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 +1,896 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.30.0"}, {"coremlc-version", "1839.0.0"}})] +{ + func main(tensor input_ids) { + tensor var_5 = const()[name = tensor("op_5"), val = tensor(-1)]; + tensor var_6 = const()[name = tensor("op_6"), val = tensor(false)]; + tensor cast_1_dtype_0 = const()[name = tensor("cast_1_dtype_0"), val = tensor("int32")]; + tensor inputs_embeds_axis_0 = const()[name = tensor("inputs_embeds_axis_0"), val = tensor(0)]; + tensor inputs_embeds_batch_dims_0 = const()[name = tensor("inputs_embeds_batch_dims_0"), val = tensor(0)]; + tensor text_encoder_text_model_embeddings_token_embedding_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor cast_2 = cast(dtype = cast_1_dtype_0, x = input_ids)[name = tensor("cast_2")]; + tensor inputs_embeds_cast = gather(axis = inputs_embeds_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = cast_2, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16)[name = tensor("inputs_embeds_cast")]; + tensor position_embeddings_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75890816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75935232))), name = tensor("position_embeddings_to_fp16_palettized"), shape = tensor([1, 77, 768])]; + tensor input_3_cast = add(x = inputs_embeds_cast, y = position_embeddings_to_fp16_palettized)[name = tensor("input_3_cast")]; + tensor hidden_states_1_axes_0 = const()[name = tensor("hidden_states_1_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75935424)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75937024)))]; + tensor var_12_to_fp16 = const()[name = tensor("op_12_to_fp16"), val = tensor(0x1.5p-17)]; + tensor hidden_states_1_cast = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_3_cast)[name = tensor("hidden_states_1_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75938624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76381056))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76381248)))]; + tensor var_86_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("op_86_cast")]; + tensor var_87_to_fp16 = const()[name = tensor("op_87_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_5_cast = mul(x = var_86_cast, y = var_87_to_fp16)[name = tensor("tensor_5_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76382848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76825280))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76825472)))]; + tensor tensor_1_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("tensor_1_cast")]; + tensor var_92 = const()[name = tensor("op_92"), val = tensor([1, -1, 12, 64])]; + tensor var_93_cast = reshape(shape = var_92, x = tensor_1_cast)[name = tensor("op_93_cast")]; + tensor var_94_perm_0 = const()[name = tensor("op_94_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76827072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77269504))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77269696)))]; + tensor tensor_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("tensor_3_cast")]; + tensor var_99 = const()[name = tensor("op_99"), val = tensor([1, -1, 12, 64])]; + tensor var_100_cast = reshape(shape = var_99, x = tensor_3_cast)[name = tensor("op_100_cast")]; + tensor var_101_perm_0 = const()[name = tensor("op_101_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_108 = const()[name = tensor("op_108"), val = tensor([1, 77, 12, 64])]; + tensor var_109_cast = reshape(shape = var_108, x = tensor_5_cast)[name = tensor("op_109_cast")]; + tensor var_110_perm_0 = const()[name = tensor("op_110_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_112 = const()[name = tensor("op_112"), val = tensor([12, -1, 64])]; + tensor transpose_59 = transpose(perm = var_110_perm_0, x = var_109_cast)[name = tensor("transpose_59")]; + tensor query_states_1_cast = reshape(shape = var_112, x = transpose_59)[name = tensor("query_states_1_cast")]; + tensor var_114 = const()[name = tensor("op_114"), val = tensor([12, -1, 64])]; + tensor transpose_58 = transpose(perm = var_94_perm_0, x = var_93_cast)[name = tensor("transpose_58")]; + tensor key_states_3_cast = reshape(shape = var_114, x = transpose_58)[name = tensor("key_states_3_cast")]; + tensor var_116 = const()[name = tensor("op_116"), val = tensor([12, -1, 64])]; + tensor transpose_57 = transpose(perm = var_101_perm_0, x = var_100_cast)[name = tensor("transpose_57")]; + tensor value_states_3_cast = reshape(shape = var_116, x = transpose_57)[name = tensor("value_states_3_cast")]; + tensor var_119_perm_0 = const()[name = tensor("op_119_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_119_perm_0, x = key_states_3_cast)[name = tensor("transpose_56")]; + tensor attn_weights_1_cast = matmul(transpose_x = attn_weights_1_transpose_x_0, transpose_y = attn_weights_1_transpose_y_0, x = query_states_1_cast, y = transpose_56)[name = tensor("attn_weights_1_cast")]; + tensor var_121 = const()[name = tensor("op_121"), val = tensor([1, 12, 77, 77])]; + tensor var_122_cast = reshape(shape = var_121, x = attn_weights_1_cast)[name = tensor("op_122_cast")]; + tensor causal_attention_mask_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77271296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77275840))), name = tensor("causal_attention_mask_to_fp16_palettized"), shape = tensor([1, 1, 77, 77])]; + tensor attn_weights_3_cast = add(x = var_122_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_3_cast")]; + tensor var_127 = const()[name = tensor("op_127"), val = tensor([12, 77, 77])]; + tensor input_5_cast = reshape(shape = var_127, x = attn_weights_3_cast)[name = tensor("input_5_cast")]; + tensor input_7_cast = softmax(axis = var_5, x = input_5_cast)[name = tensor("input_7_cast")]; + tensor attn_output_1_transpose_x_0 = const()[name = tensor("attn_output_1_transpose_x_0"), val = tensor(false)]; + tensor attn_output_1_transpose_y_0 = const()[name = tensor("attn_output_1_transpose_y_0"), val = tensor(false)]; + tensor attn_output_1_cast = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7_cast, y = value_states_3_cast)[name = tensor("attn_output_1_cast")]; + tensor var_132 = const()[name = tensor("op_132"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_3_cast = reshape(shape = var_132, x = attn_output_1_cast)[name = tensor("attn_output_3_cast")]; + tensor attn_output_5_perm_0 = const()[name = tensor("attn_output_5_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_135 = const()[name = tensor("op_135"), val = tensor([1, 77, 768])]; + tensor transpose_55 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast)[name = tensor("transpose_55")]; + tensor input_9_cast = reshape(shape = var_135, x = transpose_55)[name = tensor("input_9_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77276032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77718464))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77718656)))]; + tensor hidden_states_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized, x = input_9_cast)[name = tensor("hidden_states_3_cast")]; + tensor input_11_cast = add(x = input_3_cast, y = hidden_states_3_cast)[name = tensor("input_11_cast")]; + tensor input_13_axes_0 = const()[name = tensor("input_13_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77720256)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77721856)))]; + tensor input_13_cast = layer_norm(axes = input_13_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_11_cast)[name = tensor("input_13_cast")]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77723456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79492992))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79493184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79495552))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_15_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized, x = input_13_cast)[name = tensor("input_15_cast")]; + tensor var_150_to_fp16 = const()[name = tensor("op_150_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_151_cast = mul(x = input_15_cast, y = var_150_to_fp16)[name = tensor("op_151_cast")]; + tensor var_152_cast = sigmoid(x = var_151_cast)[name = tensor("op_152_cast")]; + tensor input_17_cast = mul(x = input_15_cast, y = var_152_cast)[name = tensor("input_17_cast")]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79495744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81265280))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81265472)))]; + tensor hidden_states_5_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized, x = input_17_cast)[name = tensor("hidden_states_5_cast")]; + tensor input_19_cast = add(x = input_11_cast, y = hidden_states_5_cast)[name = tensor("input_19_cast")]; + tensor hidden_states_7_axes_0 = const()[name = tensor("hidden_states_7_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81267072)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81268672)))]; + tensor hidden_states_7_cast = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_19_cast)[name = tensor("hidden_states_7_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81270272))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81712704))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81712896)))]; + tensor var_176_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("op_176_cast")]; + tensor var_177_to_fp16 = const()[name = tensor("op_177_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_11_cast = mul(x = var_176_cast, y = var_177_to_fp16)[name = tensor("tensor_11_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81714496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82156928))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82157120)))]; + tensor tensor_7_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("tensor_7_cast")]; + tensor var_182 = const()[name = tensor("op_182"), val = tensor([1, -1, 12, 64])]; + tensor var_183_cast = reshape(shape = var_182, x = tensor_7_cast)[name = tensor("op_183_cast")]; + tensor var_184_perm_0 = const()[name = tensor("op_184_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82158720))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82601152))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82601344)))]; + tensor tensor_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("tensor_9_cast")]; + tensor var_189 = const()[name = tensor("op_189"), val = tensor([1, -1, 12, 64])]; + tensor var_190_cast = reshape(shape = var_189, x = tensor_9_cast)[name = tensor("op_190_cast")]; + tensor var_191_perm_0 = const()[name = tensor("op_191_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_198 = const()[name = tensor("op_198"), val = tensor([1, 77, 12, 64])]; + tensor var_199_cast = reshape(shape = var_198, x = tensor_11_cast)[name = tensor("op_199_cast")]; + tensor var_200_perm_0 = const()[name = tensor("op_200_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_202 = const()[name = tensor("op_202"), val = tensor([12, -1, 64])]; + tensor transpose_54 = transpose(perm = var_200_perm_0, x = var_199_cast)[name = tensor("transpose_54")]; + tensor query_states_3_cast = reshape(shape = var_202, x = transpose_54)[name = tensor("query_states_3_cast")]; + tensor var_204 = const()[name = tensor("op_204"), val = tensor([12, -1, 64])]; + tensor transpose_53 = transpose(perm = var_184_perm_0, x = var_183_cast)[name = tensor("transpose_53")]; + tensor key_states_7_cast = reshape(shape = var_204, x = transpose_53)[name = tensor("key_states_7_cast")]; + tensor var_206 = const()[name = tensor("op_206"), val = tensor([12, -1, 64])]; + tensor transpose_52 = transpose(perm = var_191_perm_0, x = var_190_cast)[name = tensor("transpose_52")]; + tensor value_states_7_cast = reshape(shape = var_206, x = transpose_52)[name = tensor("value_states_7_cast")]; + tensor var_209_perm_0 = const()[name = tensor("op_209_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_209_perm_0, x = key_states_7_cast)[name = tensor("transpose_51")]; + tensor attn_weights_7_cast = matmul(transpose_x = attn_weights_7_transpose_x_0, transpose_y = attn_weights_7_transpose_y_0, x = query_states_3_cast, y = transpose_51)[name = tensor("attn_weights_7_cast")]; + tensor var_211 = const()[name = tensor("op_211"), val = tensor([1, 12, 77, 77])]; + tensor var_212_cast = reshape(shape = var_211, x = attn_weights_7_cast)[name = tensor("op_212_cast")]; + tensor attn_weights_9_cast = add(x = var_212_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_9_cast")]; + tensor var_217 = const()[name = tensor("op_217"), val = tensor([12, 77, 77])]; + tensor input_21_cast = reshape(shape = var_217, x = attn_weights_9_cast)[name = tensor("input_21_cast")]; + tensor input_23_cast = softmax(axis = var_5, x = input_21_cast)[name = tensor("input_23_cast")]; + tensor attn_output_7_transpose_x_0 = const()[name = tensor("attn_output_7_transpose_x_0"), val = tensor(false)]; + tensor attn_output_7_transpose_y_0 = const()[name = tensor("attn_output_7_transpose_y_0"), val = tensor(false)]; + tensor attn_output_7_cast = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast, y = value_states_7_cast)[name = tensor("attn_output_7_cast")]; + tensor var_222 = const()[name = tensor("op_222"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_9_cast = reshape(shape = var_222, x = attn_output_7_cast)[name = tensor("attn_output_9_cast")]; + tensor attn_output_11_perm_0 = const()[name = tensor("attn_output_11_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_225 = const()[name = tensor("op_225"), val = tensor([1, 77, 768])]; + tensor transpose_50 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast)[name = tensor("transpose_50")]; + tensor input_25_cast = reshape(shape = var_225, x = transpose_50)[name = tensor("input_25_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82602944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83045376))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83045568)))]; + tensor hidden_states_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized, x = input_25_cast)[name = tensor("hidden_states_9_cast")]; + tensor input_27_cast = add(x = input_19_cast, y = hidden_states_9_cast)[name = tensor("input_27_cast")]; + tensor input_29_axes_0 = const()[name = tensor("input_29_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83047168)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83048768)))]; + tensor input_29_cast = layer_norm(axes = input_29_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_27_cast)[name = tensor("input_29_cast")]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83050368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84819904))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84820096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84822464))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_31_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized, x = input_29_cast)[name = tensor("input_31_cast")]; + tensor var_240_to_fp16 = const()[name = tensor("op_240_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_241_cast = mul(x = input_31_cast, y = var_240_to_fp16)[name = tensor("op_241_cast")]; + tensor var_242_cast = sigmoid(x = var_241_cast)[name = tensor("op_242_cast")]; + tensor input_33_cast = mul(x = input_31_cast, y = var_242_cast)[name = tensor("input_33_cast")]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84822656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86592192))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86592384)))]; + tensor hidden_states_11_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized, x = input_33_cast)[name = tensor("hidden_states_11_cast")]; + tensor input_35_cast = add(x = input_27_cast, y = hidden_states_11_cast)[name = tensor("input_35_cast")]; + tensor hidden_states_13_axes_0 = const()[name = tensor("hidden_states_13_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86593984)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86595584)))]; + tensor hidden_states_13_cast = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_35_cast)[name = tensor("hidden_states_13_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86597184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87039616))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87039808)))]; + tensor var_266_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("op_266_cast")]; + tensor var_267_to_fp16 = const()[name = tensor("op_267_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_17_cast = mul(x = var_266_cast, y = var_267_to_fp16)[name = tensor("tensor_17_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87041408))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87483840))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87484032)))]; + tensor tensor_13_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("tensor_13_cast")]; + tensor var_272 = const()[name = tensor("op_272"), val = tensor([1, -1, 12, 64])]; + tensor var_273_cast = reshape(shape = var_272, x = tensor_13_cast)[name = tensor("op_273_cast")]; + tensor var_274_perm_0 = const()[name = tensor("op_274_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87485632))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87928064))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87928256)))]; + tensor tensor_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("tensor_15_cast")]; + tensor var_279 = const()[name = tensor("op_279"), val = tensor([1, -1, 12, 64])]; + tensor var_280_cast = reshape(shape = var_279, x = tensor_15_cast)[name = tensor("op_280_cast")]; + tensor var_281_perm_0 = const()[name = tensor("op_281_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_288 = const()[name = tensor("op_288"), val = tensor([1, 77, 12, 64])]; + tensor var_289_cast = reshape(shape = var_288, x = tensor_17_cast)[name = tensor("op_289_cast")]; + tensor var_290_perm_0 = const()[name = tensor("op_290_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_292 = const()[name = tensor("op_292"), val = tensor([12, -1, 64])]; + tensor transpose_49 = transpose(perm = var_290_perm_0, x = var_289_cast)[name = tensor("transpose_49")]; + tensor query_states_5_cast = reshape(shape = var_292, x = transpose_49)[name = tensor("query_states_5_cast")]; + tensor var_294 = const()[name = tensor("op_294"), val = tensor([12, -1, 64])]; + tensor transpose_48 = transpose(perm = var_274_perm_0, x = var_273_cast)[name = tensor("transpose_48")]; + tensor key_states_11_cast = reshape(shape = var_294, x = transpose_48)[name = tensor("key_states_11_cast")]; + tensor var_296 = const()[name = tensor("op_296"), val = tensor([12, -1, 64])]; + tensor transpose_47 = transpose(perm = var_281_perm_0, x = var_280_cast)[name = tensor("transpose_47")]; + tensor value_states_11_cast = reshape(shape = var_296, x = transpose_47)[name = tensor("value_states_11_cast")]; + tensor var_299_perm_0 = const()[name = tensor("op_299_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_299_perm_0, x = key_states_11_cast)[name = tensor("transpose_46")]; + tensor attn_weights_13_cast = matmul(transpose_x = attn_weights_13_transpose_x_0, transpose_y = attn_weights_13_transpose_y_0, x = query_states_5_cast, y = transpose_46)[name = tensor("attn_weights_13_cast")]; + tensor var_301 = const()[name = tensor("op_301"), val = tensor([1, 12, 77, 77])]; + tensor var_302_cast = reshape(shape = var_301, x = attn_weights_13_cast)[name = tensor("op_302_cast")]; + tensor attn_weights_15_cast = add(x = var_302_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_15_cast")]; + tensor var_307 = const()[name = tensor("op_307"), val = tensor([12, 77, 77])]; + tensor input_37_cast = reshape(shape = var_307, x = attn_weights_15_cast)[name = tensor("input_37_cast")]; + tensor input_39_cast = softmax(axis = var_5, x = input_37_cast)[name = tensor("input_39_cast")]; + tensor attn_output_13_transpose_x_0 = const()[name = tensor("attn_output_13_transpose_x_0"), val = tensor(false)]; + tensor attn_output_13_transpose_y_0 = const()[name = tensor("attn_output_13_transpose_y_0"), val = tensor(false)]; + tensor attn_output_13_cast = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39_cast, y = value_states_11_cast)[name = tensor("attn_output_13_cast")]; + tensor var_312 = const()[name = tensor("op_312"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_15_cast = reshape(shape = var_312, x = attn_output_13_cast)[name = tensor("attn_output_15_cast")]; + tensor attn_output_17_perm_0 = const()[name = tensor("attn_output_17_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_315 = const()[name = tensor("op_315"), val = tensor([1, 77, 768])]; + tensor transpose_45 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast)[name = tensor("transpose_45")]; + tensor input_41_cast = reshape(shape = var_315, x = transpose_45)[name = tensor("input_41_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87929856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88372288))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88372480)))]; + tensor hidden_states_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized, x = input_41_cast)[name = tensor("hidden_states_15_cast")]; + tensor input_43_cast = add(x = input_35_cast, y = hidden_states_15_cast)[name = tensor("input_43_cast")]; + tensor input_45_axes_0 = const()[name = tensor("input_45_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88374080)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88375680)))]; + tensor input_45_cast = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_43_cast)[name = tensor("input_45_cast")]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88377280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90146816))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90147008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90149376))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_47_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized, x = input_45_cast)[name = tensor("input_47_cast")]; + tensor var_330_to_fp16 = const()[name = tensor("op_330_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_331_cast = mul(x = input_47_cast, y = var_330_to_fp16)[name = tensor("op_331_cast")]; + tensor var_332_cast = sigmoid(x = var_331_cast)[name = tensor("op_332_cast")]; + tensor input_49_cast = mul(x = input_47_cast, y = var_332_cast)[name = tensor("input_49_cast")]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90149568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91919104))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91919296)))]; + tensor hidden_states_17_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized, x = input_49_cast)[name = tensor("hidden_states_17_cast")]; + tensor input_51_cast = add(x = input_43_cast, y = hidden_states_17_cast)[name = tensor("input_51_cast")]; + tensor hidden_states_19_axes_0 = const()[name = tensor("hidden_states_19_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91920896)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91922496)))]; + tensor hidden_states_19_cast = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_51_cast)[name = tensor("hidden_states_19_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91924096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92366528))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92366720)))]; + tensor var_356_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("op_356_cast")]; + tensor var_357_to_fp16 = const()[name = tensor("op_357_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_23_cast = mul(x = var_356_cast, y = var_357_to_fp16)[name = tensor("tensor_23_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92368320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92810752))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92810944)))]; + tensor tensor_19_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("tensor_19_cast")]; + tensor var_362 = const()[name = tensor("op_362"), val = tensor([1, -1, 12, 64])]; + tensor var_363_cast = reshape(shape = var_362, x = tensor_19_cast)[name = tensor("op_363_cast")]; + tensor var_364_perm_0 = const()[name = tensor("op_364_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92812544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93254976))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93255168)))]; + tensor tensor_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("tensor_21_cast")]; + tensor var_369 = const()[name = tensor("op_369"), val = tensor([1, -1, 12, 64])]; + tensor var_370_cast = reshape(shape = var_369, x = tensor_21_cast)[name = tensor("op_370_cast")]; + tensor var_371_perm_0 = const()[name = tensor("op_371_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_378 = const()[name = tensor("op_378"), val = tensor([1, 77, 12, 64])]; + tensor var_379_cast = reshape(shape = var_378, x = tensor_23_cast)[name = tensor("op_379_cast")]; + tensor var_380_perm_0 = const()[name = tensor("op_380_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_382 = const()[name = tensor("op_382"), val = tensor([12, -1, 64])]; + tensor transpose_44 = transpose(perm = var_380_perm_0, x = var_379_cast)[name = tensor("transpose_44")]; + tensor query_states_7_cast = reshape(shape = var_382, x = transpose_44)[name = tensor("query_states_7_cast")]; + tensor var_384 = const()[name = tensor("op_384"), val = tensor([12, -1, 64])]; + tensor transpose_43 = transpose(perm = var_364_perm_0, x = var_363_cast)[name = tensor("transpose_43")]; + tensor key_states_15_cast = reshape(shape = var_384, x = transpose_43)[name = tensor("key_states_15_cast")]; + tensor var_386 = const()[name = tensor("op_386"), val = tensor([12, -1, 64])]; + tensor transpose_42 = transpose(perm = var_371_perm_0, x = var_370_cast)[name = tensor("transpose_42")]; + tensor value_states_15_cast = reshape(shape = var_386, x = transpose_42)[name = tensor("value_states_15_cast")]; + tensor var_389_perm_0 = const()[name = tensor("op_389_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_389_perm_0, x = key_states_15_cast)[name = tensor("transpose_41")]; + tensor attn_weights_19_cast = matmul(transpose_x = attn_weights_19_transpose_x_0, transpose_y = attn_weights_19_transpose_y_0, x = query_states_7_cast, y = transpose_41)[name = tensor("attn_weights_19_cast")]; + tensor var_391 = const()[name = tensor("op_391"), val = tensor([1, 12, 77, 77])]; + tensor var_392_cast = reshape(shape = var_391, x = attn_weights_19_cast)[name = tensor("op_392_cast")]; + tensor attn_weights_21_cast = add(x = var_392_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_21_cast")]; + tensor var_397 = const()[name = tensor("op_397"), val = tensor([12, 77, 77])]; + tensor input_53_cast = reshape(shape = var_397, x = attn_weights_21_cast)[name = tensor("input_53_cast")]; + tensor input_55_cast = softmax(axis = var_5, x = input_53_cast)[name = tensor("input_55_cast")]; + tensor attn_output_19_transpose_x_0 = const()[name = tensor("attn_output_19_transpose_x_0"), val = tensor(false)]; + tensor attn_output_19_transpose_y_0 = const()[name = tensor("attn_output_19_transpose_y_0"), val = tensor(false)]; + tensor attn_output_19_cast = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55_cast, y = value_states_15_cast)[name = tensor("attn_output_19_cast")]; + tensor var_402 = const()[name = tensor("op_402"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_21_cast = reshape(shape = var_402, x = attn_output_19_cast)[name = tensor("attn_output_21_cast")]; + tensor attn_output_23_perm_0 = const()[name = tensor("attn_output_23_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_405 = const()[name = tensor("op_405"), val = tensor([1, 77, 768])]; + tensor transpose_40 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast)[name = tensor("transpose_40")]; + tensor input_57_cast = reshape(shape = var_405, x = transpose_40)[name = tensor("input_57_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93256768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93699200))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93699392)))]; + tensor hidden_states_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized, x = input_57_cast)[name = tensor("hidden_states_21_cast")]; + tensor input_59_cast = add(x = input_51_cast, y = hidden_states_21_cast)[name = tensor("input_59_cast")]; + tensor input_61_axes_0 = const()[name = tensor("input_61_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93700992)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93702592)))]; + tensor input_61_cast = layer_norm(axes = input_61_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_59_cast)[name = tensor("input_61_cast")]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93704192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95473728))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95473920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95476288))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_63_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized, x = input_61_cast)[name = tensor("input_63_cast")]; + tensor var_420_to_fp16 = const()[name = tensor("op_420_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_421_cast = mul(x = input_63_cast, y = var_420_to_fp16)[name = tensor("op_421_cast")]; + tensor var_422_cast = sigmoid(x = var_421_cast)[name = tensor("op_422_cast")]; + tensor input_65_cast = mul(x = input_63_cast, y = var_422_cast)[name = tensor("input_65_cast")]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95476480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97246016))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97246208)))]; + tensor hidden_states_23_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized, x = input_65_cast)[name = tensor("hidden_states_23_cast")]; + tensor input_67_cast = add(x = input_59_cast, y = hidden_states_23_cast)[name = tensor("input_67_cast")]; + tensor hidden_states_25_axes_0 = const()[name = tensor("hidden_states_25_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97247808)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97249408)))]; + tensor hidden_states_25_cast = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_67_cast)[name = tensor("hidden_states_25_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97251008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97693440))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97693632)))]; + tensor var_446_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("op_446_cast")]; + tensor var_447_to_fp16 = const()[name = tensor("op_447_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_29_cast = mul(x = var_446_cast, y = var_447_to_fp16)[name = tensor("tensor_29_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97695232))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98137664))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98137856)))]; + tensor tensor_25_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("tensor_25_cast")]; + tensor var_452 = const()[name = tensor("op_452"), val = tensor([1, -1, 12, 64])]; + tensor var_453_cast = reshape(shape = var_452, x = tensor_25_cast)[name = tensor("op_453_cast")]; + tensor var_454_perm_0 = const()[name = tensor("op_454_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98139456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98581888))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98582080)))]; + tensor tensor_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("tensor_27_cast")]; + tensor var_459 = const()[name = tensor("op_459"), val = tensor([1, -1, 12, 64])]; + tensor var_460_cast = reshape(shape = var_459, x = tensor_27_cast)[name = tensor("op_460_cast")]; + tensor var_461_perm_0 = const()[name = tensor("op_461_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_468 = const()[name = tensor("op_468"), val = tensor([1, 77, 12, 64])]; + tensor var_469_cast = reshape(shape = var_468, x = tensor_29_cast)[name = tensor("op_469_cast")]; + tensor var_470_perm_0 = const()[name = tensor("op_470_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_472 = const()[name = tensor("op_472"), val = tensor([12, -1, 64])]; + tensor transpose_39 = transpose(perm = var_470_perm_0, x = var_469_cast)[name = tensor("transpose_39")]; + tensor query_states_9_cast = reshape(shape = var_472, x = transpose_39)[name = tensor("query_states_9_cast")]; + tensor var_474 = const()[name = tensor("op_474"), val = tensor([12, -1, 64])]; + tensor transpose_38 = transpose(perm = var_454_perm_0, x = var_453_cast)[name = tensor("transpose_38")]; + tensor key_states_19_cast = reshape(shape = var_474, x = transpose_38)[name = tensor("key_states_19_cast")]; + tensor var_476 = const()[name = tensor("op_476"), val = tensor([12, -1, 64])]; + tensor transpose_37 = transpose(perm = var_461_perm_0, x = var_460_cast)[name = tensor("transpose_37")]; + tensor value_states_19_cast = reshape(shape = var_476, x = transpose_37)[name = tensor("value_states_19_cast")]; + tensor var_479_perm_0 = const()[name = tensor("op_479_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_479_perm_0, x = key_states_19_cast)[name = tensor("transpose_36")]; + tensor