transpose_53)[name = tensor("value_states_7")]; + tensor var_208_perm_0 = const()[name = tensor("op_208_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_51 = transpose(perm = var_208_perm_0, x = key_states_7)[name = tensor("transpose_51")]; + tensor attn_weights_7 = matmul(transpose_x = attn_weights_7_transpose_x_0, transpose_y = attn_weights_7_transpose_y_0, x = query_states_3, y = transpose_51)[name = tensor("attn_weights_7")]; + tensor var_210 = const()[name = tensor("op_210"), val = tensor([1, 12, 77, 77])]; + tensor var_211 = reshape(shape = var_210, x = attn_weights_7)[name = tensor("op_211")]; + tensor attn_weights_9 = add(x = var_211, y = causal_attention_mask)[name = tensor("attn_weights_9")]; + tensor var_216 = const()[name = tensor("op_216"), val = tensor([12, 77, 77])]; + tensor input_21 = reshape(shape = var_216, x = attn_weights_9)[name = tensor("input_21")]; + tensor input_23 = softmax(axis = var_5, x = input_21)[name = tensor("input_23")]; + 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 = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23, y = value_states_7)[name = tensor("attn_output_7")]; + tensor var_221 = const()[name = tensor("op_221"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_9 = reshape(shape = var_221, x = attn_output_7)[name = tensor("attn_output_9")]; + tensor attn_output_11_perm_0 = const()[name = tensor("attn_output_11_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_224 = const()[name = tensor("op_224"), val = tensor([1, 77, 768])]; + tensor transpose_50 = transpose(perm = attn_output_11_perm_0, x = attn_output_9)[name = tensor("transpose_50")]; + tensor input_25 = reshape(shape = var_224, x = transpose_50)[name = tensor("input_25")]; + tensor hidden_states_9 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight, x = input_25)[name = tensor("hidden_states_9")]; + tensor input_27 = add(x = input_19, y = hidden_states_9)[name = tensor("input_27")]; + tensor input_29_axes_0 = const()[name = tensor("input_29_axes_0"), val = tensor([-1])]; + tensor input_29 = layer_norm(axes = input_29_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight, x = input_27)[name = tensor("input_29")]; + tensor input_31 = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight, x = input_29)[name = tensor("input_31")]; + tensor var_239 = const()[name = tensor("op_239"), val = tensor(0x1.b3b646p+0)]; + tensor var_240 = mul(x = input_31, y = var_239)[name = tensor("op_240")]; + tensor var_241 = sigmoid(x = var_240)[name = tensor("op_241")]; + tensor input_33 = mul(x = input_31, y = var_241)[name = tensor("input_33")]; + tensor hidden_states_11 = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight, x = input_33)[name = tensor("hidden_states_11")]; + tensor input_35 = add(x = input_27, y = hidden_states_11)[name = tensor("input_35")]; + tensor hidden_states_13_axes_0 = const()[name = tensor("hidden_states_13_axes_0"), val = tensor([-1])]; + tensor hidden_states_13 = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight, x = input_35)[name = tensor("hidden_states_13")]; + tensor var_265 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight, x = hidden_states_13)[name = tensor("op_265")]; + tensor var_266 = const()[name = tensor("op_266"), val = tensor(0x1p-3)]; + tensor tensor_17 = mul(x = var_265, y = var_266)[name = tensor("tensor_17")]; + tensor tensor_13 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight, x = hidden_states_13)[name = tensor("tensor_13")]; + tensor var_271 = const()[name = tensor("op_271"), val = tensor([1, -1, 12, 64])]; + tensor var_272 = reshape(shape = var_271, x = tensor_13)[name = tensor("op_272")]; + tensor var_273_perm_0 = const()[name = tensor("op_273_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_15 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight, x = hidden_states_13)[name = tensor("tensor_15")]; + tensor var_278 = const()[name = tensor("op_278"), val = tensor([1, -1, 12, 64])]; + tensor var_279 = reshape(shape = var_278, x = tensor_15)[name = tensor("op_279")]; + tensor var_280_perm_0 = const()[name = tensor("op_280_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_287 = const()[name = tensor("op_287"), val = tensor([1, 77, 12, 64])]; + tensor var_288 = reshape(shape = var_287, x = tensor_17)[name = tensor("op_288")]; + tensor var_289_perm_0 = const()[name = tensor("op_289_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_291 = const()[name = tensor("op_291"), val = tensor([12, -1, 64])]; + tensor transpose_47 = transpose(perm = var_289_perm_0, x = var_288)[name = tensor("transpose_47")]; + tensor query_states_5 = reshape(shape = var_291, x = transpose_47)[name = tensor("query_states_5")]; + tensor var_293 = const()[name = tensor("op_293"), val = tensor([12, -1, 64])]; + tensor transpose_49 = transpose(perm = var_273_perm_0, x = var_272)[name = tensor("transpose_49")]; + tensor key_states_11 = reshape(shape = var_293, x = transpose_49)[name = tensor("key_states_11")]; + tensor var_295 = const()[name = tensor("op_295"), val = tensor([12, -1, 64])]; + tensor transpose_48 = transpose(perm = var_280_perm_0, x = var_279)[name = tensor("transpose_48")]; + tensor value_states_11 = reshape(shape = var_295, x = transpose_48)[name = tensor("value_states_11")]; + tensor var_298_perm_0 = const()[name = tensor("op_298_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_46 = transpose(perm = var_298_perm_0, x = key_states_11)[name = tensor("transpose_46")]; + tensor attn_weights_13 = matmul(transpose_x = attn_weights_13_transpose_x_0, transpose_y = attn_weights_13_transpose_y_0, x = query_states_5, y = transpose_46)[name = tensor("attn_weights_13")]; + tensor var_300 = const()[name = tensor("op_300"), val = tensor([1, 12, 77, 77])]; + tensor var_301 = reshape(shape = var_300, x = attn_weights_13)[name = tensor("op_301")]; + tensor attn_weights_15 = add(x = var_301, y = causal_attention_mask)[name = tensor("attn_weights_15")]; + tensor var_306 = const()[name = tensor("op_306"), val = tensor([12, 77, 77])]; + tensor input_37 = reshape(shape = var_306, x = attn_weights_15)[name = tensor("input_37")]; + tensor input_39 = softmax(axis = var_5, x = input_37)[name = tensor("input_39")]; + 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 = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39, y = value_states_11)[name = tensor("attn_output_13")]; + tensor var_311 = const()[name = tensor("op_311"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_15 = reshape(shape = var_311, x = attn_output_13)[name = tensor("attn_output_15")]; + tensor attn_output_17_perm_0 = const()[name = tensor("attn_output_17_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_314 = const()[name = tensor("op_314"), val = tensor([1, 77, 768])]; + tensor transpose_45 = transpose(perm = attn_output_17_perm_0, x = attn_output_15)[name = tensor("transpose_45")]; + tensor input_41 = reshape(shape = var_314, x = transpose_45)[name = tensor("input_41")]; + tensor hidden_states_15 