program(1.0) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})] { func main(tensor cache_length, tensor decoder_key_padding_mask, tensor encoder_output_embeds, tensor input_ids, tensor key_cache, tensor kv_cache_update_mask, tensor value_cache) { tensor var_40_axis_0 = const()[name = tensor("op_40_axis_0"), val = tensor(0)]; tensor var_40_batch_dims_0 = const()[name = tensor("op_40_batch_dims_0"), val = tensor(0)]; tensor embed_tokens_weight_to_fp16 = const()[name = tensor("embed_tokens_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; tensor var_40_cast_fp16 = gather(axis = var_40_axis_0, batch_dims = var_40_batch_dims_0, indices = input_ids, x = embed_tokens_weight_to_fp16)[name = tensor("op_40_cast_fp16")]; tensor var_44_axis_0 = const()[name = tensor("op_44_axis_0"), val = tensor(0)]; tensor var_44_batch_dims_0 = const()[name = tensor("op_44_batch_dims_0"), val = tensor(0)]; tensor embed_positions_weight_to_fp16 = const()[name = tensor("embed_positions_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79664768)))]; tensor var_44_cast_fp16 = gather(axis = var_44_axis_0, batch_dims = var_44_batch_dims_0, indices = cache_length, x = embed_positions_weight_to_fp16)[name = tensor("op_44_cast_fp16")]; tensor hidden_states_1_cast_fp16 = add(x = var_40_cast_fp16, y = var_44_cast_fp16)[name = tensor("hidden_states_1_cast_fp16")]; tensor var_58_axes_0 = const()[name = tensor("op_58_axes_0"), val = tensor([2])]; tensor var_58_cast_fp16 = expand_dims(axes = var_58_axes_0, x = hidden_states_1_cast_fp16)[name = tensor("op_58_cast_fp16")]; tensor inputs_1_axes_0 = const()[name = tensor("inputs_1_axes_0"), val = tensor([3])]; tensor inputs_1_cast_fp16 = expand_dims(axes = inputs_1_axes_0, x = var_58_cast_fp16)[name = tensor("inputs_1_cast_fp16")]; tensor tile_0 = const()[name = tensor("tile_0"), val = tensor([768, 768, 768, 768, 768, 768, 768, 768, 768, 768, 768, 768])]; tensor var_63_axis_0 = const()[name = tensor("op_63_axis_0"), val = tensor(1)]; tensor var_63_cast_fp16_0, tensor var_63_cast_fp16_1, tensor var_63_cast_fp16_2, tensor var_63_cast_fp16_3, tensor var_63_cast_fp16_4, tensor var_63_cast_fp16_5, tensor var_63_cast_fp16_6, tensor var_63_cast_fp16_7, tensor var_63_cast_fp16_8, tensor var_63_cast_fp16_9, tensor var_63_cast_fp16_10, tensor var_63_cast_fp16_11 = split(axis = var_63_axis_0, split_sizes = tile_0, x = key_cache)[name = tensor("op_63_cast_fp16")]; tensor tile_1 = const()[name = tensor("tile_1"), val = tensor([768, 768, 768, 768, 768, 768, 768, 768, 768, 768, 768, 768])]; tensor var_78_axis_0 = const()[name = tensor("op_78_axis_0"), val = tensor(1)]; tensor var_78_cast_fp16_0, tensor var_78_cast_fp16_1, tensor var_78_cast_fp16_2, tensor var_78_cast_fp16_3, tensor var_78_cast_fp16_4, tensor var_78_cast_fp16_5, tensor var_78_cast_fp16_6, tensor var_78_cast_fp16_7, tensor var_78_cast_fp16_8, tensor var_78_cast_fp16_9, tensor var_78_cast_fp16_10, tensor var_78_cast_fp16_11 = split(axis = var_78_axis_0, split_sizes = tile_1, x = value_cache)[name = tensor("op_78_cast_fp16")]; tensor var_96 = const()[name = tensor("op_96"), val = tensor(3)]; tensor var_103 = const()[name = tensor("op_103"), val = tensor(1)]; tensor var_104 = const()[name = tensor("op_104"), val = tensor(true)]; tensor var_116 = const()[name = tensor("op_116"), val = tensor([1])]; tensor channels_mean_1_cast_fp16 = reduce_mean(axes = var_116, keep_dims = var_104, x = inputs_1_cast_fp16)[name = tensor("channels_mean_1_cast_fp16")]; tensor zero_mean_1_cast_fp16 = sub(x = inputs_1_cast_fp16, y = channels_mean_1_cast_fp16)[name = tensor("zero_mean_1_cast_fp16")]; tensor zero_mean_sq_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = zero_mean_1_cast_fp16)[name = tensor("zero_mean_sq_1_cast_fp16")]; tensor var_120 = const()[name = tensor("op_120"), val = tensor([1])]; tensor var_121_cast_fp16 = reduce_mean(axes = var_120, keep_dims = var_104, x = zero_mean_sq_1_cast_fp16)[name = tensor("op_121_cast_fp16")]; tensor var_122_to_fp16 = const()[name = tensor("op_122_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_123_cast_fp16 = add(x = var_121_cast_fp16, y = var_122_to_fp16)[name = tensor("op_123_cast_fp16")]; tensor denom_1_epsilon_0_to_fp16 = const()[name = tensor("denom_1_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_1_cast_fp16 = rsqrt(epsilon = denom_1_epsilon_0_to_fp16, x = var_123_cast_fp16)[name = tensor("denom_1_cast_fp16")]; tensor out_1_cast_fp16 = mul(x = zero_mean_1_cast_fp16, y = denom_1_cast_fp16)[name = tensor("out_1_cast_fp16")]; tensor obj_1_mean_0_to_fp16 = const()[name = tensor("obj_1_mean_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80352960)))]; tensor obj_1_variance_0_to_fp16 = const()[name = tensor("obj_1_variance_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80354560)))]; tensor obj_1_gamma_0_to_fp16 = const()[name = tensor("obj_1_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80356160)))]; tensor obj_1_beta_0_to_fp16 = const()[name = tensor("obj_1_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80357760)))]; tensor obj_1_epsilon_0_to_fp16 = const()[name = tensor("obj_1_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_1_cast_fp16 = batch_norm(beta = obj_1_beta_0_to_fp16, epsilon = obj_1_epsilon_0_to_fp16, gamma = obj_1_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_1_cast_fp16)[name = tensor("obj_1_cast_fp16")]; tensor var_138 = const()[name = tensor("op_138"), val = tensor([1, 1])]; tensor var_140 = const()[name = tensor("op_140"), val = tensor([1, 1])]; tensor query_1_pad_type_0 = const()[name = tensor("query_1_pad_type_0"), val = tensor("custom")]; tensor query_1_pad_0 = const()[name = tensor("query_1_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80359360)))]; tensor layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81539072)))]; tensor query_1_cast_fp16 = conv(bias = layers_0_self_attn_q_proj_bias_to_fp16, dilations = var_140, groups = var_103, pad = query_1_pad_0, pad_type = query_1_pad_type_0, strides = var_138, weight = layers_0_self_attn_q_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("query_1_cast_fp16")]; tensor var_144 = const()[name = tensor("op_144"), val = tensor([1, 1])]; tensor var_146 = const()[name = tensor("op_146"), val = tensor([1, 1])]; tensor current_key_1_pad_type_0 = const()[name = tensor("current_key_1_pad_type_0"), val = tensor("custom")]; tensor current_key_1_pad_0 = const()[name = tensor("current_key_1_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81540672)))]; tensor current_key_1_cast_fp16 = conv(dilations = var_146, groups = var_103, pad = current_key_1_pad_0, pad_type = current_key_1_pad_type_0, strides = var_144, weight = layers_0_self_attn_k_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("current_key_1_cast_fp16")]; tensor var_151 = const()[name = tensor("op_151"), val = tensor([1, 1])]; tensor var_153 = const()[name = tensor("op_153"), val = tensor([1, 1])]; tensor current_value_1_pad_type_0 = const()[name = tensor("current_value_1_pad_type_0"), val = tensor("custom")]; tensor current_value_1_pad_0 = const()[name = tensor("current_value_1_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82720384)))]; tensor layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83900096)))]; tensor current_value_1_cast_fp16 = conv(bias = layers_0_self_attn_v_proj_bias_to_fp16, dilations = var_153, groups = var_103, pad = current_value_1_pad_0, pad_type = current_value_1_pad_type_0, strides = var_151, weight = layers_0_self_attn_v_proj_weight_to_fp16, x = obj_1_cast_fp16)[name = tensor("current_value_1_cast_fp16")]; tensor var_157_axes_0 = const()[name = tensor("op_157_axes_0"), val = tensor([1])]; tensor var_157_cast_fp16 = expand_dims(axes = var_157_axes_0, x = kv_cache_update_mask)[name = tensor("op_157_cast_fp16")]; tensor var_158_axes_0 = const()[name = tensor("op_158_axes_0"), val = tensor([2])]; tensor var_158_cast_fp16 = expand_dims(axes = var_158_axes_0, x = var_157_cast_fp16)[name = tensor("op_158_cast_fp16")]; tensor var_160_cast_fp16 = mul(x = current_key_1_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_160_cast_fp16")]; tensor var_97_to_fp16 = const()[name = tensor("op_97_to_fp16"), val = tensor(0x1p+0)]; tensor var_161_cast_fp16 = sub(x = var_97_to_fp16, y = var_158_cast_fp16)[name = tensor("op_161_cast_fp16")]; tensor var_162_cast_fp16 = mul(x = var_63_cast_fp16_0, y = var_161_cast_fp16)[name = tensor("op_162_cast_fp16")]; tensor key_1_cast_fp16 = add(x = var_160_cast_fp16, y = var_162_cast_fp16)[name = tensor("key_1_cast_fp16")]; tensor var_164_cast_fp16 = mul(x = current_value_1_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_164_cast_fp16")]; tensor var_166_cast_fp16 = mul(x = var_78_cast_fp16_0, y = var_161_cast_fp16)[name = tensor("op_166_cast_fp16")]; tensor value_1_cast_fp16 = add(x = var_164_cast_fp16, y = var_166_cast_fp16)[name = tensor("value_1_cast_fp16")]; tensor var_169 = const()[name = tensor("op_169"), val = tensor([1, 12, 64, -1])]; tensor var_170_cast_fp16 = reshape(shape = var_169, x = query_1_cast_fp16)[name = tensor("op_170_cast_fp16")]; tensor var_171_to_fp16 = const()[name = tensor("op_171_to_fp16"), val = tensor(0x1p-3)]; tensor var_172_cast_fp16 = mul(x = var_170_cast_fp16, y = var_171_to_fp16)[name = tensor("op_172_cast_fp16")]; tensor var_173 = const()[name = tensor("op_173"), val = tensor([1, 12, 64, -1])]; tensor var_174_cast_fp16 = reshape(shape = var_173, x = key_1_cast_fp16)[name = tensor("op_174_cast_fp16")]; tensor mh_w_1_transpose_x_0 = const()[name = tensor("mh_w_1_transpose_x_0"), val = tensor(true)]; tensor mh_w_1_transpose_y_0 = const()[name = tensor("mh_w_1_transpose_y_0"), val = tensor(false)]; tensor mh_w_1_cast_fp16 = matmul(transpose_x = mh_w_1_transpose_x_0, transpose_y = mh_w_1_transpose_y_0, x = var_172_cast_fp16, y = var_174_cast_fp16)[name = tensor("mh_w_1_cast_fp16")]; tensor var_178_axes_0 = const()[name = tensor("op_178_axes_0"), val = tensor([1])]; tensor var_178_cast_fp16 = expand_dims(axes = var_178_axes_0, x = decoder_key_padding_mask)[name = tensor("op_178_cast_fp16")]; tensor var_179_axes_0 = const()[name = tensor("op_179_axes_0"), val = tensor([2])]; tensor var_179_cast_fp16 = expand_dims(axes = var_179_axes_0, x = var_178_cast_fp16)[name = tensor("op_179_cast_fp16")]; tensor mh_w_3_cast_fp16 = add(x = mh_w_1_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_3_cast_fp16")]; tensor var_182_cast_fp16 = softmax(axis = var_96, x = mh_w_3_cast_fp16)[name = tensor("op_182_cast_fp16")]; tensor var_183 = const()[name = tensor("op_183"), val = tensor([1, 12, 64, -1])]; tensor var_184_cast_fp16 = reshape(shape = var_183, x = value_1_cast_fp16)[name = tensor("op_184_cast_fp16")]; tensor attn_1_transpose_x_0 = const()[name = tensor("attn_1_transpose_x_0"), val = tensor(false)]; tensor attn_1_transpose_y_0 = const()[name = tensor("attn_1_transpose_y_0"), val = tensor(true)]; tensor attn_1_cast_fp16 = matmul(transpose_x = attn_1_transpose_x_0, transpose_y = attn_1_transpose_y_0, x = var_184_cast_fp16, y = var_182_cast_fp16)[name = tensor("attn_1_cast_fp16")]; tensor var_187 = const()[name = tensor("op_187"), val = tensor([1, 768, 1, -1])]; tensor input_1_cast_fp16 = reshape(shape = var_187, x = attn_1_cast_fp16)[name = tensor("input_1_cast_fp16")]; tensor var_191 = const()[name = tensor("op_191"), val = tensor([1, 1])]; tensor var_193 = const()[name = tensor("op_193"), val = tensor([1, 1])]; tensor obj_7_pad_type_0 = const()[name = tensor("obj_7_pad_type_0"), val = tensor("custom")]; tensor obj_7_pad_0 = const()[name = tensor("obj_7_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83901696)))]; tensor layers_0_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85081408)))]; tensor obj_7_cast_fp16 = conv(bias = layers_0_self_attn_o_proj_bias_to_fp16, dilations = var_193, groups = var_103, pad = obj_7_pad_0, pad_type = obj_7_pad_type_0, strides = var_191, weight = layers_0_self_attn_o_proj_weight_to_fp16, x = input_1_cast_fp16)[name = tensor("obj_7_cast_fp16")]; tensor inputs_3_cast_fp16 = add(x = inputs_1_cast_fp16, y = obj_7_cast_fp16)[name = tensor("inputs_3_cast_fp16")]; tensor var_203 = const()[name = tensor("op_203"), val = tensor([1])]; tensor channels_mean_3_cast_fp16 = reduce_mean(axes = var_203, keep_dims = var_104, x = inputs_3_cast_fp16)[name = tensor("channels_mean_3_cast_fp16")]; tensor zero_mean_3_cast_fp16 = sub(x = inputs_3_cast_fp16, y = channels_mean_3_cast_fp16)[name = tensor("zero_mean_3_cast_fp16")]; tensor zero_mean_sq_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = zero_mean_3_cast_fp16)[name = tensor("zero_mean_sq_3_cast_fp16")]; tensor var_207 = const()[name = tensor("op_207"), val = tensor([1])]; tensor var_208_cast_fp16 = reduce_mean(axes = var_207, keep_dims = var_104, x = zero_mean_sq_3_cast_fp16)[name = tensor("op_208_cast_fp16")]; tensor var_209_to_fp16 = const()[name = tensor("op_209_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_210_cast_fp16 = add(x = var_208_cast_fp16, y = var_209_to_fp16)[name = tensor("op_210_cast_fp16")]; tensor denom_3_epsilon_0_to_fp16 = const()[name = tensor("denom_3_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_3_cast_fp16 = rsqrt(epsilon = denom_3_epsilon_0_to_fp16, x = var_210_cast_fp16)[name = tensor("denom_3_cast_fp16")]; tensor out_3_cast_fp16 = mul(x = zero_mean_3_cast_fp16, y = denom_3_cast_fp16)[name = tensor("out_3_cast_fp16")]; tensor obj_9_gamma_0_to_fp16 = const()[name = tensor("obj_9_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85083008)))]; tensor obj_9_beta_0_to_fp16 = const()[name = tensor("obj_9_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85084608)))]; tensor obj_9_epsilon_0_to_fp16 = const()[name = tensor("obj_9_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_9_cast_fp16 = batch_norm(beta = obj_9_beta_0_to_fp16, epsilon = obj_9_epsilon_0_to_fp16, gamma = obj_9_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_3_cast_fp16)[name = tensor("obj_9_cast_fp16")]; tensor var_225 = const()[name = tensor("op_225"), val = tensor([1, 1])]; tensor var_227 = const()[name = tensor("op_227"), val = tensor([1, 1])]; tensor query_3_pad_type_0 = const()[name = tensor("query_3_pad_type_0"), val = tensor("custom")]; tensor query_3_pad_0 = const()[name = tensor("query_3_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85086208)))]; tensor layers_0_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86265920)))]; tensor query_3_cast_fp16 = conv(bias = layers_0_encoder_attn_q_proj_bias_to_fp16, dilations = var_227, groups = var_103, pad = query_3_pad_0, pad_type = query_3_pad_type_0, strides = var_225, weight = layers_0_encoder_attn_q_proj_weight_to_fp16, x = obj_9_cast_fp16)[name = tensor("query_3_cast_fp16")]; tensor var_231 = const()[name = tensor("op_231"), val = tensor([1, 1])]; tensor var_233 = const()[name = tensor("op_233"), val = tensor([1, 1])]; tensor key_3_pad_type_0 = const()[name = tensor("key_3_pad_type_0"), val = tensor("custom")]; tensor key_3_pad_0 = const()[name = tensor("key_3_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86267520)))]; tensor key_3_cast_fp16 = conv(dilations = var_233, groups = var_103, pad = key_3_pad_0, pad_type = key_3_pad_type_0, strides = var_231, weight = layers_0_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_3_cast_fp16")]; tensor var_238 = const()[name = tensor("op_238"), val = tensor([1, 1])]; tensor var_240 = const()[name = tensor("op_240"), val = tensor([1, 1])]; tensor value_3_pad_type_0 = const()[name = tensor("value_3_pad_type_0"), val = tensor("custom")]; tensor value_3_pad_0 = const()[name = tensor("value_3_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87447232)))]; tensor layers_0_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88626944)))]; tensor value_3_cast_fp16 = conv(bias = layers_0_encoder_attn_v_proj_bias_to_fp16, dilations = var_240, groups = var_103, pad = value_3_pad_0, pad_type = value_3_pad_type_0, strides = var_238, weight = layers_0_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_3_cast_fp16")]; tensor var_244 = const()[name = tensor("op_244"), val = tensor([1, 12, 64, -1])]; tensor var_245_cast_fp16 = reshape(shape = var_244, x = query_3_cast_fp16)[name = tensor("op_245_cast_fp16")]; tensor var_246_to_fp16 = const()[name = tensor("op_246_to_fp16"), val = tensor(0x1p-3)]; tensor var_247_cast_fp16 = mul(x = var_245_cast_fp16, y = var_246_to_fp16)[name = tensor("op_247_cast_fp16")]; tensor var_248 = const()[name = tensor("op_248"), val = tensor([1, 12, 64, -1])]; tensor var_249_cast_fp16 = reshape(shape = var_248, x = key_3_cast_fp16)[name = tensor("op_249_cast_fp16")]; tensor mh_w_5_transpose_x_0 = const()[name = tensor("mh_w_5_transpose_x_0"), val = tensor(true)]; tensor mh_w_5_transpose_y_0 = const()[name = tensor("mh_w_5_transpose_y_0"), val = tensor(false)]; tensor mh_w_5_cast_fp16 = matmul(transpose_x = mh_w_5_transpose_x_0, transpose_y = mh_w_5_transpose_y_0, x = var_247_cast_fp16, y = var_249_cast_fp16)[name = tensor("mh_w_5_cast_fp16")]; tensor obj_13_cast_fp16 = softmax(axis = var_96, x = mh_w_5_cast_fp16)[name = tensor("obj_13_cast_fp16")]; tensor var_253 = const()[name = tensor("op_253"), val = tensor([1, 12, 64, -1])]; tensor var_254_cast_fp16 = reshape(shape = var_253, x = value_3_cast_fp16)[name = tensor("op_254_cast_fp16")]; tensor attn_3_transpose_x_0 = const()[name = tensor("attn_3_transpose_x_0"), val = tensor(false)]; tensor attn_3_transpose_y_0 = const()[name = tensor("attn_3_transpose_y_0"), val = tensor(true)]; tensor attn_3_cast_fp16 = matmul(transpose_x = attn_3_transpose_x_0, transpose_y = attn_3_transpose_y_0, x = var_254_cast_fp16, y = obj_13_cast_fp16)[name = tensor("attn_3_cast_fp16")]; tensor var_257 = const()[name = tensor("op_257"), val = tensor([1, 768, 1, -1])]; tensor input_3_cast_fp16 = reshape(shape = var_257, x = attn_3_cast_fp16)[name = tensor("input_3_cast_fp16")]; tensor var_261 = const()[name = tensor("op_261"), val = tensor([1, 1])]; tensor var_263 = const()[name = tensor("op_263"), val = tensor([1, 1])]; tensor obj_11_pad_type_0 = const()[name = tensor("obj_11_pad_type_0"), val = tensor("custom")]; tensor obj_11_pad_0 = const()[name = tensor("obj_11_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_0_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88628544)))]; tensor layers_0_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_0_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89808256)))]; tensor obj_11_cast_fp16 = conv(bias = layers_0_encoder_attn_o_proj_bias_to_fp16, dilations = var_263, groups = var_103, pad = obj_11_pad_0, pad_type = obj_11_pad_type_0, strides = var_261, weight = layers_0_encoder_attn_o_proj_weight_to_fp16, x = input_3_cast_fp16)[name = tensor("obj_11_cast_fp16")]; tensor inputs_5_cast_fp16 = add(x = inputs_3_cast_fp16, y = obj_11_cast_fp16)[name = tensor("inputs_5_cast_fp16")]; tensor var_269 = const()[name = tensor("op_269"), val = tensor([1])]; tensor channels_mean_5_cast_fp16 = reduce_mean(axes = var_269, keep_dims = var_104, x = inputs_5_cast_fp16)[name = tensor("channels_mean_5_cast_fp16")]; tensor zero_mean_5_cast_fp16 = sub(x = inputs_5_cast_fp16, y = channels_mean_5_cast_fp16)[name = tensor("zero_mean_5_cast_fp16")]; tensor zero_mean_sq_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = zero_mean_5_cast_fp16)[name = tensor("zero_mean_sq_5_cast_fp16")]; tensor var_273 = const()[name = tensor("op_273"), val = tensor([1])]; tensor var_274_cast_fp16 = reduce_mean(axes = var_273, keep_dims = var_104, x = zero_mean_sq_5_cast_fp16)[name = tensor("op_274_cast_fp16")]; tensor var_275_to_fp16 = const()[name = tensor("op_275_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_276_cast_fp16 = add(x = var_274_cast_fp16, y = var_275_to_fp16)[name = tensor("op_276_cast_fp16")]; tensor denom_5_epsilon_0_to_fp16 = const()[name = tensor("denom_5_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_5_cast_fp16 = rsqrt(epsilon = denom_5_epsilon_0_to_fp16, x = var_276_cast_fp16)[name = tensor("denom_5_cast_fp16")]; tensor out_5_cast_fp16 = mul(x = zero_mean_5_cast_fp16, y = denom_5_cast_fp16)[name = tensor("out_5_cast_fp16")]; tensor input_5_gamma_0_to_fp16 = const()[name = tensor("input_5_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89809856)))]; tensor input_5_beta_0_to_fp16 = const()[name = tensor("input_5_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89811456)))]; tensor input_5_epsilon_0_to_fp16 = const()[name = tensor("input_5_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_5_cast_fp16 = batch_norm(beta = input_5_beta_0_to_fp16, epsilon = input_5_epsilon_0_to_fp16, gamma = input_5_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_5_cast_fp16)[name = tensor("input_5_cast_fp16")]; tensor var_287 = const()[name = tensor("op_287"), val = tensor([1, 1])]; tensor var_289 = const()[name = tensor("op_289"), val = tensor([1, 1])]; tensor input_7_pad_type_0 = const()[name = tensor("input_7_pad_type_0"), val = tensor("custom")]; tensor input_7_pad_0 = const()[name = tensor("input_7_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_fc1_weight_to_fp16 = const()[name = tensor("layers_0_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89813056)))]; tensor layers_0_fc1_bias_to_fp16 = const()[name = tensor("layers_0_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94531712)))]; tensor input_7_cast_fp16 = conv(bias = layers_0_fc1_bias_to_fp16, dilations = var_289, groups = var_103, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = var_287, weight = layers_0_fc1_weight_to_fp16, x = input_5_cast_fp16)[name = tensor("input_7_cast_fp16")]; tensor input_9_mode_0 = const()[name = tensor("input_9_mode_0"), val = tensor("EXACT")]; tensor input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = input_7_cast_fp16)[name = tensor("input_9_cast_fp16")]; tensor var_295 = const()[name = tensor("op_295"), val = tensor([1, 1])]; tensor var_297 = const()[name = tensor("op_297"), val = tensor([1, 1])]; tensor hidden_states_3_pad_type_0 = const()[name = tensor("hidden_states_3_pad_type_0"), val = tensor("custom")]; tensor hidden_states_3_pad_0 = const()[name = tensor("hidden_states_3_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_0_fc2_weight_to_fp16 = const()[name = tensor("layers_0_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94537920)))]; tensor layers_0_fc2_bias_to_fp16 = const()[name = tensor("layers_0_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99256576)))]; tensor hidden_states_3_cast_fp16 = conv(bias = layers_0_fc2_bias_to_fp16, dilations = var_297, groups = var_103, pad = hidden_states_3_pad_0, pad_type = hidden_states_3_pad_type_0, strides = var_295, weight = layers_0_fc2_weight_to_fp16, x = input_9_cast_fp16)[name = tensor("hidden_states_3_cast_fp16")]; tensor inputs_7_cast_fp16 = add(x = inputs_5_cast_fp16, y = hidden_states_3_cast_fp16)[name = tensor("inputs_7_cast_fp16")]; tensor var_310 = const()[name = tensor("op_310"), val = tensor(3)]; tensor var_317 = const()[name = tensor("op_317"), val = tensor(1)]; tensor var_318 = const()[name = tensor("op_318"), val = tensor(true)]; tensor var_330 = const()[name = tensor("op_330"), val = tensor([1])]; tensor channels_mean_7_cast_fp16 = reduce_mean(axes = var_330, keep_dims = var_318, x = inputs_7_cast_fp16)[name = tensor("channels_mean_7_cast_fp16")]; tensor zero_mean_7_cast_fp16 = sub(x = inputs_7_cast_fp16, y = channels_mean_7_cast_fp16)[name = tensor("zero_mean_7_cast_fp16")]; tensor zero_mean_sq_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = zero_mean_7_cast_fp16)[name = tensor("zero_mean_sq_7_cast_fp16")]; tensor var_334 = const()[name = tensor("op_334"), val = tensor([1])]; tensor var_335_cast_fp16 = reduce_mean(axes = var_334, keep_dims = var_318, x = zero_mean_sq_7_cast_fp16)[name = tensor("op_335_cast_fp16")]; tensor var_336_to_fp16 = const()[name = tensor("op_336_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_337_cast_fp16 = add(x = var_335_cast_fp16, y = var_336_to_fp16)[name = tensor("op_337_cast_fp16")]; tensor denom_7_epsilon_0_to_fp16 = const()[name = tensor("denom_7_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_7_cast_fp16 = rsqrt(epsilon = denom_7_epsilon_0_to_fp16, x = var_337_cast_fp16)[name = tensor("denom_7_cast_fp16")]; tensor out_7_cast_fp16 = mul(x = zero_mean_7_cast_fp16, y = denom_7_cast_fp16)[name = tensor("out_7_cast_fp16")]; tensor obj_15_gamma_0_to_fp16 = const()[name = tensor("obj_15_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99258176)))]; tensor obj_15_beta_0_to_fp16 = const()[name = tensor("obj_15_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99259776)))]; tensor obj_15_epsilon_0_to_fp16 = const()[name = tensor("obj_15_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_15_cast_fp16 = batch_norm(beta = obj_15_beta_0_to_fp16, epsilon = obj_15_epsilon_0_to_fp16, gamma = obj_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_7_cast_fp16)[name = tensor("obj_15_cast_fp16")]; tensor var_352 = const()[name = tensor("op_352"), val = tensor([1, 1])]; tensor var_354 = const()[name = tensor("op_354"), val = tensor([1, 1])]; tensor query_5_pad_type_0 = const()[name = tensor("query_5_pad_type_0"), val = tensor("custom")]; tensor query_5_pad_0 = const()[name = tensor("query_5_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99261376)))]; tensor layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100441088)))]; tensor query_5_cast_fp16 = conv(bias = layers_1_self_attn_q_proj_bias_to_fp16, dilations = var_354, groups = var_317, pad = query_5_pad_0, pad_type = query_5_pad_type_0, strides = var_352, weight = layers_1_self_attn_q_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("query_5_cast_fp16")]; tensor var_358 = const()[name = tensor("op_358"), val = tensor([1, 1])]; tensor var_360 = const()[name = tensor("op_360"), val = tensor([1, 1])]; tensor current_key_3_pad_type_0 = const()[name = tensor("current_key_3_pad_type_0"), val = tensor("custom")]; tensor current_key_3_pad_0 = const()[name = tensor("current_key_3_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100442688)))]; tensor current_key_3_cast_fp16 = conv(dilations = var_360, groups = var_317, pad = current_key_3_pad_0, pad_type = current_key_3_pad_type_0, strides = var_358, weight = layers_1_self_attn_k_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("current_key_3_cast_fp16")]; tensor var_365 = const()[name = tensor("op_365"), val = tensor([1, 1])]; tensor var_367 = const()[name = tensor("op_367"), val = tensor([1, 1])]; tensor current_value_3_pad_type_0 = const()[name = tensor("current_value_3_pad_type_0"), val = tensor("custom")]; tensor current_value_3_pad_0 = const()[name = tensor("current_value_3_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101622400)))]; tensor layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102802112)))]; tensor current_value_3_cast_fp16 = conv(bias = layers_1_self_attn_v_proj_bias_to_fp16, dilations = var_367, groups = var_317, pad = current_value_3_pad_0, pad_type = current_value_3_pad_type_0, strides = var_365, weight = layers_1_self_attn_v_proj_weight_to_fp16, x = obj_15_cast_fp16)[name = tensor("current_value_3_cast_fp16")]; tensor var_374_cast_fp16 = mul(x = current_key_3_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_374_cast_fp16")]; tensor var_376_cast_fp16 = mul(x = var_63_cast_fp16_1, y = var_161_cast_fp16)[name = tensor("op_376_cast_fp16")]; tensor key_5_cast_fp16 = add(x = var_374_cast_fp16, y = var_376_cast_fp16)[name = tensor("key_5_cast_fp16")]; tensor var_378_cast_fp16 = mul(x = current_value_3_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_378_cast_fp16")]; tensor var_380_cast_fp16 = mul(x = var_78_cast_fp16_1, y = var_161_cast_fp16)[name = tensor("op_380_cast_fp16")]; tensor value_5_cast_fp16 = add(x = var_378_cast_fp16, y = var_380_cast_fp16)[name = tensor("value_5_cast_fp16")]; tensor var_383 = const()[name = tensor("op_383"), val = tensor([1, 12, 64, -1])]; tensor var_384_cast_fp16 = reshape(shape = var_383, x = query_5_cast_fp16)[name = tensor("op_384_cast_fp16")]; tensor var_385_to_fp16 = const()[name = tensor("op_385_to_fp16"), val = tensor(0x1p-3)]; tensor var_386_cast_fp16 = mul(x = var_384_cast_fp16, y = var_385_to_fp16)[name = tensor("op_386_cast_fp16")]; tensor var_387 = const()[name = tensor("op_387"), val = tensor([1, 12, 64, -1])]; tensor var_388_cast_fp16 = reshape(shape = var_387, x = key_5_cast_fp16)[name = tensor("op_388_cast_fp16")]; tensor mh_w_7_transpose_x_0 = const()[name = tensor("mh_w_7_transpose_x_0"), val = tensor(true)]; tensor mh_w_7_transpose_y_0 = const()[name = tensor("mh_w_7_transpose_y_0"), val = tensor(false)]; tensor mh_w_7_cast_fp16 = matmul(transpose_x = mh_w_7_transpose_x_0, transpose_y = mh_w_7_transpose_y_0, x = var_386_cast_fp16, y = var_388_cast_fp16)[name = tensor("mh_w_7_cast_fp16")]; tensor mh_w_9_cast_fp16 = add(x = mh_w_7_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_9_cast_fp16")]; tensor var_396_cast_fp16 = softmax(axis = var_310, x = mh_w_9_cast_fp16)[name = tensor("op_396_cast_fp16")]; tensor var_397 = const()[name = tensor("op_397"), val = tensor([1, 12, 64, -1])]; tensor var_398_cast_fp16 = reshape(shape = var_397, x = value_5_cast_fp16)[name = tensor("op_398_cast_fp16")]; tensor attn_5_transpose_x_0 = const()[name = tensor("attn_5_transpose_x_0"), val = tensor(false)]; tensor attn_5_transpose_y_0 = const()[name = tensor("attn_5_transpose_y_0"), val = tensor(true)]; tensor attn_5_cast_fp16 = matmul(transpose_x = attn_5_transpose_x_0, transpose_y = attn_5_transpose_y_0, x = var_398_cast_fp16, y = var_396_cast_fp16)[name = tensor("attn_5_cast_fp16")]; tensor var_401 = const()[name = tensor("op_401"), val = tensor([1, 768, 1, -1])]; tensor input_11_cast_fp16 = reshape(shape = var_401, x = attn_5_cast_fp16)[name = tensor("input_11_cast_fp16")]; tensor var_405 = const()[name = tensor("op_405"), val = tensor([1, 1])]; tensor var_407 = const()[name = tensor("op_407"), val = tensor([1, 1])]; tensor obj_21_pad_type_0 = const()[name = tensor("obj_21_pad_type_0"), val = tensor("custom")]; tensor obj_21_pad_0 = const()[name = tensor("obj_21_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102803712)))]; tensor layers_1_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103983424)))]; tensor obj_21_cast_fp16 = conv(bias = layers_1_self_attn_o_proj_bias_to_fp16, dilations = var_407, groups = var_317, pad = obj_21_pad_0, pad_type = obj_21_pad_type_0, strides = var_405, weight = layers_1_self_attn_o_proj_weight_to_fp16, x = input_11_cast_fp16)[name = tensor("obj_21_cast_fp16")]; tensor inputs_9_cast_fp16 = add(x = inputs_7_cast_fp16, y = obj_21_cast_fp16)[name = tensor("inputs_9_cast_fp16")]; tensor var_417 = const()[name = tensor("op_417"), val = tensor([1])]; tensor channels_mean_9_cast_fp16 = reduce_mean(axes = var_417, keep_dims = var_318, x = inputs_9_cast_fp16)[name = tensor("channels_mean_9_cast_fp16")]; tensor zero_mean_9_cast_fp16 = sub(x = inputs_9_cast_fp16, y = channels_mean_9_cast_fp16)[name = tensor("zero_mean_9_cast_fp16")]; tensor zero_mean_sq_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = zero_mean_9_cast_fp16)[name = tensor("zero_mean_sq_9_cast_fp16")]; tensor var_421 = const()[name = tensor("op_421"), val = tensor([1])]; tensor var_422_cast_fp16 = reduce_mean(axes = var_421, keep_dims = var_318, x = zero_mean_sq_9_cast_fp16)[name = tensor("op_422_cast_fp16")]; tensor var_423_to_fp16 = const()[name = tensor("op_423_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_424_cast_fp16 = add(x = var_422_cast_fp16, y = var_423_to_fp16)[name = tensor("op_424_cast_fp16")]; tensor denom_9_epsilon_0_to_fp16 = const()[name = tensor("denom_9_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_9_cast_fp16 = rsqrt(epsilon = denom_9_epsilon_0_to_fp16, x = var_424_cast_fp16)[name = tensor("denom_9_cast_fp16")]; tensor out_9_cast_fp16 = mul(x = zero_mean_9_cast_fp16, y = denom_9_cast_fp16)[name = tensor("out_9_cast_fp16")]; tensor obj_23_gamma_0_to_fp16 = const()[name = tensor("obj_23_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103985024)))]; tensor obj_23_beta_0_to_fp16 = const()[name = tensor("obj_23_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103986624)))]; tensor obj_23_epsilon_0_to_fp16 = const()[name = tensor("obj_23_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_23_cast_fp16 = batch_norm(beta = obj_23_beta_0_to_fp16, epsilon = obj_23_epsilon_0_to_fp16, gamma = obj_23_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_9_cast_fp16)[name = tensor("obj_23_cast_fp16")]; tensor var_439 = const()[name = tensor("op_439"), val = tensor([1, 1])]; tensor var_441 = const()[name = tensor("op_441"), val = tensor([1, 1])]; tensor query_7_pad_type_0 = const()[name = tensor("query_7_pad_type_0"), val = tensor("custom")]; tensor query_7_pad_0 = const()[name = tensor("query_7_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103988224)))]; tensor layers_1_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105167936)))]; tensor query_7_cast_fp16 = conv(bias = layers_1_encoder_attn_q_proj_bias_to_fp16, dilations = var_441, groups = var_317, pad = query_7_pad_0, pad_type = query_7_pad_type_0, strides = var_439, weight = layers_1_encoder_attn_q_proj_weight_to_fp16, x = obj_23_cast_fp16)[name = tensor("query_7_cast_fp16")]; tensor var_445 = const()[name = tensor("op_445"), val = tensor([1, 1])]; tensor var_447 = const()[name = tensor("op_447"), val = tensor([1, 1])]; tensor key_7_pad_type_0 = const()[name = tensor("key_7_pad_type_0"), val = tensor("custom")]; tensor key_7_pad_0 = const()[name = tensor("key_7_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105169536)))]; tensor key_7_cast_fp16 = conv(dilations = var_447, groups = var_317, pad = key_7_pad_0, pad_type = key_7_pad_type_0, strides = var_445, weight = layers_1_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_7_cast_fp16")]; tensor var_452 = const()[name = tensor("op_452"), val = tensor([1, 1])]; tensor var_454 = const()[name = tensor("op_454"), val = tensor([1, 1])]; tensor value_7_pad_type_0 = const()[name = tensor("value_7_pad_type_0"), val = tensor("custom")]; tensor value_7_pad_0 = const()[name = tensor("value_7_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106349248)))]; tensor layers_1_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107528960)))]; tensor value_7_cast_fp16 = conv(bias = layers_1_encoder_attn_v_proj_bias_to_fp16, dilations = var_454, groups = var_317, pad = value_7_pad_0, pad_type = value_7_pad_type_0, strides = var_452, weight = layers_1_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_7_cast_fp16")]; tensor var_458 = const()[name = tensor("op_458"), val = tensor([1, 12, 64, -1])]; tensor var_459_cast_fp16 = reshape(shape = var_458, x = query_7_cast_fp16)[name = tensor("op_459_cast_fp16")]; tensor var_460_to_fp16 = const()[name = tensor("op_460_to_fp16"), val = tensor(0x1p-3)]; tensor var_461_cast_fp16 = mul(x = var_459_cast_fp16, y = var_460_to_fp16)[name = tensor("op_461_cast_fp16")]; tensor var_462 = const()[name = tensor("op_462"), val = tensor([1, 12, 64, -1])]; tensor var_463_cast_fp16 = reshape(shape = var_462, x = key_7_cast_fp16)[name = tensor("op_463_cast_fp16")]; tensor mh_w_11_transpose_x_0 = const()[name = tensor("mh_w_11_transpose_x_0"), val = tensor(true)]; tensor mh_w_11_transpose_y_0 = const()[name = tensor("mh_w_11_transpose_y_0"), val = tensor(false)]; tensor mh_w_11_cast_fp16 = matmul(transpose_x = mh_w_11_transpose_x_0, transpose_y = mh_w_11_transpose_y_0, x = var_461_cast_fp16, y = var_463_cast_fp16)[name = tensor("mh_w_11_cast_fp16")]; tensor obj_27_cast_fp16 = softmax(axis = var_310, x = mh_w_11_cast_fp16)[name = tensor("obj_27_cast_fp16")]; tensor var_467 = const()[name = tensor("op_467"), val = tensor([1, 12, 64, -1])]; tensor var_468_cast_fp16 = reshape(shape = var_467, x = value_7_cast_fp16)[name = tensor("op_468_cast_fp16")]; tensor attn_7_transpose_x_0 = const()[name = tensor("attn_7_transpose_x_0"), val = tensor(false)]; tensor attn_7_transpose_y_0 = const()[name = tensor("attn_7_transpose_y_0"), val = tensor(true)]; tensor attn_7_cast_fp16 = matmul(transpose_x = attn_7_transpose_x_0, transpose_y = attn_7_transpose_y_0, x = var_468_cast_fp16, y = obj_27_cast_fp16)[name = tensor("attn_7_cast_fp16")]; tensor var_471 = const()[name = tensor("op_471"), val = tensor([1, 768, 1, -1])]; tensor input_13_cast_fp16 = reshape(shape = var_471, x = attn_7_cast_fp16)[name = tensor("input_13_cast_fp16")]; tensor var_475 = const()[name = tensor("op_475"), val = tensor([1, 1])]; tensor var_477 = const()[name = tensor("op_477"), val = tensor([1, 1])]; tensor obj_25_pad_type_0 = const()[name = tensor("obj_25_pad_type_0"), val = tensor("custom")]; tensor obj_25_pad_0 = const()[name = tensor("obj_25_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_1_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107530560)))]; tensor layers_1_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_1_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108710272)))]; tensor obj_25_cast_fp16 = conv(bias = layers_1_encoder_attn_o_proj_bias_to_fp16, dilations = var_477, groups = var_317, pad = obj_25_pad_0, pad_type = obj_25_pad_type_0, strides = var_475, weight = layers_1_encoder_attn_o_proj_weight_to_fp16, x = input_13_cast_fp16)[name = tensor("obj_25_cast_fp16")]; tensor inputs_11_cast_fp16 = add(x = inputs_9_cast_fp16, y = obj_25_cast_fp16)[name = tensor("inputs_11_cast_fp16")]; tensor var_483 = const()[name = tensor("op_483"), val = tensor([1])]; tensor channels_mean_11_cast_fp16 = reduce_mean(axes = var_483, keep_dims = var_318, x = inputs_11_cast_fp16)[name = tensor("channels_mean_11_cast_fp16")]; tensor zero_mean_11_cast_fp16 = sub(x = inputs_11_cast_fp16, y = channels_mean_11_cast_fp16)[name = tensor("zero_mean_11_cast_fp16")]; tensor zero_mean_sq_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = zero_mean_11_cast_fp16)[name = tensor("zero_mean_sq_11_cast_fp16")]; tensor var_487 = const()[name = tensor("op_487"), val = tensor([1])]; tensor var_488_cast_fp16 = reduce_mean(axes = var_487, keep_dims = var_318, x = zero_mean_sq_11_cast_fp16)[name = tensor("op_488_cast_fp16")]; tensor var_489_to_fp16 = const()[name = tensor("op_489_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_490_cast_fp16 = add(x = var_488_cast_fp16, y = var_489_to_fp16)[name = tensor("op_490_cast_fp16")]; tensor denom_11_epsilon_0_to_fp16 = const()[name = tensor("denom_11_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_11_cast_fp16 = rsqrt(epsilon = denom_11_epsilon_0_to_fp16, x = var_490_cast_fp16)[name = tensor("denom_11_cast_fp16")]; tensor out_11_cast_fp16 = mul(x = zero_mean_11_cast_fp16, y = denom_11_cast_fp16)[name = tensor("out_11_cast_fp16")]; tensor input_15_gamma_0_to_fp16 = const()[name = tensor("input_15_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108711872)))]; tensor input_15_beta_0_to_fp16 = const()[name = tensor("input_15_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108713472)))]; tensor input_15_epsilon_0_to_fp16 = const()[name = tensor("input_15_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_15_cast_fp16 = batch_norm(beta = input_15_beta_0_to_fp16, epsilon = input_15_epsilon_0_to_fp16, gamma = input_15_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_11_cast_fp16)[name = tensor("input_15_cast_fp16")]; tensor var_501 = const()[name = tensor("op_501"), val = tensor([1, 1])]; tensor var_503 = const()[name = tensor("op_503"), val = tensor([1, 1])]; tensor input_17_pad_type_0 = const()[name = tensor("input_17_pad_type_0"), val = tensor("custom")]; tensor input_17_pad_0 = const()[name = tensor("input_17_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_fc1_weight_to_fp16 = const()[name = tensor("layers_1_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108715072)))]; tensor layers_1_fc1_bias_to_fp16 = const()[name = tensor("layers_1_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113433728)))]; tensor input_17_cast_fp16 = conv(bias = layers_1_fc1_bias_to_fp16, dilations = var_503, groups = var_317, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = var_501, weight = layers_1_fc1_weight_to_fp16, x = input_15_cast_fp16)[name = tensor("input_17_cast_fp16")]; tensor input_19_mode_0 = const()[name = tensor("input_19_mode_0"), val = tensor("EXACT")]; tensor input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = input_17_cast_fp16)[name = tensor("input_19_cast_fp16")]; tensor var_509 = const()[name = tensor("op_509"), val = tensor([1, 1])]; tensor var_511 = const()[name = tensor("op_511"), val = tensor([1, 1])]; tensor hidden_states_5_pad_type_0 = const()[name = tensor("hidden_states_5_pad_type_0"), val = tensor("custom")]; tensor hidden_states_5_pad_0 = const()[name = tensor("hidden_states_5_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_1_fc2_weight_to_fp16 = const()[name = tensor("layers_1_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113439936)))]; tensor layers_1_fc2_bias_to_fp16 = const()[name = tensor("layers_1_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118158592)))]; tensor hidden_states_5_cast_fp16 = conv(bias = layers_1_fc2_bias_to_fp16, dilations = var_511, groups = var_317, pad = hidden_states_5_pad_0, pad_type = hidden_states_5_pad_type_0, strides = var_509, weight = layers_1_fc2_weight_to_fp16, x = input_19_cast_fp16)[name = tensor("hidden_states_5_cast_fp16")]; tensor inputs_13_cast_fp16 = add(x = inputs_11_cast_fp16, y = hidden_states_5_cast_fp16)[name = tensor("inputs_13_cast_fp16")]; tensor var_524 = const()[name = tensor("op_524"), val = tensor(3)]; tensor var_531 = const()[name = tensor("op_531"), val = tensor(1)]; tensor var_532 = const()[name = tensor("op_532"), val = tensor(true)]; tensor var_544 = const()[name = tensor("op_544"), val = tensor([1])]; tensor channels_mean_13_cast_fp16 = reduce_mean(axes = var_544, keep_dims = var_532, x = inputs_13_cast_fp16)[name = tensor("channels_mean_13_cast_fp16")]; tensor zero_mean_13_cast_fp16 = sub(x = inputs_13_cast_fp16, y = channels_mean_13_cast_fp16)[name = tensor("zero_mean_13_cast_fp16")]; tensor zero_mean_sq_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = zero_mean_13_cast_fp16)[name = tensor("zero_mean_sq_13_cast_fp16")]; tensor var_548 = const()[name = tensor("op_548"), val = tensor([1])]; tensor var_549_cast_fp16 = reduce_mean(axes = var_548, keep_dims = var_532, x = zero_mean_sq_13_cast_fp16)[name = tensor("op_549_cast_fp16")]; tensor var_550_to_fp16 = const()[name = tensor("op_550_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_551_cast_fp16 = add(x = var_549_cast_fp16, y = var_550_to_fp16)[name = tensor("op_551_cast_fp16")]; tensor denom_13_epsilon_0_to_fp16 = const()[name = tensor("denom_13_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_13_cast_fp16 = rsqrt(epsilon = denom_13_epsilon_0_to_fp16, x = var_551_cast_fp16)[name = tensor("denom_13_cast_fp16")]; tensor out_13_cast_fp16 = mul(x = zero_mean_13_cast_fp16, y = denom_13_cast_fp16)[name = tensor("out_13_cast_fp16")]; tensor obj_29_gamma_0_to_fp16 = const()[name = tensor("obj_29_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118160192)))]; tensor obj_29_beta_0_to_fp16 = const()[name = tensor("obj_29_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118161792)))]; tensor obj_29_epsilon_0_to_fp16 = const()[name = tensor("obj_29_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_29_cast_fp16 = batch_norm(beta = obj_29_beta_0_to_fp16, epsilon = obj_29_epsilon_0_to_fp16, gamma = obj_29_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_13_cast_fp16)[name = tensor("obj_29_cast_fp16")]; tensor var_566 = const()[name = tensor("op_566"), val = tensor([1, 1])]; tensor var_568 = const()[name = tensor("op_568"), val = tensor([1, 1])]; tensor query_9_pad_type_0 = const()[name = tensor("query_9_pad_type_0"), val = tensor("custom")]; tensor query_9_pad_0 = const()[name = tensor("query_9_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118163392)))]; tensor layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119343104)))]; tensor query_9_cast_fp16 = conv(bias = layers_2_self_attn_q_proj_bias_to_fp16, dilations = var_568, groups = var_531, pad = query_9_pad_0, pad_type = query_9_pad_type_0, strides = var_566, weight = layers_2_self_attn_q_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("query_9_cast_fp16")]; tensor var_572 = const()[name = tensor("op_572"), val = tensor([1, 1])]; tensor var_574 = const()[name = tensor("op_574"), val = tensor([1, 1])]; tensor current_key_5_pad_type_0 = const()[name = tensor("current_key_5_pad_type_0"), val = tensor("custom")]; tensor current_key_5_pad_0 = const()[name = tensor("current_key_5_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119344704)))]; tensor current_key_5_cast_fp16 = conv(dilations = var_574, groups = var_531, pad = current_key_5_pad_0, pad_type = current_key_5_pad_type_0, strides = var_572, weight = layers_2_self_attn_k_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("current_key_5_cast_fp16")]; tensor var_579 = const()[name = tensor("op_579"), val = tensor([1, 1])]; tensor var_581 = const()[name = tensor("op_581"), val = tensor([1, 1])]; tensor current_value_5_pad_type_0 = const()[name = tensor("current_value_5_pad_type_0"), val = tensor("custom")]; tensor current_value_5_pad_0 = const()[name = tensor("current_value_5_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120524416)))]; tensor layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121704128)))]; tensor current_value_5_cast_fp16 = conv(bias = layers_2_self_attn_v_proj_bias_to_fp16, dilations = var_581, groups = var_531, pad = current_value_5_pad_0, pad_type = current_value_5_pad_type_0, strides = var_579, weight = layers_2_self_attn_v_proj_weight_to_fp16, x = obj_29_cast_fp16)[name = tensor("current_value_5_cast_fp16")]; tensor var_588_cast_fp16 = mul(x = current_key_5_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_588_cast_fp16")]; tensor var_590_cast_fp16 = mul(x = var_63_cast_fp16_2, y = var_161_cast_fp16)[name = tensor("op_590_cast_fp16")]; tensor key_9_cast_fp16 = add(x = var_588_cast_fp16, y = var_590_cast_fp16)[name = tensor("key_9_cast_fp16")]; tensor var_592_cast_fp16 = mul(x = current_value_5_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_592_cast_fp16")]; tensor var_594_cast_fp16 = mul(x = var_78_cast_fp16_2, y = var_161_cast_fp16)[name = tensor("op_594_cast_fp16")]; tensor value_9_cast_fp16 = add(x = var_592_cast_fp16, y = var_594_cast_fp16)[name = tensor("value_9_cast_fp16")]; tensor var_597 = const()[name = tensor("op_597"), val = tensor([1, 12, 64, -1])]; tensor var_598_cast_fp16 = reshape(shape = var_597, x = query_9_cast_fp16)[name = tensor("op_598_cast_fp16")]; tensor var_599_to_fp16 = const()[name = tensor("op_599_to_fp16"), val = tensor(0x1p-3)]; tensor var_600_cast_fp16 = mul(x = var_598_cast_fp16, y = var_599_to_fp16)[name = tensor("op_600_cast_fp16")]; tensor var_601 = const()[name = tensor("op_601"), val = tensor([1, 12, 64, -1])]; tensor var_602_cast_fp16 = reshape(shape = var_601, x = key_9_cast_fp16)[name = tensor("op_602_cast_fp16")]; tensor mh_w_13_transpose_x_0 = const()[name = tensor("mh_w_13_transpose_x_0"), val = tensor(true)]; tensor mh_w_13_transpose_y_0 = const()[name = tensor("mh_w_13_transpose_y_0"), val = tensor(false)]; tensor mh_w_13_cast_fp16 = matmul(transpose_x = mh_w_13_transpose_x_0, transpose_y = mh_w_13_transpose_y_0, x = var_600_cast_fp16, y = var_602_cast_fp16)[name = tensor("mh_w_13_cast_fp16")]; tensor mh_w_15_cast_fp16 = add(x = mh_w_13_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_15_cast_fp16")]; tensor var_610_cast_fp16 = softmax(axis = var_524, x = mh_w_15_cast_fp16)[name = tensor("op_610_cast_fp16")]; tensor var_611 = const()[name = tensor("op_611"), val = tensor([1, 12, 64, -1])]; tensor var_612_cast_fp16 = reshape(shape = var_611, x = value_9_cast_fp16)[name = tensor("op_612_cast_fp16")]; tensor attn_9_transpose_x_0 = const()[name = tensor("attn_9_transpose_x_0"), val = tensor(false)]; tensor attn_9_transpose_y_0 = const()[name = tensor("attn_9_transpose_y_0"), val = tensor(true)]; tensor attn_9_cast_fp16 = matmul(transpose_x = attn_9_transpose_x_0, transpose_y = attn_9_transpose_y_0, x = var_612_cast_fp16, y = var_610_cast_fp16)[name = tensor("attn_9_cast_fp16")]; tensor var_615 = const()[name = tensor("op_615"), val = tensor([1, 768, 1, -1])]; tensor input_21_cast_fp16 = reshape(shape = var_615, x = attn_9_cast_fp16)[name = tensor("input_21_cast_fp16")]; tensor var_619 = const()[name = tensor("op_619"), val = tensor([1, 1])]; tensor var_621 = const()[name = tensor("op_621"), val = tensor([1, 1])]; tensor obj_35_pad_type_0 = const()[name = tensor("obj_35_pad_type_0"), val = tensor("custom")]; tensor obj_35_pad_0 = const()[name = tensor("obj_35_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121705728)))]; tensor layers_2_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122885440)))]; tensor obj_35_cast_fp16 = conv(bias = layers_2_self_attn_o_proj_bias_to_fp16, dilations = var_621, groups = var_531, pad = obj_35_pad_0, pad_type = obj_35_pad_type_0, strides = var_619, weight = layers_2_self_attn_o_proj_weight_to_fp16, x = input_21_cast_fp16)[name = tensor("obj_35_cast_fp16")]; tensor inputs_15_cast_fp16 = add(x = inputs_13_cast_fp16, y = obj_35_cast_fp16)[name = tensor("inputs_15_cast_fp16")]; tensor var_631 = const()[name = tensor("op_631"), val = tensor([1])]; tensor channels_mean_15_cast_fp16 = reduce_mean(axes = var_631, keep_dims = var_532, x = inputs_15_cast_fp16)[name = tensor("channels_mean_15_cast_fp16")]; tensor zero_mean_15_cast_fp16 = sub(x = inputs_15_cast_fp16, y = channels_mean_15_cast_fp16)[name = tensor("zero_mean_15_cast_fp16")]; tensor zero_mean_sq_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = zero_mean_15_cast_fp16)[name = tensor("zero_mean_sq_15_cast_fp16")]; tensor var_635 = const()[name = tensor("op_635"), val = tensor([1])]; tensor var_636_cast_fp16 = reduce_mean(axes = var_635, keep_dims = var_532, x = zero_mean_sq_15_cast_fp16)[name = tensor("op_636_cast_fp16")]; tensor var_637_to_fp16 = const()[name = tensor("op_637_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_638_cast_fp16 = add(x = var_636_cast_fp16, y = var_637_to_fp16)[name = tensor("op_638_cast_fp16")]; tensor denom_15_epsilon_0_to_fp16 = const()[name = tensor("denom_15_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_15_cast_fp16 = rsqrt(epsilon = denom_15_epsilon_0_to_fp16, x = var_638_cast_fp16)[name = tensor("denom_15_cast_fp16")]; tensor out_15_cast_fp16 = mul(x = zero_mean_15_cast_fp16, y = denom_15_cast_fp16)[name = tensor("out_15_cast_fp16")]; tensor obj_37_gamma_0_to_fp16 = const()[name = tensor("obj_37_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122887040)))]; tensor obj_37_beta_0_to_fp16 = const()[name = tensor("obj_37_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122888640)))]; tensor obj_37_epsilon_0_to_fp16 = const()[name = tensor("obj_37_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_37_cast_fp16 = batch_norm(beta = obj_37_beta_0_to_fp16, epsilon = obj_37_epsilon_0_to_fp16, gamma = obj_37_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_15_cast_fp16)[name = tensor("obj_37_cast_fp16")]; tensor var_653 = const()[name = tensor("op_653"), val = tensor([1, 1])]; tensor var_655 = const()[name = tensor("op_655"), val = tensor([1, 1])]; tensor query_11_pad_type_0 = const()[name = tensor("query_11_pad_type_0"), val = tensor("custom")]; tensor query_11_pad_0 = const()[name = tensor("query_11_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122890240)))]; tensor layers_2_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124069952)))]; tensor query_11_cast_fp16 = conv(bias = layers_2_encoder_attn_q_proj_bias_to_fp16, dilations = var_655, groups = var_531, pad = query_11_pad_0, pad_type = query_11_pad_type_0, strides = var_653, weight = layers_2_encoder_attn_q_proj_weight_to_fp16, x = obj_37_cast_fp16)[name = tensor("query_11_cast_fp16")]; tensor var_659 = const()[name = tensor("op_659"), val = tensor([1, 1])]; tensor var_661 = const()[name = tensor("op_661"), val = tensor([1, 1])]; tensor key_11_pad_type_0 = const()[name = tensor("key_11_pad_type_0"), val = tensor("custom")]; tensor key_11_pad_0 = const()[name = tensor("key_11_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124071552)))]; tensor key_11_cast_fp16 = conv(dilations = var_661, groups = var_531, pad = key_11_pad_0, pad_type = key_11_pad_type_0, strides = var_659, weight = layers_2_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_11_cast_fp16")]; tensor var_666 = const()[name = tensor("op_666"), val = tensor([1, 1])]; tensor var_668 = const()[name = tensor("op_668"), val = tensor([1, 1])]; tensor value_11_pad_type_0 = const()[name = tensor("value_11_pad_type_0"), val = tensor("custom")]; tensor value_11_pad_0 = const()[name = tensor("value_11_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125251264)))]; tensor layers_2_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126430976)))]; tensor value_11_cast_fp16 = conv(bias = layers_2_encoder_attn_v_proj_bias_to_fp16, dilations = var_668, groups = var_531, pad = value_11_pad_0, pad_type = value_11_pad_type_0, strides = var_666, weight = layers_2_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_11_cast_fp16")]; tensor var_672 = const()[name = tensor("op_672"), val = tensor([1, 12, 64, -1])]; tensor var_673_cast_fp16 = reshape(shape = var_672, x = query_11_cast_fp16)[name = tensor("op_673_cast_fp16")]; tensor var_674_to_fp16 = const()[name = tensor("op_674_to_fp16"), val = tensor(0x1p-3)]; tensor var_675_cast_fp16 = mul(x = var_673_cast_fp16, y = var_674_to_fp16)[name = tensor("op_675_cast_fp16")]; tensor var_676 = const()[name = tensor("op_676"), val = tensor([1, 12, 64, -1])]; tensor var_677_cast_fp16 = reshape(shape = var_676, x = key_11_cast_fp16)[name = tensor("op_677_cast_fp16")]; tensor mh_w_17_transpose_x_0 = const()[name = tensor("mh_w_17_transpose_x_0"), val = tensor(true)]; tensor mh_w_17_transpose_y_0 = const()[name = tensor("mh_w_17_transpose_y_0"), val = tensor(false)]; tensor mh_w_17_cast_fp16 = matmul(transpose_x = mh_w_17_transpose_x_0, transpose_y = mh_w_17_transpose_y_0, x = var_675_cast_fp16, y = var_677_cast_fp16)[name = tensor("mh_w_17_cast_fp16")]; tensor obj_41_cast_fp16 = softmax(axis = var_524, x = mh_w_17_cast_fp16)[name = tensor("obj_41_cast_fp16")]; tensor var_681 = const()[name = tensor("op_681"), val = tensor([1, 12, 64, -1])]; tensor var_682_cast_fp16 = reshape(shape = var_681, x = value_11_cast_fp16)[name = tensor("op_682_cast_fp16")]; tensor attn_11_transpose_x_0 = const()[name = tensor("attn_11_transpose_x_0"), val = tensor(false)]; tensor attn_11_transpose_y_0 = const()[name = tensor("attn_11_transpose_y_0"), val = tensor(true)]; tensor attn_11_cast_fp16 = matmul(transpose_x = attn_11_transpose_x_0, transpose_y = attn_11_transpose_y_0, x = var_682_cast_fp16, y = obj_41_cast_fp16)[name = tensor("attn_11_cast_fp16")]; tensor var_685 = const()[name = tensor("op_685"), val = tensor([1, 768, 1, -1])]; tensor input_23_cast_fp16 = reshape(shape = var_685, x = attn_11_cast_fp16)[name = tensor("input_23_cast_fp16")]; tensor var_689 = const()[name = tensor("op_689"), val = tensor([1, 1])]; tensor var_691 = const()[name = tensor("op_691"), val = tensor([1, 1])]; tensor obj_39_pad_type_0 = const()[name = tensor("obj_39_pad_type_0"), val = tensor("custom")]; tensor obj_39_pad_0 = const()[name = tensor("obj_39_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_2_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126432576)))]; tensor layers_2_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_2_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127612288)))]; tensor obj_39_cast_fp16 = conv(bias = layers_2_encoder_attn_o_proj_bias_to_fp16, dilations = var_691, groups = var_531, pad = obj_39_pad_0, pad_type = obj_39_pad_type_0, strides = var_689, weight = layers_2_encoder_attn_o_proj_weight_to_fp16, x = input_23_cast_fp16)[name = tensor("obj_39_cast_fp16")]; tensor inputs_17_cast_fp16 = add(x = inputs_15_cast_fp16, y = obj_39_cast_fp16)[name = tensor("inputs_17_cast_fp16")]; tensor var_697 = const()[name = tensor("op_697"), val = tensor([1])]; tensor channels_mean_17_cast_fp16 = reduce_mean(axes = var_697, keep_dims = var_532, x = inputs_17_cast_fp16)[name = tensor("channels_mean_17_cast_fp16")]; tensor zero_mean_17_cast_fp16 = sub(x = inputs_17_cast_fp16, y = channels_mean_17_cast_fp16)[name = tensor("zero_mean_17_cast_fp16")]; tensor zero_mean_sq_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = zero_mean_17_cast_fp16)[name = tensor("zero_mean_sq_17_cast_fp16")]; tensor var_701 = const()[name = tensor("op_701"), val = tensor([1])]; tensor var_702_cast_fp16 = reduce_mean(axes = var_701, keep_dims = var_532, x = zero_mean_sq_17_cast_fp16)[name = tensor("op_702_cast_fp16")]; tensor var_703_to_fp16 = const()[name = tensor("op_703_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_704_cast_fp16 = add(x = var_702_cast_fp16, y = var_703_to_fp16)[name = tensor("op_704_cast_fp16")]; tensor denom_17_epsilon_0_to_fp16 = const()[name = tensor("denom_17_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_17_cast_fp16 = rsqrt(epsilon = denom_17_epsilon_0_to_fp16, x = var_704_cast_fp16)[name = tensor("denom_17_cast_fp16")]; tensor out_17_cast_fp16 = mul(x = zero_mean_17_cast_fp16, y = denom_17_cast_fp16)[name = tensor("out_17_cast_fp16")]; tensor input_25_gamma_0_to_fp16 = const()[name = tensor("input_25_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127613888)))]; tensor input_25_beta_0_to_fp16 = const()[name = tensor("input_25_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127615488)))]; tensor input_25_epsilon_0_to_fp16 = const()[name = tensor("input_25_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_25_cast_fp16 = batch_norm(beta = input_25_beta_0_to_fp16, epsilon = input_25_epsilon_0_to_fp16, gamma = input_25_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_17_cast_fp16)[name = tensor("input_25_cast_fp16")]; tensor var_715 = const()[name = tensor("op_715"), val = tensor([1, 1])]; tensor var_717 = const()[name = tensor("op_717"), val = tensor([1, 1])]; tensor input_27_pad_type_0 = const()[name = tensor("input_27_pad_type_0"), val = tensor("custom")]; tensor input_27_pad_0 = const()[name = tensor("input_27_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_fc1_weight_to_fp16 = const()[name = tensor("layers_2_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127617088)))]; tensor layers_2_fc1_bias_to_fp16 = const()[name = tensor("layers_2_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132335744)))]; tensor input_27_cast_fp16 = conv(bias = layers_2_fc1_bias_to_fp16, dilations = var_717, groups = var_531, pad = input_27_pad_0, pad_type = input_27_pad_type_0, strides = var_715, weight = layers_2_fc1_weight_to_fp16, x = input_25_cast_fp16)[name = tensor("input_27_cast_fp16")]; tensor input_29_mode_0 = const()[name = tensor("input_29_mode_0"), val = tensor("EXACT")]; tensor input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; tensor var_723 = const()[name = tensor("op_723"), val = tensor([1, 1])]; tensor var_725 = const()[name = tensor("op_725"), val = tensor([1, 1])]; tensor hidden_states_7_pad_type_0 = const()[name = tensor("hidden_states_7_pad_type_0"), val = tensor("custom")]; tensor hidden_states_7_pad_0 = const()[name = tensor("hidden_states_7_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_2_fc2_weight_to_fp16 = const()[name = tensor("layers_2_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132341952)))]; tensor layers_2_fc2_bias_to_fp16 = const()[name = tensor("layers_2_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137060608)))]; tensor hidden_states_7_cast_fp16 = conv(bias = layers_2_fc2_bias_to_fp16, dilations = var_725, groups = var_531, pad = hidden_states_7_pad_0, pad_type = hidden_states_7_pad_type_0, strides = var_723, weight = layers_2_fc2_weight_to_fp16, x = input_29_cast_fp16)[name = tensor("hidden_states_7_cast_fp16")]; tensor inputs_19_cast_fp16 = add(x = inputs_17_cast_fp16, y = hidden_states_7_cast_fp16)[name = tensor("inputs_19_cast_fp16")]; tensor var_738 = const()[name = tensor("op_738"), val = tensor(3)]; tensor var_745 = const()[name = tensor("op_745"), val = tensor(1)]; tensor var_746 = const()[name = tensor("op_746"), val = tensor(true)]; tensor var_758 = const()[name = tensor("op_758"), val = tensor([1])]; tensor channels_mean_19_cast_fp16 = reduce_mean(axes = var_758, keep_dims = var_746, x = inputs_19_cast_fp16)[name = tensor("channels_mean_19_cast_fp16")]; tensor zero_mean_19_cast_fp16 = sub(x = inputs_19_cast_fp16, y = channels_mean_19_cast_fp16)[name = tensor("zero_mean_19_cast_fp16")]; tensor zero_mean_sq_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = zero_mean_19_cast_fp16)[name = tensor("zero_mean_sq_19_cast_fp16")]; tensor var_762 = const()[name = tensor("op_762"), val = tensor([1])]; tensor var_763_cast_fp16 = reduce_mean(axes = var_762, keep_dims = var_746, x = zero_mean_sq_19_cast_fp16)[name = tensor("op_763_cast_fp16")]; tensor var_764_to_fp16 = const()[name = tensor("op_764_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_765_cast_fp16 = add(x = var_763_cast_fp16, y = var_764_to_fp16)[name = tensor("op_765_cast_fp16")]; tensor denom_19_epsilon_0_to_fp16 = const()[name = tensor("denom_19_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_19_cast_fp16 = rsqrt(epsilon = denom_19_epsilon_0_to_fp16, x = var_765_cast_fp16)[name = tensor("denom_19_cast_fp16")]; tensor out_19_cast_fp16 = mul(x = zero_mean_19_cast_fp16, y = denom_19_cast_fp16)[name = tensor("out_19_cast_fp16")]; tensor obj_43_gamma_0_to_fp16 = const()[name = tensor("obj_43_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137062208)))]; tensor obj_43_beta_0_to_fp16 = const()[name = tensor("obj_43_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137063808)))]; tensor obj_43_epsilon_0_to_fp16 = const()[name = tensor("obj_43_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_43_cast_fp16 = batch_norm(beta = obj_43_beta_0_to_fp16, epsilon = obj_43_epsilon_0_to_fp16, gamma = obj_43_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_19_cast_fp16)[name = tensor("obj_43_cast_fp16")]; tensor var_780 = const()[name = tensor("op_780"), val = tensor([1, 1])]; tensor var_782 = const()[name = tensor("op_782"), val = tensor([1, 1])]; tensor query_13_pad_type_0 = const()[name = tensor("query_13_pad_type_0"), val = tensor("custom")]; tensor query_13_pad_0 = const()[name = tensor("query_13_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137065408)))]; tensor layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138245120)))]; tensor query_13_cast_fp16 = conv(bias = layers_3_self_attn_q_proj_bias_to_fp16, dilations = var_782, groups = var_745, pad = query_13_pad_0, pad_type = query_13_pad_type_0, strides = var_780, weight = layers_3_self_attn_q_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("query_13_cast_fp16")]; tensor var_786 = const()[name = tensor("op_786"), val = tensor([1, 1])]; tensor var_788 = const()[name = tensor("op_788"), val = tensor([1, 1])]; tensor current_key_7_pad_type_0 = const()[name = tensor("current_key_7_pad_type_0"), val = tensor("custom")]; tensor current_key_7_pad_0 = const()[name = tensor("current_key_7_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138246720)))]; tensor current_key_7_cast_fp16 = conv(dilations = var_788, groups = var_745, pad = current_key_7_pad_0, pad_type = current_key_7_pad_type_0, strides = var_786, weight = layers_3_self_attn_k_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("current_key_7_cast_fp16")]; tensor var_793 = const()[name = tensor("op_793"), val = tensor([1, 1])]; tensor var_795 = const()[name = tensor("op_795"), val = tensor([1, 1])]; tensor current_value_7_pad_type_0 = const()[name = tensor("current_value_7_pad_type_0"), val = tensor("custom")]; tensor current_value_7_pad_0 = const()[name = tensor("current_value_7_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139426432)))]; tensor layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140606144)))]; tensor current_value_7_cast_fp16 = conv(bias = layers_3_self_attn_v_proj_bias_to_fp16, dilations = var_795, groups = var_745, pad = current_value_7_pad_0, pad_type = current_value_7_pad_type_0, strides = var_793, weight = layers_3_self_attn_v_proj_weight_to_fp16, x = obj_43_cast_fp16)[name = tensor("current_value_7_cast_fp16")]; tensor var_802_cast_fp16 = mul(x = current_key_7_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_802_cast_fp16")]; tensor var_804_cast_fp16 = mul(x = var_63_cast_fp16_3, y = var_161_cast_fp16)[name = tensor("op_804_cast_fp16")]; tensor key_13_cast_fp16 = add(x = var_802_cast_fp16, y = var_804_cast_fp16)[name = tensor("key_13_cast_fp16")]; tensor var_806_cast_fp16 = mul(x = current_value_7_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_806_cast_fp16")]; tensor var_808_cast_fp16 = mul(x = var_78_cast_fp16_3, y = var_161_cast_fp16)[name = tensor("op_808_cast_fp16")]; tensor value_13_cast_fp16 = add(x = var_806_cast_fp16, y = var_808_cast_fp16)[name = tensor("value_13_cast_fp16")]; tensor var_811 = const()[name = tensor("op_811"), val = tensor([1, 12, 64, -1])]; tensor var_812_cast_fp16 = reshape(shape = var_811, x = query_13_cast_fp16)[name = tensor("op_812_cast_fp16")]; tensor var_813_to_fp16 = const()[name = tensor("op_813_to_fp16"), val = tensor(0x1p-3)]; tensor var_814_cast_fp16 = mul(x = var_812_cast_fp16, y = var_813_to_fp16)[name = tensor("op_814_cast_fp16")]; tensor var_815 = const()[name = tensor("op_815"), val = tensor([1, 12, 64, -1])]; tensor var_816_cast_fp16 = reshape(shape = var_815, x = key_13_cast_fp16)[name = tensor("op_816_cast_fp16")]; tensor mh_w_19_transpose_x_0 = const()[name = tensor("mh_w_19_transpose_x_0"), val = tensor(true)]; tensor mh_w_19_transpose_y_0 = const()[name = tensor("mh_w_19_transpose_y_0"), val = tensor(false)]; tensor mh_w_19_cast_fp16 = matmul(transpose_x = mh_w_19_transpose_x_0, transpose_y = mh_w_19_transpose_y_0, x = var_814_cast_fp16, y = var_816_cast_fp16)[name = tensor("mh_w_19_cast_fp16")]; tensor mh_w_21_cast_fp16 = add(x = mh_w_19_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_21_cast_fp16")]; tensor var_824_cast_fp16 = softmax(axis = var_738, x = mh_w_21_cast_fp16)[name = tensor("op_824_cast_fp16")]; tensor var_825 = const()[name = tensor("op_825"), val = tensor([1, 12, 64, -1])]; tensor var_826_cast_fp16 = reshape(shape = var_825, x = value_13_cast_fp16)[name = tensor("op_826_cast_fp16")]; tensor attn_13_transpose_x_0 = const()[name = tensor("attn_13_transpose_x_0"), val = tensor(false)]; tensor attn_13_transpose_y_0 = const()[name = tensor("attn_13_transpose_y_0"), val = tensor(true)]; tensor attn_13_cast_fp16 = matmul(transpose_x = attn_13_transpose_x_0, transpose_y = attn_13_transpose_y_0, x = var_826_cast_fp16, y = var_824_cast_fp16)[name = tensor("attn_13_cast_fp16")]; tensor var_829 = const()[name = tensor("op_829"), val = tensor([1, 768, 1, -1])]; tensor input_31_cast_fp16 = reshape(shape = var_829, x = attn_13_cast_fp16)[name = tensor("input_31_cast_fp16")]; tensor var_833 = const()[name = tensor("op_833"), val = tensor([1, 1])]; tensor var_835 = const()[name = tensor("op_835"), val = tensor([1, 1])]; tensor obj_49_pad_type_0 = const()[name = tensor("obj_49_pad_type_0"), val = tensor("custom")]; tensor obj_49_pad_0 = const()[name = tensor("obj_49_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140607744)))]; tensor layers_3_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141787456)))]; tensor obj_49_cast_fp16 = conv(bias = layers_3_self_attn_o_proj_bias_to_fp16, dilations = var_835, groups = var_745, pad = obj_49_pad_0, pad_type = obj_49_pad_type_0, strides = var_833, weight = layers_3_self_attn_o_proj_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("obj_49_cast_fp16")]; tensor inputs_21_cast_fp16 = add(x = inputs_19_cast_fp16, y = obj_49_cast_fp16)[name = tensor("inputs_21_cast_fp16")]; tensor var_845 = const()[name = tensor("op_845"), val = tensor([1])]; tensor channels_mean_21_cast_fp16 = reduce_mean(axes = var_845, keep_dims = var_746, x = inputs_21_cast_fp16)[name = tensor("channels_mean_21_cast_fp16")]; tensor zero_mean_21_cast_fp16 = sub(x = inputs_21_cast_fp16, y = channels_mean_21_cast_fp16)[name = tensor("zero_mean_21_cast_fp16")]; tensor zero_mean_sq_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = zero_mean_21_cast_fp16)[name = tensor("zero_mean_sq_21_cast_fp16")]; tensor var_849 = const()[name = tensor("op_849"), val = tensor([1])]; tensor var_850_cast_fp16 = reduce_mean(axes = var_849, keep_dims = var_746, x = zero_mean_sq_21_cast_fp16)[name = tensor("op_850_cast_fp16")]; tensor var_851_to_fp16 = const()[name = tensor("op_851_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_852_cast_fp16 = add(x = var_850_cast_fp16, y = var_851_to_fp16)[name = tensor("op_852_cast_fp16")]; tensor denom_21_epsilon_0_to_fp16 = const()[name = tensor("denom_21_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_21_cast_fp16 = rsqrt(epsilon = denom_21_epsilon_0_to_fp16, x = var_852_cast_fp16)[name = tensor("denom_21_cast_fp16")]; tensor out_21_cast_fp16 = mul(x = zero_mean_21_cast_fp16, y = denom_21_cast_fp16)[name = tensor("out_21_cast_fp16")]; tensor obj_51_gamma_0_to_fp16 = const()[name = tensor("obj_51_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141789056)))]; tensor obj_51_beta_0_to_fp16 = const()[name = tensor("obj_51_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141790656)))]; tensor obj_51_epsilon_0_to_fp16 = const()[name = tensor("obj_51_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_51_cast_fp16 = batch_norm(beta = obj_51_beta_0_to_fp16, epsilon = obj_51_epsilon_0_to_fp16, gamma = obj_51_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_21_cast_fp16)[name = tensor("obj_51_cast_fp16")]; tensor var_867 = const()[name = tensor("op_867"), val = tensor([1, 1])]; tensor var_869 = const()[name = tensor("op_869"), val = tensor([1, 1])]; tensor query_15_pad_type_0 = const()[name = tensor("query_15_pad_type_0"), val = tensor("custom")]; tensor query_15_pad_0 = const()[name = tensor("query_15_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141792256)))]; tensor layers_3_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142971968)))]; tensor query_15_cast_fp16 = conv(bias = layers_3_encoder_attn_q_proj_bias_to_fp16, dilations = var_869, groups = var_745, pad = query_15_pad_0, pad_type = query_15_pad_type_0, strides = var_867, weight = layers_3_encoder_attn_q_proj_weight_to_fp16, x = obj_51_cast_fp16)[name = tensor("query_15_cast_fp16")]; tensor var_873 = const()[name = tensor("op_873"), val = tensor([1, 1])]; tensor var_875 = const()[name = tensor("op_875"), val = tensor([1, 1])]; tensor key_15_pad_type_0 = const()[name = tensor("key_15_pad_type_0"), val = tensor("custom")]; tensor key_15_pad_0 = const()[name = tensor("key_15_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142973568)))]; tensor key_15_cast_fp16 = conv(dilations = var_875, groups = var_745, pad = key_15_pad_0, pad_type = key_15_pad_type_0, strides = var_873, weight = layers_3_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_15_cast_fp16")]; tensor var_880 = const()[name = tensor("op_880"), val = tensor([1, 1])]; tensor var_882 = const()[name = tensor("op_882"), val = tensor([1, 1])]; tensor value_15_pad_type_0 = const()[name = tensor("value_15_pad_type_0"), val = tensor("custom")]; tensor value_15_pad_0 = const()[name = tensor("value_15_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(144153280)))]; tensor layers_3_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145332992)))]; tensor value_15_cast_fp16 = conv(bias = layers_3_encoder_attn_v_proj_bias_to_fp16, dilations = var_882, groups = var_745, pad = value_15_pad_0, pad_type = value_15_pad_type_0, strides = var_880, weight = layers_3_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_15_cast_fp16")]; tensor var_886 = const()[name = tensor("op_886"), val = tensor([1, 12, 64, -1])]; tensor var_887_cast_fp16 = reshape(shape = var_886, x = query_15_cast_fp16)[name = tensor("op_887_cast_fp16")]; tensor var_888_to_fp16 = const()[name = tensor("op_888_to_fp16"), val = tensor(0x1p-3)]; tensor var_889_cast_fp16 = mul(x = var_887_cast_fp16, y = var_888_to_fp16)[name = tensor("op_889_cast_fp16")]; tensor var_890 = const()[name = tensor("op_890"), val = tensor([1, 12, 64, -1])]; tensor var_891_cast_fp16 = reshape(shape = var_890, x = key_15_cast_fp16)[name = tensor("op_891_cast_fp16")]; tensor mh_w_23_transpose_x_0 = const()[name = tensor("mh_w_23_transpose_x_0"), val = tensor(true)]; tensor mh_w_23_transpose_y_0 = const()[name = tensor("mh_w_23_transpose_y_0"), val = tensor(false)]; tensor mh_w_23_cast_fp16 = matmul(transpose_x = mh_w_23_transpose_x_0, transpose_y = mh_w_23_transpose_y_0, x = var_889_cast_fp16, y = var_891_cast_fp16)[name = tensor("mh_w_23_cast_fp16")]; tensor obj_55_cast_fp16 = softmax(axis = var_738, x = mh_w_23_cast_fp16)[name = tensor("obj_55_cast_fp16")]; tensor var_895 = const()[name = tensor("op_895"), val = tensor([1, 12, 64, -1])]; tensor var_896_cast_fp16 = reshape(shape = var_895, x = value_15_cast_fp16)[name = tensor("op_896_cast_fp16")]; tensor attn_15_transpose_x_0 = const()[name = tensor("attn_15_transpose_x_0"), val = tensor(false)]; tensor attn_15_transpose_y_0 = const()[name = tensor("attn_15_transpose_y_0"), val = tensor(true)]; tensor attn_15_cast_fp16 = matmul(transpose_x = attn_15_transpose_x_0, transpose_y = attn_15_transpose_y_0, x = var_896_cast_fp16, y = obj_55_cast_fp16)[name = tensor("attn_15_cast_fp16")]; tensor var_899 = const()[name = tensor("op_899"), val = tensor([1, 768, 1, -1])]; tensor input_33_cast_fp16 = reshape(shape = var_899, x = attn_15_cast_fp16)[name = tensor("input_33_cast_fp16")]; tensor var_903 = const()[name = tensor("op_903"), val = tensor([1, 1])]; tensor var_905 = const()[name = tensor("op_905"), val = tensor([1, 1])]; tensor obj_53_pad_type_0 = const()[name = tensor("obj_53_pad_type_0"), val = tensor("custom")]; tensor obj_53_pad_0 = const()[name = tensor("obj_53_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_3_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145334592)))]; tensor layers_3_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_3_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146514304)))]; tensor obj_53_cast_fp16 = conv(bias = layers_3_encoder_attn_o_proj_bias_to_fp16, dilations = var_905, groups = var_745, pad = obj_53_pad_0, pad_type = obj_53_pad_type_0, strides = var_903, weight = layers_3_encoder_attn_o_proj_weight_to_fp16, x = input_33_cast_fp16)[name = tensor("obj_53_cast_fp16")]; tensor inputs_23_cast_fp16 = add(x = inputs_21_cast_fp16, y = obj_53_cast_fp16)[name = tensor("inputs_23_cast_fp16")]; tensor var_911 = const()[name = tensor("op_911"), val = tensor([1])]; tensor channels_mean_23_cast_fp16 = reduce_mean(axes = var_911, keep_dims = var_746, x = inputs_23_cast_fp16)[name = tensor("channels_mean_23_cast_fp16")]; tensor zero_mean_23_cast_fp16 = sub(x = inputs_23_cast_fp16, y = channels_mean_23_cast_fp16)[name = tensor("zero_mean_23_cast_fp16")]; tensor zero_mean_sq_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = zero_mean_23_cast_fp16)[name = tensor("zero_mean_sq_23_cast_fp16")]; tensor var_915 = const()[name = tensor("op_915"), val = tensor([1])]; tensor var_916_cast_fp16 = reduce_mean(axes = var_915, keep_dims = var_746, x = zero_mean_sq_23_cast_fp16)[name = tensor("op_916_cast_fp16")]; tensor var_917_to_fp16 = const()[name = tensor("op_917_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_918_cast_fp16 = add(x = var_916_cast_fp16, y = var_917_to_fp16)[name = tensor("op_918_cast_fp16")]; tensor denom_23_epsilon_0_to_fp16 = const()[name = tensor("denom_23_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_23_cast_fp16 = rsqrt(epsilon = denom_23_epsilon_0_to_fp16, x = var_918_cast_fp16)[name = tensor("denom_23_cast_fp16")]; tensor out_23_cast_fp16 = mul(x = zero_mean_23_cast_fp16, y = denom_23_cast_fp16)[name = tensor("out_23_cast_fp16")]; tensor input_35_gamma_0_to_fp16 = const()[name = tensor("input_35_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146515904)))]; tensor input_35_beta_0_to_fp16 = const()[name = tensor("input_35_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146517504)))]; tensor input_35_epsilon_0_to_fp16 = const()[name = tensor("input_35_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_35_cast_fp16 = batch_norm(beta = input_35_beta_0_to_fp16, epsilon = input_35_epsilon_0_to_fp16, gamma = input_35_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_23_cast_fp16)[name = tensor("input_35_cast_fp16")]; tensor var_929 = const()[name = tensor("op_929"), val = tensor([1, 1])]; tensor var_931 = const()[name = tensor("op_931"), val = tensor([1, 1])]; tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("custom")]; tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_fc1_weight_to_fp16 = const()[name = tensor("layers_3_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146519104)))]; tensor layers_3_fc1_bias_to_fp16 = const()[name = tensor("layers_3_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151237760)))]; tensor input_37_cast_fp16 = conv(bias = layers_3_fc1_bias_to_fp16, dilations = var_931, groups = var_745, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = var_929, weight = layers_3_fc1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor("input_37_cast_fp16")]; tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("EXACT")]; tensor input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = input_37_cast_fp16)[name = tensor("input_39_cast_fp16")]; tensor var_937 = const()[name = tensor("op_937"), val = tensor([1, 1])]; tensor var_939 = const()[name = tensor("op_939"), val = tensor([1, 1])]; tensor hidden_states_9_pad_type_0 = const()[name = tensor("hidden_states_9_pad_type_0"), val = tensor("custom")]; tensor hidden_states_9_pad_0 = const()[name = tensor("hidden_states_9_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_3_fc2_weight_to_fp16 = const()[name = tensor("layers_3_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151243968)))]; tensor layers_3_fc2_bias_to_fp16 = const()[name = tensor("layers_3_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155962624)))]; tensor hidden_states_9_cast_fp16 = conv(bias = layers_3_fc2_bias_to_fp16, dilations = var_939, groups = var_745, pad = hidden_states_9_pad_0, pad_type = hidden_states_9_pad_type_0, strides = var_937, weight = layers_3_fc2_weight_to_fp16, x = input_39_cast_fp16)[name = tensor("hidden_states_9_cast_fp16")]; tensor inputs_25_cast_fp16 = add(x = inputs_23_cast_fp16, y = hidden_states_9_cast_fp16)[name = tensor("inputs_25_cast_fp16")]; tensor var_952 = const()[name = tensor("op_952"), val = tensor(3)]; tensor var_959 = const()[name = tensor("op_959"), val = tensor(1)]; tensor var_960 = const()[name = tensor("op_960"), val = tensor(true)]; tensor var_972 = const()[name = tensor("op_972"), val = tensor([1])]; tensor channels_mean_25_cast_fp16 = reduce_mean(axes = var_972, keep_dims = var_960, x = inputs_25_cast_fp16)[name = tensor("channels_mean_25_cast_fp16")]; tensor zero_mean_25_cast_fp16 = sub(x = inputs_25_cast_fp16, y = channels_mean_25_cast_fp16)[name = tensor("zero_mean_25_cast_fp16")]; tensor zero_mean_sq_25_cast_fp16 = mul(x = zero_mean_25_cast_fp16, y = zero_mean_25_cast_fp16)[name = tensor("zero_mean_sq_25_cast_fp16")]; tensor var_976 = const()[name = tensor("op_976"), val = tensor([1])]; tensor var_977_cast_fp16 = reduce_mean(axes = var_976, keep_dims = var_960, x = zero_mean_sq_25_cast_fp16)[name = tensor("op_977_cast_fp16")]; tensor var_978_to_fp16 = const()[name = tensor("op_978_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_979_cast_fp16 = add(x = var_977_cast_fp16, y = var_978_to_fp16)[name = tensor("op_979_cast_fp16")]; tensor denom_25_epsilon_0_to_fp16 = const()[name = tensor("denom_25_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_25_cast_fp16 = rsqrt(epsilon = denom_25_epsilon_0_to_fp16, x = var_979_cast_fp16)[name = tensor("denom_25_cast_fp16")]; tensor out_25_cast_fp16 = mul(x = zero_mean_25_cast_fp16, y = denom_25_cast_fp16)[name = tensor("out_25_cast_fp16")]; tensor obj_57_gamma_0_to_fp16 = const()[name = tensor("obj_57_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155964224)))]; tensor obj_57_beta_0_to_fp16 = const()[name = tensor("obj_57_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155965824)))]; tensor obj_57_epsilon_0_to_fp16 = const()[name = tensor("obj_57_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_57_cast_fp16 = batch_norm(beta = obj_57_beta_0_to_fp16, epsilon = obj_57_epsilon_0_to_fp16, gamma = obj_57_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_25_cast_fp16)[name = tensor("obj_57_cast_fp16")]; tensor var_994 = const()[name = tensor("op_994"), val = tensor([1, 1])]; tensor var_996 = const()[name = tensor("op_996"), val = tensor([1, 1])]; tensor query_17_pad_type_0 = const()[name = tensor("query_17_pad_type_0"), val = tensor("custom")]; tensor query_17_pad_0 = const()[name = tensor("query_17_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155967424)))]; tensor layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157147136)))]; tensor query_17_cast_fp16 = conv(bias = layers_4_self_attn_q_proj_bias_to_fp16, dilations = var_996, groups = var_959, pad = query_17_pad_0, pad_type = query_17_pad_type_0, strides = var_994, weight = layers_4_self_attn_q_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("query_17_cast_fp16")]; tensor var_1000 = const()[name = tensor("op_1000"), val = tensor([1, 1])]; tensor var_1002 = const()[name = tensor("op_1002"), val = tensor([1, 1])]; tensor current_key_9_pad_type_0 = const()[name = tensor("current_key_9_pad_type_0"), val = tensor("custom")]; tensor current_key_9_pad_0 = const()[name = tensor("current_key_9_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(157148736)))]; tensor current_key_9_cast_fp16 = conv(dilations = var_1002, groups = var_959, pad = current_key_9_pad_0, pad_type = current_key_9_pad_type_0, strides = var_1000, weight = layers_4_self_attn_k_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("current_key_9_cast_fp16")]; tensor var_1007 = const()[name = tensor("op_1007"), val = tensor([1, 1])]; tensor var_1009 = const()[name = tensor("op_1009"), val = tensor([1, 1])]; tensor current_value_9_pad_type_0 = const()[name = tensor("current_value_9_pad_type_0"), val = tensor("custom")]; tensor current_value_9_pad_0 = const()[name = tensor("current_value_9_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158328448)))]; tensor layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159508160)))]; tensor current_value_9_cast_fp16 = conv(bias = layers_4_self_attn_v_proj_bias_to_fp16, dilations = var_1009, groups = var_959, pad = current_value_9_pad_0, pad_type = current_value_9_pad_type_0, strides = var_1007, weight = layers_4_self_attn_v_proj_weight_to_fp16, x = obj_57_cast_fp16)[name = tensor("current_value_9_cast_fp16")]; tensor var_1016_cast_fp16 = mul(x = current_key_9_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1016_cast_fp16")]; tensor var_1018_cast_fp16 = mul(x = var_63_cast_fp16_4, y = var_161_cast_fp16)[name = tensor("op_1018_cast_fp16")]; tensor key_17_cast_fp16 = add(x = var_1016_cast_fp16, y = var_1018_cast_fp16)[name = tensor("key_17_cast_fp16")]; tensor var_1020_cast_fp16 = mul(x = current_value_9_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1020_cast_fp16")]; tensor var_1022_cast_fp16 = mul(x = var_78_cast_fp16_4, y = var_161_cast_fp16)[name = tensor("op_1022_cast_fp16")]; tensor value_17_cast_fp16 = add(x = var_1020_cast_fp16, y = var_1022_cast_fp16)[name = tensor("value_17_cast_fp16")]; tensor var_1025 = const()[name = tensor("op_1025"), val = tensor([1, 12, 64, -1])]; tensor var_1026_cast_fp16 = reshape(shape = var_1025, x = query_17_cast_fp16)[name = tensor("op_1026_cast_fp16")]; tensor var_1027_to_fp16 = const()[name = tensor("op_1027_to_fp16"), val = tensor(0x1p-3)]; tensor var_1028_cast_fp16 = mul(x = var_1026_cast_fp16, y = var_1027_to_fp16)[name = tensor("op_1028_cast_fp16")]; tensor var_1029 = const()[name = tensor("op_1029"), val = tensor([1, 12, 64, -1])]; tensor var_1030_cast_fp16 = reshape(shape = var_1029, x = key_17_cast_fp16)[name = tensor("op_1030_cast_fp16")]; tensor mh_w_25_transpose_x_0 = const()[name = tensor("mh_w_25_transpose_x_0"), val = tensor(true)]; tensor mh_w_25_transpose_y_0 = const()[name = tensor("mh_w_25_transpose_y_0"), val = tensor(false)]; tensor mh_w_25_cast_fp16 = matmul(transpose_x = mh_w_25_transpose_x_0, transpose_y = mh_w_25_transpose_y_0, x = var_1028_cast_fp16, y = var_1030_cast_fp16)[name = tensor("mh_w_25_cast_fp16")]; tensor mh_w_27_cast_fp16 = add(x = mh_w_25_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_27_cast_fp16")]; tensor var_1038_cast_fp16 = softmax(axis = var_952, x = mh_w_27_cast_fp16)[name = tensor("op_1038_cast_fp16")]; tensor var_1039 = const()[name = tensor("op_1039"), val = tensor([1, 12, 64, -1])]; tensor var_1040_cast_fp16 = reshape(shape = var_1039, x = value_17_cast_fp16)[name = tensor("op_1040_cast_fp16")]; tensor attn_17_transpose_x_0 = const()[name = tensor("attn_17_transpose_x_0"), val = tensor(false)]; tensor attn_17_transpose_y_0 = const()[name = tensor("attn_17_transpose_y_0"), val = tensor(true)]; tensor attn_17_cast_fp16 = matmul(transpose_x = attn_17_transpose_x_0, transpose_y = attn_17_transpose_y_0, x = var_1040_cast_fp16, y = var_1038_cast_fp16)[name = tensor("attn_17_cast_fp16")]; tensor var_1043 = const()[name = tensor("op_1043"), val = tensor([1, 768, 1, -1])]; tensor input_41_cast_fp16 = reshape(shape = var_1043, x = attn_17_cast_fp16)[name = tensor("input_41_cast_fp16")]; tensor var_1047 = const()[name = tensor("op_1047"), val = tensor([1, 1])]; tensor var_1049 = const()[name = tensor("op_1049"), val = tensor([1, 1])]; tensor obj_63_pad_type_0 = const()[name = tensor("obj_63_pad_type_0"), val = tensor("custom")]; tensor obj_63_pad_0 = const()[name = tensor("obj_63_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159509760)))]; tensor layers_4_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160689472)))]; tensor obj_63_cast_fp16 = conv(bias = layers_4_self_attn_o_proj_bias_to_fp16, dilations = var_1049, groups = var_959, pad = obj_63_pad_0, pad_type = obj_63_pad_type_0, strides = var_1047, weight = layers_4_self_attn_o_proj_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("obj_63_cast_fp16")]; tensor inputs_27_cast_fp16 = add(x = inputs_25_cast_fp16, y = obj_63_cast_fp16)[name = tensor("inputs_27_cast_fp16")]; tensor var_1059 = const()[name = tensor("op_1059"), val = tensor([1])]; tensor channels_mean_27_cast_fp16 = reduce_mean(axes = var_1059, keep_dims = var_960, x = inputs_27_cast_fp16)[name = tensor("channels_mean_27_cast_fp16")]; tensor zero_mean_27_cast_fp16 = sub(x = inputs_27_cast_fp16, y = channels_mean_27_cast_fp16)[name = tensor("zero_mean_27_cast_fp16")]; tensor zero_mean_sq_27_cast_fp16 = mul(x = zero_mean_27_cast_fp16, y = zero_mean_27_cast_fp16)[name = tensor("zero_mean_sq_27_cast_fp16")]; tensor var_1063 = const()[name = tensor("op_1063"), val = tensor([1])]; tensor var_1064_cast_fp16 = reduce_mean(axes = var_1063, keep_dims = var_960, x = zero_mean_sq_27_cast_fp16)[name = tensor("op_1064_cast_fp16")]; tensor var_1065_to_fp16 = const()[name = tensor("op_1065_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1066_cast_fp16 = add(x = var_1064_cast_fp16, y = var_1065_to_fp16)[name = tensor("op_1066_cast_fp16")]; tensor denom_27_epsilon_0_to_fp16 = const()[name = tensor("denom_27_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_27_cast_fp16 = rsqrt(epsilon = denom_27_epsilon_0_to_fp16, x = var_1066_cast_fp16)[name = tensor("denom_27_cast_fp16")]; tensor out_27_cast_fp16 = mul(x = zero_mean_27_cast_fp16, y = denom_27_cast_fp16)[name = tensor("out_27_cast_fp16")]; tensor obj_65_gamma_0_to_fp16 = const()[name = tensor("obj_65_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160691072)))]; tensor obj_65_beta_0_to_fp16 = const()[name = tensor("obj_65_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160692672)))]; tensor obj_65_epsilon_0_to_fp16 = const()[name = tensor("obj_65_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_65_cast_fp16 = batch_norm(beta = obj_65_beta_0_to_fp16, epsilon = obj_65_epsilon_0_to_fp16, gamma = obj_65_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_27_cast_fp16)[name = tensor("obj_65_cast_fp16")]; tensor var_1081 = const()[name = tensor("op_1081"), val = tensor([1, 1])]; tensor var_1083 = const()[name = tensor("op_1083"), val = tensor([1, 1])]; tensor query_19_pad_type_0 = const()[name = tensor("query_19_pad_type_0"), val = tensor("custom")]; tensor query_19_pad_0 = const()[name = tensor("query_19_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160694272)))]; tensor layers_4_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161873984)))]; tensor query_19_cast_fp16 = conv(bias = layers_4_encoder_attn_q_proj_bias_to_fp16, dilations = var_1083, groups = var_959, pad = query_19_pad_0, pad_type = query_19_pad_type_0, strides = var_1081, weight = layers_4_encoder_attn_q_proj_weight_to_fp16, x = obj_65_cast_fp16)[name = tensor("query_19_cast_fp16")]; tensor var_1087 = const()[name = tensor("op_1087"), val = tensor([1, 1])]; tensor var_1089 = const()[name = tensor("op_1089"), val = tensor([1, 1])]; tensor key_19_pad_type_0 = const()[name = tensor("key_19_pad_type_0"), val = tensor("custom")]; tensor key_19_pad_0 = const()[name = tensor("key_19_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161875584)))]; tensor key_19_cast_fp16 = conv(dilations = var_1089, groups = var_959, pad = key_19_pad_0, pad_type = key_19_pad_type_0, strides = var_1087, weight = layers_4_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_19_cast_fp16")]; tensor var_1094 = const()[name = tensor("op_1094"), val = tensor([1, 1])]; tensor var_1096 = const()[name = tensor("op_1096"), val = tensor([1, 1])]; tensor value_19_pad_type_0 = const()[name = tensor("value_19_pad_type_0"), val = tensor("custom")]; tensor value_19_pad_0 = const()[name = tensor("value_19_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163055296)))]; tensor layers_4_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164235008)))]; tensor value_19_cast_fp16 = conv(bias = layers_4_encoder_attn_v_proj_bias_to_fp16, dilations = var_1096, groups = var_959, pad = value_19_pad_0, pad_type = value_19_pad_type_0, strides = var_1094, weight = layers_4_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_19_cast_fp16")]; tensor var_1100 = const()[name = tensor("op_1100"), val = tensor([1, 12, 64, -1])]; tensor var_1101_cast_fp16 = reshape(shape = var_1100, x = query_19_cast_fp16)[name = tensor("op_1101_cast_fp16")]; tensor var_1102_to_fp16 = const()[name = tensor("op_1102_to_fp16"), val = tensor(0x1p-3)]; tensor var_1103_cast_fp16 = mul(x = var_1101_cast_fp16, y = var_1102_to_fp16)[name = tensor("op_1103_cast_fp16")]; tensor var_1104 = const()[name = tensor("op_1104"), val = tensor([1, 12, 64, -1])]; tensor var_1105_cast_fp16 = reshape(shape = var_1104, x = key_19_cast_fp16)[name = tensor("op_1105_cast_fp16")]; tensor mh_w_29_transpose_x_0 = const()[name = tensor("mh_w_29_transpose_x_0"), val = tensor(true)]; tensor mh_w_29_transpose_y_0 = const()[name = tensor("mh_w_29_transpose_y_0"), val = tensor(false)]; tensor mh_w_29_cast_fp16 = matmul(transpose_x = mh_w_29_transpose_x_0, transpose_y = mh_w_29_transpose_y_0, x = var_1103_cast_fp16, y = var_1105_cast_fp16)[name = tensor("mh_w_29_cast_fp16")]; tensor obj_69_cast_fp16 = softmax(axis = var_952, x = mh_w_29_cast_fp16)[name = tensor("obj_69_cast_fp16")]; tensor var_1109 = const()[name = tensor("op_1109"), val = tensor([1, 12, 64, -1])]; tensor var_1110_cast_fp16 = reshape(shape = var_1109, x = value_19_cast_fp16)[name = tensor("op_1110_cast_fp16")]; tensor attn_19_transpose_x_0 = const()[name = tensor("attn_19_transpose_x_0"), val = tensor(false)]; tensor attn_19_transpose_y_0 = const()[name = tensor("attn_19_transpose_y_0"), val = tensor(true)]; tensor attn_19_cast_fp16 = matmul(transpose_x = attn_19_transpose_x_0, transpose_y = attn_19_transpose_y_0, x = var_1110_cast_fp16, y = obj_69_cast_fp16)[name = tensor("attn_19_cast_fp16")]; tensor var_1113 = const()[name = tensor("op_1113"), val = tensor([1, 768, 1, -1])]; tensor input_43_cast_fp16 = reshape(shape = var_1113, x = attn_19_cast_fp16)[name = tensor("input_43_cast_fp16")]; tensor var_1117 = const()[name = tensor("op_1117"), val = tensor([1, 1])]; tensor var_1119 = const()[name = tensor("op_1119"), val = tensor([1, 1])]; tensor obj_67_pad_type_0 = const()[name = tensor("obj_67_pad_type_0"), val = tensor("custom")]; tensor obj_67_pad_0 = const()[name = tensor("obj_67_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_4_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164236608)))]; tensor layers_4_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_4_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165416320)))]; tensor obj_67_cast_fp16 = conv(bias = layers_4_encoder_attn_o_proj_bias_to_fp16, dilations = var_1119, groups = var_959, pad = obj_67_pad_0, pad_type = obj_67_pad_type_0, strides = var_1117, weight = layers_4_encoder_attn_o_proj_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("obj_67_cast_fp16")]; tensor inputs_29_cast_fp16 = add(x = inputs_27_cast_fp16, y = obj_67_cast_fp16)[name = tensor("inputs_29_cast_fp16")]; tensor var_1125 = const()[name = tensor("op_1125"), val = tensor([1])]; tensor channels_mean_29_cast_fp16 = reduce_mean(axes = var_1125, keep_dims = var_960, x = inputs_29_cast_fp16)[name = tensor("channels_mean_29_cast_fp16")]; tensor zero_mean_29_cast_fp16 = sub(x = inputs_29_cast_fp16, y = channels_mean_29_cast_fp16)[name = tensor("zero_mean_29_cast_fp16")]; tensor zero_mean_sq_29_cast_fp16 = mul(x = zero_mean_29_cast_fp16, y = zero_mean_29_cast_fp16)[name = tensor("zero_mean_sq_29_cast_fp16")]; tensor var_1129 = const()[name = tensor("op_1129"), val = tensor([1])]; tensor var_1130_cast_fp16 = reduce_mean(axes = var_1129, keep_dims = var_960, x = zero_mean_sq_29_cast_fp16)[name = tensor("op_1130_cast_fp16")]; tensor var_1131_to_fp16 = const()[name = tensor("op_1131_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1132_cast_fp16 = add(x = var_1130_cast_fp16, y = var_1131_to_fp16)[name = tensor("op_1132_cast_fp16")]; tensor denom_29_epsilon_0_to_fp16 = const()[name = tensor("denom_29_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_29_cast_fp16 = rsqrt(epsilon = denom_29_epsilon_0_to_fp16, x = var_1132_cast_fp16)[name = tensor("denom_29_cast_fp16")]; tensor out_29_cast_fp16 = mul(x = zero_mean_29_cast_fp16, y = denom_29_cast_fp16)[name = tensor("out_29_cast_fp16")]; tensor input_45_gamma_0_to_fp16 = const()[name = tensor("input_45_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165417920)))]; tensor