attn_weights_25_cast = matmul(transpose_x = attn_weights_25_transpose_x_0, transpose_y = attn_weights_25_transpose_y_0, x = query_states_9_cast, y = transpose_36)[name = tensor("attn_weights_25_cast")]; + tensor var_481 = const()[name = tensor("op_481"), val = tensor([1, 12, 77, 77])]; + tensor var_482_cast = reshape(shape = var_481, x = attn_weights_25_cast)[name = tensor("op_482_cast")]; + tensor attn_weights_27_cast = add(x = var_482_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_27_cast")]; + tensor var_487 = const()[name = tensor("op_487"), val = tensor([12, 77, 77])]; + tensor input_69_cast = reshape(shape = var_487, x = attn_weights_27_cast)[name = tensor("input_69_cast")]; + tensor input_71_cast = softmax(axis = var_5, x = input_69_cast)[name = tensor("input_71_cast")]; + tensor attn_output_25_transpose_x_0 = const()[name = tensor("attn_output_25_transpose_x_0"), val = tensor(false)]; + tensor attn_output_25_transpose_y_0 = const()[name = tensor("attn_output_25_transpose_y_0"), val = tensor(false)]; + tensor attn_output_25_cast = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71_cast, y = value_states_19_cast)[name = tensor("attn_output_25_cast")]; + tensor var_492 = const()[name = tensor("op_492"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_27_cast = reshape(shape = var_492, x = attn_output_25_cast)[name = tensor("attn_output_27_cast")]; + tensor attn_output_29_perm_0 = const()[name = tensor("attn_output_29_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_495 = const()[name = tensor("op_495"), val = tensor([1, 77, 768])]; + tensor transpose_35 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast)[name = tensor("transpose_35")]; + tensor input_73_cast = reshape(shape = var_495, x = transpose_35)[name = tensor("input_73_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98583680))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99026112))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99026304)))]; + tensor hidden_states_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized, x = input_73_cast)[name = tensor("hidden_states_27_cast")]; + tensor input_75_cast = add(x = input_67_cast, y = hidden_states_27_cast)[name = tensor("input_75_cast")]; + tensor input_77_axes_0 = const()[name = tensor("input_77_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99027904)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99029504)))]; + tensor input_77_cast = layer_norm(axes = input_77_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_75_cast)[name = tensor("input_77_cast")]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99031104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100800640))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100800832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100803200))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_79_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized, x = input_77_cast)[name = tensor("input_79_cast")]; + tensor var_510_to_fp16 = const()[name = tensor("op_510_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_511_cast = mul(x = input_79_cast, y = var_510_to_fp16)[name = tensor("op_511_cast")]; + tensor var_512_cast = sigmoid(x = var_511_cast)[name = tensor("op_512_cast")]; + tensor input_81_cast = mul(x = input_79_cast, y = var_512_cast)[name = tensor("input_81_cast")]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100803392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102572928))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102573120)))]; + tensor hidden_states_29_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized, x = input_81_cast)[name = tensor("hidden_states_29_cast")]; + tensor input_83_cast = add(x = input_75_cast, y = hidden_states_29_cast)[name = tensor("input_83_cast")]; + tensor hidden_states_31_axes_0 = const()[name = tensor("hidden_states_31_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102574720)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102576320)))]; + tensor hidden_states_31_cast = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_83_cast)[name = tensor("hidden_states_31_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102577920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103020352))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103020544)))]; + tensor var_536_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("op_536_cast")]; + tensor var_537_to_fp16 = const()[name = tensor("op_537_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_35_cast = mul(x = var_536_cast, y = var_537_to_fp16)[name = tensor("tensor_35_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103022144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103464576))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103464768)))]; + tensor tensor_31_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("tensor_31_cast")]; + tensor var_542 = const()[name = tensor("op_542"), val = tensor([1, -1, 12, 64])]; + tensor var_543_cast = reshape(shape = var_542, x = tensor_31_cast)[name = tensor("op_543_cast")]; + tensor var_544_perm_0 = const()[name = tensor("op_544_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103466368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103908800))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103908992)))]; + tensor tensor_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("tensor_33_cast")]; + tensor var_549 = const()[name = tensor("op_549"), val = tensor([1, -1, 12, 64])]; + tensor var_550_cast = reshape(shape = var_549, x = tensor_33_cast)[name = tensor("op_550_cast")]; + tensor var_551_perm_0 = const()[name = tensor("op_551_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_558 = const()[name = tensor("op_558"), val = tensor([1, 77, 12, 64])]; + tensor var_559_cast = reshape(shape = var_558, x = tensor_35_cast)[name = tensor("op_559_cast")]; + tensor var_560_perm_0 = const()[name = tensor("op_560_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_562 = const()[name = tensor("op_562"), val = tensor([12, -1, 64])]; + tensor transpose_34 = transpose(perm = var_560_perm_0, x = var_559_cast)[name = tensor("transpose_34")]; + tensor query_states_11_cast = reshape(shape = var_562, x = transpose_34)[name = tensor("query_states_11_cast")]; + tensor var_564 = const()[name = tensor("op_564"), val = tensor([12, -1, 64])]; + tensor transpose_33 = transpose(perm = var_544_perm_0, x = var_543_cast)[name = tensor("transpose_33")]; + tensor key_states_23_cast = reshape(shape = var_564, x = transpose_33)[name = tensor("key_states_23_cast")]; + tensor var_566 = const()[name = tensor("op_566"), val = tensor([12, -1, 64])]; + tensor transpose_32 = transpose(perm = var_551_perm_0, x = var_550_cast)[name = tensor("transpose_32")]; + tensor value_states_23_cast = reshape(shape = var_566, x = transpose_32)[name = tensor("value_states_23_cast")]; + tensor var_569_perm_0 = const()[name = tensor("op_569_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_569_perm_0, x = key_states_23_cast)[name = tensor("transpose_31")]; + tensor attn_weights_31_cast = matmul(transpose_x = attn_weights_31_transpose_x_0, transpose_y = attn_weights_31_transpose_y_0, x = query_states_11_cast, y = transpose_31)[name = tensor("attn_weights_31_cast")]; + tensor var_571 = const()[name = tensor("op_571"), val = tensor([1, 12, 77, 77])]; + tensor var_572_cast = reshape(shape = var_571, x = attn_weights_31_cast)[name = tensor("op_572_cast")]; + tensor attn_weights_33_cast = add(x = var_572_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_33_cast")]; + tensor var_577 = const()[name = tensor("op_577"), val = tensor([12, 77, 77])]; + tensor input_85_cast = reshape(shape = var_577, x = attn_weights_33_cast)[name = tensor("input_85_cast")]; + tensor input_87_cast = softmax(axis = var_5, x = input_85_cast)[name = tensor("input_87_cast")]; + tensor attn_output_31_transpose_x_0 = const()[name = tensor("attn_output_31_transpose_x_0"), val = tensor(false)]; + tensor attn_output_31_transpose_y_0 = const()[name = tensor("attn_output_31_transpose_y_0"), val = tensor(false)]; + tensor attn_output_31_cast = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87_cast, y = value_states_23_cast)[name = tensor("attn_output_31_cast")]; + tensor var_582 = const()[name = tensor("op_582"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_33_cast = reshape(shape = var_582, x = attn_output_31_cast)[name = tensor("attn_output_33_cast")]; + tensor attn_output_35_perm_0 = const()[name = tensor("attn_output_35_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_585 = const()[name = tensor("op_585"), val = tensor([1, 77, 768])]; + tensor transpose_30 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast)[name = tensor("transpose_30")]; + tensor input_89_cast = reshape(shape = var_585, x = transpose_30)[name = tensor("input_89_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103910592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104353024))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104353216)))]; + tensor hidden_states_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized, x = input_89_cast)[name = tensor("hidden_states_33_cast")]; + tensor input_91_cast = add(x = input_83_cast, y = hidden_states_33_cast)[name = tensor("input_91_cast")]; + tensor input_93_axes_0 = const()[name = tensor("input_93_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104354816)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104356416)))]; + tensor input_93_cast = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_91_cast)[name = tensor("input_93_cast")]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104358016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106127552))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106127744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106130112))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_95_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized, x = input_93_cast)[name = tensor("input_95_cast")]; + tensor var_600_to_fp16 = const()[name = tensor("op_600_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_601_cast = mul(x = input_95_cast, y = var_600_to_fp16)[name = tensor("op_601_cast")]; + tensor var_602_cast = sigmoid(x = var_601_cast)[name = tensor("op_602_cast")]; + tensor input_97_cast = mul(x = input_95_cast, y = var_602_cast)[name = tensor("input_97_cast")]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106130304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107899840))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107900032)))]; + tensor hidden_states_35_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized, x = input_97_cast)[name = tensor("hidden_states_35_cast")]; + tensor input_99_cast = add(x = input_91_cast, y = hidden_states_35_cast)[name = tensor("input_99_cast")]; + tensor hidden_states_37_axes_0 = const()[name = tensor("hidden_states_37_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107901632)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107903232)))]; + tensor