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight, x = input_41)[name = tensor("hidden_states_15")]; + tensor input_43 = add(x = input_35, y = hidden_states_15)[name = tensor("input_43")]; + tensor input_45_axes_0 = const()[name = tensor("input_45_axes_0"), val = tensor([-1])]; + tensor input_45 = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight, x = input_43)[name = tensor("input_45")]; + tensor input_47 = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight, x = input_45)[name = tensor("input_47")]; + tensor var_329 = const()[name = tensor("op_329"), val = tensor(0x1.b3b646p+0)]; + tensor var_330 = mul(x = input_47, y = var_329)[name = tensor("op_330")]; + tensor var_331 = sigmoid(x = var_330)[name = tensor("op_331")]; + tensor input_49 = mul(x = input_47, y = var_331)[name = tensor("input_49")]; + tensor hidden_states_17 = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight, x = input_49)[name = tensor("hidden_states_17")]; + tensor input_51 = add(x = input_43, y = hidden_states_17)[name = tensor("input_51")]; + tensor hidden_states_19_axes_0 = const()[name = tensor("hidden_states_19_axes_0"), val = tensor([-1])]; + tensor hidden_states_19 = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight, x = input_51)[name = tensor("hidden_states_19")]; + tensor var_355 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight, x = hidden_states_19)[name = tensor("op_355")]; + tensor var_356 = const()[name = tensor("op_356"), val = tensor(0x1p-3)]; + tensor tensor_23 = mul(x = var_355, y = var_356)[name = tensor("tensor_23")]; + tensor tensor_19 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight, x = hidden_states_19)[name = tensor("tensor_19")]; + tensor var_361 = const()[name = tensor("op_361"), val = tensor([1, -1, 12, 64])]; + tensor var_362 = reshape(shape = var_361, x = tensor_19)[name = tensor("op_362")]; + tensor var_363_perm_0 = const()[name = tensor("op_363_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_21 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight, x = hidden_states_19)[name = tensor("tensor_21")]; + tensor var_368 = const()[name = tensor("op_368"), val = tensor([1, -1, 12, 64])]; + tensor var_369 = reshape(shape = var_368, x = tensor_21)[name = tensor("op_369")]; + tensor var_370_perm_0 = const()[name = tensor("op_370_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_377 = const()[name = tensor("op_377"), val = tensor([1, 77, 12, 64])]; + tensor var_378 = reshape(shape = var_377, x = tensor_23)[name = tensor("op_378")]; + tensor var_379_perm_0 = const()[name = tensor("op_379_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_381 = const()[name = tensor("op_381"), val = tensor([12, -1, 64])]; + tensor transpose_42 = transpose(perm = var_379_perm_0, x = var_378)[name = tensor("transpose_42")]; + tensor query_states_7 = reshape(shape = var_381, x = transpose_42)[name = tensor("query_states_7")]; + tensor var_383 = const()[name = tensor("op_383"), val = tensor([12, -1, 64])]; + tensor transpose_44 = transpose(perm = var_363_perm_0, x = var_362)[name = tensor("transpose_44")]; + tensor key_states_15 = reshape(shape = var_383, x = transpose_44)[name = tensor("key_states_15")]; + tensor var_385 = const()[name = tensor("op_385"), val = tensor([12, -1, 64])]; + tensor transpose_43 = transpose(perm = var_370_perm_0, x = var_369)[name = tensor("transpose_43")]; + tensor value_states_15 = reshape(shape = var_385, x = transpose_43)[name = tensor("value_states_15")]; + tensor var_388_perm_0 = const()[name = tensor("op_388_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_41 = transpose(perm = var_388_perm_0, x = key_states_15)[name = tensor("transpose_41")]; + tensor attn_weights_19 = matmul(transpose_x = attn_weights_19_transpose_x_0, transpose_y = attn_weights_19_transpose_y_0, x = query_states_7, y = transpose_41)[name = tensor("attn_weights_19")]; + tensor var_390 = const()[name = tensor("op_390"), val = tensor([1, 12, 77, 77])]; + tensor var_391 = reshape(shape = var_390, x = attn_weights_19)[name = tensor("op_391")]; + tensor attn_weights_21 = add(x = var_391, y = causal_attention_mask)[name = tensor("attn_weights_21")]; + tensor var_396 = const()[name = tensor("op_396"), val = tensor([12, 77, 77])]; + tensor input_53 = reshape(shape = var_396, x = attn_weights_21)[name = tensor("input_53")]; + tensor input_55 = softmax(axis = var_5, x = input_53)[name = tensor("input_55")]; + 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 = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55, y = value_states_15)[name = tensor("attn_output_19")]; + tensor var_401 = const()[name = tensor("op_401"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_21 = reshape(shape = var_401, x = attn_output_19)[name = tensor("attn_output_21")]; + tensor attn_output_23_perm_0 = const()[name = tensor("attn_output_23_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_404 = const()[name = tensor("op_404"), val = tensor([1, 77, 768])]; + tensor transpose_40 = transpose(perm = attn_output_23_perm_0, x = attn_output_21)[name = tensor("transpose_40")]; + tensor input_57 = reshape(shape = var_404, x = transpose_40)[name = tensor("input_57")]; + tensor hidden_states_21 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight, x = input_57)[name = tensor("hidden_states_21")]; + tensor input_59 = add(x = input_51, y = hidden_states_21)[name = tensor("input_59")]; + tensor input_61_axes_0 = const()[name = tensor("input_61_axes_0"), val = tensor([-1])]; + tensor input_61 = layer_norm(axes = input_61_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight, x = input_59)[name = tensor("input_61")]; + tensor input_63 = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight, x = input_61)[name = tensor("input_63")]; + tensor var_419 = const()[name = tensor("op_419"), val = tensor(0x1.b3b646p+0)]; + tensor var_420 = mul(x = input_63, y = var_419)[name = tensor("op_420")]; + tensor var_421 = sigmoid(x = var_420)[name = tensor("op_421")]; + tensor input_65 = mul(x = input_63, y = var_421)[name = tensor("input_65")]; + tensor hidden_states_23 = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight, x = input_65)[name = tensor("hidden_states_23")]; + tensor input_67 = add(x = input_59, y = hidden_states_23)[name = tensor("input_67")]; + tensor hidden_states_25_axes_0 = const()[name = tensor("hidden_states_25_axes_0"), val = tensor([-1])]; + tensor hidden_states_25 = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight, x = input_67)[name = tensor("hidden_states_25")]; + tensor var_445 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight, x = hidden_states_25)[name = tensor("op_445")]; + tensor var_446 = const()[name = tensor("op_446"), val = tensor(0x1p-3)]; + tensor tensor_29 = mul(x = var_445, y = var_446)[name = tensor("tensor_29")]; + tensor tensor_25 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight, x = hidden_states_25)[name = tensor("tensor_25")]; + tensor var_451 = const()[name = tensor("op_451"), val = tensor([1, -1, 12, 64])]; + tensor var_452 = reshape(shape = var_451, x = tensor_25)[name = tensor("op_452")]; + tensor var_453_perm_0 = const()[name = tensor("op_453_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_27 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight, x = hidden_states_25)[name = tensor("tensor_27")]; + tensor var_458 = const()[name = tensor("op_458"), val = tensor([1, -1, 12, 64])]; + tensor var_459 = reshape(shape = var_458, x = tensor_27)[name = tensor("op_459")]; + tensor var_460_perm_0 = const()[name = tensor("op_460_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_467 = const()[name = tensor("op_467"), val = tensor([1, 77, 12, 64])]; + tensor var_468 = reshape(shape = var_467, x = tensor_29)[name = tensor("op_468")]; + tensor var_469_perm_0 = const()[name = tensor("op_469_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_471 = const()[name = tensor("op_471"), val = tensor([12, -1, 64])]; + tensor transpose_37 = transpose(perm = var_469_perm_0, x = var_468)[name = tensor("transpose_37")]; + tensor query_states_9 = reshape(shape = var_471, x = transpose_37)[name = tensor("query_states_9")]; + tensor var_473 = const()[name = tensor("op_473"), val = tensor([12, -1, 64])]; + tensor transpose_39 = transpose(perm = var_453_perm_0, x = var_452)[name = tensor("transpose_39")]; + tensor key_states_19 = reshape(shape = var_473, x = transpose_39)[name = tensor("key_states_19")]; + tensor var_475 = const()[name = tensor("op_475"), val = tensor([12, -1, 64])]; + tensor transpose_38 = transpose(perm = var_460_perm_0, x = var_459)[name = tensor("transpose_38")]; + tensor value_states_19 = reshape(shape = var_475, x = transpose_38)[name = tensor("value_states_19")]; + tensor var_478_perm_0 = const()[name = tensor("op_478_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_36 = transpose(perm = var_478_perm_0, x = key_states_19)[name = tensor("transpose_36")]; + tensor attn_weights_25 = matmul(transpose_x = attn_weights_25_transpose_x_0, transpose_y = attn_weights_25_transpose_y_0, x = query_states_9, y = transpose_36)[name = tensor("attn_weights_25")]; + tensor var_480 = const()[name = tensor("op_480"), val = tensor([1, 12, 77, 77])]; + tensor var_481 = reshape(shape = var_480, x = attn_weights_25)[name = tensor("op_481")]; + tensor attn_weights_27 = add(x = var_481, y = causal_attention_mask)[name = tensor("attn_weights_27")]; + tensor var_486 = const()[name = tensor("op_486"), val = tensor([12, 77, 77])]; + tensor input_69 = reshape(shape = var_486, x = attn_weights_27)[name = tensor("input_69")]; + tensor input_71 = softmax(axis = var_5, x = input_69)[name = tensor("input_71")]; + 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 = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71, y = value_states_19)[name = tensor("attn_output_25")]; + tensor var_491 = const()[name = tensor("op_491"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_27 = reshape(shape = var_491, x = attn_output_25)[name = tensor("attn_output_27")]; + tensor attn_output_29_perm_0 = const()[name = tensor("attn_output_29_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_494 = const()[name = tensor("op_494"), val = tensor([1, 77, 768])]; + tensor transpose_35 = transpose(perm = attn_output_29_perm_0, x = attn_output_27)[name = tensor("transpose_35")]; + tensor input_73 = reshape(shape = var_494, x = transpose_35)[name = tensor("input_73")]; + tensor hidden_states_27 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight, x = input_73)[name = tensor("hidden_states_27")]; + tensor input_75 = add(x = input_67, y = hidden_states_27)[name = tensor("input_75")]; + tensor input_77_axes_0 = const()[name = tensor("input_77_axes_0"), val = tensor([-1])]; + tensor input_77 = layer_norm(axes = input_77_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight, x = input_75)[name = tensor("input_77")]; + tensor input_79 = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight, x = input_77)[name = tensor("input_79")]; + tensor var_509 = const()[name = tensor("op_509"), val = tensor(0x1.b3b646p+0)]; + tensor var_510 = mul(x = input_79, y = var_509)[name = tensor("op_510")]; + tensor var_511 = sigmoid(x = var_510)[name = tensor("op_511")]; + tensor input_81 = mul(x = input_79, y = var_511)[name = tensor("input_81")]; + tensor hidden_states_29 = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight, x = input_81)[name = tensor("hidden_states_29")]; + tensor input_83 = add(x = input_75, y = hidden_states_29)[name = tensor("input_83")]; + tensor hidden_states_31_axes_0 = const()[name = tensor("hidden_states_31_axes_0"), val = tensor([-1])]; + tensor hidden_states_31 = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight, x = input_83)[name = tensor("hidden_states_31")]; + tensor var_535 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight, x = hidden_states_31)[name = tensor("op_535")]; + tensor var_536 = const()[name = tensor("op_536"), val = tensor(0x1p-3)]; + tensor tensor_35 = mul(x = var_535, y = var_536)[name = tensor("tensor_35")]; + tensor tensor_31 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight, x = hidden_states_31)[name = tensor("tensor_31")]; + tensor var_541 = const()[name = tensor("op_541"), val = tensor([1, -1, 12, 64])]; + tensor var_542 = reshape(shape = var_541, x = tensor_31)[name = tensor("op_542")]; + tensor var_543_perm_0 = const()[name = tensor("op_543_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_33 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight, x = hidden_states_31)[name = tensor("tensor_33")]; + tensor var_548 = const()[name = tensor("op_548"), val = tensor([1, -1, 12, 64])]; + tensor var_549 = reshape(shape = var_548, x = tensor_33)[name = tensor("op_549")]; + tensor var_550_perm_0 = const()[name = tensor("op_550_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_557 = const()[name = tensor("op_557"), val = tensor([1, 77, 12, 64])]; + tensor var_558 = reshape(shape = var_557, x = tensor_35)[name = tensor("op_558")]; + tensor var_559_perm_0 = const()[name = tensor("op_559_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_561 = const()[name = tensor("op_561"), val = tensor([12, -1, 64])]; + tensor transpose_32 = transpose(perm = var_559_perm_0, x = var_558)[name = tensor("transpose_32")]; + tensor query_states_11 = reshape(shape = var_561, x = transpose_32)[name = tensor("query_states_11")]; + tensor var_563 = const()[name = tensor("op_563"), val = tensor([12, -1, 64])]; + tensor transpose_34 = transpose(perm = var_543_perm_0, x = var_542)[name = tensor("transpose_34")]; + tensor key_states_23 = reshape(shape = var_563, x = transpose_34)[name = tensor("key_states_23")]; + tensor var_565 = const()[name = tensor("op_565"), val = tensor([12, -1, 64])]; + tensor transpose_33 = transpose(perm = var_550_perm_0, x = var_549)[name = tensor("transpose_33")]; + tensor value_states_23 = reshape(shape = var_565, x = transpose_33)[name = tensor("value_states_23")]; + tensor