diff --git "a/split_einsum_v2/compiled/TextEncoder.mlmodelc/model.mil" "b/split_einsum_v2/compiled/TextEncoder.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/split_einsum_v2/compiled/TextEncoder.mlmodelc/model.mil" @@ -0,0 +1,896 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3304.5.2"}, {"coremlc-version", "3304.6.2"}})] +{ + 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([-0x1.854p-7, -0x1.17cp-10, 0x1.c1cp-8, 0x1.9acp-5]), 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(75905664)))]; + 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(75907264)))]; + tensor var_15_to_fp16 = const()[name = tensor("op_15_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_15_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(75908864))), lut = tensor([-0x1.13p-5, -0x1.3e8p-7, 0x1.42p-7, 0x1.134p-5]), 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(76056384)))]; + tensor linear_0_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("linear_0_cast")]; + tensor var_107_to_fp16 = const()[name = tensor("op_107_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_5_cast = mul(x = linear_0_cast, y = var_107_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(76057984))), lut = tensor([-0x1.0dcp-5, -0x1.3a8p-7, 0x1.334p-7, 0x1.0bcp-5]), 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(76205504)))]; + tensor linear_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("linear_1_cast")]; + tensor var_112 = const()[name = tensor("op_112"), val = tensor([1, -1, 12, 64])]; + tensor var_113_cast = reshape(shape = var_112, x = linear_1_cast)[name = tensor("op_113_cast")]; + tensor var_114_perm_0 = const()[name = tensor("op_114_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(76207104))), lut = tensor([-0x1.468p-6, -0x1.848p-8, 0x1.794p-8, 0x1.44cp-6]), 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(76354624)))]; + tensor linear_2_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("linear_2_cast")]; + tensor var_119 = const()[name = tensor("op_119"), val = tensor([1, -1, 12, 64])]; + tensor var_120_cast = reshape(shape = var_119, x = linear_2_cast)[name = tensor("op_120_cast")]; + tensor var_121_perm_0 = const()[name = tensor("op_121_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_128 = const()[name = tensor("op_128"), val = tensor([1, 77, 12, 64])]; + tensor var_129_cast = reshape(shape = var_128, x = tensor_5_cast)[name = tensor("op_129_cast")]; + tensor var_130_perm_0 = const()[name = tensor("op_130_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_132 = const()[name = tensor("op_132"), val = tensor([12, -1, 64])]; + tensor transpose_59 = transpose(perm = var_130_perm_0, x = var_129_cast)[name = tensor("transpose_59")]; + tensor query_states_1_cast = reshape(shape = var_132, x = transpose_59)[name = tensor("query_states_1_cast")]; + tensor var_134 = const()[name = tensor("op_134"), val = tensor([12, -1, 64])]; + tensor transpose_58 = transpose(perm = var_114_perm_0, x = var_113_cast)[name = tensor("transpose_58")]; + tensor key_states_3_cast = reshape(shape = var_134, x = transpose_58)[name = tensor("key_states_3_cast")]; + tensor var_136 = const()[name = tensor("op_136"), val = tensor([12, -1, 64])]; + tensor transpose_57 = transpose(perm = var_121_perm_0, x = var_120_cast)[name = tensor("transpose_57")]; + tensor value_states_3_cast = reshape(shape = var_136, x = transpose_57)[name = tensor("value_states_3_cast")]; + tensor var_139_perm_0 = const()[name = tensor("op_139_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_139_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_141 = const()[name = tensor("op_141"), val = tensor([1, 12, 77, 77])]; + tensor var_142_cast = reshape(shape = var_141, x = attn_weights_1_cast)[name = tensor("op_142_cast")]; + tensor op_56_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76356224))), lut = tensor([-0x0p+0, -0x1.388p+13, -0x1.388p+13, -0x1.388p+13]), name = tensor("op_56_to_fp16_palettized"), shape = tensor([1, 1, 77, 77])]; + tensor attn_weights_3_cast = add(x = var_142_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_3_cast")]; + tensor var_147 = const()[name = tensor("op_147"), val = tensor([12, 77, 77])]; + tensor input_5_cast = reshape(shape = var_147, 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_152 = const()[name = tensor("op_152"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_3_cast = reshape(shape = var_152, 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_155 = const()[name = tensor("op_155"), 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_155, 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(76357824))), lut = tensor([-0x1.3e4p-6, -0x1.7ap-8, 0x1.78cp-8, 0x1.3d4p-6]), 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(76505344)))]; + tensor linear_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("linear_3_cast")]; + tensor input_11_cast = add(x = input_3_cast, y = linear_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(76506944)))]; + 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(76508544)))]; + 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_15_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(76510144))), lut = tensor([-0x1.abcp-6, -0x1.06p-7, 0x1.dc8p-8, 0x1.9fp-6]), 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(77100032))), lut = tensor([-0x1.9a8p-3, -0x1.be8p+1, -0x1.cp-2, -0x1.44p-2]), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_4_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("linear_4_cast")]; + tensor var_170_to_fp16 = const()[name = tensor("op_170_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_171_cast = mul(x = linear_4_cast, y = var_170_to_fp16)[name = tensor("op_171_cast")]; + tensor var_172_cast = sigmoid(x = var_171_cast)[name = tensor("op_172_cast")]; + tensor input_17_cast = mul(x = linear_4_cast, y = var_172_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(77100864))), lut = tensor([-0x1.2fp-6, -0x1.668p-8, 0x1.6c4p-8, 0x1.30cp-6]), 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(77690752)))]; + tensor linear_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("linear_5_cast")]; + tensor input_19_cast = add(x = input_11_cast, y = linear_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(77692352)))]; + 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(77693952)))]; + 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_15_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(77695552))), lut = tensor([-0x1.118p-5, -0x1.3e8p-7, 0x1.394p-7, 0x1.104p-5]), 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(77843072)))]; + tensor linear_6_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("linear_6_cast")]; + tensor var_197_to_fp16 = const()[name = tensor("op_197_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_11_cast = mul(x = linear_6_cast, y = var_197_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(77844672))), lut = tensor([-0x1.19p-5, -0x1.3c4p-7, 0x1.3b4p-7, 0x1.178p-5]), 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(77992192)))]; + tensor linear_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("linear_7_cast")]; + tensor var_202 = const()[name = tensor("op_202"), val = tensor([1, -1, 12, 64])]; + tensor var_203_cast = reshape(shape = var_202, x = linear_7_cast)[name = tensor("op_203_cast")]; + tensor var_204_perm_0 = const()[name = tensor("op_204_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(77993792))), lut = tensor([-0x1.3fcp-6, -0x1.768p-8, 0x1.748p-8, 0x1.3ecp-6]), 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(78141312)))]; + tensor linear_8_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("linear_8_cast")]; + tensor var_209 = const()[name = tensor("op_209"), val = tensor([1, -1, 12, 64])]; + tensor var_210_cast = reshape(shape = var_209, x = linear_8_cast)[name = tensor("op_210_cast")]; + tensor var_211_perm_0 = const()[name = tensor("op_211_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_218 = const()[name = tensor("op_218"), val = tensor([1, 77, 12, 64])]; + tensor var_219_cast = reshape(shape = var_218, x = tensor_11_cast)[name = tensor("op_219_cast")]; + tensor var_220_perm_0 = const()[name = tensor("op_220_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_222 = const()[name = tensor("op_222"), val = tensor([12, -1, 64])]; + tensor transpose_54 = transpose(perm = var_220_perm_0, x = var_219_cast)[name = tensor("transpose_54")]; + tensor query_states_3_cast = reshape(shape = var_222, x = transpose_54)[name = tensor("query_states_3_cast")]; + tensor var_224 = const()[name = tensor("op_224"), val = tensor([12, -1, 