hidden_states_37_cast = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_99_cast)[name = tensor("hidden_states_37_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107904832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108347264))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108347456)))]; + tensor var_626_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("op_626_cast")]; + tensor var_627_to_fp16 = const()[name = tensor("op_627_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_41_cast = mul(x = var_626_cast, y = var_627_to_fp16)[name = tensor("tensor_41_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108349056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108791488))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108791680)))]; + tensor tensor_37_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("tensor_37_cast")]; + tensor var_632 = const()[name = tensor("op_632"), val = tensor([1, -1, 12, 64])]; + tensor var_633_cast = reshape(shape = var_632, x = tensor_37_cast)[name = tensor("op_633_cast")]; + tensor var_634_perm_0 = const()[name = tensor("op_634_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108793280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109235712))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109235904)))]; + tensor tensor_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("tensor_39_cast")]; + tensor var_639 = const()[name = tensor("op_639"), val = tensor([1, -1, 12, 64])]; + tensor var_640_cast = reshape(shape = var_639, x = tensor_39_cast)[name = tensor("op_640_cast")]; + tensor var_641_perm_0 = const()[name = tensor("op_641_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_648 = const()[name = tensor("op_648"), val = tensor([1, 77, 12, 64])]; + tensor var_649_cast = reshape(shape = var_648, x = tensor_41_cast)[name = tensor("op_649_cast")]; + tensor var_650_perm_0 = const()[name = tensor("op_650_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_652 = const()[name = tensor("op_652"), val = tensor([12, -1, 64])]; + tensor transpose_29 = transpose(perm = var_650_perm_0, x = var_649_cast)[name = tensor("transpose_29")]; + tensor query_states_13_cast = reshape(shape = var_652, x = transpose_29)[name = tensor("query_states_13_cast")]; + tensor var_654 = const()[name = tensor("op_654"), val = tensor([12, -1, 64])]; + tensor transpose_28 = transpose(perm = var_634_perm_0, x = var_633_cast)[name = tensor("transpose_28")]; + tensor key_states_27_cast = reshape(shape = var_654, x = transpose_28)[name = tensor("key_states_27_cast")]; + tensor var_656 = const()[name = tensor("op_656"), val = tensor([12, -1, 64])]; + tensor transpose_27 = transpose(perm = var_641_perm_0, x = var_640_cast)[name = tensor("transpose_27")]; + tensor value_states_27_cast = reshape(shape = var_656, x = transpose_27)[name = tensor("value_states_27_cast")]; + tensor var_659_perm_0 = const()[name = tensor("op_659_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_659_perm_0, x = key_states_27_cast)[name = tensor("transpose_26")]; + tensor attn_weights_37_cast = matmul(transpose_x = attn_weights_37_transpose_x_0, transpose_y = attn_weights_37_transpose_y_0, x = query_states_13_cast, y = transpose_26)[name = tensor("attn_weights_37_cast")]; + tensor var_661 = const()[name = tensor("op_661"), val = tensor([1, 12, 77, 77])]; + tensor var_662_cast = reshape(shape = var_661, x = attn_weights_37_cast)[name = tensor("op_662_cast")]; + tensor attn_weights_39_cast = add(x = var_662_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_39_cast")]; + tensor var_667 = const()[name = tensor("op_667"), val = tensor([12, 77, 77])]; + tensor input_101_cast = reshape(shape = var_667, x = attn_weights_39_cast)[name = tensor("input_101_cast")]; + tensor input_103_cast = softmax(axis = var_5, x = input_101_cast)[name = tensor("input_103_cast")]; + tensor attn_output_37_transpose_x_0 = const()[name = tensor("attn_output_37_transpose_x_0"), val = tensor(false)]; + tensor attn_output_37_transpose_y_0 = const()[name = tensor("attn_output_37_transpose_y_0"), val = tensor(false)]; + tensor attn_output_37_cast = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103_cast, y = value_states_27_cast)[name = tensor("attn_output_37_cast")]; + tensor var_672 = const()[name = tensor("op_672"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_39_cast = reshape(shape = var_672, x = attn_output_37_cast)[name = tensor("attn_output_39_cast")]; + tensor attn_output_41_perm_0 = const()[name = tensor("attn_output_41_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_675 = const()[name = tensor("op_675"), val = tensor([1, 77, 768])]; + tensor transpose_25 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast)[name = tensor("transpose_25")]; + tensor input_105_cast = reshape(shape = var_675, x = transpose_25)[name = tensor("input_105_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109237504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109679936))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109680128)))]; + tensor hidden_states_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized, x = input_105_cast)[name = tensor("hidden_states_39_cast")]; + tensor input_107_cast = add(x = input_99_cast, y = hidden_states_39_cast)[name = tensor("input_107_cast")]; + tensor input_109_axes_0 = const()[name = tensor("input_109_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109681728)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109683328)))]; + tensor input_109_cast = layer_norm(axes = input_109_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_107_cast)[name = tensor("input_109_cast")]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109684928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111454464))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111454656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111457024))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_111_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized, x = input_109_cast)[name = tensor("input_111_cast")]; + tensor var_690_to_fp16 = const()[name = tensor("op_690_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_691_cast = mul(x = input_111_cast, y = var_690_to_fp16)[name = tensor("op_691_cast")]; + tensor var_692_cast = sigmoid(x = var_691_cast)[name = tensor("op_692_cast")]; + tensor input_113_cast = mul(x = input_111_cast, y = var_692_cast)[name = tensor("input_113_cast")]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111457216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113226752))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113226944)))]; + tensor hidden_states_41_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized, x = input_113_cast)[name = tensor("hidden_states_41_cast")]; + tensor input_115_cast = add(x = input_107_cast, y = hidden_states_41_cast)[name = tensor("input_115_cast")]; + tensor hidden_states_43_axes_0 = const()[name = tensor("hidden_states_43_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113228544)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113230144)))]; + tensor hidden_states_43_cast = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_115_cast)[name = tensor("hidden_states_43_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113231744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113674176))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113674368)))]; + tensor var_716_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("op_716_cast")]; + tensor var_717_to_fp16 = const()[name = tensor("op_717_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_47_cast = mul(x = var_716_cast, y = var_717_to_fp16)[name = tensor("tensor_47_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113675968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114118400))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114118592)))]; + tensor tensor_43_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("tensor_43_cast")]; + tensor var_722 = const()[name = tensor("op_722"), val = tensor([1, -1, 12, 64])]; + tensor var_723_cast = reshape(shape = var_722, x = tensor_43_cast)[name = tensor("op_723_cast")]; + tensor var_724_perm_0 = const()[name = tensor("op_724_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114120192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114562624))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114562816)))]; + tensor tensor_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("tensor_45_cast")]; + tensor var_729 = const()[name = tensor("op_729"), val = tensor([1, -1, 12, 64])]; + tensor var_730_cast = reshape(shape = var_729, x = tensor_45_cast)[name = tensor("op_730_cast")]; + tensor var_731_perm_0 = const()[name = tensor("op_731_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_738 = const()[name = tensor("op_738"), val = tensor([1, 77, 12, 64])]; + tensor var_739_cast = reshape(shape = var_738, x = tensor_47_cast)[name = tensor("op_739_cast")]; + tensor var_740_perm_0 = const()[name = tensor("op_740_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_742 = const()[name = tensor("op_742"), val = tensor([12, -1, 64])]; + tensor transpose_24 = transpose(perm = var_740_perm_0, x = var_739_cast)[name = tensor("transpose_24")]; + tensor query_states_15_cast = reshape(shape = var_742, x = transpose_24)[name = tensor("query_states_15_cast")]; + tensor var_744 = const()[name = tensor("op_744"), val = tensor([12, -1, 64])]; + tensor transpose_23 = transpose(perm = var_724_perm_0, x = var_723_cast)[name = tensor("transpose_23")]; + tensor key_states_31_cast = reshape(shape = var_744, x = transpose_23)[name = tensor("key_states_31_cast")]; + tensor var_746 = const()[name = tensor("op_746"), val = tensor([12, -1, 64])]; + tensor transpose_22 = transpose(perm = var_731_perm_0, x = var_730_cast)[name = tensor("transpose_22")]; + tensor value_states_31_cast = reshape(shape = var_746, x = transpose_22)[name = tensor("value_states_31_cast")]; + tensor var_749_perm_0 = const()[name = tensor("op_749_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_749_perm_0, x = key_states_31_cast)[name = tensor("transpose_21")]; + tensor attn_weights_43_cast = matmul(transpose_x = attn_weights_43_transpose_x_0, transpose_y = attn_weights_43_transpose_y_0, x = query_states_15_cast, y = transpose_21)[name = tensor("attn_weights_43_cast")]; + tensor var_751 = const()[name = tensor("op_751"), val = tensor([1, 12, 77, 77])]; + tensor var_752_cast = reshape(shape = var_751, x = attn_weights_43_cast)[name = tensor("op_752_cast")]; + tensor attn_weights_45_cast = add(x = var_752_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_45_cast")]; + tensor var_757 = const()[name = tensor("op_757"), val = tensor([12, 77, 77])]; + tensor input_117_cast = reshape(shape = var_757, x = attn_weights_45_cast)[name = tensor("input_117_cast")]; + tensor input_119_cast = softmax(axis = var_5, x = input_117_cast)[name = tensor("input_119_cast")]; + tensor attn_output_43_transpose_x_0 = const()[name = tensor("attn_output_43_transpose_x_0"), val = tensor(false)]; + tensor attn_output_43_transpose_y_0 = const()[name = tensor("attn_output_43_transpose_y_0"), val = tensor(false)]; + tensor attn_output_43_cast = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119_cast, y = value_states_31_cast)[name = tensor("attn_output_43_cast")]; + tensor var_762 = const()[name = tensor("op_762"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_45_cast = reshape(shape = var_762, x = attn_output_43_cast)[name = tensor("attn_output_45_cast")]; + tensor attn_output_47_perm_0 = const()[name = tensor("attn_output_47_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_765 = const()[name = tensor("op_765"), val = tensor([1, 77, 768])]; + tensor transpose_20 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast)[name = tensor("transpose_20")]; + tensor input_121_cast = reshape(shape = var_765, x = transpose_20)[name = tensor("input_121_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114564416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115006848))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115007040)))]; + tensor hidden_states_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized, x = input_121_cast)[name = tensor("hidden_states_45_cast")]; + tensor input_123_cast = add(x = input_115_cast, y = hidden_states_45_cast)[name = tensor("input_123_cast")]; + tensor input_125_axes_0 = const()[name = tensor("input_125_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115008640)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115010240)))]; + tensor input_125_cast = layer_norm(axes = input_125_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_123_cast)[name = tensor("input_125_cast")]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115011840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116781376))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116781568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116783936))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_127_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized, x = input_125_cast)[name = tensor("input_127_cast")]; + tensor var_780_to_fp16 = const()[name = tensor("op_780_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_781_cast = mul(x = input_127_cast, y = var_780_to_fp16)[name = tensor("op_781_cast")]; + tensor var_782_cast = sigmoid(x = var_781_cast)[name = tensor("op_782_cast")]; + tensor input_129_cast = mul(x = input_127_cast, y = var_782_cast)[name = tensor("input_129_cast")]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116784128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118553664))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118553856)))]; + tensor hidden_states_47_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized, x = input_129_cast)[name = tensor("hidden_states_47_cast")]; + tensor input_131_cast = add(x = input_123_cast, y = hidden_states_47_cast)[name = tensor("input_131_cast")]; + tensor hidden_states_49_axes_0 = const()[name = tensor("hidden_states_49_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118555456)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118557056)))]; + tensor hidden_states_49_cast = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_131_cast)[name = tensor("hidden_states_49_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118558656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119001088))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119001280)))]; + tensor var_806_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("op_806_cast")]; + tensor var_807_to_fp16 = const()[name = tensor("op_807_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_53_cast = mul(x = var_806_cast, y = var_807_to_fp16)[name = tensor("tensor_53_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119002880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119445312))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119445504)))]; + tensor tensor_49_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("tensor_49_cast")]; + tensor var_812 = const()[name = tensor("op_812"), val = tensor([1, -1, 12, 64])]; + tensor var_813_cast = reshape(shape = var_812, x = tensor_49_cast)[name = tensor("op_813_cast")]; + tensor var_814_perm_0 = const()[name = tensor("op_814_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119447104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119889536))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119889728)))]; + tensor tensor_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("tensor_51_cast")]; + tensor var_819 = const()[name = tensor("op_819"), val = tensor([1, -1, 12, 64])]; + tensor var_820_cast = reshape(shape = var_819, x = tensor_51_cast)[name = tensor("op_820_cast")]; + tensor var_821_perm_0 = const()[name = tensor("op_821_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_828 = const()[name = tensor("op_828"), val = tensor([1, 77, 12, 64])]; + tensor var_829_cast = reshape(shape = var_828, x = tensor_53_cast)[name = tensor("op_829_cast")]; + tensor var_830_perm_0 = const()[name = tensor("op_830_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_832 = const()[name = tensor("op_832"), val = tensor([12, -1, 64])]; + tensor transpose_19 = transpose(perm = var_830_perm_0, x = var_829_cast)[name = tensor("transpose_19")]; + tensor query_states_17_cast = reshape(shape = var_832, x = transpose_19)[name = tensor("query_states_17_cast")]; + tensor var_834 = const()[name = tensor("op_834"), val = tensor([12, -1, 64])]; + tensor transpose_18 = transpose(perm = var_814_perm_0, x = var_813_cast)[name = tensor("transpose_18")]; + tensor key_states_35_cast = reshape(shape = var_834, x = transpose_18)[name = tensor("key_states_35_cast")]; + tensor var_836 = const()[name = tensor("op_836"), val = tensor([12, -1, 64])]; + tensor transpose_17 = transpose(perm = var_821_perm_0, x = var_820_cast)[name = tensor("transpose_17")]; + tensor value_states_35_cast = reshape(shape = var_836, x = transpose_17)[name = tensor("value_states_35_cast")]; + tensor var_839_perm_0 = const()[name = tensor("op_839_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_839_perm_0, x = key_states_35_cast)[name = tensor("transpose_16")]; + tensor attn_weights_49_cast = matmul(transpose_x = attn_weights_49_transpose_x_0, transpose_y = attn_weights_49_transpose_y_0, x = query_states_17_cast, y = transpose_16)[name = tensor("attn_weights_49_cast")]; + tensor var_841 = const()[name = tensor("op_841"), val = tensor([1, 12, 77, 77])]; + tensor var_842_cast = reshape(shape = var_841, x = attn_weights_49_cast)[name = tensor("op_842_cast")]; + tensor attn_weights_51_cast = add(x = var_842_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_51_cast")]; + tensor var_847 = const()[name = tensor("op_847"), val = tensor([12, 77, 77])]; + tensor input_133_cast = reshape(shape = var_847, x = attn_weights_51_cast)[name = tensor("input_133_cast")]; + tensor input_135_cast = softmax(axis = var_5, x = input_133_cast)[name = tensor("input_135_cast")]; + tensor attn_output_49_transpose_x_0 = const()[name = tensor("attn_output_49_transpose_x_0"), val = tensor(false)]; + tensor attn_output_49_transpose_y_0 = const()[name = tensor("attn_output_49_transpose_y_0"), val = tensor(false)]; + tensor attn_output_49_cast = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast, y = value_states_35_cast)[name = tensor("attn_output_49_cast")]; + tensor var_852 = const()[name = tensor("op_852"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_51_cast = reshape(shape = var_852, x = attn_output_49_cast)[name = tensor("attn_output_51_cast")]; + tensor attn_output_53_perm_0 = const()[name = tensor("attn_output_53_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_855 = const()[name = tensor("op_855"), val = tensor([1, 77, 768])]; + tensor transpose_15 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast)[name = tensor("transpose_15")]; + tensor input_137_cast = reshape(shape = var_855, x = transpose_15)[name = tensor("input_137_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119891328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120333760))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120333952)))]; + tensor hidden_states_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized, x = input_137_cast)[name = tensor("hidden_states_51_cast")]; + tensor input_139_cast = add(x = input_131_cast, y = hidden_states_51_cast)[name = tensor("input_139_cast")]; + tensor input_141_axes_0 = const()[name = tensor("input_141_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120335552)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120337152)))]; + tensor input_141_cast = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_139_cast)[name = tensor("input_141_cast")]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120338752))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122108288))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122108480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122110848))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_143_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized, x = input_141_cast)[name = tensor("input_143_cast")]; + tensor var_870_to_fp16 = const()[name = tensor("op_870_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_871_cast = mul(x = input_143_cast, y = var_870_to_fp16)[name = tensor("op_871_cast")]; + tensor var_872_cast = sigmoid(x = var_871_cast)[name = tensor("op_872_cast")]; + tensor input_145_cast = mul(x = input_143_cast, y = var_872_cast)[name = tensor("input_145_cast")]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122111040))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123880576))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123880768)))]; + tensor hidden_states_53_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized, x = input_145_cast)[name = tensor("hidden_states_53_cast")]; + tensor input_147_cast = add(x = input_139_cast, y = hidden_states_53_cast)[name = tensor("input_147_cast")]; + tensor hidden_states_55_axes_0 = const()[name = tensor("hidden_states_55_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123882368)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123883968)))]; + tensor hidden_states_55_cast = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_147_cast)[name = tensor("hidden_states_55_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123885568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124328000))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124328192)))]; + tensor var_896_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("op_896_cast")]; + tensor var_897_to_fp16 = const()[name = tensor("op_897_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_59_cast = mul(x = var_896_cast, y = var_897_to_fp16)[name = tensor("tensor_59_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124329792))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124772224))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124772416)))]; + tensor