var_568_perm_0 = const()[name = tensor("op_568_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_31 = transpose(perm = var_568_perm_0, x = key_states_23)[name = tensor("transpose_31")]; + tensor attn_weights_31 = matmul(transpose_x = attn_weights_31_transpose_x_0, transpose_y = attn_weights_31_transpose_y_0, x = query_states_11, y = transpose_31)[name = tensor("attn_weights_31")]; + tensor var_570 = const()[name = tensor("op_570"), val = tensor([1, 12, 77, 77])]; + tensor var_571 = reshape(shape = var_570, x = attn_weights_31)[name = tensor("op_571")]; + tensor attn_weights_33 = add(x = var_571, y = causal_attention_mask)[name = tensor("attn_weights_33")]; + tensor var_576 = const()[name = tensor("op_576"), val = tensor([12, 77, 77])]; + tensor input_85 = reshape(shape = var_576, x = attn_weights_33)[name = tensor("input_85")]; + tensor input_87 = softmax(axis = var_5, x = input_85)[name = tensor("input_87")]; + 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 = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87, y = value_states_23)[name = tensor("attn_output_31")]; + tensor var_581 = const()[name = tensor("op_581"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_33 = reshape(shape = var_581, x = attn_output_31)[name = tensor("attn_output_33")]; + tensor attn_output_35_perm_0 = const()[name = tensor("attn_output_35_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_584 = const()[name = tensor("op_584"), val = tensor([1, 77, 768])]; + tensor transpose_30 = transpose(perm = attn_output_35_perm_0, x = attn_output_33)[name = tensor("transpose_30")]; + tensor input_89 = reshape(shape = var_584, x = transpose_30)[name = tensor("input_89")]; + tensor hidden_states_33 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight, x = input_89)[name = tensor("hidden_states_33")]; + tensor input_91 = add(x = input_83, y = hidden_states_33)[name = tensor("input_91")]; + tensor input_93_axes_0 = const()[name = tensor("input_93_axes_0"), val = tensor([-1])]; + tensor input_93 = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight, x = input_91)[name = tensor("input_93")]; + tensor input_95 = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight, x = input_93)[name = tensor("input_95")]; + tensor var_599 = const()[name = tensor("op_599"), val = tensor(0x1.b3b646p+0)]; + tensor var_600 = mul(x = input_95, y = var_599)[name = tensor("op_600")]; + tensor var_601 = sigmoid(x = var_600)[name = tensor("op_601")]; + tensor input_97 = mul(x = input_95, y = var_601)[name = tensor("input_97")]; + tensor hidden_states_35 = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight, x = input_97)[name = tensor("hidden_states_35")]; + tensor input_99 = add(x = input_91, y = hidden_states_35)[name = tensor("input_99")]; + tensor hidden_states_37_axes_0 = const()[name = tensor("hidden_states_37_axes_0"), val = tensor([-1])]; + tensor hidden_states_37 = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight, x = input_99)[name = tensor("hidden_states_37")]; + tensor var_625 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight, x = hidden_states_37)[name = tensor("op_625")]; + tensor var_626 = const()[name = tensor("op_626"), val = tensor(0x1p-3)]; + tensor tensor_41 = mul(x = var_625, y = var_626)[name = tensor("tensor_41")]; + tensor tensor_37 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight, x = hidden_states_37)[name = tensor("tensor_37")]; + tensor var_631 = const()[name = tensor("op_631"), val = tensor([1, -1, 12, 64])]; + tensor var_632 = reshape(shape = var_631, x = tensor_37)[name = tensor("op_632")]; + tensor var_633_perm_0 = const()[name = tensor("op_633_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_39 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight, x = hidden_states_37)[name = tensor("tensor_39")]; + tensor var_638 = const()[name = tensor("op_638"), val = tensor([1, -1, 12, 64])]; + tensor var_639 = reshape(shape = var_638, x = tensor_39)[name = tensor("op_639")]; + tensor var_640_perm_0 = const()[name = tensor("op_640_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_647 = const()[name = tensor("op_647"), val = tensor([1, 77, 12, 64])]; + tensor var_648 = reshape(shape = var_647, x = tensor_41)[name = tensor("op_648")]; + tensor var_649_perm_0 = const()[name = tensor("op_649_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_651 = const()[name = tensor("op_651"), val = tensor([12, -1, 64])]; + tensor transpose_27 = transpose(perm = var_649_perm_0, x = var_648)[name = tensor("transpose_27")]; + tensor query_states_13 = reshape(shape = var_651, x = transpose_27)[name = tensor("query_states_13")]; + tensor var_653 = const()[name = tensor("op_653"), val = tensor([12, -1, 64])]; + tensor transpose_29 = transpose(perm = var_633_perm_0, x = var_632)[name = tensor("transpose_29")]; + tensor key_states_27 = reshape(shape = var_653, x = transpose_29)[name = tensor("key_states_27")]; + tensor var_655 = const()[name = tensor("op_655"), val = tensor([12, -1, 64])]; + tensor transpose_28 = transpose(perm = var_640_perm_0, x = var_639)[name = tensor("transpose_28")]; + tensor value_states_27 = reshape(shape = var_655, x = transpose_28)[name = tensor("value_states_27")]; + tensor var_658_perm_0 = const()[name = tensor("op_658_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_26 = transpose(perm = var_658_perm_0, x = key_states_27)[name = tensor("transpose_26")]; + tensor attn_weights_37 = matmul(transpose_x = attn_weights_37_transpose_x_0, transpose_y = attn_weights_37_transpose_y_0, x = query_states_13, y = transpose_26)[name = tensor("attn_weights_37")]; + tensor var_660 = const()[name = tensor("op_660"), val = tensor([1, 12, 77, 77])]; + tensor var_661 = reshape(shape = var_660, x = attn_weights_37)[name = tensor("op_661")]; + tensor attn_weights_39 = add(x = var_661, y = causal_attention_mask)[name = tensor("attn_weights_39")]; + tensor var_666 = const()[name = tensor("op_666"), val = tensor([12, 77, 77])]; + tensor input_101 = reshape(shape = var_666, x = attn_weights_39)[name = tensor("input_101")]; + tensor input_103 = softmax(axis = var_5, x = input_101)[name = tensor("input_103")]; + 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 = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103, y = value_states_27)[name = tensor("attn_output_37")]; + tensor var_671 = const()[name = tensor("op_671"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_39 = reshape(shape = var_671, x = attn_output_37)[name = tensor("attn_output_39")]; + tensor attn_output_41_perm_0 = const()[name = tensor("attn_output_41_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_674 = const()[name = tensor("op_674"), val = tensor([1, 77, 768])]; + tensor transpose_25 = transpose(perm = attn_output_41_perm_0, x = attn_output_39)[name = tensor("transpose_25")]; + tensor input_105 = reshape(shape = var_674, x = transpose_25)[name = tensor("input_105")]; + tensor hidden_states_39 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight, x = input_105)[name = tensor("hidden_states_39")]; + tensor input_107 = add(x = input_99, y = hidden_states_39)[name = tensor("input_107")]; + tensor input_109_axes_0 = const()[name = tensor("input_109_axes_0"), val = tensor([-1])]; + tensor input_109 = layer_norm(axes = input_109_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight, x = input_107)[name = tensor("input_109")]; + tensor input_111 = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight, x = input_109)[name = tensor("input_111")]; + tensor var_689 = const()[name = tensor("op_689"), val = tensor(0x1.b3b646p+0)]; + tensor var_690 = mul(x = input_111, y = var_689)[name = tensor("op_690")]; + tensor var_691 = sigmoid(x = var_690)[name = tensor("op_691")]; + tensor input_113 = mul(x = input_111, y = var_691)[name = tensor("input_113")]; + tensor hidden_states_41 = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight, x = input_113)[name = tensor("hidden_states_41")]; + tensor input_115 = add(x = input_107, y = hidden_states_41)[name = tensor("input_115")]; + tensor hidden_states_43_axes_0 = const()[name = tensor("hidden_states_43_axes_0"), val = tensor([-1])]; + tensor hidden_states_43 = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight, x = input_115)[name = tensor("hidden_states_43")]; + tensor var_715 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight, x = hidden_states_43)[name = tensor("op_715")]; + tensor var_716 = const()[name = tensor("op_716"), val = tensor(0x1p-3)]; + tensor tensor_47 = mul(x = var_715, y = var_716)[name = tensor("tensor_47")]; + tensor tensor_43 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight, x = hidden_states_43)[name = tensor("tensor_43")]; + tensor var_721 = const()[name = tensor("op_721"), val = tensor([1, -1, 12, 64])]; + tensor var_722 = reshape(shape = var_721, x = tensor_43)[name = tensor("op_722")]; + tensor var_723_perm_0 = const()[name = tensor("op_723_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_45 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight, x = hidden_states_43)[name = tensor("tensor_45")]; + tensor var_728 = const()[name = tensor("op_728"), val = tensor([1, -1, 12, 64])]; + tensor var_729 = reshape(shape = var_728, x = tensor_45)[name = tensor("op_729")]; + tensor var_730_perm_0 = const()[name = tensor("op_730_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_737 = const()[name = tensor("op_737"), val = tensor([1, 77, 12, 64])]; + tensor var_738 = reshape(shape = var_737, x = tensor_47)[name = tensor("op_738")]; + tensor var_739_perm_0 = const()[name = tensor("op_739_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_741 = const()[name = tensor("op_741"), val = tensor([12, -1, 64])]; + tensor transpose_22 = transpose(perm = var_739_perm_0, x = var_738)[name = tensor("transpose_22")]; + tensor query_states_15 = reshape(shape = var_741, x = transpose_22)[name = tensor("query_states_15")]; + tensor var_743 = const()[name = tensor("op_743"), val = tensor([12, -1, 64])]; + tensor transpose_24 = transpose(perm = var_723_perm_0, x = var_722)[name = tensor("transpose_24")]; + tensor key_states_31 = reshape(shape = var_743, x = transpose_24)[name = tensor("key_states_31")]; + tensor var_745 = const()[name = tensor("op_745"), val = tensor([12, -1, 64])]; + tensor transpose_23 = transpose(perm = var_730_perm_0, x = var_729)[name = tensor("transpose_23")]; + tensor value_states_31 = reshape(shape = var_745, x = transpose_23)[name = tensor("value_states_31")]; + tensor var_748_perm_0 = const()[name = tensor("op_748_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_21 = transpose(perm = var_748_perm_0, x = key_states_31)[name = tensor("transpose_21")]; + tensor attn_weights_43 = matmul(transpose_x = attn_weights_43_transpose_x_0, transpose_y = attn_weights_43_transpose_y_0, x = query_states_15, y = transpose_21)[name = tensor("attn_weights_43")]; + tensor var_750 = const()[name = tensor("op_750"), val = tensor([1, 12, 77, 77])]; + tensor var_751 = reshape(shape = var_750, x = attn_weights_43)[name = tensor("op_751")]; + tensor attn_weights_45 = add(x = var_751, y = causal_attention_mask)[name = tensor("attn_weights_45")]; + tensor var_756 = const()[name = tensor("op_756"), val = tensor([12, 77, 77])]; + tensor input_117 = reshape(shape = var_756, x = attn_weights_45)[name = tensor("input_117")]; + tensor input_119 = softmax(axis = var_5, x = input_117)[name = tensor("input_119")]; + 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 = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119, y = value_states_31)[name = tensor("attn_output_43")]; + tensor var_761 = const()[name = tensor("op_761"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_45 = reshape(shape = var_761, x = attn_output_43)[name = tensor("attn_output_45")]; + tensor attn_output_47_perm_0 = const()[name = tensor("attn_output_47_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_764 = const()[name = tensor("op_764"), val = tensor([1, 77, 768])]; + tensor transpose_20 = transpose(perm = attn_output_47_perm_0, x = attn_output_45)[name = tensor("transpose_20")]; + tensor input_121 = reshape(shape = var_764, x = transpose_20)[name = tensor("input_121")]; + tensor hidden_states_45 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight, x = input_121)[name = tensor("hidden_states_45")]; + tensor input_123 = add(x = input_115, y = hidden_states_45)[name = tensor("input_123")]; + tensor input_125_axes_0 = const()[name = tensor("input_125_axes_0"), val = tensor([-1])]; + tensor input_125 = layer_norm(axes = input_125_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight, x = input_123)[name = tensor("input_125")]; + tensor input_127 = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight, x = input_125)[name = tensor("input_127")]; + tensor var_779 = const()[name = tensor("op_779"), val = tensor(0x1.b3b646p+0)]; + tensor var_780 = mul(x = input_127, y = var_779)[name = tensor("op_780")]; + tensor var_781 = sigmoid(x = var_780)[name = tensor("op_781")]; + tensor input_129 = mul(x = input_127, y = var_781)[name = tensor("input_129")]; + tensor hidden_states_47 = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight, x = input_129)[name = tensor("hidden_states_47")]; + tensor input_131 = add(x = input_123, y = hidden_states_47)[name = tensor("input_131")]; + tensor hidden_states_49_axes_0 = const()[name = tensor("hidden_states_49_axes_0"), val = tensor([-1])]; + tensor hidden_states_49 = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight, x = input_131)[name = tensor("hidden_states_49")]; + tensor var_805 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight, x = hidden_states_49)[name = tensor("op_805")]; + tensor var_806 = const()[name = tensor("op_806"), val = tensor(0x1p-3)]; + tensor tensor_53 = mul(x = var_805, y = var_806)[name = tensor("tensor_53")]; + tensor tensor_49 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight, x = hidden_states_49)[name = tensor("tensor_49")]; + tensor