64])]; + tensor transpose_53 = transpose(perm = var_204_perm_0, x = var_203_cast)[name = tensor("transpose_53")]; + tensor key_states_7_cast = reshape(shape = var_224, x = transpose_53)[name = tensor("key_states_7_cast")]; + tensor var_226 = const()[name = tensor("op_226"), val = tensor([12, -1, 64])]; + tensor transpose_52 = transpose(perm = var_211_perm_0, x = var_210_cast)[name = tensor("transpose_52")]; + tensor value_states_7_cast = reshape(shape = var_226, x = transpose_52)[name = tensor("value_states_7_cast")]; + tensor var_229_perm_0 = const()[name = tensor("op_229_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_229_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_231 = const()[name = tensor("op_231"), val = tensor([1, 12, 77, 77])]; + tensor var_232_cast = reshape(shape = var_231, x = attn_weights_7_cast)[name = tensor("op_232_cast")]; + tensor attn_weights_9_cast = add(x = var_232_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_9_cast")]; + tensor var_237 = const()[name = tensor("op_237"), val = tensor([12, 77, 77])]; + tensor input_21_cast = reshape(shape = var_237, 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_242 = const()[name = tensor("op_242"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_9_cast = reshape(shape = var_242, 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_245 = const()[name = tensor("op_245"), 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_245, 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(78142912))), lut = tensor([-0x1.3a8p-6, -0x1.7p-8, 0x1.74p-8, 0x1.3c4p-6]), 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(78290432)))]; + tensor linear_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("linear_9_cast")]; + tensor input_27_cast = add(x = input_19_cast, y = linear_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(78292032)))]; + 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(78293632)))]; + 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_15_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(78295232))), lut = tensor([-0x1.9a8p-6, -0x1.e2cp-8, 0x1.f6p-8, 0x1.9fcp-6]), 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(78885120))), lut = tensor([-0x1.c2cp-2, -0x1.868p-4, -0x1.5c4p-2, -0x1.fe8p-3]), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_10_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("linear_10_cast")]; + tensor var_260_to_fp16 = const()[name = tensor("op_260_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_261_cast = mul(x = linear_10_cast, y = var_260_to_fp16)[name = tensor("op_261_cast")]; + tensor var_262_cast = sigmoid(x = var_261_cast)[name = tensor("op_262_cast")]; + tensor input_33_cast = mul(x = linear_10_cast, y = var_262_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(78885952))), lut = tensor([-0x1.3e8p-6, -0x1.7b8p-8, 0x1.7b4p-8, 0x1.3e4p-6]), 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(79475840)))]; + tensor linear_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("linear_11_cast")]; + tensor input_35_cast = add(x = input_27_cast, y = linear_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(79477440)))]; + 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(79479040)))]; + 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_15_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(79480640))), lut = tensor([-0x1.ffcp-6, -0x1.2ap-7, 0x1.2b4p-7, 0x1.008p-5]), 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(79628160)))]; + tensor linear_12_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("linear_12_cast")]; + tensor var_287_to_fp16 = const()[name = tensor("op_287_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_17_cast = mul(x = linear_12_cast, y = var_287_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(79629760))), lut = tensor([-0x1.fep-6, -0x1.23cp-7, 0x1.298p-7, 0x1p-5]), 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(79777280)))]; + tensor linear_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("linear_13_cast")]; + tensor var_292 = const()[name = tensor("op_292"), val = tensor([1, -1, 12, 64])]; + tensor var_293_cast = reshape(shape = var_292, x = linear_13_cast)[name = tensor("op_293_cast")]; + tensor var_294_perm_0 = const()[name = tensor("op_294_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(79778880))), lut = tensor([-0x1.5b8p-6, -0x1.9ap-8, 0x1.a3p-8, 0x1.5e4p-6]), 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(79926400)))]; + tensor linear_14_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("linear_14_cast")]; + tensor var_299 = const()[name = tensor("op_299"), val = tensor([1, -1, 12, 64])]; + tensor var_300_cast = reshape(shape = var_299, x = linear_14_cast)[name = tensor("op_300_cast")]; + tensor var_301_perm_0 = const()[name = tensor("op_301_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_308 = const()[name = tensor("op_308"), val = tensor([1, 77, 12, 64])]; + tensor var_309_cast = reshape(shape = var_308, x = tensor_17_cast)[name = tensor("op_309_cast")]; + tensor var_310_perm_0 = const()[name = tensor("op_310_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_312 = const()[name = tensor("op_312"), val = tensor([12, -1, 64])]; + tensor transpose_49 = transpose(perm = var_310_perm_0, x = var_309_cast)[name = tensor("transpose_49")]; + tensor query_states_5_cast = reshape(shape = var_312, x = transpose_49)[name = tensor("query_states_5_cast")]; + tensor var_314 = const()[name = tensor("op_314"), val = tensor([12, -1, 64])]; + tensor transpose_48 = transpose(perm = var_294_perm_0, x = var_293_cast)[name = tensor("transpose_48")]; + tensor key_states_11_cast = reshape(shape = var_314, x = transpose_48)[name = tensor("key_states_11_cast")]; + tensor var_316 = const()[name = tensor("op_316"), val = tensor([12, -1, 64])]; + tensor transpose_47 = transpose(perm = var_301_perm_0, x = var_300_cast)[name = tensor("transpose_47")]; + tensor value_states_11_cast = reshape(shape = var_316, x = transpose_47)[name = tensor("value_states_11_cast")]; + tensor var_319_perm_0 = const()[name = tensor("op_319_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_319_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_321 = const()[name = tensor("op_321"), val = tensor([1, 12, 77, 77])]; + tensor var_322_cast = reshape(shape = var_321, x = attn_weights_13_cast)[name = tensor("op_322_cast")]; + tensor attn_weights_15_cast = add(x = var_322_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_15_cast")]; + tensor var_327 = const()[name = tensor("op_327"), val = tensor([12, 77, 77])]; + tensor input_37_cast = reshape(shape = var_327, 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_332 = const()[name = tensor("op_332"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_15_cast = reshape(shape = var_332, 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_335 = const()[name = tensor("op_335"), 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_335, 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(79928000))), lut = tensor([-0x1.54p-6, -0x1.964p-8, 0x1.94p-8, 0x1.538p-6]), 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(80075520)))]; + tensor linear_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("linear_15_cast")]; + tensor input_43_cast = add(x = input_35_cast, y = linear_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(80077120)))]; + 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(80078720)))]; + 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_15_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(80080320))), lut = tensor([-0x1.9c8p-6, -0x1.edp-8, 0x1.e88p-8, 0x1.9b4p-6]), 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(80670208))), lut = tensor([-0x1.254p-2, 0x1.27cp-6, -0x1.9bcp-2, -0x1.57cp-3]), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_16_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("linear_16_cast")]; + tensor var_350_to_fp16 = const()[name = tensor("op_350_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_351_cast = mul(x = linear_16_cast, y = var_350_to_fp16)[name = tensor("op_351_cast")]; + tensor var_352_cast = sigmoid(x = var_351_cast)[name = tensor("op_352_cast")]; + tensor input_49_cast = mul(x = linear_16_cast, y = var_352_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(80671040))), lut = tensor([-0x1.47cp-6, -0x1.85cp-8, 0x1.84cp-8, 0x1.47cp-6]), 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(81260928)))]; + tensor linear_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("linear_17_cast")]; + tensor input_51_cast = add(x = input_43_cast, y = linear_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(81262528)))]; + 