tensor_55_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("tensor_55_cast")]; + tensor var_902 = const()[name = tensor("op_902"), val = tensor([1, -1, 12, 64])]; + tensor var_903_cast = reshape(shape = var_902, x = tensor_55_cast)[name = tensor("op_903_cast")]; + tensor var_904_perm_0 = const()[name = tensor("op_904_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124774016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125216448))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125216640)))]; + tensor tensor_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("tensor_57_cast")]; + tensor var_909 = const()[name = tensor("op_909"), val = tensor([1, -1, 12, 64])]; + tensor var_910_cast = reshape(shape = var_909, x = tensor_57_cast)[name = tensor("op_910_cast")]; + tensor var_911_perm_0 = const()[name = tensor("op_911_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_918 = const()[name = tensor("op_918"), val = tensor([1, 77, 12, 64])]; + tensor var_919_cast = reshape(shape = var_918, x = tensor_59_cast)[name = tensor("op_919_cast")]; + tensor var_920_perm_0 = const()[name = tensor("op_920_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_922 = const()[name = tensor("op_922"), val = tensor([12, -1, 64])]; + tensor transpose_14 = transpose(perm = var_920_perm_0, x = var_919_cast)[name = tensor("transpose_14")]; + tensor query_states_19_cast = reshape(shape = var_922, x = transpose_14)[name = tensor("query_states_19_cast")]; + tensor var_924 = const()[name = tensor("op_924"), val = tensor([12, -1, 64])]; + tensor transpose_13 = transpose(perm = var_904_perm_0, x = var_903_cast)[name = tensor("transpose_13")]; + tensor key_states_39_cast = reshape(shape = var_924, x = transpose_13)[name = tensor("key_states_39_cast")]; + tensor var_926 = const()[name = tensor("op_926"), val = tensor([12, -1, 64])]; + tensor transpose_12 = transpose(perm = var_911_perm_0, x = var_910_cast)[name = tensor("transpose_12")]; + tensor value_states_39_cast = reshape(shape = var_926, x = transpose_12)[name = tensor("value_states_39_cast")]; + tensor var_929_perm_0 = const()[name = tensor("op_929_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_929_perm_0, x = key_states_39_cast)[name = tensor("transpose_11")]; + tensor attn_weights_55_cast = matmul(transpose_x = attn_weights_55_transpose_x_0, transpose_y = attn_weights_55_transpose_y_0, x = query_states_19_cast, y = transpose_11)[name = tensor("attn_weights_55_cast")]; + tensor var_931 = const()[name = tensor("op_931"), val = tensor([1, 12, 77, 77])]; + tensor var_932_cast = reshape(shape = var_931, x = attn_weights_55_cast)[name = tensor("op_932_cast")]; + tensor attn_weights_57_cast = add(x = var_932_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_57_cast")]; + tensor var_937 = const()[name = tensor("op_937"), val = tensor([12, 77, 77])]; + tensor input_149_cast = reshape(shape = var_937, x = attn_weights_57_cast)[name = tensor("input_149_cast")]; + tensor input_151_cast = softmax(axis = var_5, x = input_149_cast)[name = tensor("input_151_cast")]; + tensor attn_output_55_transpose_x_0 = const()[name = tensor("attn_output_55_transpose_x_0"), val = tensor(false)]; + tensor attn_output_55_transpose_y_0 = const()[name = tensor("attn_output_55_transpose_y_0"), val = tensor(false)]; + tensor attn_output_55_cast = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151_cast, y = value_states_39_cast)[name = tensor("attn_output_55_cast")]; + tensor var_942 = const()[name = tensor("op_942"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_57_cast = reshape(shape = var_942, x = attn_output_55_cast)[name = tensor("attn_output_57_cast")]; + tensor attn_output_59_perm_0 = const()[name = tensor("attn_output_59_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_945 = const()[name = tensor("op_945"), val = tensor([1, 77, 768])]; + tensor transpose_10 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast)[name = tensor("transpose_10")]; + tensor input_153_cast = reshape(shape = var_945, x = transpose_10)[name = tensor("input_153_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125218240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125660672))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125660864)))]; + tensor hidden_states_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized, x = input_153_cast)[name = tensor("hidden_states_57_cast")]; + tensor input_155_cast = add(x = input_147_cast, y = hidden_states_57_cast)[name = tensor("input_155_cast")]; + tensor input_157_axes_0 = const()[name = tensor("input_157_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125662464)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125664064)))]; + tensor input_157_cast = layer_norm(axes = input_157_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_155_cast)[name = tensor("input_157_cast")]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125665664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127435200))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127435392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127437760))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_159_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized, x = input_157_cast)[name = tensor("input_159_cast")]; + tensor var_960_to_fp16 = const()[name = tensor("op_960_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_961_cast = mul(x = input_159_cast, y = var_960_to_fp16)[name = tensor("op_961_cast")]; + tensor var_962_cast = sigmoid(x = var_961_cast)[name = tensor("op_962_cast")]; + tensor input_161_cast = mul(x = input_159_cast, y = var_962_cast)[name = tensor("input_161_cast")]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127437952))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129207488))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129207680)))]; + tensor hidden_states_59_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized, x = input_161_cast)[name = tensor("hidden_states_59_cast")]; + tensor input_163_cast = add(x = input_155_cast, y = hidden_states_59_cast)[name = tensor("input_163_cast")]; + tensor hidden_states_61_axes_0 = const()[name = tensor("hidden_states_61_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129209280)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129210880)))]; + tensor hidden_states_61_cast = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_163_cast)[name = tensor("hidden_states_61_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129212480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129654912))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129655104)))]; + tensor var_986_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("op_986_cast")]; + tensor var_987_to_fp16 = const()[name = tensor("op_987_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_65_cast = mul(x = var_986_cast, y = var_987_to_fp16)[name = tensor("tensor_65_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129656704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130099136))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130099328)))]; + tensor tensor_61_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("tensor_61_cast")]; + tensor var_992 = const()[name = tensor("op_992"), val = tensor([1, -1, 12, 64])]; + tensor var_993_cast = reshape(shape = var_992, x = tensor_61_cast)[name = tensor("op_993_cast")]; + tensor var_994_perm_0 = const()[name = tensor("op_994_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130100928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130543360))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130543552)))]; + tensor tensor_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("tensor_63_cast")]; + tensor var_999 = const()[name = tensor("op_999"), val = tensor([1, -1, 12, 64])]; + tensor var_1000_cast = reshape(shape = var_999, x = tensor_63_cast)[name = tensor("op_1000_cast")]; + tensor var_1001_perm_0 = const()[name = tensor("op_1001_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1008 = const()[name = tensor("op_1008"), val = tensor([1, 77, 12, 64])]; + tensor var_1009_cast = reshape(shape = var_1008, x = tensor_65_cast)[name = tensor("op_1009_cast")]; + tensor var_1010_perm_0 = const()[name = tensor("op_1010_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1012 = const()[name = tensor("op_1012"), val = tensor([12, -1, 64])]; + tensor transpose_9 = transpose(perm = var_1010_perm_0, x = var_1009_cast)[name = tensor("transpose_9")]; + tensor query_states_21_cast = reshape(shape = var_1012, x = transpose_9)[name = tensor("query_states_21_cast")]; + tensor var_1014 = const()[name = tensor("op_1014"), val = tensor([12, -1, 64])]; + tensor transpose_8 = transpose(perm = var_994_perm_0, x = var_993_cast)[name = tensor("transpose_8")]; + tensor key_states_43_cast = reshape(shape = var_1014, x = transpose_8)[name = tensor("key_states_43_cast")]; + tensor var_1016 = const()[name = tensor("op_1016"), val = tensor([12, -1, 64])]; + tensor transpose_7 = transpose(perm = var_1001_perm_0, x = var_1000_cast)[name = tensor("transpose_7")]; + tensor value_states_43_cast = reshape(shape = var_1016, x = transpose_7)[name = tensor("value_states_43_cast")]; + tensor var_1019_perm_0 = const()[name = tensor("op_1019_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_1019_perm_0, x = key_states_43_cast)[name = tensor("transpose_6")]; + tensor attn_weights_61_cast = matmul(transpose_x = attn_weights_61_transpose_x_0, transpose_y = attn_weights_61_transpose_y_0, x = query_states_21_cast, y = transpose_6)[name = tensor("attn_weights_61_cast")]; + tensor var_1021 = const()[name = tensor("op_1021"), val = tensor([1, 12, 77, 77])]; + tensor var_1022_cast = reshape(shape = var_1021, x = attn_weights_61_cast)[name = tensor("op_1022_cast")]; + tensor attn_weights_63_cast = add(x = var_1022_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_63_cast")]; + tensor var_1027 = const()[name = tensor("op_1027"), val = tensor([12, 77, 77])]; + tensor input_165_cast = reshape(shape = var_1027, x = attn_weights_63_cast)[name = tensor("input_165_cast")]; + tensor input_167_cast = softmax(axis = var_5, x = input_165_cast)[name = tensor("input_167_cast")]; + tensor attn_output_61_transpose_x_0 = const()[name = tensor("attn_output_61_transpose_x_0"), val = tensor(false)]; + tensor attn_output_61_transpose_y_0 = const()[name = tensor("attn_output_61_transpose_y_0"), val = tensor(false)]; + tensor attn_output_61_cast = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167_cast, y = value_states_43_cast)[name = tensor("attn_output_61_cast")]; + tensor var_1032 = const()[name = tensor("op_1032"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_63_cast = reshape(shape = var_1032, x = attn_output_61_cast)[name = tensor("attn_output_63_cast")]; + tensor attn_output_65_perm_0 = const()[name = tensor("attn_output_65_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1035 = const()[name = tensor("op_1035"), val = tensor([1, 77, 