input_45_beta_0_to_fp16 = const()[name = tensor("input_45_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165419520)))]; tensor input_45_epsilon_0_to_fp16 = const()[name = tensor("input_45_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_45_cast_fp16 = batch_norm(beta = input_45_beta_0_to_fp16, epsilon = input_45_epsilon_0_to_fp16, gamma = input_45_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_29_cast_fp16)[name = tensor("input_45_cast_fp16")]; tensor var_1143 = const()[name = tensor("op_1143"), val = tensor([1, 1])]; tensor var_1145 = const()[name = tensor("op_1145"), val = tensor([1, 1])]; tensor input_47_pad_type_0 = const()[name = tensor("input_47_pad_type_0"), val = tensor("custom")]; tensor input_47_pad_0 = const()[name = tensor("input_47_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_fc1_weight_to_fp16 = const()[name = tensor("layers_4_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165421120)))]; tensor layers_4_fc1_bias_to_fp16 = const()[name = tensor("layers_4_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170139776)))]; tensor input_47_cast_fp16 = conv(bias = layers_4_fc1_bias_to_fp16, dilations = var_1145, groups = var_959, pad = input_47_pad_0, pad_type = input_47_pad_type_0, strides = var_1143, weight = layers_4_fc1_weight_to_fp16, x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; tensor input_49_mode_0 = const()[name = tensor("input_49_mode_0"), val = tensor("EXACT")]; tensor input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = input_47_cast_fp16)[name = tensor("input_49_cast_fp16")]; tensor var_1151 = const()[name = tensor("op_1151"), val = tensor([1, 1])]; tensor var_1153 = const()[name = tensor("op_1153"), val = tensor([1, 1])]; tensor hidden_states_11_pad_type_0 = const()[name = tensor("hidden_states_11_pad_type_0"), val = tensor("custom")]; tensor hidden_states_11_pad_0 = const()[name = tensor("hidden_states_11_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_4_fc2_weight_to_fp16 = const()[name = tensor("layers_4_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170145984)))]; tensor layers_4_fc2_bias_to_fp16 = const()[name = tensor("layers_4_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174864640)))]; tensor hidden_states_11_cast_fp16 = conv(bias = layers_4_fc2_bias_to_fp16, dilations = var_1153, groups = var_959, pad = hidden_states_11_pad_0, pad_type = hidden_states_11_pad_type_0, strides = var_1151, weight = layers_4_fc2_weight_to_fp16, x = input_49_cast_fp16)[name = tensor("hidden_states_11_cast_fp16")]; tensor inputs_31_cast_fp16 = add(x = inputs_29_cast_fp16, y = hidden_states_11_cast_fp16)[name = tensor("inputs_31_cast_fp16")]; tensor var_1166 = const()[name = tensor("op_1166"), val = tensor(3)]; tensor var_1173 = const()[name = tensor("op_1173"), val = tensor(1)]; tensor var_1174 = const()[name = tensor("op_1174"), val = tensor(true)]; tensor var_1186 = const()[name = tensor("op_1186"), val = tensor([1])]; tensor channels_mean_31_cast_fp16 = reduce_mean(axes = var_1186, keep_dims = var_1174, x = inputs_31_cast_fp16)[name = tensor("channels_mean_31_cast_fp16")]; tensor zero_mean_31_cast_fp16 = sub(x = inputs_31_cast_fp16, y = channels_mean_31_cast_fp16)[name = tensor("zero_mean_31_cast_fp16")]; tensor zero_mean_sq_31_cast_fp16 = mul(x = zero_mean_31_cast_fp16, y = zero_mean_31_cast_fp16)[name = tensor("zero_mean_sq_31_cast_fp16")]; tensor var_1190 = const()[name = tensor("op_1190"), val = tensor([1])]; tensor var_1191_cast_fp16 = reduce_mean(axes = var_1190, keep_dims = var_1174, x = zero_mean_sq_31_cast_fp16)[name = tensor("op_1191_cast_fp16")]; tensor var_1192_to_fp16 = const()[name = tensor("op_1192_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1193_cast_fp16 = add(x = var_1191_cast_fp16, y = var_1192_to_fp16)[name = tensor("op_1193_cast_fp16")]; tensor denom_31_epsilon_0_to_fp16 = const()[name = tensor("denom_31_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_31_cast_fp16 = rsqrt(epsilon = denom_31_epsilon_0_to_fp16, x = var_1193_cast_fp16)[name = tensor("denom_31_cast_fp16")]; tensor out_31_cast_fp16 = mul(x = zero_mean_31_cast_fp16, y = denom_31_cast_fp16)[name = tensor("out_31_cast_fp16")]; tensor obj_71_gamma_0_to_fp16 = const()[name = tensor("obj_71_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174866240)))]; tensor obj_71_beta_0_to_fp16 = const()[name = tensor("obj_71_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174867840)))]; tensor obj_71_epsilon_0_to_fp16 = const()[name = tensor("obj_71_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_71_cast_fp16 = batch_norm(beta = obj_71_beta_0_to_fp16, epsilon = obj_71_epsilon_0_to_fp16, gamma = obj_71_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_31_cast_fp16)[name = tensor("obj_71_cast_fp16")]; tensor var_1208 = const()[name = tensor("op_1208"), val = tensor([1, 1])]; tensor var_1210 = const()[name = tensor("op_1210"), val = tensor([1, 1])]; tensor query_21_pad_type_0 = const()[name = tensor("query_21_pad_type_0"), val = tensor("custom")]; tensor query_21_pad_0 = const()[name = tensor("query_21_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174869440)))]; tensor layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176049152)))]; tensor query_21_cast_fp16 = conv(bias = layers_5_self_attn_q_proj_bias_to_fp16, dilations = var_1210, groups = var_1173, pad = query_21_pad_0, pad_type = query_21_pad_type_0, strides = var_1208, weight = layers_5_self_attn_q_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("query_21_cast_fp16")]; tensor var_1214 = const()[name = tensor("op_1214"), val = tensor([1, 1])]; tensor var_1216 = const()[name = tensor("op_1216"), val = tensor([1, 1])]; tensor current_key_11_pad_type_0 = const()[name = tensor("current_key_11_pad_type_0"), val = tensor("custom")]; tensor current_key_11_pad_0 = const()[name = tensor("current_key_11_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176050752)))]; tensor current_key_11_cast_fp16 = conv(dilations = var_1216, groups = var_1173, pad = current_key_11_pad_0, pad_type = current_key_11_pad_type_0, strides = var_1214, weight = layers_5_self_attn_k_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("current_key_11_cast_fp16")]; tensor var_1221 = const()[name = tensor("op_1221"), val = tensor([1, 1])]; tensor var_1223 = const()[name = tensor("op_1223"), val = tensor([1, 1])]; tensor current_value_11_pad_type_0 = const()[name = tensor("current_value_11_pad_type_0"), val = tensor("custom")]; tensor current_value_11_pad_0 = const()[name = tensor("current_value_11_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177230464)))]; tensor layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178410176)))]; tensor current_value_11_cast_fp16 = conv(bias = layers_5_self_attn_v_proj_bias_to_fp16, dilations = var_1223, groups = var_1173, pad = current_value_11_pad_0, pad_type = current_value_11_pad_type_0, strides = var_1221, weight = layers_5_self_attn_v_proj_weight_to_fp16, x = obj_71_cast_fp16)[name = tensor("current_value_11_cast_fp16")]; tensor var_1230_cast_fp16 = mul(x = current_key_11_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1230_cast_fp16")]; tensor var_1232_cast_fp16 = mul(x = var_63_cast_fp16_5, y = var_161_cast_fp16)[name = tensor("op_1232_cast_fp16")]; tensor key_21_cast_fp16 = add(x = var_1230_cast_fp16, y = var_1232_cast_fp16)[name = tensor("key_21_cast_fp16")]; tensor var_1234_cast_fp16 = mul(x = current_value_11_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1234_cast_fp16")]; tensor var_1236_cast_fp16 = mul(x = var_78_cast_fp16_5, y = var_161_cast_fp16)[name = tensor("op_1236_cast_fp16")]; tensor value_21_cast_fp16 = add(x = var_1234_cast_fp16, y = var_1236_cast_fp16)[name = tensor("value_21_cast_fp16")]; tensor var_1239 = const()[name = tensor("op_1239"), val = tensor([1, 12, 64, -1])]; tensor var_1240_cast_fp16 = reshape(shape = var_1239, x = query_21_cast_fp16)[name = tensor("op_1240_cast_fp16")]; tensor var_1241_to_fp16 = const()[name = tensor("op_1241_to_fp16"), val = tensor(0x1p-3)]; tensor var_1242_cast_fp16 = mul(x = var_1240_cast_fp16, y = var_1241_to_fp16)[name = tensor("op_1242_cast_fp16")]; tensor var_1243 = const()[name = tensor("op_1243"), val = tensor([1, 12, 64, -1])]; tensor var_1244_cast_fp16 = reshape(shape = var_1243, x = key_21_cast_fp16)[name = tensor("op_1244_cast_fp16")]; tensor mh_w_31_transpose_x_0 = const()[name = tensor("mh_w_31_transpose_x_0"), val = tensor(true)]; tensor mh_w_31_transpose_y_0 = const()[name = tensor("mh_w_31_transpose_y_0"), val = tensor(false)]; tensor mh_w_31_cast_fp16 = matmul(transpose_x = mh_w_31_transpose_x_0, transpose_y = mh_w_31_transpose_y_0, x = var_1242_cast_fp16, y = var_1244_cast_fp16)[name = tensor("mh_w_31_cast_fp16")]; tensor mh_w_33_cast_fp16 = add(x = mh_w_31_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_33_cast_fp16")]; tensor var_1252_cast_fp16 = softmax(axis = var_1166, x = mh_w_33_cast_fp16)[name = tensor("op_1252_cast_fp16")]; tensor var_1253 = const()[name = tensor("op_1253"), val = tensor([1, 12, 64, -1])]; tensor var_1254_cast_fp16 = reshape(shape = var_1253, x = value_21_cast_fp16)[name = tensor("op_1254_cast_fp16")]; tensor attn_21_transpose_x_0 = const()[name = tensor("attn_21_transpose_x_0"), val = tensor(false)]; tensor attn_21_transpose_y_0 = const()[name = tensor("attn_21_transpose_y_0"), val = tensor(true)]; tensor attn_21_cast_fp16 = matmul(transpose_x = attn_21_transpose_x_0, transpose_y = attn_21_transpose_y_0, x = var_1254_cast_fp16, y = var_1252_cast_fp16)[name = tensor("attn_21_cast_fp16")]; tensor var_1257 = const()[name = tensor("op_1257"), val = tensor([1, 768, 1, -1])]; tensor input_51_cast_fp16 = reshape(shape = var_1257, x = attn_21_cast_fp16)[name = tensor("input_51_cast_fp16")]; tensor var_1261 = const()[name = tensor("op_1261"), val = tensor([1, 1])]; tensor var_1263 = const()[name = tensor("op_1263"), val = tensor([1, 1])]; tensor obj_77_pad_type_0 = const()[name = tensor("obj_77_pad_type_0"), val = tensor("custom")]; tensor obj_77_pad_0 = const()[name = tensor("obj_77_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178411776)))]; tensor layers_5_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179591488)))]; tensor obj_77_cast_fp16 = conv(bias = layers_5_self_attn_o_proj_bias_to_fp16, dilations = var_1263, groups = var_1173, pad = obj_77_pad_0, pad_type = obj_77_pad_type_0, strides = var_1261, weight = layers_5_self_attn_o_proj_weight_to_fp16, x = input_51_cast_fp16)[name = tensor("obj_77_cast_fp16")]; tensor inputs_33_cast_fp16 = add(x = inputs_31_cast_fp16, y = obj_77_cast_fp16)[name = tensor("inputs_33_cast_fp16")]; tensor var_1273 = const()[name = tensor("op_1273"), val = tensor([1])]; tensor channels_mean_33_cast_fp16 = reduce_mean(axes = var_1273, keep_dims = var_1174, x = inputs_33_cast_fp16)[name = tensor("channels_mean_33_cast_fp16")]; tensor zero_mean_33_cast_fp16 = sub(x = inputs_33_cast_fp16, y = channels_mean_33_cast_fp16)[name = tensor("zero_mean_33_cast_fp16")]; tensor zero_mean_sq_33_cast_fp16 = mul(x = zero_mean_33_cast_fp16, y = zero_mean_33_cast_fp16)[name = tensor("zero_mean_sq_33_cast_fp16")]; tensor var_1277 = const()[name = tensor("op_1277"), val = tensor([1])]; tensor var_1278_cast_fp16 = reduce_mean(axes = var_1277, keep_dims = var_1174, x = zero_mean_sq_33_cast_fp16)[name = tensor("op_1278_cast_fp16")]; tensor var_1279_to_fp16 = const()[name = tensor("op_1279_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1280_cast_fp16 = add(x = var_1278_cast_fp16, y = var_1279_to_fp16)[name = tensor("op_1280_cast_fp16")]; tensor denom_33_epsilon_0_to_fp16 = const()[name = tensor("denom_33_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_33_cast_fp16 = rsqrt(epsilon = denom_33_epsilon_0_to_fp16, x = var_1280_cast_fp16)[name = tensor("denom_33_cast_fp16")]; tensor out_33_cast_fp16 = mul(x = zero_mean_33_cast_fp16, y = denom_33_cast_fp16)[name = tensor("out_33_cast_fp16")]; tensor obj_79_gamma_0_to_fp16 = const()[name = tensor("obj_79_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179593088)))]; tensor obj_79_beta_0_to_fp16 = const()[name = tensor("obj_79_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179594688)))]; tensor obj_79_epsilon_0_to_fp16 = const()[name = tensor("obj_79_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_79_cast_fp16 = batch_norm(beta = obj_79_beta_0_to_fp16, epsilon = obj_79_epsilon_0_to_fp16, gamma = obj_79_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_33_cast_fp16)[name = tensor("obj_79_cast_fp16")]; tensor var_1295 = const()[name = tensor("op_1295"), val = tensor([1, 1])]; tensor var_1297 = const()[name = tensor("op_1297"), val = tensor([1, 1])]; tensor query_23_pad_type_0 = const()[name = tensor("query_23_pad_type_0"), val = tensor("custom")]; tensor query_23_pad_0 = const()[name = tensor("query_23_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179596288)))]; tensor layers_5_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180776000)))]; tensor query_23_cast_fp16 = conv(bias = layers_5_encoder_attn_q_proj_bias_to_fp16, dilations = var_1297, groups = var_1173, pad = query_23_pad_0, pad_type = query_23_pad_type_0, strides = var_1295, weight = layers_5_encoder_attn_q_proj_weight_to_fp16, x = obj_79_cast_fp16)[name = tensor("query_23_cast_fp16")]; tensor var_1301 = const()[name = tensor("op_1301"), val = tensor([1, 1])]; tensor var_1303 = const()[name = tensor("op_1303"), val = tensor([1, 1])]; tensor key_23_pad_type_0 = const()[name = tensor("key_23_pad_type_0"), val = tensor("custom")]; tensor key_23_pad_0 = const()[name = tensor("key_23_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180777600)))]; tensor key_23_cast_fp16 = conv(dilations = var_1303, groups = var_1173, pad = key_23_pad_0, pad_type = key_23_pad_type_0, strides = var_1301, weight = layers_5_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_23_cast_fp16")]; tensor var_1308 = const()[name = tensor("op_1308"), val = tensor([1, 1])]; tensor var_1310 = const()[name = tensor("op_1310"), val = tensor([1, 1])]; tensor value_23_pad_type_0 = const()[name = tensor("value_23_pad_type_0"), val = tensor("custom")]; tensor value_23_pad_0 = const()[name = tensor("value_23_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181957312)))]; tensor layers_5_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183137024)))]; tensor value_23_cast_fp16 = conv(bias = layers_5_encoder_attn_v_proj_bias_to_fp16, dilations = var_1310, groups = var_1173, pad = value_23_pad_0, pad_type = value_23_pad_type_0, strides = var_1308, weight = layers_5_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_23_cast_fp16")]; tensor var_1314 = const()[name = tensor("op_1314"), val = tensor([1, 12, 64, -1])]; tensor var_1315_cast_fp16 = reshape(shape = var_1314, x = query_23_cast_fp16)[name = tensor("op_1315_cast_fp16")]; tensor var_1316_to_fp16 = const()[name = tensor("op_1316_to_fp16"), val = tensor(0x1p-3)]; tensor var_1317_cast_fp16 = mul(x = var_1315_cast_fp16, y = var_1316_to_fp16)[name = tensor("op_1317_cast_fp16")]; tensor var_1318 = const()[name = tensor("op_1318"), val = tensor([1, 12, 64, -1])]; tensor var_1319_cast_fp16 = reshape(shape = var_1318, x = key_23_cast_fp16)[name = tensor("op_1319_cast_fp16")]; tensor mh_w_35_transpose_x_0 = const()[name = tensor("mh_w_35_transpose_x_0"), val = tensor(true)]; tensor mh_w_35_transpose_y_0 = const()[name = tensor("mh_w_35_transpose_y_0"), val = tensor(false)]; tensor mh_w_35_cast_fp16 = matmul(transpose_x = mh_w_35_transpose_x_0, transpose_y = mh_w_35_transpose_y_0, x = var_1317_cast_fp16, y = var_1319_cast_fp16)[name = tensor("mh_w_35_cast_fp16")]; tensor obj_83_cast_fp16 = softmax(axis = var_1166, x = mh_w_35_cast_fp16)[name = tensor("obj_83_cast_fp16")]; tensor var_1323 = const()[name = tensor("op_1323"), val = tensor([1, 12, 64, -1])]; tensor var_1324_cast_fp16 = reshape(shape = var_1323, x = value_23_cast_fp16)[name = tensor("op_1324_cast_fp16")]; tensor attn_23_transpose_x_0 = const()[name = tensor("attn_23_transpose_x_0"), val = tensor(false)]; tensor attn_23_transpose_y_0 = const()[name = tensor("attn_23_transpose_y_0"), val = tensor(true)]; tensor attn_23_cast_fp16 = matmul(transpose_x = attn_23_transpose_x_0, transpose_y = attn_23_transpose_y_0, x = var_1324_cast_fp16, y = obj_83_cast_fp16)[name = tensor("attn_23_cast_fp16")]; tensor var_1327 = const()[name = tensor("op_1327"), val = tensor([1, 768, 1, -1])]; tensor input_53_cast_fp16 = reshape(shape = var_1327, x = attn_23_cast_fp16)[name = tensor("input_53_cast_fp16")]; tensor var_1331 = const()[name = tensor("op_1331"), val = tensor([1, 1])]; tensor var_1333 = const()[name = tensor("op_1333"), val = tensor([1, 1])]; tensor obj_81_pad_type_0 = const()[name = tensor("obj_81_pad_type_0"), val = tensor("custom")]; tensor obj_81_pad_0 = const()[name = tensor("obj_81_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_5_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183138624)))]; tensor layers_5_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_5_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184318336)))]; tensor obj_81_cast_fp16 = conv(bias = layers_5_encoder_attn_o_proj_bias_to_fp16, dilations = var_1333, groups = var_1173, pad = obj_81_pad_0, pad_type = obj_81_pad_type_0, strides = var_1331, weight = layers_5_encoder_attn_o_proj_weight_to_fp16, x = input_53_cast_fp16)[name = tensor("obj_81_cast_fp16")]; tensor inputs_35_cast_fp16 = add(x = inputs_33_cast_fp16, y = obj_81_cast_fp16)[name = tensor("inputs_35_cast_fp16")]; tensor var_1342 = const()[name = tensor("op_1342"), val = tensor([1])]; tensor channels_mean_35_cast_fp16 = reduce_mean(axes = var_1342, keep_dims = var_1174, x = inputs_35_cast_fp16)[name = tensor("channels_mean_35_cast_fp16")]; tensor zero_mean_35_cast_fp16 = sub(x = inputs_35_cast_fp16, y = channels_mean_35_cast_fp16)[name = tensor("zero_mean_35_cast_fp16")]; tensor zero_mean_sq_35_cast_fp16 = mul(x = zero_mean_35_cast_fp16, y = zero_mean_35_cast_fp16)[name = tensor("zero_mean_sq_35_cast_fp16")]; tensor var_1346 = const()[name = tensor("op_1346"), val = tensor([1])]; tensor var_1347_cast_fp16 = reduce_mean(axes = var_1346, keep_dims = var_1174, x = zero_mean_sq_35_cast_fp16)[name = tensor("op_1347_cast_fp16")]; tensor var_1348_to_fp16 = const()[name = tensor("op_1348_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1349_cast_fp16 = add(x = var_1347_cast_fp16, y = var_1348_to_fp16)[name = tensor("op_1349_cast_fp16")]; tensor denom_35_epsilon_0_to_fp16 = const()[name = tensor("denom_35_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_35_cast_fp16 = rsqrt(epsilon = denom_35_epsilon_0_to_fp16, x = var_1349_cast_fp16)[name = tensor("denom_35_cast_fp16")]; tensor out_35_cast_fp16 = mul(x = zero_mean_35_cast_fp16, y = denom_35_cast_fp16)[name = tensor("out_35_cast_fp16")]; tensor input_55_gamma_0_to_fp16 = const()[name = tensor("input_55_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184319936)))]; tensor input_55_beta_0_to_fp16 = const()[name = tensor("input_55_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184321536)))]; tensor input_55_epsilon_0_to_fp16 = const()[name = tensor("input_55_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_55_cast_fp16 = batch_norm(beta = input_55_beta_0_to_fp16, epsilon = input_55_epsilon_0_to_fp16, gamma = input_55_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_35_cast_fp16)[name = tensor("input_55_cast_fp16")]; tensor var_1360 = const()[name = tensor("op_1360"), val = tensor([1, 1])]; tensor var_1362 = const()[name = tensor("op_1362"), val = tensor([1, 1])]; tensor input_57_pad_type_0 = const()[name = tensor("input_57_pad_type_0"), val = tensor("custom")]; tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_fc1_weight_to_fp16 = const()[name = tensor("layers_5_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184323136)))]; tensor layers_5_fc1_bias_to_fp16 = const()[name = tensor("layers_5_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189041792)))]; tensor input_57_cast_fp16 = conv(bias = layers_5_fc1_bias_to_fp16, dilations = var_1362, groups = var_1173, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = var_1360, weight = layers_5_fc1_weight_to_fp16, x = input_55_cast_fp16)[name = tensor("input_57_cast_fp16")]; tensor input_59_mode_0 = const()[name = tensor("input_59_mode_0"), val = tensor("EXACT")]; tensor input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = input_57_cast_fp16)[name = tensor("input_59_cast_fp16")]; tensor var_1368 = const()[name = tensor("op_1368"), val = tensor([1, 1])]; tensor var_1370 = const()[name = tensor("op_1370"), val = tensor([1, 1])]; tensor hidden_states_13_pad_type_0 = const()[name = tensor("hidden_states_13_pad_type_0"), val = tensor("custom")]; tensor hidden_states_13_pad_0 = const()[name = tensor("hidden_states_13_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_5_fc2_weight_to_fp16 = const()[name = tensor("layers_5_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189048000)))]; tensor layers_5_fc2_bias_to_fp16 = const()[name = tensor("layers_5_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193766656)))]; tensor hidden_states_13_cast_fp16 = conv(bias = layers_5_fc2_bias_to_fp16, dilations = var_1370, groups = var_1173, pad = hidden_states_13_pad_0, pad_type = hidden_states_13_pad_type_0, strides = var_1368, weight = layers_5_fc2_weight_to_fp16, x = input_59_cast_fp16)[name = tensor("hidden_states_13_cast_fp16")]; tensor inputs_37_cast_fp16 = add(x = inputs_35_cast_fp16, y = hidden_states_13_cast_fp16)[name = tensor("inputs_37_cast_fp16")]; tensor var_1384 = const()[name = tensor("op_1384"), val = tensor(3)]; tensor var_1391 = const()[name = tensor("op_1391"), val = tensor(1)]; tensor var_1392 = const()[name = tensor("op_1392"), val = tensor(true)]; tensor var_1404 = const()[name = tensor("op_1404"), val = tensor([1])]; tensor channels_mean_37_cast_fp16 = reduce_mean(axes = var_1404, keep_dims = var_1392, x = inputs_37_cast_fp16)[name = tensor("channels_mean_37_cast_fp16")]; tensor zero_mean_37_cast_fp16 = sub(x = inputs_37_cast_fp16, y = channels_mean_37_cast_fp16)[name = tensor("zero_mean_37_cast_fp16")]; tensor zero_mean_sq_37_cast_fp16 = mul(x = zero_mean_37_cast_fp16, y = zero_mean_37_cast_fp16)[name = tensor("zero_mean_sq_37_cast_fp16")]; tensor var_1408 = const()[name = tensor("op_1408"), val = tensor([1])]; tensor var_1409_cast_fp16 = reduce_mean(axes = var_1408, keep_dims = var_1392, x = zero_mean_sq_37_cast_fp16)[name = tensor("op_1409_cast_fp16")]; tensor var_1410_to_fp16 = const()[name = tensor("op_1410_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1411_cast_fp16 = add(x = var_1409_cast_fp16, y = var_1410_to_fp16)[name = tensor("op_1411_cast_fp16")]; tensor denom_37_epsilon_0_to_fp16 = const()[name = tensor("denom_37_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_37_cast_fp16 = rsqrt(epsilon = denom_37_epsilon_0_to_fp16, x = var_1411_cast_fp16)[name = tensor("denom_37_cast_fp16")]; tensor out_37_cast_fp16 = mul(x = zero_mean_37_cast_fp16, y = denom_37_cast_fp16)[name = tensor("out_37_cast_fp16")]; tensor obj_85_gamma_0_to_fp16 = const()[name = tensor("obj_85_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193768256)))]; tensor obj_85_beta_0_to_fp16 = const()[name = tensor("obj_85_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193769856)))]; tensor obj_85_epsilon_0_to_fp16 = const()[name = tensor("obj_85_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_85_cast_fp16 = batch_norm(beta = obj_85_beta_0_to_fp16, epsilon = obj_85_epsilon_0_to_fp16, gamma = obj_85_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_37_cast_fp16)[name = tensor("obj_85_cast_fp16")]; tensor var_1426 = const()[name = tensor("op_1426"), val = tensor([1, 