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(81264128)))]; + 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_15_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(81265728))), lut = tensor([-0x1.03cp-5, -0x1.304p-7, 0x1.304p-7, 0x1.048p-5]), 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(81413248)))]; + tensor linear_18_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("linear_18_cast")]; + tensor var_377_to_fp16 = const()[name = tensor("op_377_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_23_cast = mul(x = linear_18_cast, y = var_377_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(81414848))), lut = tensor([-0x1.f6cp-6, -0x1.21p-7, 0x1.2a4p-7, 0x1.facp-6]), 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(81562368)))]; + tensor linear_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("linear_19_cast")]; + tensor var_382 = const()[name = tensor("op_382"), val = tensor([1, -1, 12, 64])]; + tensor var_383_cast = reshape(shape = var_382, x = linear_19_cast)[name = tensor("op_383_cast")]; + tensor var_384_perm_0 = const()[name = tensor("op_384_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(81563968))), lut = tensor([-0x1.5b8p-6, -0x1.9a8p-8, 0x1.9ep-8, 0x1.5c8p-6]), 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(81711488)))]; + tensor linear_20_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("linear_20_cast")]; + tensor var_389 = const()[name = tensor("op_389"), val = tensor([1, -1, 12, 64])]; + tensor var_390_cast = reshape(shape = var_389, x = linear_20_cast)[name = tensor("op_390_cast")]; + tensor var_391_perm_0 = const()[name = tensor("op_391_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_398 = const()[name = tensor("op_398"), val = tensor([1, 77, 12, 64])]; + tensor var_399_cast = reshape(shape = var_398, x = tensor_23_cast)[name = tensor("op_399_cast")]; + tensor var_400_perm_0 = const()[name = tensor("op_400_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_402 = const()[name = tensor("op_402"), val = tensor([12, -1, 64])]; + tensor transpose_44 = transpose(perm = var_400_perm_0, x = var_399_cast)[name = tensor("transpose_44")]; + tensor query_states_7_cast = reshape(shape = var_402, x = transpose_44)[name = tensor("query_states_7_cast")]; + tensor var_404 = const()[name = tensor("op_404"), val = tensor([12, -1, 64])]; + tensor transpose_43 = transpose(perm = var_384_perm_0, x = var_383_cast)[name = tensor("transpose_43")]; + tensor key_states_15_cast = reshape(shape = var_404, x = transpose_43)[name = tensor("key_states_15_cast")]; + tensor var_406 = const()[name = tensor("op_406"), val = tensor([12, -1, 64])]; + tensor transpose_42 = transpose(perm = var_391_perm_0, x = var_390_cast)[name = tensor("transpose_42")]; + tensor value_states_15_cast = reshape(shape = var_406, x = transpose_42)[name = tensor("value_states_15_cast")]; + tensor var_409_perm_0 = const()[name = tensor("op_409_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_409_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_411 = const()[name = tensor("op_411"), val = tensor([1, 12, 77, 77])]; + tensor var_412_cast = reshape(shape = var_411, x = attn_weights_19_cast)[name = tensor("op_412_cast")]; + tensor attn_weights_21_cast = add(x = var_412_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_21_cast")]; + tensor var_417 = const()[name = tensor("op_417"), val = tensor([12, 77, 77])]; + tensor input_53_cast = reshape(shape = var_417, 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_422 = const()[name = tensor("op_422"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_21_cast = reshape(shape = var_422, 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_425 = const()[name = tensor("op_425"), 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_425, 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(81713088))), lut = tensor([-0x1.53p-6, -0x1.8dcp-8, 0x1.9d4p-8, 0x1.55cp-6]), 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(81860608)))]; + tensor linear_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("linear_21_cast")]; + tensor input_59_cast = add(x = input_51_cast, y = linear_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(81862208)))]; + 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(81863808)))]; + 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_15_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(81865408))), lut = tensor([-0x1.9e8p-6, -0x1.f14p-8, 0x1.df4p-8, 0x1.998p-6]), 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(82455296))), lut = tensor([-0x1.988p-2, -0x1.8ap-3, 0x1.64cp-7, -0x1.3ecp-2]), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_22_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("linear_22_cast")]; + tensor var_440_to_fp16 = const()[name = tensor("op_440_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_441_cast = mul(x = linear_22_cast, y = var_440_to_fp16)[name = tensor("op_441_cast")]; + tensor var_442_cast = sigmoid(x = var_441_cast)[name = tensor("op_442_cast")]; + tensor input_65_cast = mul(x = linear_22_cast, y = var_442_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(82456128))), lut = tensor([-0x1.4fcp-6, -0x1.8acp-8, 0x1.9p-8, 0x1.51p-6]), 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(83046016)))]; + tensor linear_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("linear_23_cast")]; + tensor input_67_cast = add(x = input_59_cast, y = linear_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(83047616)))]; + 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(83049216)))]; + 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_15_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(83050816))), lut = tensor([-0x1.f1p-6, -0x1.224p-7, 0x1.2b8p-7, 0x1.f58p-6]), 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(83198336)))]; + tensor linear_24_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("linear_24_cast")]; + tensor var_467_to_fp16 = const()[name = tensor("op_467_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_29_cast = mul(x = linear_24_cast, y = var_467_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(83199936))), lut = tensor([-0x1.e94p-6, -0x1.224p-7, 0x1.1ap-7, 0x1.e3cp-6]), 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(83347456)))]; + tensor linear_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("linear_25_cast")]; + tensor var_472 = const()[name = tensor("op_472"), val = tensor([1, -1, 12, 64])]; + tensor var_473_cast = reshape(shape = var_472, x = linear_25_cast)[name = tensor("op_473_cast")]; + tensor var_474_perm_0 = const()[name = tensor("op_474_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(83349056))), lut = tensor([-0x1.664p-6, -0x1.acp-8, 0x1.a7cp-8, 0x1.64cp-6]), 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(83496576)))]; + tensor linear_26_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("linear_26_cast")]; + tensor var_479 = const()[name = tensor("op_479"), val = tensor([1, -1, 12, 64])]; + tensor var_480_cast = reshape(shape = var_479, x = linear_26_cast)[name = tensor("op_480_cast")]; + tensor var_481_perm_0 = const()[name = tensor("op_481_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_488 = const()[name = tensor("op_488"), val = tensor([1, 77, 12, 64])]; + tensor var_489_cast = reshape(shape = var_488, x = tensor_29_cast)[name = tensor("op_489_cast")]; + tensor var_490_perm_0 = const()[name = tensor("op_490_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_492 = const()[name = tensor("op_492"), val = tensor([12, -1, 64])]; + tensor transpose_39 = transpose(perm = var_490_perm_0, x = var_489_cast)[name = tensor("transpose_39")]; + tensor query_states_9_cast = reshape(shape = var_492, x = transpose_39)[name = tensor("query_states_9_cast")]; + tensor var_494 = const()[name = tensor("op_494"), val = tensor([12, -1, 64])]; + tensor transpose_38 = transpose(perm = var_474_perm_0, x = var_473_cast)[name = tensor("transpose_38")]; + tensor key_states_19_cast = reshape(shape = var_494, x = transpose_38)[name = tensor("key_states_19_cast")]; + tensor var_496 = const()[name = tensor("op_496"), val = tensor([12, -1, 64])]; + tensor transpose_37 = transpose(perm = var_481_perm_0, x = var_480_cast)[name = tensor("transpose_37")]; + tensor value_states_19_cast = reshape(shape = var_496, x = transpose_37)[name = tensor("value_states_19_cast")]; + tensor var_499_perm_0 = const()[name = tensor("op_499_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_499_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_501 = const()[name = tensor("op_501"), val = tensor([1, 12, 77, 77])]; + tensor var_502_cast = reshape(shape = var_501, x = attn_weights_25_cast)[name = tensor("op_502_cast")]; + tensor attn_weights_27_cast = add(x = var_502_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_27_cast")]; + tensor var_507 = const()[name = tensor("op_507"), val = tensor([12, 77, 77])]; + tensor input_69_cast = reshape(shape = var_507, 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_512 = const()[name = tensor("op_512"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_27_cast = reshape(shape = var_512, 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_515 = const()[name = tensor("op_515"), 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_515, 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(83498176))), lut = tensor([-0x1.5ep-6, -0x1.a34p-8, 0x1.a2cp-8, 0x1.5ep-6]), 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(83645696)))]; + tensor linear_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("linear_27_cast")]; + tensor input_75_cast = add(x = input_67_cast, y = linear_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(83647296)))]; + 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(83648896)))]; + 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_15_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(83650496))), lut = tensor([-0x1.9acp-6, -0x1.ea4p-8, 0x1.e0cp-8, 0x1.98p-6]), 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(84240384))), lut = tensor([-0x1.ed8p-3, -0x1.714p-2, 0x1.3d4p-3, -0x1.a14p-5]), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_28_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("linear_28_cast")]; + tensor var_530_to_fp16 = const()[name = tensor("op_530_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_531_cast = mul(x = linear_28_cast, y = var_530_to_fp16)[name = tensor("op_531_cast")]; + tensor var_532_cast = sigmoid(x = var_531_cast)[name = tensor("op_532_cast")]; + tensor input_81_cast = mul(x = linear_28_cast, y = var_532_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(84241216))), lut = tensor([-0x1.59p-6, -0x1.944p-8, 0x1.9d8p-8, 0x1.5b4p-6]), 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(84831104)))]; + tensor linear_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("linear_29_cast")]; + tensor input_83_cast = add(x = input_75_cast, y = linear_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(84832704)))]; + 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(84834304)))]; + 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_15_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(84835904))), lut = tensor([-0x1.e7p-6, -0x1.1ecp-7, 0x1.238p-7, 0x1.ea8p-6]), 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(84983424)))]; + tensor linear_30_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("linear_30_cast")]; + tensor var_557_to_fp16 = const()[name = tensor("op_557_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_35_cast = mul(x = linear_30_cast, y = var_557_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(84985024))), lut = tensor([-0x1.d98p-6, -0x1.14cp-7, 0x1.1fp-7, 0x1.de4p-6]), 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(85132544)))]; + tensor linear_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("linear_31_cast")]; + tensor var_562 = const()[name = tensor("op_562"), val = tensor([1, -1, 12, 64])]; + tensor var_563_cast = reshape(shape = var_562, x = linear_31_cast)[name = tensor("op_563_cast")]; + tensor var_564_perm_0 = const()[name = tensor("op_564_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(85134144))), lut = tensor([-0x1.678p-6, -0x1.ac4p-8, 0x1.aacp-8, 0x1.678p-6]), 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(85281664)))]; + tensor linear_32_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("linear_32_cast")]; + tensor var_569 = const()[name = tensor("op_569"), val = tensor([1, -1, 12, 64])]; + tensor var_570_cast = reshape(shape = var_569, x = linear_32_cast)[name = tensor("op_570_cast")]; + tensor var_571_perm_0 = const()[name = tensor("op_571_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_578 = const()[name = tensor("op_578"), val = tensor([1, 77, 12, 64])]; + tensor var_579_cast = reshape(shape = var_578, x = tensor_35_cast)[name = tensor("op_579_cast")]; + tensor var_580_perm_0 = const()[name = tensor("op_580_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_582 = const()[name = tensor("op_582"), val = tensor([12, -1, 64])]; + tensor transpose_34 = transpose(perm = var_580_perm_0, x = var_579_cast)[name = tensor("transpose_34")]; + tensor query_states_11_cast = reshape(shape = var_582, x = transpose_34)[name = tensor("query_states_11_cast")]; + tensor var_584 = const()[name = tensor("op_584"), val = tensor([12, -1, 64])]; + tensor transpose_33 = transpose(perm = var_564_perm_0, x = var_563_cast)[name = tensor("transpose_33")]; + tensor key_states_23_cast = reshape(shape = var_584, x = transpose_33)[name = tensor("key_states_23_cast")]; + tensor var_586 = const()[name = tensor("op_586"), val = tensor([12, -1, 64])]; + tensor transpose_32 = transpose(perm = var_571_perm_0, x = var_570_cast)[name = tensor("transpose_32")]; + tensor value_states_23_cast = reshape(shape = var_586, x = transpose_32)[name = tensor("value_states_23_cast")]; + tensor var_589_perm_0 = const()[name = tensor("op_589_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_589_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_591 = const()[name = tensor("op_591"), val = tensor([1, 12, 77, 77])]; + tensor var_592_cast = reshape(shape = var_591, x = attn_weights_31_cast)[name = tensor("op_592_cast")]; + tensor attn_weights_33_cast = add(x = var_592_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_33_cast")]; + tensor var_597 = const()[name = tensor("op_597"), val = tensor([12, 77, 77])]; + tensor input_85_cast = reshape(shape = var_597, 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_602 = const()[name = tensor("op_602"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_33_cast = reshape(shape = var_602, 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_605 = const()[name = tensor("op_605"), 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_605, 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(85283264))), lut = tensor([-0x1.638p-6, -0x1.ac8p-8, 0x1.a2p-8, 0x1.614p-6]), 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(85430784)))]; + tensor linear_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("linear_33_cast")]; + tensor input_91_cast = add(x = input_83_cast, y = linear_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(85432384)))]; + 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(85433984)))]; + 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_15_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(85435584))), lut = tensor([-0x1.97p-6, -0x1.db8p-8, 0x1.edcp-8, 0x1.9acp-6]), 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(86025472))), lut = tensor([-0x1.45cp-2, -0x1.344p-7, -0x1.afcp-3, -0x1.9acp-2]), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_34_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("linear_34_cast")]; + tensor var_620_to_fp16 = const()[name = tensor("op_620_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_621_cast = mul(x = linear_34_cast, y = var_620_to_fp16)[name = tensor("op_621_cast")]; + tensor var_622_cast = sigmoid(x = var_621_cast)[name = tensor("op_622_cast")]; + tensor input_97_cast = mul(x = linear_34_cast, y = var_622_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(86026304))), lut = tensor([-0x1.63cp-6, -0x1.9ecp-8, 0x1.aa8p-8, 0x1.65cp-6]), 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(86616192)))]; + tensor linear_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("linear_35_cast")]; + tensor input_99_cast = add(x = input_91_cast, y = linear_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(86617792)))]; + 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(86619392)))]; + 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_15_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(86620992))), lut = tensor([-0x1.de8p-6, -0x1.1d8p-7, 0x1.1a4p-7, 0x1.dd8p-6]), 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(86768512)))]; + tensor linear_36_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("linear_36_cast")]; + tensor var_647_to_fp16 = const()[name = tensor("op_647_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_41_cast = mul(x = linear_36_cast, y = var_647_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(86770112))), lut = tensor([-0x1.d1p-6, -0x1.168p-7, 0x1.13p-7, 