768])]; + tensor transpose_5 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast)[name = tensor("transpose_5")]; + tensor input_169_cast = reshape(shape = var_1035, x = transpose_5)[name = tensor("input_169_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130545152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130987584))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130987776)))]; + tensor hidden_states_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized, x = input_169_cast)[name = tensor("hidden_states_63_cast")]; + tensor input_171_cast = add(x = input_163_cast, y = hidden_states_63_cast)[name = tensor("input_171_cast")]; + tensor input_173_axes_0 = const()[name = tensor("input_173_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130989376)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130990976)))]; + tensor input_173_cast = layer_norm(axes = input_173_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_171_cast)[name = tensor("input_173_cast")]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130992576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132762112))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132762304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132764672))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_175_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized, x = input_173_cast)[name = tensor("input_175_cast")]; + tensor var_1050_to_fp16 = const()[name = tensor("op_1050_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_1051_cast = mul(x = input_175_cast, y = var_1050_to_fp16)[name = tensor("op_1051_cast")]; + tensor var_1052_cast = sigmoid(x = var_1051_cast)[name = tensor("op_1052_cast")]; + tensor input_177_cast = mul(x = input_175_cast, y = var_1052_cast)[name = tensor("input_177_cast")]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132764864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134534400))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134534592)))]; + tensor hidden_states_65_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized, x = input_177_cast)[name = tensor("hidden_states_65_cast")]; + tensor input_179_cast = add(x = input_171_cast, y = hidden_states_65_cast)[name = tensor("input_179_cast")]; + tensor hidden_states_67_axes_0 = const()[name = tensor("hidden_states_67_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134536192)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134537792)))]; + tensor hidden_states_67_cast = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_179_cast)[name = tensor("hidden_states_67_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134539392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134981824))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134982016)))]; + tensor var_1076_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("op_1076_cast")]; + tensor var_1077_to_fp16 = const()[name = tensor("op_1077_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_cast = mul(x = var_1076_cast, y = var_1077_to_fp16)[name = tensor("tensor_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134983616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135426048))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135426240)))]; + tensor tensor_67_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("tensor_67_cast")]; + tensor var_1082 = const()[name = tensor("op_1082"), val = tensor([1, -1, 12, 64])]; + tensor var_1083_cast = reshape(shape = var_1082, x = tensor_67_cast)[name = tensor("op_1083_cast")]; + tensor var_1084_perm_0 = const()[name = tensor("op_1084_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135427840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135870272))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135870464)))]; + tensor tensor_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("tensor_69_cast")]; + tensor var_1089 = const()[name = tensor("op_1089"), val = tensor([1, -1, 12, 64])]; + tensor var_1090_cast = reshape(shape = var_1089, x = tensor_69_cast)[name = tensor("op_1090_cast")]; + tensor var_1091_perm_0 = const()[name = tensor("op_1091_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1098 = const()[name = tensor("op_1098"), val = tensor([1, 77, 12, 64])]; + tensor var_1099_cast = reshape(shape = var_1098, x = tensor_cast)[name = tensor("op_1099_cast")]; + tensor var_1100_perm_0 = const()[name = tensor("op_1100_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1102 = const()[name = tensor("op_1102"), val = tensor([12, -1, 64])]; + tensor transpose_4 = transpose(perm = var_1100_perm_0, x = var_1099_cast)[name = tensor("transpose_4")]; + tensor query_states_cast = reshape(shape = var_1102, x = transpose_4)[name = tensor("query_states_cast")]; + tensor var_1104 = const()[name = tensor("op_1104"), val = tensor([12, -1, 64])]; + tensor transpose_3 = transpose(perm = var_1084_perm_0, x = var_1083_cast)[name = tensor("transpose_3")]; + tensor key_states_cast = reshape(shape = var_1104, x = transpose_3)[name = tensor("key_states_cast")]; + tensor var_1106 = const()[name = tensor("op_1106"), val = tensor([12, -1, 64])]; + tensor transpose_2 = transpose(perm = var_1091_perm_0, x = var_1090_cast)[name = tensor("transpose_2")]; + tensor value_states_cast = reshape(shape = var_1106, x = transpose_2)[name = tensor("value_states_cast")]; + tensor var_1109_perm_0 = const()[name = tensor("op_1109_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_1109_perm_0, x = key_states_cast)[name = tensor("transpose_1")]; + tensor attn_weights_67_cast = matmul(transpose_x = attn_weights_67_transpose_x_0, transpose_y = attn_weights_67_transpose_y_0, x = query_states_cast, y = transpose_1)[name = tensor("attn_weights_67_cast")]; + tensor var_1111 = const()[name = tensor("op_1111"), val = tensor([1, 12, 77, 77])]; + tensor var_1112_cast = reshape(shape = var_1111, x = attn_weights_67_cast)[name = tensor("op_1112_cast")]; + tensor attn_weights_69_cast = add(x = var_1112_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_69_cast")]; + tensor var_1117 = const()[name = tensor("op_1117"), val = tensor([12, 77, 77])]; + tensor input_181_cast = reshape(shape = var_1117, x = attn_weights_69_cast)[name = tensor("input_181_cast")]; + tensor input_183_cast = softmax(axis = var_5, x = input_181_cast)[name = tensor("input_183_cast")]; + tensor attn_output_67_transpose_x_0 = const()[name = tensor("attn_output_67_transpose_x_0"), val = tensor(false)]; + tensor attn_output_67_transpose_y_0 = const()[name = tensor("attn_output_67_transpose_y_0"), val = tensor(false)]; + tensor attn_output_67_cast = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183_cast, y = value_states_cast)[name = tensor("attn_output_67_cast")]; + tensor var_1122 = const()[name = tensor("op_1122"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_69_cast = reshape(shape = var_1122, x = attn_output_67_cast)[name = tensor("attn_output_69_cast")]; + tensor attn_output_perm_0 = const()[name = tensor("attn_output_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1125 = const()[name = tensor("op_1125"), val = tensor([1, 77, 768])]; + tensor transpose_0 = transpose(perm = attn_output_perm_0, x = attn_output_69_cast)[name = tensor("transpose_0")]; + tensor input_185_cast = reshape(shape = var_1125, x = transpose_0)[name = tensor("input_185_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135872064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136314496))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136314688)))]; + tensor hidden_states_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized, x = input_185_cast)[name = tensor("hidden_states_69_cast")]; + tensor input_187_cast = add(x = input_179_cast, y = hidden_states_69_cast)[name = tensor("input_187_cast")]; + tensor input_189_axes_0 = const()[name = tensor("input_189_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136316288)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136317888)))]; + tensor input_189_cast = layer_norm(axes = input_189_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_187_cast)[name = tensor("input_189_cast")]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136319488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138089024))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138089216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138091584))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_191_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized, x = input_189_cast)[name = tensor("input_191_cast")]; + tensor var_1140_to_fp16 = const()[name = tensor("op_1140_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_1141_cast = mul(x = input_191_cast, y = var_1140_to_fp16)[name = tensor("op_1141_cast")]; + tensor var_1142_cast = sigmoid(x = var_1141_cast)[name = tensor("op_1142_cast")]; + tensor input_193_cast = mul(x = input_191_cast, y = var_1142_cast)[name = tensor("input_193_cast")]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138091776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139861312))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139861504)))]; + tensor hidden_states_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized, x = input_193_cast)[name = tensor("hidden_states_cast")]; + tensor input_cast = add(x = input_187_cast, y = hidden_states_cast)[name = tensor("input_cast")]; + tensor last_hidden_state_axes_0 = const()[name = tensor("last_hidden_state_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139863104)))]; + tensor text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139864704)))]; + tensor last_hidden_state_cast = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_final_layer_norm_weight_to_fp16, x = input_cast)[name = tensor("last_hidden_state_cast")]; + tensor last_hidden_state_cast_to_fp32_dtype_0 = const()[name = tensor("last_hidden_state_cast_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor var_1153 = const()[name = tensor("op_1153"), val = tensor([0])]; + tensor var_1155 = reduce_argmax(axis = var_5, keep_dims = var_6, x = cast_2)[name = tensor("op_1155")]; + tensor stack_0_axis_0 = const()[name = tensor("stack_0_axis_0"), val = tensor(1)]; + tensor stack_0 = stack(axis = stack_0_axis_0, values = (var_1153, var_1155))[name = tensor("stack_0")]; + tensor var_1157_transpose_batch_dims_0 = const()[name = tensor("op_1157_transpose_batch_dims_0"), val = tensor(0)]; + tensor var_1157_transpose_cast = gather_nd(batch_dims = var_1157_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast)[name = tensor("op_1157_transpose_cast")]; + tensor var_1157_cast_to_fp32_dtype_0 = const()[name = tensor("op_1157_cast_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor last_hidden_state = cast(dtype = last_hidden_state_cast_to_fp32_dtype_0, x = last_hidden_state_cast)[name = tensor("cast_0")]; + tensor pooled_outputs = cast(dtype = var_1157_cast_to_fp32_dtype_0, x = var_1157_transpose_cast)[name = tensor("cast_1")]; + } -> (last_hidden_state, pooled_outputs); +} \ No newline at end of file