1])]; tensor var_1428 = const()[name = tensor("op_1428"), val = tensor([1, 1])]; tensor query_25_pad_type_0 = const()[name = tensor("query_25_pad_type_0"), val = tensor("custom")]; tensor query_25_pad_0 = const()[name = tensor("query_25_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193771456)))]; tensor layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194951168)))]; tensor query_25_cast_fp16 = conv(bias = layers_6_self_attn_q_proj_bias_to_fp16, dilations = var_1428, groups = var_1391, pad = query_25_pad_0, pad_type = query_25_pad_type_0, strides = var_1426, weight = layers_6_self_attn_q_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("query_25_cast_fp16")]; tensor var_1432 = const()[name = tensor("op_1432"), val = tensor([1, 1])]; tensor var_1434 = const()[name = tensor("op_1434"), val = tensor([1, 1])]; tensor current_key_13_pad_type_0 = const()[name = tensor("current_key_13_pad_type_0"), val = tensor("custom")]; tensor current_key_13_pad_0 = const()[name = tensor("current_key_13_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194952768)))]; tensor current_key_13_cast_fp16 = conv(dilations = var_1434, groups = var_1391, pad = current_key_13_pad_0, pad_type = current_key_13_pad_type_0, strides = var_1432, weight = layers_6_self_attn_k_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("current_key_13_cast_fp16")]; tensor var_1439 = const()[name = tensor("op_1439"), val = tensor([1, 1])]; tensor var_1441 = const()[name = tensor("op_1441"), val = tensor([1, 1])]; tensor current_value_13_pad_type_0 = const()[name = tensor("current_value_13_pad_type_0"), val = tensor("custom")]; tensor current_value_13_pad_0 = const()[name = tensor("current_value_13_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196132480)))]; tensor layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197312192)))]; tensor current_value_13_cast_fp16 = conv(bias = layers_6_self_attn_v_proj_bias_to_fp16, dilations = var_1441, groups = var_1391, pad = current_value_13_pad_0, pad_type = current_value_13_pad_type_0, strides = var_1439, weight = layers_6_self_attn_v_proj_weight_to_fp16, x = obj_85_cast_fp16)[name = tensor("current_value_13_cast_fp16")]; tensor var_1448_cast_fp16 = mul(x = current_key_13_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1448_cast_fp16")]; tensor var_1450_cast_fp16 = mul(x = var_63_cast_fp16_6, y = var_161_cast_fp16)[name = tensor("op_1450_cast_fp16")]; tensor key_25_cast_fp16 = add(x = var_1448_cast_fp16, y = var_1450_cast_fp16)[name = tensor("key_25_cast_fp16")]; tensor var_1452_cast_fp16 = mul(x = current_value_13_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1452_cast_fp16")]; tensor var_1454_cast_fp16 = mul(x = var_78_cast_fp16_6, y = var_161_cast_fp16)[name = tensor("op_1454_cast_fp16")]; tensor value_25_cast_fp16 = add(x = var_1452_cast_fp16, y = var_1454_cast_fp16)[name = tensor("value_25_cast_fp16")]; tensor var_1457 = const()[name = tensor("op_1457"), val = tensor([1, 12, 64, -1])]; tensor var_1458_cast_fp16 = reshape(shape = var_1457, x = query_25_cast_fp16)[name = tensor("op_1458_cast_fp16")]; tensor var_1459_to_fp16 = const()[name = tensor("op_1459_to_fp16"), val = tensor(0x1p-3)]; tensor var_1460_cast_fp16 = mul(x = var_1458_cast_fp16, y = var_1459_to_fp16)[name = tensor("op_1460_cast_fp16")]; tensor var_1461 = const()[name = tensor("op_1461"), val = tensor([1, 12, 64, -1])]; tensor var_1462_cast_fp16 = reshape(shape = var_1461, x = key_25_cast_fp16)[name = tensor("op_1462_cast_fp16")]; tensor mh_w_37_transpose_x_0 = const()[name = tensor("mh_w_37_transpose_x_0"), val = tensor(true)]; tensor mh_w_37_transpose_y_0 = const()[name = tensor("mh_w_37_transpose_y_0"), val = tensor(false)]; tensor mh_w_37_cast_fp16 = matmul(transpose_x = mh_w_37_transpose_x_0, transpose_y = mh_w_37_transpose_y_0, x = var_1460_cast_fp16, y = var_1462_cast_fp16)[name = tensor("mh_w_37_cast_fp16")]; tensor mh_w_39_cast_fp16 = add(x = mh_w_37_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_39_cast_fp16")]; tensor var_1470_cast_fp16 = softmax(axis = var_1384, x = mh_w_39_cast_fp16)[name = tensor("op_1470_cast_fp16")]; tensor var_1471 = const()[name = tensor("op_1471"), val = tensor([1, 12, 64, -1])]; tensor var_1472_cast_fp16 = reshape(shape = var_1471, x = value_25_cast_fp16)[name = tensor("op_1472_cast_fp16")]; tensor attn_25_transpose_x_0 = const()[name = tensor("attn_25_transpose_x_0"), val = tensor(false)]; tensor attn_25_transpose_y_0 = const()[name = tensor("attn_25_transpose_y_0"), val = tensor(true)]; tensor attn_25_cast_fp16 = matmul(transpose_x = attn_25_transpose_x_0, transpose_y = attn_25_transpose_y_0, x = var_1472_cast_fp16, y = var_1470_cast_fp16)[name = tensor("attn_25_cast_fp16")]; tensor var_1475 = const()[name = tensor("op_1475"), val = tensor([1, 768, 1, -1])]; tensor input_61_cast_fp16 = reshape(shape = var_1475, x = attn_25_cast_fp16)[name = tensor("input_61_cast_fp16")]; tensor var_1479 = const()[name = tensor("op_1479"), val = tensor([1, 1])]; tensor var_1481 = const()[name = tensor("op_1481"), val = tensor([1, 1])]; tensor obj_91_pad_type_0 = const()[name = tensor("obj_91_pad_type_0"), val = tensor("custom")]; tensor obj_91_pad_0 = const()[name = tensor("obj_91_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197313792)))]; tensor layers_6_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198493504)))]; tensor obj_91_cast_fp16 = conv(bias = layers_6_self_attn_o_proj_bias_to_fp16, dilations = var_1481, groups = var_1391, pad = obj_91_pad_0, pad_type = obj_91_pad_type_0, strides = var_1479, weight = layers_6_self_attn_o_proj_weight_to_fp16, x = input_61_cast_fp16)[name = tensor("obj_91_cast_fp16")]; tensor inputs_39_cast_fp16 = add(x = inputs_37_cast_fp16, y = obj_91_cast_fp16)[name = tensor("inputs_39_cast_fp16")]; tensor var_1491 = const()[name = tensor("op_1491"), val = tensor([1])]; tensor channels_mean_39_cast_fp16 = reduce_mean(axes = var_1491, keep_dims = var_1392, x = inputs_39_cast_fp16)[name = tensor("channels_mean_39_cast_fp16")]; tensor zero_mean_39_cast_fp16 = sub(x = inputs_39_cast_fp16, y = channels_mean_39_cast_fp16)[name = tensor("zero_mean_39_cast_fp16")]; tensor zero_mean_sq_39_cast_fp16 = mul(x = zero_mean_39_cast_fp16, y = zero_mean_39_cast_fp16)[name = tensor("zero_mean_sq_39_cast_fp16")]; tensor var_1495 = const()[name = tensor("op_1495"), val = tensor([1])]; tensor var_1496_cast_fp16 = reduce_mean(axes = var_1495, keep_dims = var_1392, x = zero_mean_sq_39_cast_fp16)[name = tensor("op_1496_cast_fp16")]; tensor var_1497_to_fp16 = const()[name = tensor("op_1497_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1498_cast_fp16 = add(x = var_1496_cast_fp16, y = var_1497_to_fp16)[name = tensor("op_1498_cast_fp16")]; tensor denom_39_epsilon_0_to_fp16 = const()[name = tensor("denom_39_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_39_cast_fp16 = rsqrt(epsilon = denom_39_epsilon_0_to_fp16, x = var_1498_cast_fp16)[name = tensor("denom_39_cast_fp16")]; tensor out_39_cast_fp16 = mul(x = zero_mean_39_cast_fp16, y = denom_39_cast_fp16)[name = tensor("out_39_cast_fp16")]; tensor obj_93_gamma_0_to_fp16 = const()[name = tensor("obj_93_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198495104)))]; tensor obj_93_beta_0_to_fp16 = const()[name = tensor("obj_93_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198496704)))]; tensor obj_93_epsilon_0_to_fp16 = const()[name = tensor("obj_93_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_93_cast_fp16 = batch_norm(beta = obj_93_beta_0_to_fp16, epsilon = obj_93_epsilon_0_to_fp16, gamma = obj_93_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_39_cast_fp16)[name = tensor("obj_93_cast_fp16")]; tensor var_1513 = const()[name = tensor("op_1513"), val = tensor([1, 1])]; tensor var_1515 = const()[name = tensor("op_1515"), val = tensor([1, 1])]; tensor query_27_pad_type_0 = const()[name = tensor("query_27_pad_type_0"), val = tensor("custom")]; tensor query_27_pad_0 = const()[name = tensor("query_27_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198498304)))]; tensor layers_6_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199678016)))]; tensor query_27_cast_fp16 = conv(bias = layers_6_encoder_attn_q_proj_bias_to_fp16, dilations = var_1515, groups = var_1391, pad = query_27_pad_0, pad_type = query_27_pad_type_0, strides = var_1513, weight = layers_6_encoder_attn_q_proj_weight_to_fp16, x = obj_93_cast_fp16)[name = tensor("query_27_cast_fp16")]; tensor var_1519 = const()[name = tensor("op_1519"), val = tensor([1, 1])]; tensor var_1521 = const()[name = tensor("op_1521"), val = tensor([1, 1])]; tensor key_27_pad_type_0 = const()[name = tensor("key_27_pad_type_0"), val = tensor("custom")]; tensor key_27_pad_0 = const()[name = tensor("key_27_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199679616)))]; tensor key_27_cast_fp16 = conv(dilations = var_1521, groups = var_1391, pad = key_27_pad_0, pad_type = key_27_pad_type_0, strides = var_1519, weight = layers_6_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_27_cast_fp16")]; tensor var_1526 = const()[name = tensor("op_1526"), val = tensor([1, 1])]; tensor var_1528 = const()[name = tensor("op_1528"), val = tensor([1, 1])]; tensor value_27_pad_type_0 = const()[name = tensor("value_27_pad_type_0"), val = tensor("custom")]; tensor value_27_pad_0 = const()[name = tensor("value_27_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200859328)))]; tensor layers_6_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202039040)))]; tensor value_27_cast_fp16 = conv(bias = layers_6_encoder_attn_v_proj_bias_to_fp16, dilations = var_1528, groups = var_1391, pad = value_27_pad_0, pad_type = value_27_pad_type_0, strides = var_1526, weight = layers_6_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_27_cast_fp16")]; tensor var_1532 = const()[name = tensor("op_1532"), val = tensor([1, 12, 64, -1])]; tensor var_1533_cast_fp16 = reshape(shape = var_1532, x = query_27_cast_fp16)[name = tensor("op_1533_cast_fp16")]; tensor var_1534_to_fp16 = const()[name = tensor("op_1534_to_fp16"), val = tensor(0x1p-3)]; tensor var_1535_cast_fp16 = mul(x = var_1533_cast_fp16, y = var_1534_to_fp16)[name = tensor("op_1535_cast_fp16")]; tensor var_1536 = const()[name = tensor("op_1536"), val = tensor([1, 12, 64, -1])]; tensor var_1537_cast_fp16 = reshape(shape = var_1536, x = key_27_cast_fp16)[name = tensor("op_1537_cast_fp16")]; tensor mh_w_41_transpose_x_0 = const()[name = tensor("mh_w_41_transpose_x_0"), val = tensor(true)]; tensor mh_w_41_transpose_y_0 = const()[name = tensor("mh_w_41_transpose_y_0"), val = tensor(false)]; tensor mh_w_41_cast_fp16 = matmul(transpose_x = mh_w_41_transpose_x_0, transpose_y = mh_w_41_transpose_y_0, x = var_1535_cast_fp16, y = var_1537_cast_fp16)[name = tensor("mh_w_41_cast_fp16")]; tensor obj_97_cast_fp16 = softmax(axis = var_1384, x = mh_w_41_cast_fp16)[name = tensor("obj_97_cast_fp16")]; tensor var_1541 = const()[name = tensor("op_1541"), val = tensor([1, 12, 64, -1])]; tensor var_1542_cast_fp16 = reshape(shape = var_1541, x = value_27_cast_fp16)[name = tensor("op_1542_cast_fp16")]; tensor attn_27_transpose_x_0 = const()[name = tensor("attn_27_transpose_x_0"), val = tensor(false)]; tensor attn_27_transpose_y_0 = const()[name = tensor("attn_27_transpose_y_0"), val = tensor(true)]; tensor attn_27_cast_fp16 = matmul(transpose_x = attn_27_transpose_x_0, transpose_y = attn_27_transpose_y_0, x = var_1542_cast_fp16, y = obj_97_cast_fp16)[name = tensor("attn_27_cast_fp16")]; tensor var_1545 = const()[name = tensor("op_1545"), val = tensor([1, 768, 1, -1])]; tensor input_63_cast_fp16 = reshape(shape = var_1545, x = attn_27_cast_fp16)[name = tensor("input_63_cast_fp16")]; tensor var_1549 = const()[name = tensor("op_1549"), val = tensor([1, 1])]; tensor var_1551 = const()[name = tensor("op_1551"), val = tensor([1, 1])]; tensor obj_95_pad_type_0 = const()[name = tensor("obj_95_pad_type_0"), val = tensor("custom")]; tensor obj_95_pad_0 = const()[name = tensor("obj_95_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_6_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202040640)))]; tensor layers_6_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_6_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203220352)))]; tensor obj_95_cast_fp16 = conv(bias = layers_6_encoder_attn_o_proj_bias_to_fp16, dilations = var_1551, groups = var_1391, pad = obj_95_pad_0, pad_type = obj_95_pad_type_0, strides = var_1549, weight = layers_6_encoder_attn_o_proj_weight_to_fp16, x = input_63_cast_fp16)[name = tensor("obj_95_cast_fp16")]; tensor inputs_41_cast_fp16 = add(x = inputs_39_cast_fp16, y = obj_95_cast_fp16)[name = tensor("inputs_41_cast_fp16")]; tensor var_1557 = const()[name = tensor("op_1557"), val = tensor([1])]; tensor channels_mean_41_cast_fp16 = reduce_mean(axes = var_1557, keep_dims = var_1392, x = inputs_41_cast_fp16)[name = tensor("channels_mean_41_cast_fp16")]; tensor zero_mean_41_cast_fp16 = sub(x = inputs_41_cast_fp16, y = channels_mean_41_cast_fp16)[name = tensor("zero_mean_41_cast_fp16")]; tensor zero_mean_sq_41_cast_fp16 = mul(x = zero_mean_41_cast_fp16, y = zero_mean_41_cast_fp16)[name = tensor("zero_mean_sq_41_cast_fp16")]; tensor var_1561 = const()[name = tensor("op_1561"), val = tensor([1])]; tensor var_1562_cast_fp16 = reduce_mean(axes = var_1561, keep_dims = var_1392, x = zero_mean_sq_41_cast_fp16)[name = tensor("op_1562_cast_fp16")]; tensor var_1563_to_fp16 = const()[name = tensor("op_1563_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1564_cast_fp16 = add(x = var_1562_cast_fp16, y = var_1563_to_fp16)[name = tensor("op_1564_cast_fp16")]; tensor denom_41_epsilon_0_to_fp16 = const()[name = tensor("denom_41_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_41_cast_fp16 = rsqrt(epsilon = denom_41_epsilon_0_to_fp16, x = var_1564_cast_fp16)[name = tensor("denom_41_cast_fp16")]; tensor out_41_cast_fp16 = mul(x = zero_mean_41_cast_fp16, y = denom_41_cast_fp16)[name = tensor("out_41_cast_fp16")]; tensor input_65_gamma_0_to_fp16 = const()[name = tensor("input_65_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203221952)))]; tensor input_65_beta_0_to_fp16 = const()[name = tensor("input_65_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203223552)))]; tensor input_65_epsilon_0_to_fp16 = const()[name = tensor("input_65_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_65_cast_fp16 = batch_norm(beta = input_65_beta_0_to_fp16, epsilon = input_65_epsilon_0_to_fp16, gamma = input_65_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_41_cast_fp16)[name = tensor("input_65_cast_fp16")]; tensor var_1575 = const()[name = tensor("op_1575"), val = tensor([1, 1])]; tensor var_1577 = const()[name = tensor("op_1577"), val = tensor([1, 1])]; tensor input_67_pad_type_0 = const()[name = tensor("input_67_pad_type_0"), val = tensor("custom")]; tensor input_67_pad_0 = const()[name = tensor("input_67_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_fc1_weight_to_fp16 = const()[name = tensor("layers_6_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203225152)))]; tensor layers_6_fc1_bias_to_fp16 = const()[name = tensor("layers_6_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207943808)))]; tensor input_67_cast_fp16 = conv(bias = layers_6_fc1_bias_to_fp16, dilations = var_1577, groups = var_1391, pad = input_67_pad_0, pad_type = input_67_pad_type_0, strides = var_1575, weight = layers_6_fc1_weight_to_fp16, x = input_65_cast_fp16)[name = tensor("input_67_cast_fp16")]; tensor input_69_mode_0 = const()[name = tensor("input_69_mode_0"), val = tensor("EXACT")]; tensor input_69_cast_fp16 = gelu(mode = input_69_mode_0, x = input_67_cast_fp16)[name = tensor("input_69_cast_fp16")]; tensor var_1583 = const()[name = tensor("op_1583"), val = tensor([1, 1])]; tensor var_1585 = const()[name = tensor("op_1585"), val = tensor([1, 1])]; tensor hidden_states_15_pad_type_0 = const()[name = tensor("hidden_states_15_pad_type_0"), val = tensor("custom")]; tensor hidden_states_15_pad_0 = const()[name = tensor("hidden_states_15_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_6_fc2_weight_to_fp16 = const()[name = tensor("layers_6_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207950016)))]; tensor layers_6_fc2_bias_to_fp16 = const()[name = tensor("layers_6_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212668672)))]; tensor hidden_states_15_cast_fp16 = conv(bias = layers_6_fc2_bias_to_fp16, dilations = var_1585, groups = var_1391, pad = hidden_states_15_pad_0, pad_type = hidden_states_15_pad_type_0, strides = var_1583, weight = layers_6_fc2_weight_to_fp16, x = input_69_cast_fp16)[name = tensor("hidden_states_15_cast_fp16")]; tensor inputs_43_cast_fp16 = add(x = inputs_41_cast_fp16, y = hidden_states_15_cast_fp16)[name = tensor("inputs_43_cast_fp16")]; tensor var_1598 = const()[name = tensor("op_1598"), val = tensor(3)]; tensor var_1605 = const()[name = tensor("op_1605"), val = tensor(1)]; tensor var_1606 = const()[name = tensor("op_1606"), val = tensor(true)]; tensor var_1618 = const()[name = tensor("op_1618"), val = tensor([1])]; tensor channels_mean_43_cast_fp16 = reduce_mean(axes = var_1618, keep_dims = var_1606, x = inputs_43_cast_fp16)[name = tensor("channels_mean_43_cast_fp16")]; tensor zero_mean_43_cast_fp16 = sub(x = inputs_43_cast_fp16, y = channels_mean_43_cast_fp16)[name = tensor("zero_mean_43_cast_fp16")]; tensor zero_mean_sq_43_cast_fp16 = mul(x = zero_mean_43_cast_fp16, y = zero_mean_43_cast_fp16)[name = tensor("zero_mean_sq_43_cast_fp16")]; tensor var_1622 = const()[name = tensor("op_1622"), val = tensor([1])]; tensor var_1623_cast_fp16 = reduce_mean(axes = var_1622, keep_dims = var_1606, x = zero_mean_sq_43_cast_fp16)[name = tensor("op_1623_cast_fp16")]; tensor var_1624_to_fp16 = const()[name = tensor("op_1624_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1625_cast_fp16 = add(x = var_1623_cast_fp16, y = var_1624_to_fp16)[name = tensor("op_1625_cast_fp16")]; tensor denom_43_epsilon_0_to_fp16 = const()[name = tensor("denom_43_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_43_cast_fp16 = rsqrt(epsilon = denom_43_epsilon_0_to_fp16, x = var_1625_cast_fp16)[name = tensor("denom_43_cast_fp16")]; tensor out_43_cast_fp16 = mul(x = zero_mean_43_cast_fp16, y = denom_43_cast_fp16)[name = tensor("out_43_cast_fp16")]; tensor obj_99_gamma_0_to_fp16 = const()[name = tensor("obj_99_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212670272)))]; tensor obj_99_beta_0_to_fp16 = const()[name = tensor("obj_99_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212671872)))]; tensor obj_99_epsilon_0_to_fp16 = const()[name = tensor("obj_99_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_99_cast_fp16 = batch_norm(beta = obj_99_beta_0_to_fp16, epsilon = obj_99_epsilon_0_to_fp16, gamma = obj_99_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_43_cast_fp16)[name = tensor("obj_99_cast_fp16")]; tensor var_1640 = const()[name = tensor("op_1640"), val = tensor([1, 1])]; tensor var_1642 = const()[name = tensor("op_1642"), val = tensor([1, 1])]; tensor query_29_pad_type_0 = const()[name = tensor("query_29_pad_type_0"), val = tensor("custom")]; tensor query_29_pad_0 = const()[name = tensor("query_29_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212673472)))]; tensor layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213853184)))]; tensor query_29_cast_fp16 = conv(bias = layers_7_self_attn_q_proj_bias_to_fp16, dilations = var_1642, groups = var_1605, pad = query_29_pad_0, pad_type = query_29_pad_type_0, strides = var_1640, weight = layers_7_self_attn_q_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("query_29_cast_fp16")]; tensor var_1646 = const()[name = tensor("op_1646"), val = tensor([1, 1])]; tensor var_1648 = const()[name = tensor("op_1648"), val = tensor([1, 1])]; tensor current_key_15_pad_type_0 = const()[name = tensor("current_key_15_pad_type_0"), val = tensor("custom")]; tensor current_key_15_pad_0 = const()[name = tensor("current_key_15_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213854784)))]; tensor current_key_15_cast_fp16 = conv(dilations = var_1648, groups = var_1605, pad = current_key_15_pad_0, pad_type = current_key_15_pad_type_0, strides = var_1646, weight = layers_7_self_attn_k_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("current_key_15_cast_fp16")]; tensor var_1653 = const()[name = tensor("op_1653"), val = tensor([1, 1])]; tensor var_1655 = const()[name = tensor("op_1655"), val = tensor([1, 1])]; tensor current_value_15_pad_type_0 = const()[name = tensor("current_value_15_pad_type_0"), val = tensor("custom")]; tensor current_value_15_pad_0 = const()[name = tensor("current_value_15_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215034496)))]; tensor layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216214208)))]; tensor current_value_15_cast_fp16 = conv(bias = layers_7_self_attn_v_proj_bias_to_fp16, dilations = var_1655, groups = var_1605, pad = current_value_15_pad_0, pad_type = current_value_15_pad_type_0, strides = var_1653, weight = layers_7_self_attn_v_proj_weight_to_fp16, x = obj_99_cast_fp16)[name = tensor("current_value_15_cast_fp16")]; tensor var_1662_cast_fp16 = mul(x = current_key_15_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1662_cast_fp16")]; tensor var_1664_cast_fp16 = mul(x = var_63_cast_fp16_7, y = var_161_cast_fp16)[name = tensor("op_1664_cast_fp16")]; tensor key_29_cast_fp16 = add(x = var_1662_cast_fp16, y = var_1664_cast_fp16)[name = tensor("key_29_cast_fp16")]; tensor var_1666_cast_fp16 = mul(x = current_value_15_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1666_cast_fp16")]; tensor var_1668_cast_fp16 = mul(x = var_78_cast_fp16_7, y = var_161_cast_fp16)[name = tensor("op_1668_cast_fp16")]; tensor value_29_cast_fp16 = add(x = var_1666_cast_fp16, y = var_1668_cast_fp16)[name = tensor("value_29_cast_fp16")]; tensor var_1671 = const()[name = tensor("op_1671"), val = tensor([1, 12, 64, -1])]; tensor var_1672_cast_fp16 = reshape(shape = var_1671, x = query_29_cast_fp16)[name = tensor("op_1672_cast_fp16")]; tensor var_1673_to_fp16 = const()[name = tensor("op_1673_to_fp16"), val = tensor(0x1p-3)]; tensor var_1674_cast_fp16 = mul(x = var_1672_cast_fp16, y = var_1673_to_fp16)[name = tensor("op_1674_cast_fp16")]; tensor var_1675 = const()[name = tensor("op_1675"), val = tensor([1, 12, 64, -1])]; tensor var_1676_cast_fp16 = reshape(shape = var_1675, x = key_29_cast_fp16)[name = tensor("op_1676_cast_fp16")]; tensor mh_w_43_transpose_x_0 = const()[name = tensor("mh_w_43_transpose_x_0"), val = tensor(true)]; tensor mh_w_43_transpose_y_0 = const()[name = tensor("mh_w_43_transpose_y_0"), val = tensor(false)]; tensor mh_w_43_cast_fp16 = matmul(transpose_x = mh_w_43_transpose_x_0, transpose_y = mh_w_43_transpose_y_0, x = var_1674_cast_fp16, y = var_1676_cast_fp16)[name = tensor("mh_w_43_cast_fp16")]; tensor mh_w_45_cast_fp16 = add(x = mh_w_43_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_45_cast_fp16")]; tensor var_1684_cast_fp16 = softmax(axis = var_1598, x = mh_w_45_cast_fp16)[name = tensor("op_1684_cast_fp16")]; tensor var_1685 = const()[name = tensor("op_1685"), val = tensor([1, 12, 64, -1])]; tensor var_1686_cast_fp16 = reshape(shape = var_1685, x = value_29_cast_fp16)[name = tensor("op_1686_cast_fp16")]; tensor attn_29_transpose_x_0 = const()[name = tensor("attn_29_transpose_x_0"), val = tensor(false)]; tensor attn_29_transpose_y_0 = const()[name = tensor("attn_29_transpose_y_0"), val = tensor(true)]; tensor attn_29_cast_fp16 = matmul(transpose_x = attn_29_transpose_x_0, transpose_y = attn_29_transpose_y_0, x = var_1686_cast_fp16, y = var_1684_cast_fp16)[name = tensor("attn_29_cast_fp16")]; tensor var_1689 = const()[name = tensor("op_1689"), val = tensor([1, 768, 