0x1.d14p-6]), 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(86917632)))]; + tensor linear_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("linear_37_cast")]; + tensor var_652 = const()[name = tensor("op_652"), val = tensor([1, -1, 12, 64])]; + tensor var_653_cast = reshape(shape = var_652, x = linear_37_cast)[name = tensor("op_653_cast")]; + tensor var_654_perm_0 = const()[name = tensor("op_654_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(86919232))), lut = tensor([-0x1.6ccp-6, -0x1.b38p-8, 0x1.b38p-8, 0x1.6d8p-6]), 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(87066752)))]; + tensor linear_38_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("linear_38_cast")]; + tensor var_659 = const()[name = tensor("op_659"), val = tensor([1, -1, 12, 64])]; + tensor var_660_cast = reshape(shape = var_659, x = linear_38_cast)[name = tensor("op_660_cast")]; + tensor var_661_perm_0 = const()[name = tensor("op_661_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_668 = const()[name = tensor("op_668"), val = tensor([1, 77, 12, 64])]; + tensor var_669_cast = reshape(shape = var_668, x = tensor_41_cast)[name = tensor("op_669_cast")]; + tensor var_670_perm_0 = const()[name = tensor("op_670_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_672 = const()[name = tensor("op_672"), val = tensor([12, -1, 64])]; + tensor transpose_29 = transpose(perm = var_670_perm_0, x = var_669_cast)[name = tensor("transpose_29")]; + tensor query_states_13_cast = reshape(shape = var_672, x = transpose_29)[name = tensor("query_states_13_cast")]; + tensor var_674 = const()[name = tensor("op_674"), val = tensor([12, -1, 64])]; + tensor transpose_28 = transpose(perm = var_654_perm_0, x = var_653_cast)[name = tensor("transpose_28")]; + tensor key_states_27_cast = reshape(shape = var_674, x = transpose_28)[name = tensor("key_states_27_cast")]; + tensor var_676 = const()[name = tensor("op_676"), val = tensor([12, -1, 64])]; + tensor transpose_27 = transpose(perm = var_661_perm_0, x = var_660_cast)[name = tensor("transpose_27")]; + tensor value_states_27_cast = reshape(shape = var_676, x = transpose_27)[name = tensor("value_states_27_cast")]; + tensor var_679_perm_0 = const()[name = tensor("op_679_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_679_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_681 = const()[name = tensor("op_681"), val = tensor([1, 12, 77, 77])]; + tensor var_682_cast = reshape(shape = var_681, x = attn_weights_37_cast)[name = tensor("op_682_cast")]; + tensor attn_weights_39_cast = add(x = var_682_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_39_cast")]; + tensor var_687 = const()[name = tensor("op_687"), val = tensor([12, 77, 77])]; + tensor input_101_cast = reshape(shape = var_687, 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_692 = const()[name = tensor("op_692"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_39_cast = reshape(shape = var_692, 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_695 = const()[name = tensor("op_695"), 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_695, 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(87068352))), lut = tensor([-0x1.67cp-6, -0x1.bp-8, 0x1.ac4p-8, 0x1.668p-6]), 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(87215872)))]; + tensor linear_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("linear_39_cast")]; + tensor input_107_cast = add(x = input_99_cast, y = linear_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(87217472)))]; + 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(87219072)))]; + 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_15_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(87220672))), lut = tensor([-0x1.94cp-6, -0x1.dc8p-8, 0x1.e5p-8, 0x1.96p-6]), 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(87810560))), lut = tensor([-0x1.74cp-2, -0x1.a6p-4, -0x1.06p-2, 0x1.6c8p-4]), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_40_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("linear_40_cast")]; + tensor var_710_to_fp16 = const()[name = tensor("op_710_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_711_cast = mul(x = linear_40_cast, y = var_710_to_fp16)[name = tensor("op_711_cast")]; + tensor var_712_cast = sigmoid(x = var_711_cast)[name = tensor("op_712_cast")]; + tensor input_113_cast = mul(x = linear_40_cast, y = var_712_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(87811392))), lut = tensor([-0x1.7ap-6, -0x1.bd8p-8, 0x1.bf4p-8, 0x1.7a8p-6]), 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(88401280)))]; + tensor linear_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("linear_41_cast")]; + tensor input_115_cast = add(x = input_107_cast, y = linear_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(88402880)))]; + 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(88404480)))]; + 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_15_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(88406080))), lut = tensor([-0x1.d9p-6, -0x1.198p-7, 0x1.16cp-7, 0x1.d8p-6]), 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(88553600)))]; + tensor linear_42_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("linear_42_cast")]; + tensor var_737_to_fp16 = const()[name = tensor("op_737_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_47_cast = mul(x = linear_42_cast, y = var_737_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(88555200))), lut = tensor([-0x1.cd8p-6, -0x1.0f4p-7, 0x1.174p-7, 0x1.d1p-6]), 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(88702720)))]; + tensor linear_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("linear_43_cast")]; + tensor var_742 = const()[name = tensor("op_742"), val = tensor([1, -1, 12, 64])]; + tensor var_743_cast = reshape(shape = var_742, x = linear_43_cast)[name = tensor("op_743_cast")]; + tensor var_744_perm_0 = const()[name = tensor("op_744_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(88704320))), lut = tensor([-0x1.744p-6, -0x1.bc8p-8, 0x1.ba8p-8, 0x1.74cp-6]), 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(88851840)))]; + tensor linear_44_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("linear_44_cast")]; + tensor var_749 = const()[name = tensor("op_749"), val = tensor([1, -1, 12, 64])]; + tensor var_750_cast = reshape(shape = var_749, x = linear_44_cast)[name = tensor("op_750_cast")]; + tensor var_751_perm_0 = const()[name = tensor("op_751_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_758 = const()[name = tensor("op_758"), val = tensor([1, 77, 12, 64])]; + tensor var_759_cast = reshape(shape = var_758, x = tensor_47_cast)[name = tensor("op_759_cast")]; + tensor var_760_perm_0 = const()[name = tensor("op_760_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_762 = const()[name = tensor("op_762"), val = tensor([12, -1, 64])]; + tensor transpose_24 = transpose(perm = var_760_perm_0, x = var_759_cast)[name = tensor("transpose_24")]; + tensor query_states_15_cast = reshape(shape = var_762, x = transpose_24)[name = tensor("query_states_15_cast")]; + tensor var_764 = const()[name = tensor("op_764"), val = tensor([12, -1, 64])]; + tensor transpose_23 = transpose(perm = var_744_perm_0, x = var_743_cast)[name = tensor("transpose_23")]; + tensor key_states_31_cast = reshape(shape = var_764, x = transpose_23)[name = tensor("key_states_31_cast")]; + tensor var_766 = const()[name = tensor("op_766"), val = tensor([12, -1, 64])]; + tensor transpose_22 = transpose(perm = var_751_perm_0, x = var_750_cast)[name = tensor("transpose_22")]; + tensor value_states_31_cast = reshape(shape = var_766, x = transpose_22)[name = tensor("value_states_31_cast")]; + tensor var_769_perm_0 = const()[name = tensor("op_769_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_769_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_771 = const()[name = tensor("op_771"), val = tensor([1, 12, 77, 77])]; + tensor var_772_cast = reshape(shape = var_771, x = attn_weights_43_cast)[name = tensor("op_772_cast")]; + tensor attn_weights_45_cast = add(x = var_772_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_45_cast")]; + tensor var_777 = const()[name = tensor("op_777"), val = tensor([12, 77, 77])]; + tensor input_117_cast = reshape(shape = var_777, 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_782 = const()[name = tensor("op_782"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_45_cast = reshape(shape = var_782, 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_785 = const()[name = tensor("op_785"), 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_785, 