var_811 = const()[name = tensor("op_811"), val = tensor([1, -1, 12, 64])]; + tensor var_812 = reshape(shape = var_811, x = tensor_49)[name = tensor("op_812")]; + tensor var_813_perm_0 = const()[name = tensor("op_813_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_51 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight, x = hidden_states_49)[name = tensor("tensor_51")]; + tensor var_818 = const()[name = tensor("op_818"), val = tensor([1, -1, 12, 64])]; + tensor var_819 = reshape(shape = var_818, x = tensor_51)[name = tensor("op_819")]; + tensor var_820_perm_0 = const()[name = tensor("op_820_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_827 = const()[name = tensor("op_827"), val = tensor([1, 77, 12, 64])]; + tensor var_828 = reshape(shape = var_827, x = tensor_53)[name = tensor("op_828")]; + tensor var_829_perm_0 = const()[name = tensor("op_829_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_831 = const()[name = tensor("op_831"), val = tensor([12, -1, 64])]; + tensor transpose_17 = transpose(perm = var_829_perm_0, x = var_828)[name = tensor("transpose_17")]; + tensor query_states_17 = reshape(shape = var_831, x = transpose_17)[name = tensor("query_states_17")]; + tensor var_833 = const()[name = tensor("op_833"), val = tensor([12, -1, 64])]; + tensor transpose_19 = transpose(perm = var_813_perm_0, x = var_812)[name = tensor("transpose_19")]; + tensor key_states_35 = reshape(shape = var_833, x = transpose_19)[name = tensor("key_states_35")]; + tensor var_835 = const()[name = tensor("op_835"), val = tensor([12, -1, 64])]; + tensor transpose_18 = transpose(perm = var_820_perm_0, x = var_819)[name = tensor("transpose_18")]; + tensor value_states_35 = reshape(shape = var_835, x = transpose_18)[name = tensor("value_states_35")]; + tensor var_838_perm_0 = const()[name = tensor("op_838_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_16 = transpose(perm = var_838_perm_0, x = key_states_35)[name = tensor("transpose_16")]; + tensor attn_weights_49 = matmul(transpose_x = attn_weights_49_transpose_x_0, transpose_y = attn_weights_49_transpose_y_0, x = query_states_17, y = transpose_16)[name = tensor("attn_weights_49")]; + tensor var_840 = const()[name = tensor("op_840"), val = tensor([1, 12, 77, 77])]; + tensor var_841 = reshape(shape = var_840, x = attn_weights_49)[name = tensor("op_841")]; + tensor attn_weights_51 = add(x = var_841, y = causal_attention_mask)[name = tensor("attn_weights_51")]; + tensor var_846 = const()[name = tensor("op_846"), val = tensor([12, 77, 77])]; + tensor input_133 = reshape(shape = var_846, x = attn_weights_51)[name = tensor("input_133")]; + tensor input_135 = softmax(axis = var_5, x = input_133)[name = tensor("input_135")]; + 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 = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135, y = value_states_35)[name = tensor("attn_output_49")]; + tensor var_851 = const()[name = tensor("op_851"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_51 = reshape(shape = var_851, x = attn_output_49)[name = tensor("attn_output_51")]; + tensor attn_output_53_perm_0 = const()[name = tensor("attn_output_53_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_854 = const()[name = tensor("op_854"), val = tensor([1, 77, 768])]; + tensor transpose_15 = transpose(perm = attn_output_53_perm_0, x = attn_output_51)[name = tensor("transpose_15")]; + tensor input_137 = reshape(shape = var_854, x = transpose_15)[name = tensor("input_137")]; + tensor hidden_states_51 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight, x = input_137)[name = tensor("hidden_states_51")]; + tensor input_139 = add(x = input_131, y = hidden_states_51)[name = tensor("input_139")]; + tensor input_141_axes_0 = const()[name = tensor("input_141_axes_0"), val = tensor([-1])]; + tensor input_141 = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight, x = input_139)[name = tensor("input_141")]; + tensor input_143 = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight, x = input_141)[name = tensor("input_143")]; + tensor var_869 = const()[name = tensor("op_869"), val = tensor(0x1.b3b646p+0)]; + tensor var_870 = mul(x = input_143, y = var_869)[name = tensor("op_870")]; + tensor var_871 = sigmoid(x = var_870)[name = tensor("op_871")]; + tensor input_145 = mul(x = input_143, y = var_871)[name = tensor("input_145")]; + tensor hidden_states_53 = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight, x = input_145)[name = tensor("hidden_states_53")]; + tensor input_147 = add(x = input_139, y = hidden_states_53)[name = tensor("input_147")]; + tensor hidden_states_55_axes_0 = const()[name = tensor("hidden_states_55_axes_0"), val = tensor([-1])]; + tensor hidden_states_55 = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight, x = input_147)[name = tensor("hidden_states_55")]; + tensor var_895 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight, x = hidden_states_55)[name = tensor("op_895")]; + tensor var_896 = const()[name = tensor("op_896"), val = tensor(0x1p-3)]; + tensor tensor_59 = mul(x = var_895, y = var_896)[name = tensor("tensor_59")]; + tensor tensor_55 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight, x = hidden_states_55)[name = tensor("tensor_55")]; + tensor var_901 = const()[name = tensor("op_901"), val = tensor([1, -1, 12, 64])]; + tensor var_902 = reshape(shape = var_901, x = tensor_55)[name = tensor("op_902")]; + tensor var_903_perm_0 = const()[name = tensor("op_903_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_57 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight, x = hidden_states_55)[name = tensor("tensor_57")]; + tensor var_908 = const()[name = tensor("op_908"), val = tensor([1, -1, 12, 64])]; + tensor var_909 = reshape(shape = var_908, x = tensor_57)[name = tensor("op_909")]; + tensor var_910_perm_0 = const()[name = tensor("op_910_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_917 = const()[name = tensor("op_917"), val = tensor([1, 77, 12, 64])]; + tensor var_918 = reshape(shape = var_917, x = tensor_59)[name = tensor("op_918")]; + tensor var_919_perm_0 = const()[name = tensor("op_919_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_921 = const()[name = tensor("op_921"), val = tensor([12, -1, 64])]; + tensor transpose_12 = transpose(perm = var_919_perm_0, x = var_918)[name = tensor("transpose_12")]; + tensor query_states_19 = reshape(shape = var_921, x = transpose_12)[name = tensor("query_states_19")]; + tensor var_923 = const()[name = tensor("op_923"), val = tensor([12, -1, 64])]; + tensor transpose_14 = transpose(perm = var_903_perm_0, x = var_902)[name = tensor("transpose_14")]; + tensor key_states_39 = reshape(shape = var_923, x = transpose_14)[name = tensor("key_states_39")]; + tensor var_925 = const()[name = tensor("op_925"), val = tensor([12, -1, 64])]; + tensor transpose_13 = transpose(perm = var_910_perm_0, x = var_909)[name = tensor("transpose_13")]; + tensor value_states_39 = reshape(shape = var_925, x = transpose_13)[name = tensor("value_states_39")]; + tensor var_928_perm_0 = const()[name = tensor("op_928_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_11 = transpose(perm = var_928_perm_0, x = key_states_39)[name = tensor("transpose_11")]; + tensor attn_weights_55 = matmul(transpose_x = attn_weights_55_transpose_x_0, transpose_y = attn_weights_55_transpose_y_0, x = query_states_19, y = transpose_11)[name = tensor("attn_weights_55")]; + tensor var_930 = const()[name = tensor("op_930"), val = tensor([1, 12, 77, 77])]; + tensor var_931 = reshape(shape = var_930, x = attn_weights_55)[name = tensor("op_931")]; + tensor attn_weights_57 = add(x = var_931, y = causal_attention_mask)[name = tensor("attn_weights_57")]; + tensor var_936 = const()[name = tensor("op_936"), val = tensor([12, 77, 77])]; + tensor input_149 = reshape(shape = var_936, x = attn_weights_57)[name = tensor("input_149")]; + tensor input_151 = softmax(axis = var_5, x = input_149)[name = tensor("input_151")]; + 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 = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151, y = value_states_39)[name = tensor("attn_output_55")]; + tensor var_941 = const()[name = tensor("op_941"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_57 = reshape(shape = var_941, x = attn_output_55)[name = tensor("attn_output_57")]; + tensor attn_output_59_perm_0 = const()[name = tensor("attn_output_59_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_944 = const()[name = tensor("op_944"), val = tensor([1, 77, 768])]; + tensor transpose_10 = transpose(perm = attn_output_59_perm_0, x = attn_output_57)[name = tensor("transpose_10")]; + tensor input_153 = reshape(shape = var_944, x = transpose_10)[name = tensor("input_153")]; + tensor hidden_states_57 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight, x = input_153)[name = tensor("hidden_states_57")]; + tensor input_155 = add(x = input_147, y = hidden_states_57)[name = tensor("input_155")]; + tensor input_157_axes_0 = const()[name = tensor("input_157_axes_0"), val = tensor([-1])]; + tensor input_157 = layer_norm(axes = input_157_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight, x = input_155)[name = tensor("input_157")]; + tensor input_159 = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight, x = input_157)[name = tensor("input_159")]; + tensor var_959 = const()[name = tensor("op_959"), val = tensor(0x1.b3b646p+0)]; + tensor var_960 = mul(x = input_159, y = var_959)[name = tensor("op_960")]; + tensor var_961 = sigmoid(x = var_960)[name = tensor("op_961")]; + tensor input_161 = mul(x = input_159, y = var_961)[name = tensor("input_161")]; + tensor hidden_states_59 = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight, x = input_161)[name = tensor("hidden_states_59")]; + tensor input_163 = add(x = input_155, y = hidden_states_59)[name = tensor("input_163")]; + tensor hidden_states_61_axes_0 = const()[name = tensor("hidden_states_61_axes_0"), val = tensor([-1])]; + tensor hidden_states_61 = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight, x = input_163)[name = tensor("hidden_states_61")]; + tensor var_985 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight, x = hidden_states_61)[name = tensor("op_985")]; + tensor var_986 = const()[name = tensor("op_986"), val = tensor(0x1p-3)]; + tensor tensor_65 = mul(x = var_985, y = var_986)[name = tensor("tensor_65")]; + tensor tensor_61 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight, x = hidden_states_61)[name = tensor("tensor_61")]; + tensor var_991 = const()[name = tensor("op_991"), val = tensor([1, -1, 12, 64])]; + tensor var_992 = reshape(shape = var_991, x = tensor_61)[name = tensor("op_992")]; + tensor var_993_perm_0 = const()[name = tensor("op_993_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_63 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight, x = hidden_states_61)[name = tensor("tensor_63")]; + tensor var_998 = const()[name = tensor("op_998"), val = tensor([1, -1, 12, 64])]; + tensor var_999 = reshape(shape = var_998, x = tensor_63)[name = tensor("op_999")]; + tensor var_1000_perm_0 = const()[name = tensor("op_1000_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1007 = const()[name = tensor("op_1007"), val = tensor([1, 77, 12, 64])]; + tensor var_1008 = reshape(shape = var_1007, x = tensor_65)[name = tensor("op_1008")]; + tensor var_1009_perm_0 = const()[name = tensor("op_1009_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1011 = const()[name = tensor("op_1011"), val = tensor([12, -1, 64])]; + tensor transpose_7 = transpose(perm = var_1009_perm_0, x = var_1008)[name = tensor("transpose_7")]; + tensor query_states_21 = reshape(shape = var_1011, x = transpose_7)[name = tensor("query_states_21")]; + tensor var_1013 = const()[name = tensor("op_1013"), val = tensor([12, -1, 64])]; + tensor transpose_9 = transpose(perm = var_993_perm_0, x = var_992)[name = tensor("transpose_9")]; + tensor key_states_43 = reshape(shape = var_1013, x = transpose_9)[name = tensor("key_states_43")]; + tensor var_1015 = const()[name = tensor("op_1015"), val = tensor([12, -1, 64])]; + tensor transpose_8 = transpose(perm = var_1000_perm_0, x = var_999)[name = tensor("transpose_8")]; + tensor value_states_43 = reshape(shape = var_1015, x = transpose_8)[name = tensor("value_states_43")]; + tensor var_1018_perm_0 = const()[name = tensor("op_1018_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_6 = transpose(perm = var_1018_perm_0, x = key_states_43)[name = tensor("transpose_6")]; + tensor attn_weights_61 = matmul(transpose_x = attn_weights_61_transpose_x_0, transpose_y = attn_weights_61_transpose_y_0, x = query_states_21, y = transpose_6)[name = tensor("attn_weights_61")]; + tensor var_1020 = const()[name = tensor("op_1020"), val = tensor([1, 12, 77, 77])]; + tensor var_1021 = reshape(shape = var_1020, x = attn_weights_61)[name = tensor("op_1021")]; + tensor attn_weights_63 = add(x = var_1021, y = causal_attention_mask)[name = tensor("attn_weights_63")]; + tensor var_1026 = const()[name = tensor("op_1026"), val = tensor([12, 77, 77])]; + tensor input_165 = reshape(shape = var_1026, x = attn_weights_63)[name = tensor("input_165")]; + tensor input_167 = softmax(axis = var_5, x = input_165)[name = tensor("input_167")]; + 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 = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167, y = value_states_43)[name = tensor("attn_output_61")]; + tensor var_1031 = const()[name = tensor("op_1031"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_63 = reshape(shape = var_1031, x = attn_output_61)[name = tensor("attn_output_63")]; + tensor attn_output_65_perm_0 = const()[name = tensor("attn_output_65_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1034 = const()[name = tensor("op_1034"), val = tensor([1, 77, 768])]; + tensor transpose_5 = transpose(perm = attn_output_65_perm_0, x = attn_output_63)[name = tensor("transpose_5")]; + tensor input_169 = reshape(shape = var_1034, x = transpose_5)[name = tensor("input_169")]; + tensor hidden_states_63 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight, x = input_169)[name = tensor("hidden_states_63")]; + tensor input_171 = add(x = input_163, y = hidden_states_63)[name = tensor("input_171")]; + tensor input_173_axes_0 = const()[name = tensor("input_173_axes_0"), val = tensor([-1])]; + tensor input_173 = layer_norm(axes = input_173_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight, x = input_171)[name = tensor("input_173")]; + tensor input_175 = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight, x = input_173)[name = tensor("input_175")]; + tensor var_1049 = const()[name = tensor("op_1049"), val = tensor(0x1.b3b646p+0)]; + tensor var_1050 = mul(x = input_175, y = var_1049)[name = tensor("op_1050")]; + tensor var_1051 = sigmoid(x = var_1050)[name = tensor("op_1051")]; + tensor input_177 = mul(x = input_175, y = var_1051)[name = tensor("input_177")]; + tensor hidden_states_65 = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight, x = input_177)[name = tensor("hidden_states_65")]; + tensor last_hidden_state = add(x = input_171, y = hidden_states_65)[name = tensor("input_179")]; + tensor hidden_states_67_axes_0 = const()[name = tensor("hidden_states_67_axes_0"), val = tensor([-1])]; + tensor hidden_states_67 = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight, x = last_hidden_state)[name = tensor("hidden_states_67")]; + tensor var_1075 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight, x = hidden_states_67)[name = tensor("op_1075")]; + tensor var_1076 = const()[name = tensor("op_1076"), val = tensor(0x1p-3)]; + tensor tensor_workaround = mul(x = var_1075, y = var_1076)[name = tensor("tensor_workaround")]; + tensor tensor_67 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight, x = hidden_states_67)[name = tensor("tensor_67")]; + tensor var_1081 = const()[name = tensor("op_1081"), val = tensor([1, -1, 12, 64])]; + tensor var_1082 = reshape(shape = var_1081, x = tensor_67)[name = tensor("op_1082")]; + tensor var_1083_perm_0 = const()[name = tensor("op_1083_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor tensor_69 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight, x = hidden_states_67)[name = tensor("tensor_69")]; + tensor var_1088 = const()[name = tensor("op_1088"), val = tensor([1, -1, 12, 64])]; + tensor var_1089 = reshape(shape = var_1088, x = tensor_69)[name = tensor("op_1089")]; + tensor var_1090_perm_0 = const()[name = tensor("op_1090_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1097 = const()[name = tensor("op_1097"), val = tensor([1, 77, 12, 64])]; + tensor var_1098 = reshape(shape = var_1097, x = tensor_workaround)[name = tensor("op_1098")]; + tensor var_1099_perm_0 = const()[name = tensor("op_1099_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1101 = const()[name = tensor("op_1101"), val = tensor([12, -1, 64])]; + tensor transpose_2 = transpose(perm = var_1099_perm_0, x = var_1098)[name = tensor("transpose_2")]; + tensor query_states = reshape(shape = var_1101, x = transpose_2)[name = tensor("query_states")]; + tensor var_1103 = const()[name = tensor("op_1103"), val = tensor([12, -1, 64])]; + tensor transpose_4 = transpose(perm = var_1083_perm_0, x = var_1082)[name = tensor("transpose_4")]; + tensor key_states = reshape(shape = var_1103, x = transpose_4)[name = tensor("key_states")]; + tensor var_1105 = const()[name = tensor("op_1105"), val = tensor([12, -1, 64])]; + tensor transpose_3 = transpose(perm = var_1090_perm_0, x = var_1089)[name = tensor("transpose_3")]; + tensor value_states = reshape(shape = var_1105, x = transpose_3)[name = tensor("value_states")]; + tensor var_1108_perm_0 = const()[name = tensor("op_1108_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_1 = transpose(perm = var_1108_perm_0, x = key_states)[name = tensor("transpose_1")]; + tensor attn_weights_67 = matmul(transpose_x = attn_weights_67_transpose_x_0, transpose_y = attn_weights_67_transpose_y_0, x = query_states, y = transpose_1)[name = tensor("attn_weights_67")]; + tensor var_1110 = const()[name = tensor("op_1110"), val = tensor([1, 12, 77, 77])]; + tensor var_1111 = reshape(shape = var_1110, x = attn_weights_67)[name = tensor("op_1111")]; + tensor attn_weights_69 = add(x = var_1111, y = causal_attention_mask)[name = tensor("attn_weights_69")]; + tensor var_1116 = const()[name = tensor("op_1116"), val = tensor([12, 77, 77])]; + tensor input_181 = reshape(shape = var_1116, x = attn_weights_69)[name = tensor("input_181")]; + tensor input_183 = softmax(axis = var_5, x = input_181)[name = tensor("input_183")]; + 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 = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183, y = value_states)[name = tensor("attn_output_67")]; + tensor var_1121 = const()[name = tensor("op_1121"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_69 = reshape(shape = var_1121, x = attn_output_67)[name = tensor("attn_output_69")]; + tensor attn_output_perm_0 = const()[name = tensor("attn_output_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1124 = const()[name = tensor("op_1124"), val = tensor([1, 77, 768])]; + tensor transpose_0 = transpose(perm = attn_output_perm_0, x = attn_output_69)[name = tensor("transpose_0")]; + tensor input_185 = reshape(shape = var_1124, x = transpose_0)[name = tensor("input_185")]; + tensor hidden_states_69 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight, x = input_185)[name = tensor("hidden_states_69")]; + tensor input_187 = add(x = last_hidden_state, y = hidden_states_69)[name = tensor("input_187")]; + tensor input_189_axes_0 = const()[name = tensor("input_189_axes_0"), val = tensor([-1])]; + tensor input_189 = layer_norm(axes = input_189_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias, epsilon = var_12, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight, x = input_187)[name = tensor("input_189")]; + tensor input_191 = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight, x = input_189)[name = tensor("input_191")]; + tensor var_1139 = const()[name = tensor("op_1139"), val = tensor(0x1.b3b646p+0)]; + tensor var_1140 = mul(x = input_191, y = var_1139)[name = tensor("op_1140")]; + tensor var_1141 = sigmoid(x = var_1140)[name = tensor("op_1141")]; + tensor input_193 = mul(x = input_191, y = var_1141)[name = tensor("input_193")]; + tensor hidden_states = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight, x = input_193)[name = tensor("hidden_states")]; + tensor input = add(x = input_187, y = hidden_states)[name = tensor("input")]; + tensor last_hidden_state_axes_0 = const()[name = tensor("last_hidden_state_axes_0"), val = tensor([-1])]; + tensor pooled_outputs = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias, epsilon = var_12, gamma = text_encoder_text_model_final_layer_norm_weight, x = input)[name = tensor("last_hidden_state")]; + } -> (last_hidden_state, pooled_outputs); +} \ No newline at end of file