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(88853440))), lut = tensor([-0x1.6f4p-6, -0x1.b68p-8, 0x1.b84p-8, 0x1.6fp-6]), 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(89000960)))]; + tensor linear_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("linear_45_cast")]; + tensor input_123_cast = add(x = input_115_cast, y = linear_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(89002560)))]; + 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(89004160)))]; + 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_15_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(89005760))), lut = tensor([-0x1.914p-6, -0x1.dbcp-8, 0x1.de8p-8, 0x1.918p-6]), 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(89595648))), lut = tensor([-0x1.2dcp-2, 0x1.9fcp-5, -0x1.4ccp-3, -0x1.88cp-2]), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_46_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("linear_46_cast")]; + tensor var_800_to_fp16 = const()[name = tensor("op_800_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_801_cast = mul(x = linear_46_cast, y = var_800_to_fp16)[name = tensor("op_801_cast")]; + tensor var_802_cast = sigmoid(x = var_801_cast)[name = tensor("op_802_cast")]; + tensor input_129_cast = mul(x = linear_46_cast, y = var_802_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(89596480))), lut = tensor([-0x1.864p-6, -0x1.cfp-8, 0x1.ccp-8, 0x1.85cp-6]), 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(90186368)))]; + tensor linear_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("linear_47_cast")]; + tensor input_131_cast = add(x = input_123_cast, y = linear_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(90187968)))]; + 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(90189568)))]; + 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_15_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(90191168))), lut = tensor([-0x1.cb8p-6, -0x1.104p-7, 0x1.108p-7, 0x1.ccp-6]), 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(90338688)))]; + tensor linear_48_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("linear_48_cast")]; + tensor var_827_to_fp16 = const()[name = tensor("op_827_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_53_cast = mul(x = linear_48_cast, y = var_827_to_fp16)[name = tensor("tensor_53_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90340288))), lut = tensor([-0x1.c44p-6, -0x1.0dp-7, 0x1.0bcp-7, 0x1.c48p-6]), 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(90487808)))]; + tensor linear_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("linear_49_cast")]; + tensor var_832 = const()[name = tensor("op_832"), val = tensor([1, -1, 12, 64])]; + tensor var_833_cast = reshape(shape = var_832, x = linear_49_cast)[name = tensor("op_833_cast")]; + tensor var_834_perm_0 = const()[name = tensor("op_834_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90489408))), lut = tensor([-0x1.808p-6, -0x1.c6cp-8, 0x1.dp-8, 0x1.82cp-6]), 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(90636928)))]; + tensor linear_50_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("linear_50_cast")]; + tensor var_839 = const()[name = tensor("op_839"), val = tensor([1, -1, 12, 64])]; + tensor var_840_cast = reshape(shape = var_839, x = linear_50_cast)[name = tensor("op_840_cast")]; + tensor var_841_perm_0 = const()[name = tensor("op_841_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_848 = const()[name = tensor("op_848"), val = tensor([1, 77, 12, 64])]; + tensor var_849_cast = reshape(shape = var_848, x = tensor_53_cast)[name = tensor("op_849_cast")]; + tensor var_850_perm_0 = const()[name = tensor("op_850_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_852 = const()[name = tensor("op_852"), val = tensor([12, -1, 64])]; + tensor transpose_19 = transpose(perm = var_850_perm_0, x = var_849_cast)[name = tensor("transpose_19")]; + tensor query_states_17_cast = reshape(shape = var_852, x = transpose_19)[name = tensor("query_states_17_cast")]; + tensor var_854 = const()[name = tensor("op_854"), val = tensor([12, -1, 64])]; + tensor transpose_18 = transpose(perm = var_834_perm_0, x = var_833_cast)[name = tensor("transpose_18")]; + tensor key_states_35_cast = reshape(shape = var_854, x = transpose_18)[name = tensor("key_states_35_cast")]; + tensor var_856 = const()[name = tensor("op_856"), val = tensor([12, -1, 64])]; + tensor transpose_17 = transpose(perm = var_841_perm_0, x = var_840_cast)[name = tensor("transpose_17")]; + tensor value_states_35_cast = reshape(shape = var_856, x = transpose_17)[name = tensor("value_states_35_cast")]; + tensor var_859_perm_0 = const()[name = tensor("op_859_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_49_transpose_x_0 = const()[name = tensor("attn_weights_49_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_49_transpose_y_0 = const()[name = tensor("attn_weights_49_transpose_y_0"), val = tensor(false)]; + tensor transpose_16 = transpose(perm = var_859_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_861 = const()[name = tensor("op_861"), val = tensor([1, 12, 77, 77])]; + tensor var_862_cast = reshape(shape = var_861, x = attn_weights_49_cast)[name = tensor("op_862_cast")]; + tensor attn_weights_51_cast = add(x = var_862_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_51_cast")]; + tensor var_867 = const()[name = tensor("op_867"), val = tensor([12, 77, 77])]; + tensor input_133_cast = reshape(shape = var_867, x = attn_weights_51_cast)[name = tensor("input_133_cast")]; + tensor input_135_cast = softmax(axis = var_5, x = input_133_cast)[name = tensor("input_135_cast")]; + tensor attn_output_49_transpose_x_0 = const()[name = tensor("attn_output_49_transpose_x_0"), val = tensor(false)]; + tensor attn_output_49_transpose_y_0 = const()[name = tensor("attn_output_49_transpose_y_0"), val = tensor(false)]; + tensor attn_output_49_cast = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast, y = value_states_35_cast)[name = tensor("attn_output_49_cast")]; + tensor var_872 = const()[name = tensor("op_872"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_51_cast = reshape(shape = var_872, x = attn_output_49_cast)[name = tensor("attn_output_51_cast")]; + tensor attn_output_53_perm_0 = const()[name = tensor("attn_output_53_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_875 = const()[name = tensor("op_875"), val = tensor([1, 77, 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_875, 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(90638528))), lut = tensor([-0x1.7b8p-6, -0x1.c78p-8, 0x1.be8p-8, 0x1.798p-6]), 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(90786048)))]; + tensor linear_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("linear_51_cast")]; + tensor input_139_cast = add(x = input_131_cast, y = linear_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(90787648)))]; + 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(90789248)))]; + 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_15_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(90790848))), lut = tensor([-0x1.8acp-6, -0x1.ca8p-8, 0x1.ebp-8, 0x1.93p-6]), 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(91380736))), lut = tensor([-0x1.91cp-2, -0x1.87cp-3, -0x1.384p-2, 0x1.fd4p-7]), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_52_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("linear_52_cast")]; + tensor var_890_to_fp16 = const()[name = tensor("op_890_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_891_cast = mul(x = linear_52_cast, y = var_890_to_fp16)[name = tensor("op_891_cast")]; + tensor var_892_cast = sigmoid(x = var_891_cast)[name = tensor("op_892_cast")]; + tensor input_145_cast = mul(x = linear_52_cast, y = var_892_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(91381568))), lut = tensor([-0x1.944p-6, -0x1.e04p-8, 0x1.ddp-8, 0x1.938p-6]), 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(91971456)))]; + tensor linear_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("linear_53_cast")]; + tensor input_147_cast = add(x = input_139_cast, y = linear_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(91973056)))]; + 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(91974656)))]; + 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_15_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(91976256))), lut = tensor([-0x1.bfcp-6, -0x1.0c4p-7, 0x1.068p-7, 0x1.bcp-6]), 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(92123776)))]; + tensor linear_54_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("linear_54_cast")]; + tensor var_917_to_fp16 = const()[name = tensor("op_917_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_59_cast = mul(x = linear_54_cast, y = var_917_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(92125376))), lut = tensor([-0x1.b94p-6, -0x1.05p-7, 0x1.0b4p-7, 0x1.bd4p-6]), 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(92272896)))]; + tensor linear_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("linear_55_cast")]; + tensor var_922 = const()[name = tensor("op_922"), val = tensor([1, -1, 12, 64])]; + tensor var_923_cast = reshape(shape = var_922, x = linear_55_cast)[name = tensor("op_923_cast")]; + tensor var_924_perm_0 = const()[name = tensor("op_924_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(92274496))), lut = tensor([-0x1.88cp-6, -0x1.d48p-8, 0x1.d3cp-8, 0x1.894p-6]), 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(92422016)))]; + tensor linear_56_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("linear_56_cast")]; + tensor var_929 = const()[name = tensor("op_929"), val = tensor([1, -1, 12, 64])]; + tensor var_930_cast = reshape(shape = var_929, x = linear_56_cast)[name = tensor("op_930_cast")]; + tensor var_931_perm_0 = const()[name = tensor("op_931_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_938 = const()[name = tensor("op_938"), val = tensor([1, 77, 12, 64])]; + tensor var_939_cast = reshape(shape = var_938, x = tensor_59_cast)[name = tensor("op_939_cast")]; + tensor var_940_perm_0 = const()[name = tensor("op_940_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_942 = const()[name = tensor("op_942"), val = tensor([12, -1, 64])]; + tensor transpose_14 = transpose(perm = var_940_perm_0, x = var_939_cast)[name = tensor("transpose_14")]; + tensor query_states_19_cast = reshape(shape = var_942, x = transpose_14)[name = tensor("query_states_19_cast")]; + tensor var_944 = const()[name = tensor("op_944"), val = tensor([12, -1, 64])]; + tensor transpose_13 = transpose(perm = var_924_perm_0, x = var_923_cast)[name = tensor("transpose_13")]; + tensor key_states_39_cast = reshape(shape = var_944, x = transpose_13)[name = tensor("key_states_39_cast")]; + tensor var_946 = const()[name = tensor("op_946"), val = tensor([12, -1, 64])]; + tensor transpose_12 = transpose(perm = var_931_perm_0, x = var_930_cast)[name = tensor("transpose_12")]; + tensor value_states_39_cast = reshape(shape = var_946, x = transpose_12)[name = tensor("value_states_39_cast")]; + tensor var_949_perm_0 = const()[name = tensor("op_949_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_949_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_951 = const()[name = tensor("op_951"), val = tensor([1, 12, 77, 77])]; + tensor var_952_cast = reshape(shape = var_951, x = attn_weights_55_cast)[name = tensor("op_952_cast")]; + tensor attn_weights_57_cast = add(x = var_952_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_57_cast")]; + tensor var_957 = const()[name = tensor("op_957"), val = tensor([12, 77, 77])]; + tensor input_149_cast = reshape(shape = var_957, 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_962 = const()[name = tensor("op_962"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_57_cast = reshape(shape = var_962, 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_965 = const()[name = tensor("op_965"), 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_965, 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(92423616))), lut = tensor([-0x1.818p-6, -0x1.cd8p-8, 0x1.cc8p-8, 0x1.81p-6]), 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(92571136)))]; + tensor linear_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("linear_57_cast")]; + tensor input_155_cast = add(x = input_147_cast, y = linear_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(92572736)))]; + 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(92574336)))]; + 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_15_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(92575936))), lut = tensor([-0x1.8bp-6, -0x1.cdcp-8, 0x1.e44p-8, 0x1.904p-6]), 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(93165824))), lut = tensor([-0x1.01p-2, -0x1.5p-2, -0x1.bfcp-4, -0x1.accp-2]), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_58_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("linear_58_cast")]; + tensor var_980_to_fp16 = const()[name = tensor("op_980_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_981_cast = mul(x = linear_58_cast, y = var_980_to_fp16)[name = tensor("op_981_cast")]; + tensor var_982_cast = sigmoid(x = var_981_cast)[name = tensor("op_982_cast")]; + tensor input_161_cast = mul(x = linear_58_cast, y = var_982_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(93166656))), lut = tensor([-0x1.a5p-6, -0x1.f4cp-8, 0x1.f24p-8, 0x1.a3cp-6]), 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(93756544)))]; + tensor linear_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("linear_59_cast")]; + tensor input_163_cast = add(x = input_155_cast, y = linear_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(93758144)))]; + 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(93759744)))]; + 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_15_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(93761344))), lut = tensor([-0x1.9ep-6, -0x1.eb4p-8, 0x1.eecp-8, 0x1.9fp-6]), 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(93908864)))]; + tensor linear_60_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("linear_60_cast")]; + tensor var_1007_to_fp16 = const()[name = tensor("op_1007_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_65_cast = mul(x = linear_60_cast, y = var_1007_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(93910464))), lut = tensor([-0x1.9c8p-6, -0x1.e8cp-8, 0x1.ec8p-8, 0x1.9ccp-6]), 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(94057984)))]; + tensor linear_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("linear_61_cast")]; + tensor var_1012 = const()[name = tensor("op_1012"), val = tensor([1, -1, 12, 64])]; + tensor var_1013_cast = reshape(shape = var_1012, x = linear_61_cast)[name = tensor("op_1013_cast")]; + tensor var_1014_perm_0 = const()[name = tensor("op_1014_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(94059584))), lut = tensor([-0x1.b88p-6, -0x1.01cp-7, 0x1.0ap-7, 0x1.bccp-6]), 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(94207104)))]; + tensor linear_62_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("linear_62_cast")]; + tensor var_1019 = const()[name = tensor("op_1019"), val = tensor([1, -1, 12, 64])]; + tensor var_1020_cast = reshape(shape = var_1019, x = linear_62_cast)[name = tensor("op_1020_cast")]; + tensor var_1021_perm_0 = const()[name = tensor("op_1021_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1028 = const()[name = tensor("op_1028"), val = tensor([1, 77, 12, 64])]; + tensor var_1029_cast = reshape(shape = var_1028, x = tensor_65_cast)[name = tensor("op_1029_cast")]; + tensor var_1030_perm_0 = const()[name = tensor("op_1030_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1032 = const()[name = tensor("op_1032"), val = tensor([12, -1, 64])]; + tensor transpose_9 = transpose(perm = var_1030_perm_0, x = var_1029_cast)[name = tensor("transpose_9")]; + tensor query_states_21_cast = reshape(shape = var_1032, x = transpose_9)[name = tensor("query_states_21_cast")]; + tensor var_1034 = const()[name = tensor("op_1034"), val = tensor([12, -1, 64])]; + tensor transpose_8 = transpose(perm = var_1014_perm_0, x = var_1013_cast)[name = tensor("transpose_8")]; + tensor key_states_43_cast = reshape(shape = var_1034, x = transpose_8)[name = tensor("key_states_43_cast")]; + tensor var_1036 = const()[name = tensor("op_1036"), val = tensor([12, -1, 64])]; + tensor transpose_7 = transpose(perm = var_1021_perm_0, x = var_1020_cast)[name = tensor("transpose_7")]; + tensor value_states_43_cast = reshape(shape = var_1036, x = transpose_7)[name = tensor("value_states_43_cast")]; + tensor var_1039_perm_0 = const()[name = tensor("op_1039_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_1039_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_1041 = const()[name = tensor("op_1041"), val = tensor([1, 12, 77, 77])]; + tensor var_1042_cast = reshape(shape = var_1041, x = attn_weights_61_cast)[name = tensor("op_1042_cast")]; + tensor attn_weights_63_cast = add(x = var_1042_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_63_cast")]; + tensor var_1047 = const()[name = tensor("op_1047"), val = tensor([12, 77, 77])]; + tensor input_165_cast = reshape(shape = var_1047, 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_1052 = const()[name = tensor("op_1052"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_63_cast = reshape(shape = var_1052, 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_1055 = const()[name = tensor("op_1055"), 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_1055, 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(94208704))), lut = tensor([-0x1.a34p-6, -0x1.f2p-8, 0x1.f4p-8, 0x1.a5cp-6]), 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(94356224)))]; + tensor linear_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("linear_63_cast")]; + tensor input_171_cast = add(x = input_163_cast, y = linear_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(94357824)))]; + 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(94359424)))]; + 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_15_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(94361024))), lut = tensor([-0x1.8ap-6, -0x1.c7cp-8, 0x1.f18p-8, 0x1.948p-6]), 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(94950912))), lut = tensor([-0x1.414p-2, -0x1.168p-3, -0x1.9fcp-2, -0x1.ec8p-3]), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_64_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("linear_64_cast")]; + tensor var_1070_to_fp16 = const()[name = tensor("op_1070_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_1071_cast = mul(x = linear_64_cast, y = var_1070_to_fp16)[name = tensor("op_1071_cast")]; + tensor var_1072_cast = sigmoid(x = var_1071_cast)[name = tensor("op_1072_cast")]; + tensor input_177_cast = mul(x = linear_64_cast, y = var_1072_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(94951744))), lut = tensor([-0x1.a44p-6, -0x1.f38p-8, 0x1.f78p-8, 0x1.a5cp-6]), 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(95541632)))]; + tensor linear_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("linear_65_cast")]; + tensor input_179_cast = add(x = input_171_cast, y = linear_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(95543232)))]; + 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(95544832)))]; + 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_15_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(95546432))), lut = tensor([-0x1.8p-6, -0x1.cdp-8, 0x1.be4p-8, 0x1.7dp-6]), 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(95693952)))]; + tensor linear_66_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("linear_66_cast")]; + tensor var_1097_to_fp16 = const()[name = tensor("op_1097_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_cast = mul(x = linear_66_cast, y = var_1097_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(95695552))), lut = tensor([-0x1.78cp-6, -0x1.bcp-8, 0x1.bep-8, 0x1.788p-6]), 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(95843072)))]; + tensor linear_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("linear_67_cast")]; + tensor var_1102 = const()[name = tensor("op_1102"), val = tensor([1, -1, 12, 64])]; + tensor var_1103_cast = reshape(shape = var_1102, x = linear_67_cast)[name = tensor("op_1103_cast")]; + tensor var_1104_perm_0 = const()[name = tensor("op_1104_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(95844672))), lut = tensor([-0x1.01p-5, -0x1.31p-7, 0x1.308p-7, 0x1.014p-5]), 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(95992192)))]; + tensor linear_68_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("linear_68_cast")]; + tensor var_1109 = const()[name = tensor("op_1109"), val = tensor([1, -1, 12, 64])]; + tensor var_1110_cast = reshape(shape = var_1109, x = linear_68_cast)[name = tensor("op_1110_cast")]; + tensor var_1111_perm_0 = const()[name = tensor("op_1111_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1118 = const()[name = tensor("op_1118"), val = tensor([1, 77, 12, 64])]; + tensor var_1119_cast = reshape(shape = var_1118, x = tensor_cast)[name = tensor("op_1119_cast")]; + tensor var_1120_perm_0 = const()[name = tensor("op_1120_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1122 = const()[name = tensor("op_1122"), val = tensor([12, -1, 64])]; + tensor transpose_4 = transpose(perm = var_1120_perm_0, x = var_1119_cast)[name = tensor("transpose_4")]; + tensor query_states_cast = reshape(shape = var_1122, x = transpose_4)[name = tensor("query_states_cast")]; + tensor var_1124 = const()[name = tensor("op_1124"), val = tensor([12, -1, 64])]; + tensor transpose_3 = transpose(perm = var_1104_perm_0, x = var_1103_cast)[name = tensor("transpose_3")]; + tensor key_states_cast = reshape(shape = var_1124, x = transpose_3)[name = tensor("key_states_cast")]; + tensor var_1126 = const()[name = tensor("op_1126"), val = tensor([12, -1, 64])]; + tensor transpose_2 = transpose(perm = var_1111_perm_0, x = var_1110_cast)[name = tensor("transpose_2")]; + tensor value_states_cast = reshape(shape = var_1126, x = transpose_2)[name = tensor("value_states_cast")]; + tensor var_1129_perm_0 = const()[name = tensor("op_1129_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_1129_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_1131 = const()[name = tensor("op_1131"), val = tensor([1, 12, 77, 77])]; + tensor var_1132_cast = reshape(shape = var_1131, x = attn_weights_67_cast)[name = tensor("op_1132_cast")]; + tensor attn_weights_69_cast = add(x = var_1132_cast, y = op_56_to_fp16_palettized)[name = tensor("attn_weights_69_cast")]; + tensor var_1137 = const()[name = tensor("op_1137"), val = tensor([12, 77, 77])]; + tensor input_181_cast = reshape(shape = var_1137, 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_1142 = const()[name = tensor("op_1142"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_69_cast = reshape(shape = var_1142, 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_1145 = const()[name = tensor("op_1145"), 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_1145, 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(95993792))), lut = tensor([-0x1.df4p-6, -0x1.1e4p-7, 0x1.184p-7, 0x1.ddp-6]), 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(96141312)))]; + tensor linear_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("linear_69_cast")]; + tensor input_187_cast = add(x = input_179_cast, y = linear_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(96142912)))]; + 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(96144512)))]; + 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_15_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(96146112))), lut = tensor([-0x1.92p-6, -0x1.d7p-8, 0x1.ecp-8, 0x1.984p-6]), 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(96736000))), lut = tensor([-0x1.3b8p-2, -0x1.618p-3, 0x1.134p-4, -0x1.cc8p-2]), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor linear_70_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("linear_70_cast")]; + tensor var_1160_to_fp16 = const()[name = tensor("op_1160_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_1161_cast = mul(x = linear_70_cast, y = var_1160_to_fp16)[name = tensor("op_1161_cast")]; + tensor var_1162_cast = sigmoid(x = var_1161_cast)[name = tensor("op_1162_cast")]; + tensor input_193_cast = mul(x = linear_70_cast, y = var_1162_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(96736832))), lut = tensor([-0x1.9acp-6, -0x1.e6p-8, 0x1.eap-8, 0x1.9bcp-6]), 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(97326720)))]; + tensor linear_71_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized, x = input_193_cast)[name = tensor("linear_71_cast")]; + tensor input_cast = add(x = input_187_cast, y = linear_71_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(97328320)))]; + 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(97329920)))]; + 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_15_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_1173 = const()[name = tensor("op_1173"), val = tensor([0])]; + tensor var_1175 = reduce_argmax(axis = var_5, keep_dims = var_6, x = cast_2)[name = tensor("op_1175")]; + 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_1173, var_1175))[name = tensor("stack_0")]; + tensor var_1177_transpose_batch_dims_0 = const()[name = tensor("op_1177_transpose_batch_dims_0"), val = tensor(0)]; + tensor var_1177_transpose_cast = gather_nd(batch_dims = var_1177_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast)[name = tensor("op_1177_transpose_cast")]; + tensor var_1177_cast_to_fp32_dtype_0 = const()[name = tensor("op_1177_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_1177_cast_to_fp32_dtype_0, x = var_1177_transpose_cast)[name = tensor("cast_1")]; + } -> (last_hidden_state, pooled_outputs); +} \ No newline at end of file