1, -1])]; tensor input_71_cast_fp16 = reshape(shape = var_1689, x = attn_29_cast_fp16)[name = tensor("input_71_cast_fp16")]; tensor var_1693 = const()[name = tensor("op_1693"), val = tensor([1, 1])]; tensor var_1695 = const()[name = tensor("op_1695"), val = tensor([1, 1])]; tensor obj_105_pad_type_0 = const()[name = tensor("obj_105_pad_type_0"), val = tensor("custom")]; tensor obj_105_pad_0 = const()[name = tensor("obj_105_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216215808)))]; tensor layers_7_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217395520)))]; tensor obj_105_cast_fp16 = conv(bias = layers_7_self_attn_o_proj_bias_to_fp16, dilations = var_1695, groups = var_1605, pad = obj_105_pad_0, pad_type = obj_105_pad_type_0, strides = var_1693, weight = layers_7_self_attn_o_proj_weight_to_fp16, x = input_71_cast_fp16)[name = tensor("obj_105_cast_fp16")]; tensor inputs_45_cast_fp16 = add(x = inputs_43_cast_fp16, y = obj_105_cast_fp16)[name = tensor("inputs_45_cast_fp16")]; tensor var_1705 = const()[name = tensor("op_1705"), val = tensor([1])]; tensor channels_mean_45_cast_fp16 = reduce_mean(axes = var_1705, keep_dims = var_1606, x = inputs_45_cast_fp16)[name = tensor("channels_mean_45_cast_fp16")]; tensor zero_mean_45_cast_fp16 = sub(x = inputs_45_cast_fp16, y = channels_mean_45_cast_fp16)[name = tensor("zero_mean_45_cast_fp16")]; tensor zero_mean_sq_45_cast_fp16 = mul(x = zero_mean_45_cast_fp16, y = zero_mean_45_cast_fp16)[name = tensor("zero_mean_sq_45_cast_fp16")]; tensor var_1709 = const()[name = tensor("op_1709"), val = tensor([1])]; tensor var_1710_cast_fp16 = reduce_mean(axes = var_1709, keep_dims = var_1606, x = zero_mean_sq_45_cast_fp16)[name = tensor("op_1710_cast_fp16")]; tensor var_1711_to_fp16 = const()[name = tensor("op_1711_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1712_cast_fp16 = add(x = var_1710_cast_fp16, y = var_1711_to_fp16)[name = tensor("op_1712_cast_fp16")]; tensor denom_45_epsilon_0_to_fp16 = const()[name = tensor("denom_45_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_45_cast_fp16 = rsqrt(epsilon = denom_45_epsilon_0_to_fp16, x = var_1712_cast_fp16)[name = tensor("denom_45_cast_fp16")]; tensor out_45_cast_fp16 = mul(x = zero_mean_45_cast_fp16, y = denom_45_cast_fp16)[name = tensor("out_45_cast_fp16")]; tensor obj_107_gamma_0_to_fp16 = const()[name = tensor("obj_107_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217397120)))]; tensor obj_107_beta_0_to_fp16 = const()[name = tensor("obj_107_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217398720)))]; tensor obj_107_epsilon_0_to_fp16 = const()[name = tensor("obj_107_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_107_cast_fp16 = batch_norm(beta = obj_107_beta_0_to_fp16, epsilon = obj_107_epsilon_0_to_fp16, gamma = obj_107_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_45_cast_fp16)[name = tensor("obj_107_cast_fp16")]; tensor var_1727 = const()[name = tensor("op_1727"), val = tensor([1, 1])]; tensor var_1729 = const()[name = tensor("op_1729"), val = tensor([1, 1])]; tensor query_31_pad_type_0 = const()[name = tensor("query_31_pad_type_0"), val = tensor("custom")]; tensor query_31_pad_0 = const()[name = tensor("query_31_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217400320)))]; tensor layers_7_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218580032)))]; tensor query_31_cast_fp16 = conv(bias = layers_7_encoder_attn_q_proj_bias_to_fp16, dilations = var_1729, groups = var_1605, pad = query_31_pad_0, pad_type = query_31_pad_type_0, strides = var_1727, weight = layers_7_encoder_attn_q_proj_weight_to_fp16, x = obj_107_cast_fp16)[name = tensor("query_31_cast_fp16")]; tensor var_1733 = const()[name = tensor("op_1733"), val = tensor([1, 1])]; tensor var_1735 = const()[name = tensor("op_1735"), val = tensor([1, 1])]; tensor key_31_pad_type_0 = const()[name = tensor("key_31_pad_type_0"), val = tensor("custom")]; tensor key_31_pad_0 = const()[name = tensor("key_31_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(218581632)))]; tensor key_31_cast_fp16 = conv(dilations = var_1735, groups = var_1605, pad = key_31_pad_0, pad_type = key_31_pad_type_0, strides = var_1733, weight = layers_7_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_31_cast_fp16")]; tensor var_1740 = const()[name = tensor("op_1740"), val = tensor([1, 1])]; tensor var_1742 = const()[name = tensor("op_1742"), val = tensor([1, 1])]; tensor value_31_pad_type_0 = const()[name = tensor("value_31_pad_type_0"), val = tensor("custom")]; tensor value_31_pad_0 = const()[name = tensor("value_31_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219761344)))]; tensor layers_7_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220941056)))]; tensor value_31_cast_fp16 = conv(bias = layers_7_encoder_attn_v_proj_bias_to_fp16, dilations = var_1742, groups = var_1605, pad = value_31_pad_0, pad_type = value_31_pad_type_0, strides = var_1740, weight = layers_7_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_31_cast_fp16")]; tensor var_1746 = const()[name = tensor("op_1746"), val = tensor([1, 12, 64, -1])]; tensor var_1747_cast_fp16 = reshape(shape = var_1746, x = query_31_cast_fp16)[name = tensor("op_1747_cast_fp16")]; tensor var_1748_to_fp16 = const()[name = tensor("op_1748_to_fp16"), val = tensor(0x1p-3)]; tensor var_1749_cast_fp16 = mul(x = var_1747_cast_fp16, y = var_1748_to_fp16)[name = tensor("op_1749_cast_fp16")]; tensor var_1750 = const()[name = tensor("op_1750"), val = tensor([1, 12, 64, -1])]; tensor var_1751_cast_fp16 = reshape(shape = var_1750, x = key_31_cast_fp16)[name = tensor("op_1751_cast_fp16")]; tensor mh_w_47_transpose_x_0 = const()[name = tensor("mh_w_47_transpose_x_0"), val = tensor(true)]; tensor mh_w_47_transpose_y_0 = const()[name = tensor("mh_w_47_transpose_y_0"), val = tensor(false)]; tensor mh_w_47_cast_fp16 = matmul(transpose_x = mh_w_47_transpose_x_0, transpose_y = mh_w_47_transpose_y_0, x = var_1749_cast_fp16, y = var_1751_cast_fp16)[name = tensor("mh_w_47_cast_fp16")]; tensor obj_111_cast_fp16 = softmax(axis = var_1598, x = mh_w_47_cast_fp16)[name = tensor("obj_111_cast_fp16")]; tensor var_1755 = const()[name = tensor("op_1755"), val = tensor([1, 12, 64, -1])]; tensor var_1756_cast_fp16 = reshape(shape = var_1755, x = value_31_cast_fp16)[name = tensor("op_1756_cast_fp16")]; tensor attn_31_transpose_x_0 = const()[name = tensor("attn_31_transpose_x_0"), val = tensor(false)]; tensor attn_31_transpose_y_0 = const()[name = tensor("attn_31_transpose_y_0"), val = tensor(true)]; tensor attn_31_cast_fp16 = matmul(transpose_x = attn_31_transpose_x_0, transpose_y = attn_31_transpose_y_0, x = var_1756_cast_fp16, y = obj_111_cast_fp16)[name = tensor("attn_31_cast_fp16")]; tensor var_1759 = const()[name = tensor("op_1759"), val = tensor([1, 768, 1, -1])]; tensor input_73_cast_fp16 = reshape(shape = var_1759, x = attn_31_cast_fp16)[name = tensor("input_73_cast_fp16")]; tensor var_1763 = const()[name = tensor("op_1763"), val = tensor([1, 1])]; tensor var_1765 = const()[name = tensor("op_1765"), val = tensor([1, 1])]; tensor obj_109_pad_type_0 = const()[name = tensor("obj_109_pad_type_0"), val = tensor("custom")]; tensor obj_109_pad_0 = const()[name = tensor("obj_109_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_7_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(220942656)))]; tensor layers_7_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_7_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222122368)))]; tensor obj_109_cast_fp16 = conv(bias = layers_7_encoder_attn_o_proj_bias_to_fp16, dilations = var_1765, groups = var_1605, pad = obj_109_pad_0, pad_type = obj_109_pad_type_0, strides = var_1763, weight = layers_7_encoder_attn_o_proj_weight_to_fp16, x = input_73_cast_fp16)[name = tensor("obj_109_cast_fp16")]; tensor inputs_47_cast_fp16 = add(x = inputs_45_cast_fp16, y = obj_109_cast_fp16)[name = tensor("inputs_47_cast_fp16")]; tensor var_1771 = const()[name = tensor("op_1771"), val = tensor([1])]; tensor channels_mean_47_cast_fp16 = reduce_mean(axes = var_1771, keep_dims = var_1606, x = inputs_47_cast_fp16)[name = tensor("channels_mean_47_cast_fp16")]; tensor zero_mean_47_cast_fp16 = sub(x = inputs_47_cast_fp16, y = channels_mean_47_cast_fp16)[name = tensor("zero_mean_47_cast_fp16")]; tensor zero_mean_sq_47_cast_fp16 = mul(x = zero_mean_47_cast_fp16, y = zero_mean_47_cast_fp16)[name = tensor("zero_mean_sq_47_cast_fp16")]; tensor var_1775 = const()[name = tensor("op_1775"), val = tensor([1])]; tensor var_1776_cast_fp16 = reduce_mean(axes = var_1775, keep_dims = var_1606, x = zero_mean_sq_47_cast_fp16)[name = tensor("op_1776_cast_fp16")]; tensor var_1777_to_fp16 = const()[name = tensor("op_1777_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1778_cast_fp16 = add(x = var_1776_cast_fp16, y = var_1777_to_fp16)[name = tensor("op_1778_cast_fp16")]; tensor denom_47_epsilon_0_to_fp16 = const()[name = tensor("denom_47_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_47_cast_fp16 = rsqrt(epsilon = denom_47_epsilon_0_to_fp16, x = var_1778_cast_fp16)[name = tensor("denom_47_cast_fp16")]; tensor out_47_cast_fp16 = mul(x = zero_mean_47_cast_fp16, y = denom_47_cast_fp16)[name = tensor("out_47_cast_fp16")]; tensor input_75_gamma_0_to_fp16 = const()[name = tensor("input_75_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222123968)))]; tensor input_75_beta_0_to_fp16 = const()[name = tensor("input_75_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222125568)))]; tensor input_75_epsilon_0_to_fp16 = const()[name = tensor("input_75_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_75_cast_fp16 = batch_norm(beta = input_75_beta_0_to_fp16, epsilon = input_75_epsilon_0_to_fp16, gamma = input_75_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_47_cast_fp16)[name = tensor("input_75_cast_fp16")]; tensor var_1789 = const()[name = tensor("op_1789"), val = tensor([1, 1])]; tensor var_1791 = const()[name = tensor("op_1791"), val = tensor([1, 1])]; tensor input_77_pad_type_0 = const()[name = tensor("input_77_pad_type_0"), val = tensor("custom")]; tensor input_77_pad_0 = const()[name = tensor("input_77_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_fc1_weight_to_fp16 = const()[name = tensor("layers_7_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222127168)))]; tensor layers_7_fc1_bias_to_fp16 = const()[name = tensor("layers_7_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226845824)))]; tensor input_77_cast_fp16 = conv(bias = layers_7_fc1_bias_to_fp16, dilations = var_1791, groups = var_1605, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = var_1789, weight = layers_7_fc1_weight_to_fp16, x = input_75_cast_fp16)[name = tensor("input_77_cast_fp16")]; tensor input_79_mode_0 = const()[name = tensor("input_79_mode_0"), val = tensor("EXACT")]; tensor input_79_cast_fp16 = gelu(mode = input_79_mode_0, x = input_77_cast_fp16)[name = tensor("input_79_cast_fp16")]; tensor var_1797 = const()[name = tensor("op_1797"), val = tensor([1, 1])]; tensor var_1799 = const()[name = tensor("op_1799"), val = tensor([1, 1])]; tensor hidden_states_17_pad_type_0 = const()[name = tensor("hidden_states_17_pad_type_0"), val = tensor("custom")]; tensor hidden_states_17_pad_0 = const()[name = tensor("hidden_states_17_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_7_fc2_weight_to_fp16 = const()[name = tensor("layers_7_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226852032)))]; tensor layers_7_fc2_bias_to_fp16 = const()[name = tensor("layers_7_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231570688)))]; tensor hidden_states_17_cast_fp16 = conv(bias = layers_7_fc2_bias_to_fp16, dilations = var_1799, groups = var_1605, pad = hidden_states_17_pad_0, pad_type = hidden_states_17_pad_type_0, strides = var_1797, weight = layers_7_fc2_weight_to_fp16, x = input_79_cast_fp16)[name = tensor("hidden_states_17_cast_fp16")]; tensor inputs_49_cast_fp16 = add(x = inputs_47_cast_fp16, y = hidden_states_17_cast_fp16)[name = tensor("inputs_49_cast_fp16")]; tensor var_1812 = const()[name = tensor("op_1812"), val = tensor(3)]; tensor var_1819 = const()[name = tensor("op_1819"), val = tensor(1)]; tensor var_1820 = const()[name = tensor("op_1820"), val = tensor(true)]; tensor var_1832 = const()[name = tensor("op_1832"), val = tensor([1])]; tensor channels_mean_49_cast_fp16 = reduce_mean(axes = var_1832, keep_dims = var_1820, x = inputs_49_cast_fp16)[name = tensor("channels_mean_49_cast_fp16")]; tensor zero_mean_49_cast_fp16 = sub(x = inputs_49_cast_fp16, y = channels_mean_49_cast_fp16)[name = tensor("zero_mean_49_cast_fp16")]; tensor zero_mean_sq_49_cast_fp16 = mul(x = zero_mean_49_cast_fp16, y = zero_mean_49_cast_fp16)[name = tensor("zero_mean_sq_49_cast_fp16")]; tensor var_1836 = const()[name = tensor("op_1836"), val = tensor([1])]; tensor var_1837_cast_fp16 = reduce_mean(axes = var_1836, keep_dims = var_1820, x = zero_mean_sq_49_cast_fp16)[name = tensor("op_1837_cast_fp16")]; tensor var_1838_to_fp16 = const()[name = tensor("op_1838_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1839_cast_fp16 = add(x = var_1837_cast_fp16, y = var_1838_to_fp16)[name = tensor("op_1839_cast_fp16")]; tensor denom_49_epsilon_0_to_fp16 = const()[name = tensor("denom_49_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_49_cast_fp16 = rsqrt(epsilon = denom_49_epsilon_0_to_fp16, x = var_1839_cast_fp16)[name = tensor("denom_49_cast_fp16")]; tensor out_49_cast_fp16 = mul(x = zero_mean_49_cast_fp16, y = denom_49_cast_fp16)[name = tensor("out_49_cast_fp16")]; tensor obj_113_gamma_0_to_fp16 = const()[name = tensor("obj_113_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231572288)))]; tensor obj_113_beta_0_to_fp16 = const()[name = tensor("obj_113_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231573888)))]; tensor obj_113_epsilon_0_to_fp16 = const()[name = tensor("obj_113_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_113_cast_fp16 = batch_norm(beta = obj_113_beta_0_to_fp16, epsilon = obj_113_epsilon_0_to_fp16, gamma = obj_113_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_49_cast_fp16)[name = tensor("obj_113_cast_fp16")]; tensor var_1854 = const()[name = tensor("op_1854"), val = tensor([1, 1])]; tensor var_1856 = const()[name = tensor("op_1856"), val = tensor([1, 1])]; tensor query_33_pad_type_0 = const()[name = tensor("query_33_pad_type_0"), val = tensor("custom")]; tensor query_33_pad_0 = const()[name = tensor("query_33_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231575488)))]; tensor layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232755200)))]; tensor query_33_cast_fp16 = conv(bias = layers_8_self_attn_q_proj_bias_to_fp16, dilations = var_1856, groups = var_1819, pad = query_33_pad_0, pad_type = query_33_pad_type_0, strides = var_1854, weight = layers_8_self_attn_q_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("query_33_cast_fp16")]; tensor var_1860 = const()[name = tensor("op_1860"), val = tensor([1, 1])]; tensor var_1862 = const()[name = tensor("op_1862"), val = tensor([1, 1])]; tensor current_key_17_pad_type_0 = const()[name = tensor("current_key_17_pad_type_0"), val = tensor("custom")]; tensor current_key_17_pad_0 = const()[name = tensor("current_key_17_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232756800)))]; tensor current_key_17_cast_fp16 = conv(dilations = var_1862, groups = var_1819, pad = current_key_17_pad_0, pad_type = current_key_17_pad_type_0, strides = var_1860, weight = layers_8_self_attn_k_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("current_key_17_cast_fp16")]; tensor var_1867 = const()[name = tensor("op_1867"), val = tensor([1, 1])]; tensor var_1869 = const()[name = tensor("op_1869"), val = tensor([1, 1])]; tensor current_value_17_pad_type_0 = const()[name = tensor("current_value_17_pad_type_0"), val = tensor("custom")]; tensor current_value_17_pad_0 = const()[name = tensor("current_value_17_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233936512)))]; tensor layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235116224)))]; tensor current_value_17_cast_fp16 = conv(bias = layers_8_self_attn_v_proj_bias_to_fp16, dilations = var_1869, groups = var_1819, pad = current_value_17_pad_0, pad_type = current_value_17_pad_type_0, strides = var_1867, weight = layers_8_self_attn_v_proj_weight_to_fp16, x = obj_113_cast_fp16)[name = tensor("current_value_17_cast_fp16")]; tensor var_1876_cast_fp16 = mul(x = current_key_17_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1876_cast_fp16")]; tensor var_1878_cast_fp16 = mul(x = var_63_cast_fp16_8, y = var_161_cast_fp16)[name = tensor("op_1878_cast_fp16")]; tensor key_33_cast_fp16 = add(x = var_1876_cast_fp16, y = var_1878_cast_fp16)[name = tensor("key_33_cast_fp16")]; tensor var_1880_cast_fp16 = mul(x = current_value_17_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_1880_cast_fp16")]; tensor var_1882_cast_fp16 = mul(x = var_78_cast_fp16_8, y = var_161_cast_fp16)[name = tensor("op_1882_cast_fp16")]; tensor value_33_cast_fp16 = add(x = var_1880_cast_fp16, y = var_1882_cast_fp16)[name = tensor("value_33_cast_fp16")]; tensor var_1885 = const()[name = tensor("op_1885"), val = tensor([1, 12, 64, -1])]; tensor var_1886_cast_fp16 = reshape(shape = var_1885, x = query_33_cast_fp16)[name = tensor("op_1886_cast_fp16")]; tensor var_1887_to_fp16 = const()[name = tensor("op_1887_to_fp16"), val = tensor(0x1p-3)]; tensor var_1888_cast_fp16 = mul(x = var_1886_cast_fp16, y = var_1887_to_fp16)[name = tensor("op_1888_cast_fp16")]; tensor var_1889 = const()[name = tensor("op_1889"), val = tensor([1, 12, 64, -1])]; tensor var_1890_cast_fp16 = reshape(shape = var_1889, x = key_33_cast_fp16)[name = tensor("op_1890_cast_fp16")]; tensor mh_w_49_transpose_x_0 = const()[name = tensor("mh_w_49_transpose_x_0"), val = tensor(true)]; tensor mh_w_49_transpose_y_0 = const()[name = tensor("mh_w_49_transpose_y_0"), val = tensor(false)]; tensor mh_w_49_cast_fp16 = matmul(transpose_x = mh_w_49_transpose_x_0, transpose_y = mh_w_49_transpose_y_0, x = var_1888_cast_fp16, y = var_1890_cast_fp16)[name = tensor("mh_w_49_cast_fp16")]; tensor mh_w_51_cast_fp16 = add(x = mh_w_49_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_51_cast_fp16")]; tensor var_1898_cast_fp16 = softmax(axis = var_1812, x = mh_w_51_cast_fp16)[name = tensor("op_1898_cast_fp16")]; tensor var_1899 = const()[name = tensor("op_1899"), val = tensor([1, 12, 64, -1])]; tensor var_1900_cast_fp16 = reshape(shape = var_1899, x = value_33_cast_fp16)[name = tensor("op_1900_cast_fp16")]; tensor attn_33_transpose_x_0 = const()[name = tensor("attn_33_transpose_x_0"), val = tensor(false)]; tensor attn_33_transpose_y_0 = const()[name = tensor("attn_33_transpose_y_0"), val = tensor(true)]; tensor attn_33_cast_fp16 = matmul(transpose_x = attn_33_transpose_x_0, transpose_y = attn_33_transpose_y_0, x = var_1900_cast_fp16, y = var_1898_cast_fp16)[name = tensor("attn_33_cast_fp16")]; tensor var_1903 = const()[name = tensor("op_1903"), val = tensor([1, 768, 1, -1])]; tensor input_81_cast_fp16 = reshape(shape = var_1903, x = attn_33_cast_fp16)[name = tensor("input_81_cast_fp16")]; tensor var_1907 = const()[name = tensor("op_1907"), val = tensor([1, 1])]; tensor var_1909 = const()[name = tensor("op_1909"), val = tensor([1, 1])]; tensor obj_119_pad_type_0 = const()[name = tensor("obj_119_pad_type_0"), val = tensor("custom")]; tensor obj_119_pad_0 = const()[name = tensor("obj_119_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235117824)))]; tensor layers_8_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236297536)))]; tensor obj_119_cast_fp16 = conv(bias = layers_8_self_attn_o_proj_bias_to_fp16, dilations = var_1909, groups = var_1819, pad = obj_119_pad_0, pad_type = obj_119_pad_type_0, strides = var_1907, weight = layers_8_self_attn_o_proj_weight_to_fp16, x = input_81_cast_fp16)[name = tensor("obj_119_cast_fp16")]; tensor inputs_51_cast_fp16 = add(x = inputs_49_cast_fp16, y = obj_119_cast_fp16)[name = tensor("inputs_51_cast_fp16")]; tensor var_1919 = const()[name = tensor("op_1919"), val = tensor([1])]; tensor channels_mean_51_cast_fp16 = reduce_mean(axes = var_1919, keep_dims = var_1820, x = inputs_51_cast_fp16)[name = tensor("channels_mean_51_cast_fp16")]; tensor zero_mean_51_cast_fp16 = sub(x = inputs_51_cast_fp16, y = channels_mean_51_cast_fp16)[name = tensor("zero_mean_51_cast_fp16")]; tensor zero_mean_sq_51_cast_fp16 = mul(x = zero_mean_51_cast_fp16, y = zero_mean_51_cast_fp16)[name = tensor("zero_mean_sq_51_cast_fp16")]; tensor var_1923 = const()[name = tensor("op_1923"), val = tensor([1])]; tensor var_1924_cast_fp16 = reduce_mean(axes = var_1923, keep_dims = var_1820, x = zero_mean_sq_51_cast_fp16)[name = tensor("op_1924_cast_fp16")]; tensor var_1925_to_fp16 = const()[name = tensor("op_1925_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1926_cast_fp16 = add(x = var_1924_cast_fp16, y = var_1925_to_fp16)[name = tensor("op_1926_cast_fp16")]; tensor denom_51_epsilon_0_to_fp16 = const()[name = tensor("denom_51_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_51_cast_fp16 = rsqrt(epsilon = denom_51_epsilon_0_to_fp16, x = var_1926_cast_fp16)[name = tensor("denom_51_cast_fp16")]; tensor out_51_cast_fp16 = mul(x = zero_mean_51_cast_fp16, y = denom_51_cast_fp16)[name = tensor("out_51_cast_fp16")]; tensor obj_121_gamma_0_to_fp16 = const()[name = tensor("obj_121_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236299136)))]; tensor obj_121_beta_0_to_fp16 = const()[name = tensor("obj_121_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236300736)))]; tensor obj_121_epsilon_0_to_fp16 = const()[name = tensor("obj_121_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_121_cast_fp16 = batch_norm(beta = obj_121_beta_0_to_fp16, epsilon = obj_121_epsilon_0_to_fp16, gamma = obj_121_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_51_cast_fp16)[name = tensor("obj_121_cast_fp16")]; tensor var_1941 = const()[name = tensor("op_1941"), val = tensor([1, 1])]; tensor var_1943 = const()[name = tensor("op_1943"), val = tensor([1, 1])]; tensor query_35_pad_type_0 = const()[name = tensor("query_35_pad_type_0"), val = tensor("custom")]; tensor query_35_pad_0 = const()[name = tensor("query_35_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236302336)))]; tensor layers_8_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(237482048)))]; tensor query_35_cast_fp16 = conv(bias = layers_8_encoder_attn_q_proj_bias_to_fp16, dilations = var_1943, groups = var_1819, pad = query_35_pad_0, pad_type = query_35_pad_type_0, strides = var_1941, weight = layers_8_encoder_attn_q_proj_weight_to_fp16, x = obj_121_cast_fp16)[name = tensor("query_35_cast_fp16")]; tensor var_1947 = const()[name = tensor("op_1947"), val = tensor([1, 1])]; tensor var_1949 = const()[name = tensor("op_1949"), val = tensor([1, 1])]; tensor key_35_pad_type_0 = const()[name = tensor("key_35_pad_type_0"), val = tensor("custom")]; tensor key_35_pad_0 = const()[name = tensor("key_35_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(237483648)))]; tensor key_35_cast_fp16 = conv(dilations = var_1949, groups = var_1819, pad = key_35_pad_0, pad_type = key_35_pad_type_0, strides = var_1947, weight = layers_8_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_35_cast_fp16")]; tensor var_1954 = const()[name = tensor("op_1954"), val = tensor([1, 1])]; tensor var_1956 = const()[name = tensor("op_1956"), val = tensor([1, 1])]; tensor value_35_pad_type_0 = const()[name = tensor("value_35_pad_type_0"), val = tensor("custom")]; tensor value_35_pad_0 = const()[name = tensor("value_35_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238663360)))]; tensor layers_8_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239843072)))]; tensor value_35_cast_fp16 = conv(bias = layers_8_encoder_attn_v_proj_bias_to_fp16, dilations = var_1956, groups = var_1819, pad = value_35_pad_0, pad_type = value_35_pad_type_0, strides = var_1954, weight = layers_8_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_35_cast_fp16")]; tensor var_1960 = const()[name = tensor("op_1960"), val = tensor([1, 12, 64, -1])]; tensor var_1961_cast_fp16 = reshape(shape = var_1960, x = query_35_cast_fp16)[name = tensor("op_1961_cast_fp16")]; tensor var_1962_to_fp16 = const()[name = tensor("op_1962_to_fp16"), val = tensor(0x1p-3)]; tensor var_1963_cast_fp16 = mul(x = var_1961_cast_fp16, y = var_1962_to_fp16)[name = tensor("op_1963_cast_fp16")]; tensor var_1964 = const()[name = tensor("op_1964"), val = tensor([1, 12, 64, -1])]; tensor var_1965_cast_fp16 = reshape(shape = var_1964, x = key_35_cast_fp16)[name = tensor("op_1965_cast_fp16")]; tensor mh_w_53_transpose_x_0 = const()[name = tensor("mh_w_53_transpose_x_0"), val = tensor(true)]; tensor mh_w_53_transpose_y_0 = const()[name = tensor("mh_w_53_transpose_y_0"), val = tensor(false)]; tensor mh_w_53_cast_fp16 = matmul(transpose_x = mh_w_53_transpose_x_0, transpose_y = mh_w_53_transpose_y_0, x = var_1963_cast_fp16, y = var_1965_cast_fp16)[name = tensor("mh_w_53_cast_fp16")]; tensor obj_125_cast_fp16 = softmax(axis = var_1812, x = mh_w_53_cast_fp16)[name = tensor("obj_125_cast_fp16")]; tensor var_1969 = const()[name = tensor("op_1969"), val = tensor([1, 12, 64, -1])]; tensor var_1970_cast_fp16 = reshape(shape = var_1969, x = value_35_cast_fp16)[name = tensor("op_1970_cast_fp16")]; tensor attn_35_transpose_x_0 = const()[name = tensor("attn_35_transpose_x_0"), val = tensor(false)]; tensor attn_35_transpose_y_0 = const()[name = tensor("attn_35_transpose_y_0"), val = tensor(true)]; tensor attn_35_cast_fp16 = matmul(transpose_x = attn_35_transpose_x_0, transpose_y = attn_35_transpose_y_0, x = var_1970_cast_fp16, y = obj_125_cast_fp16)[name = tensor("attn_35_cast_fp16")]; tensor var_1973 = const()[name = tensor("op_1973"), val = tensor([1, 768, 1, -1])]; tensor input_83_cast_fp16 = reshape(shape = var_1973, x = attn_35_cast_fp16)[name = tensor("input_83_cast_fp16")]; tensor var_1977 = const()[name = tensor("op_1977"), val = tensor([1, 1])]; tensor var_1979 = const()[name = tensor("op_1979"), val = tensor([1, 1])]; tensor obj_123_pad_type_0 = const()[name = tensor("obj_123_pad_type_0"), val = tensor("custom")]; tensor obj_123_pad_0 = const()[name = tensor("obj_123_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_8_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239844672)))]; tensor layers_8_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_8_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241024384)))]; tensor obj_123_cast_fp16 = conv(bias = layers_8_encoder_attn_o_proj_bias_to_fp16, dilations = var_1979, groups = var_1819, pad = obj_123_pad_0, pad_type = obj_123_pad_type_0, strides = var_1977, weight = layers_8_encoder_attn_o_proj_weight_to_fp16, x = input_83_cast_fp16)[name = tensor("obj_123_cast_fp16")]; tensor inputs_53_cast_fp16 = add(x = inputs_51_cast_fp16, y = obj_123_cast_fp16)[name = tensor("inputs_53_cast_fp16")]; tensor var_1988 = const()[name = tensor("op_1988"), val = tensor([1])]; tensor channels_mean_53_cast_fp16 = reduce_mean(axes = var_1988, keep_dims = var_1820, x = inputs_53_cast_fp16)[name = tensor("channels_mean_53_cast_fp16")]; tensor zero_mean_53_cast_fp16 = sub(x = inputs_53_cast_fp16, y = channels_mean_53_cast_fp16)[name = tensor("zero_mean_53_cast_fp16")]; tensor zero_mean_sq_53_cast_fp16 = mul(x = zero_mean_53_cast_fp16, y = zero_mean_53_cast_fp16)[name = tensor("zero_mean_sq_53_cast_fp16")]; tensor var_1992 = const()[name = tensor("op_1992"), val = tensor([1])]; tensor var_1993_cast_fp16 = reduce_mean(axes = var_1992, keep_dims = var_1820, x = zero_mean_sq_53_cast_fp16)[name = tensor("op_1993_cast_fp16")]; tensor var_1994_to_fp16 = const()[name = tensor("op_1994_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_1995_cast_fp16 = add(x = var_1993_cast_fp16, y = var_1994_to_fp16)[name = tensor("op_1995_cast_fp16")]; tensor denom_53_epsilon_0_to_fp16 = const()[name = tensor("denom_53_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_53_cast_fp16 = rsqrt(epsilon = denom_53_epsilon_0_to_fp16, x = var_1995_cast_fp16)[name = tensor("denom_53_cast_fp16")]; tensor out_53_cast_fp16 = mul(x = zero_mean_53_cast_fp16, y = denom_53_cast_fp16)[name = tensor("out_53_cast_fp16")]; tensor input_85_gamma_0_to_fp16 = const()[name = tensor("input_85_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241025984)))]; tensor input_85_beta_0_to_fp16 = const()[name = tensor("input_85_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241027584)))]; tensor input_85_epsilon_0_to_fp16 = const()[name = tensor("input_85_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_85_cast_fp16 = batch_norm(beta = input_85_beta_0_to_fp16, epsilon = input_85_epsilon_0_to_fp16, gamma = input_85_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_53_cast_fp16)[name = tensor("input_85_cast_fp16")]; tensor var_2006 = const()[name = tensor("op_2006"), val = tensor([1, 1])]; tensor var_2008 = const()[name = tensor("op_2008"), val = tensor([1, 1])]; tensor input_87_pad_type_0 = const()[name = tensor("input_87_pad_type_0"), val = tensor("custom")]; tensor input_87_pad_0 = const()[name = tensor("input_87_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_fc1_weight_to_fp16 = const()[name = tensor("layers_8_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241029184)))]; tensor layers_8_fc1_bias_to_fp16 = const()[name = tensor("layers_8_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245747840)))]; tensor input_87_cast_fp16 = conv(bias = layers_8_fc1_bias_to_fp16, dilations = var_2008, groups = var_1819, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = var_2006, weight = layers_8_fc1_weight_to_fp16, x = input_85_cast_fp16)[name = tensor("input_87_cast_fp16")]; tensor input_89_mode_0 = const()[name = tensor("input_89_mode_0"), val = tensor("EXACT")]; tensor input_89_cast_fp16 = gelu(mode = input_89_mode_0, x = input_87_cast_fp16)[name = tensor("input_89_cast_fp16")]; tensor var_2014 = const()[name = tensor("op_2014"), val = tensor([1, 1])]; tensor var_2016 = const()[name = tensor("op_2016"), val = tensor([1, 1])]; tensor hidden_states_19_pad_type_0 = const()[name = tensor("hidden_states_19_pad_type_0"), val = tensor("custom")]; tensor hidden_states_19_pad_0 = const()[name = tensor("hidden_states_19_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_8_fc2_weight_to_fp16 = const()[name = tensor("layers_8_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245754048)))]; tensor layers_8_fc2_bias_to_fp16 = const()[name = tensor("layers_8_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250472704)))]; tensor hidden_states_19_cast_fp16 = conv(bias = layers_8_fc2_bias_to_fp16, dilations = var_2016, groups = var_1819, pad = hidden_states_19_pad_0, pad_type = hidden_states_19_pad_type_0, strides = var_2014, weight = layers_8_fc2_weight_to_fp16, x = input_89_cast_fp16)[name = tensor("hidden_states_19_cast_fp16")]; tensor inputs_55_cast_fp16 = add(x = inputs_53_cast_fp16, y = hidden_states_19_cast_fp16)[name = tensor("inputs_55_cast_fp16")]; tensor var_2030 = const()[name = tensor("op_2030"), val = tensor(3)]; tensor var_2037 = const()[name = tensor("op_2037"), val = tensor(1)]; tensor var_2038 = const()[name = tensor("op_2038"), val = tensor(true)]; tensor var_2050 = const()[name = tensor("op_2050"), val = tensor([1])]; tensor channels_mean_55_cast_fp16 = reduce_mean(axes = var_2050, keep_dims = var_2038, x = inputs_55_cast_fp16)[name = tensor("channels_mean_55_cast_fp16")]; tensor zero_mean_55_cast_fp16 = sub(x = inputs_55_cast_fp16, y = channels_mean_55_cast_fp16)[name = tensor("zero_mean_55_cast_fp16")]; tensor zero_mean_sq_55_cast_fp16 = mul(x = zero_mean_55_cast_fp16, y = zero_mean_55_cast_fp16)[name = tensor("zero_mean_sq_55_cast_fp16")]; tensor var_2054 = const()[name = tensor("op_2054"), val = tensor([1])]; tensor var_2055_cast_fp16 = reduce_mean(axes = var_2054, keep_dims = var_2038, x = zero_mean_sq_55_cast_fp16)[name = tensor("op_2055_cast_fp16")]; tensor var_2056_to_fp16 = const()[name = tensor("op_2056_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2057_cast_fp16 = add(x = var_2055_cast_fp16, y = var_2056_to_fp16)[name = tensor("op_2057_cast_fp16")]; tensor denom_55_epsilon_0_to_fp16 = const()[name = tensor("denom_55_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_55_cast_fp16 = rsqrt(epsilon = denom_55_epsilon_0_to_fp16, x = var_2057_cast_fp16)[name = tensor("denom_55_cast_fp16")]; tensor out_55_cast_fp16 = mul(x = zero_mean_55_cast_fp16, y = denom_55_cast_fp16)[name = tensor("out_55_cast_fp16")]; tensor obj_127_gamma_0_to_fp16 = const()[name = tensor("obj_127_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250474304)))]; tensor obj_127_beta_0_to_fp16 = const()[name = tensor("obj_127_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250475904)))]; tensor obj_127_epsilon_0_to_fp16 = const()[name = tensor("obj_127_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_127_cast_fp16 = batch_norm(beta = obj_127_beta_0_to_fp16, epsilon = obj_127_epsilon_0_to_fp16, gamma = obj_127_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_55_cast_fp16)[name = tensor("obj_127_cast_fp16")]; tensor var_2072 = const()[name = tensor("op_2072"), val = tensor([1, 1])]; tensor var_2074 = const()[name = tensor("op_2074"), val = tensor([1, 1])]; tensor query_37_pad_type_0 = const()[name = tensor("query_37_pad_type_0"), val = tensor("custom")]; tensor query_37_pad_0 = const()[name = tensor("query_37_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250477504)))]; tensor layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251657216)))]; tensor query_37_cast_fp16 = conv(bias = layers_9_self_attn_q_proj_bias_to_fp16, dilations = var_2074, groups = var_2037, pad = query_37_pad_0, pad_type = query_37_pad_type_0, strides = var_2072, weight = layers_9_self_attn_q_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("query_37_cast_fp16")]; tensor var_2078 = const()[name = tensor("op_2078"), val = tensor([1, 1])]; tensor var_2080 = const()[name = tensor("op_2080"), val = tensor([1, 1])]; tensor current_key_19_pad_type_0 = const()[name = tensor("current_key_19_pad_type_0"), val = tensor("custom")]; tensor current_key_19_pad_0 = const()[name = tensor("current_key_19_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251658816)))]; tensor current_key_19_cast_fp16 = conv(dilations = var_2080, groups = var_2037, pad = current_key_19_pad_0, pad_type = current_key_19_pad_type_0, strides = var_2078, weight = layers_9_self_attn_k_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("current_key_19_cast_fp16")]; tensor var_2085 = const()[name = tensor("op_2085"), val = tensor([1, 1])]; tensor var_2087 = const()[name = tensor("op_2087"), val = tensor([1, 1])]; tensor current_value_19_pad_type_0 = const()[name = tensor("current_value_19_pad_type_0"), val = tensor("custom")]; tensor current_value_19_pad_0 = const()[name = tensor("current_value_19_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252838528)))]; tensor layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254018240)))]; tensor current_value_19_cast_fp16 = conv(bias = layers_9_self_attn_v_proj_bias_to_fp16, dilations = var_2087, groups = var_2037, pad = current_value_19_pad_0, pad_type = current_value_19_pad_type_0, strides = var_2085, weight = layers_9_self_attn_v_proj_weight_to_fp16, x = obj_127_cast_fp16)[name = tensor("current_value_19_cast_fp16")]; tensor var_2094_cast_fp16 = mul(x = current_key_19_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2094_cast_fp16")]; tensor var_2096_cast_fp16 = mul(x = var_63_cast_fp16_9, y = var_161_cast_fp16)[name = tensor("op_2096_cast_fp16")]; tensor key_37_cast_fp16 = add(x = var_2094_cast_fp16, y = var_2096_cast_fp16)[name = tensor("key_37_cast_fp16")]; tensor var_2098_cast_fp16 = mul(x = current_value_19_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2098_cast_fp16")]; tensor var_2100_cast_fp16 = mul(x = var_78_cast_fp16_9, y = var_161_cast_fp16)[name = tensor("op_2100_cast_fp16")]; tensor value_37_cast_fp16 = add(x = var_2098_cast_fp16, y = var_2100_cast_fp16)[name = tensor("value_37_cast_fp16")]; tensor var_2103 = const()[name = tensor("op_2103"), val = tensor([1, 12, 64, -1])]; tensor var_2104_cast_fp16 = reshape(shape = var_2103, x = query_37_cast_fp16)[name = tensor("op_2104_cast_fp16")]; tensor var_2105_to_fp16 = const()[name = tensor("op_2105_to_fp16"), val = tensor(0x1p-3)]; tensor var_2106_cast_fp16 = mul(x = var_2104_cast_fp16, y = var_2105_to_fp16)[name = tensor("op_2106_cast_fp16")]; tensor var_2107 = const()[name = tensor("op_2107"), val = tensor([1, 12, 64, -1])]; tensor var_2108_cast_fp16 = reshape(shape = var_2107, x = key_37_cast_fp16)[name = tensor("op_2108_cast_fp16")]; tensor mh_w_55_transpose_x_0 = const()[name = tensor("mh_w_55_transpose_x_0"), val = tensor(true)]; tensor mh_w_55_transpose_y_0 = const()[name = tensor("mh_w_55_transpose_y_0"), val = tensor(false)]; tensor mh_w_55_cast_fp16 = matmul(transpose_x = mh_w_55_transpose_x_0, transpose_y = mh_w_55_transpose_y_0, x = var_2106_cast_fp16, y = var_2108_cast_fp16)[name = tensor("mh_w_55_cast_fp16")]; tensor mh_w_57_cast_fp16 = add(x = mh_w_55_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_57_cast_fp16")]; tensor var_2116_cast_fp16 = softmax(axis = var_2030, x = mh_w_57_cast_fp16)[name = tensor("op_2116_cast_fp16")]; tensor var_2117 = const()[name = tensor("op_2117"), val = tensor([1, 12, 64, -1])]; tensor var_2118_cast_fp16 = reshape(shape = var_2117, x = value_37_cast_fp16)[name = tensor("op_2118_cast_fp16")]; tensor attn_37_transpose_x_0 = const()[name = tensor("attn_37_transpose_x_0"), val = tensor(false)]; tensor attn_37_transpose_y_0 = const()[name = tensor("attn_37_transpose_y_0"), val = tensor(true)]; tensor attn_37_cast_fp16 = matmul(transpose_x = attn_37_transpose_x_0, transpose_y = attn_37_transpose_y_0, x = var_2118_cast_fp16, y = var_2116_cast_fp16)[name = tensor("attn_37_cast_fp16")]; tensor var_2121 = const()[name = tensor("op_2121"), val = tensor([1, 768, 1, -1])]; tensor input_91_cast_fp16 = reshape(shape = var_2121, x = attn_37_cast_fp16)[name = tensor("input_91_cast_fp16")]; tensor var_2125 = const()[name = tensor("op_2125"), val = tensor([1, 1])]; tensor var_2127 = const()[name = tensor("op_2127"), val = tensor([1, 1])]; tensor obj_133_pad_type_0 = const()[name = tensor("obj_133_pad_type_0"), val = tensor("custom")]; tensor obj_133_pad_0 = const()[name = tensor("obj_133_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254019840)))]; tensor layers_9_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255199552)))]; tensor obj_133_cast_fp16 = conv(bias = layers_9_self_attn_o_proj_bias_to_fp16, dilations = var_2127, groups = var_2037, pad = obj_133_pad_0, pad_type = obj_133_pad_type_0, strides = var_2125, weight = layers_9_self_attn_o_proj_weight_to_fp16, x = input_91_cast_fp16)[name = tensor("obj_133_cast_fp16")]; tensor inputs_57_cast_fp16 = add(x = inputs_55_cast_fp16, y = obj_133_cast_fp16)[name = tensor("inputs_57_cast_fp16")]; tensor var_2137 = const()[name = tensor("op_2137"), val = tensor([1])]; tensor channels_mean_57_cast_fp16 = reduce_mean(axes = var_2137, keep_dims = var_2038, x = inputs_57_cast_fp16)[name = tensor("channels_mean_57_cast_fp16")]; tensor zero_mean_57_cast_fp16 = sub(x = inputs_57_cast_fp16, y = channels_mean_57_cast_fp16)[name = tensor("zero_mean_57_cast_fp16")]; tensor zero_mean_sq_57_cast_fp16 = mul(x = zero_mean_57_cast_fp16, y = zero_mean_57_cast_fp16)[name = tensor("zero_mean_sq_57_cast_fp16")]; tensor var_2141 = const()[name = tensor("op_2141"), val = tensor([1])]; tensor var_2142_cast_fp16 = reduce_mean(axes = var_2141, keep_dims = var_2038, x = zero_mean_sq_57_cast_fp16)[name = tensor("op_2142_cast_fp16")]; tensor var_2143_to_fp16 = const()[name = tensor("op_2143_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2144_cast_fp16 = add(x = var_2142_cast_fp16, y = var_2143_to_fp16)[name = tensor("op_2144_cast_fp16")]; tensor denom_57_epsilon_0_to_fp16 = const()[name = tensor("denom_57_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_57_cast_fp16 = rsqrt(epsilon = denom_57_epsilon_0_to_fp16, x = var_2144_cast_fp16)[name = tensor("denom_57_cast_fp16")]; tensor out_57_cast_fp16 = mul(x = zero_mean_57_cast_fp16, y = denom_57_cast_fp16)[name = tensor("out_57_cast_fp16")]; tensor obj_135_gamma_0_to_fp16 = const()[name = tensor("obj_135_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255201152)))]; tensor obj_135_beta_0_to_fp16 = const()[name = tensor("obj_135_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255202752)))]; tensor obj_135_epsilon_0_to_fp16 = const()[name = tensor("obj_135_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_135_cast_fp16 = batch_norm(beta = obj_135_beta_0_to_fp16, epsilon = obj_135_epsilon_0_to_fp16, gamma = obj_135_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_57_cast_fp16)[name = tensor("obj_135_cast_fp16")]; tensor var_2159 = const()[name = tensor("op_2159"), val = tensor([1, 1])]; tensor var_2161 = const()[name = tensor("op_2161"), val = tensor([1, 1])]; tensor query_39_pad_type_0 = const()[name = tensor("query_39_pad_type_0"), val = tensor("custom")]; tensor query_39_pad_0 = const()[name = tensor("query_39_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255204352)))]; tensor layers_9_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(256384064)))]; tensor query_39_cast_fp16 = conv(bias = layers_9_encoder_attn_q_proj_bias_to_fp16, dilations = var_2161, groups = var_2037, pad = query_39_pad_0, pad_type = query_39_pad_type_0, strides = var_2159, weight = layers_9_encoder_attn_q_proj_weight_to_fp16, x = obj_135_cast_fp16)[name = tensor("query_39_cast_fp16")]; tensor var_2165 = const()[name = tensor("op_2165"), val = tensor([1, 1])]; tensor var_2167 = const()[name = tensor("op_2167"), val = tensor([1, 1])]; tensor key_39_pad_type_0 = const()[name = tensor("key_39_pad_type_0"), val = tensor("custom")]; tensor key_39_pad_0 = const()[name = tensor("key_39_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(256385664)))]; tensor key_39_cast_fp16 = conv(dilations = var_2167, groups = var_2037, pad = key_39_pad_0, pad_type = key_39_pad_type_0, strides = var_2165, weight = layers_9_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_39_cast_fp16")]; tensor var_2172 = const()[name = tensor("op_2172"), val = tensor([1, 1])]; tensor var_2174 = const()[name = tensor("op_2174"), val = tensor([1, 1])]; tensor value_39_pad_type_0 = const()[name = tensor("value_39_pad_type_0"), val = tensor("custom")]; tensor value_39_pad_0 = const()[name = tensor("value_39_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257565376)))]; tensor layers_9_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258745088)))]; tensor value_39_cast_fp16 = conv(bias = layers_9_encoder_attn_v_proj_bias_to_fp16, dilations = var_2174, groups = var_2037, pad = value_39_pad_0, pad_type = value_39_pad_type_0, strides = var_2172, weight = layers_9_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_39_cast_fp16")]; tensor var_2178 = const()[name = tensor("op_2178"), val = tensor([1, 12, 64, -1])]; tensor var_2179_cast_fp16 = reshape(shape = var_2178, x = query_39_cast_fp16)[name = tensor("op_2179_cast_fp16")]; tensor var_2180_to_fp16 = const()[name = tensor("op_2180_to_fp16"), val = tensor(0x1p-3)]; tensor var_2181_cast_fp16 = mul(x = var_2179_cast_fp16, y = var_2180_to_fp16)[name = tensor("op_2181_cast_fp16")]; tensor var_2182 = const()[name = tensor("op_2182"), val = tensor([1, 12, 64, -1])]; tensor var_2183_cast_fp16 = reshape(shape = var_2182, x = key_39_cast_fp16)[name = tensor("op_2183_cast_fp16")]; tensor mh_w_59_transpose_x_0 = const()[name = tensor("mh_w_59_transpose_x_0"), val = tensor(true)]; tensor mh_w_59_transpose_y_0 = const()[name = tensor("mh_w_59_transpose_y_0"), val = tensor(false)]; tensor mh_w_59_cast_fp16 = matmul(transpose_x = mh_w_59_transpose_x_0, transpose_y = mh_w_59_transpose_y_0, x = var_2181_cast_fp16, y = var_2183_cast_fp16)[name = tensor("mh_w_59_cast_fp16")]; tensor obj_139_cast_fp16 = softmax(axis = var_2030, x = mh_w_59_cast_fp16)[name = tensor("obj_139_cast_fp16")]; tensor var_2187 = const()[name = tensor("op_2187"), val = tensor([1, 12, 64, -1])]; tensor var_2188_cast_fp16 = reshape(shape = var_2187, x = value_39_cast_fp16)[name = tensor("op_2188_cast_fp16")]; tensor attn_39_transpose_x_0 = const()[name = tensor("attn_39_transpose_x_0"), val = tensor(false)]; tensor attn_39_transpose_y_0 = const()[name = tensor("attn_39_transpose_y_0"), val = tensor(true)]; tensor attn_39_cast_fp16 = matmul(transpose_x = attn_39_transpose_x_0, transpose_y = attn_39_transpose_y_0, x = var_2188_cast_fp16, y = obj_139_cast_fp16)[name = tensor("attn_39_cast_fp16")]; tensor var_2191 = const()[name = tensor("op_2191"), val = tensor([1, 768, 1, -1])]; tensor input_93_cast_fp16 = reshape(shape = var_2191, x = attn_39_cast_fp16)[name = tensor("input_93_cast_fp16")]; tensor var_2195 = const()[name = tensor("op_2195"), val = tensor([1, 1])]; tensor var_2197 = const()[name = tensor("op_2197"), val = tensor([1, 1])]; tensor obj_137_pad_type_0 = const()[name = tensor("obj_137_pad_type_0"), val = tensor("custom")]; tensor obj_137_pad_0 = const()[name = tensor("obj_137_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_9_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258746688)))]; tensor layers_9_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_9_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259926400)))]; tensor obj_137_cast_fp16 = conv(bias = layers_9_encoder_attn_o_proj_bias_to_fp16, dilations = var_2197, groups = var_2037, pad = obj_137_pad_0, pad_type = obj_137_pad_type_0, strides = var_2195, weight = layers_9_encoder_attn_o_proj_weight_to_fp16, x = input_93_cast_fp16)[name = tensor("obj_137_cast_fp16")]; tensor inputs_59_cast_fp16 = add(x = inputs_57_cast_fp16, y = obj_137_cast_fp16)[name = tensor("inputs_59_cast_fp16")]; tensor var_2206 = const()[name = tensor("op_2206"), val = tensor([1])]; tensor channels_mean_59_cast_fp16 = reduce_mean(axes = var_2206, keep_dims = var_2038, x = inputs_59_cast_fp16)[name = tensor("channels_mean_59_cast_fp16")]; tensor zero_mean_59_cast_fp16 = sub(x = inputs_59_cast_fp16, y = channels_mean_59_cast_fp16)[name = tensor("zero_mean_59_cast_fp16")]; tensor zero_mean_sq_59_cast_fp16 = mul(x = zero_mean_59_cast_fp16, y = zero_mean_59_cast_fp16)[name = tensor("zero_mean_sq_59_cast_fp16")]; tensor var_2210 = const()[name = tensor("op_2210"), val = tensor([1])]; tensor var_2211_cast_fp16 = reduce_mean(axes = var_2210, keep_dims = var_2038, x = zero_mean_sq_59_cast_fp16)[name = tensor("op_2211_cast_fp16")]; tensor var_2212_to_fp16 = const()[name = tensor("op_2212_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2213_cast_fp16 = add(x = var_2211_cast_fp16, y = var_2212_to_fp16)[name = tensor("op_2213_cast_fp16")]; tensor denom_59_epsilon_0_to_fp16 = const()[name = tensor("denom_59_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_59_cast_fp16 = rsqrt(epsilon = denom_59_epsilon_0_to_fp16, x = var_2213_cast_fp16)[name = tensor("denom_59_cast_fp16")]; tensor out_59_cast_fp16 = mul(x = zero_mean_59_cast_fp16, y = denom_59_cast_fp16)[name = tensor("out_59_cast_fp16")]; tensor input_95_gamma_0_to_fp16 = const()[name = tensor("input_95_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259928000)))]; tensor input_95_beta_0_to_fp16 = const()[name = tensor("input_95_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259929600)))]; tensor input_95_epsilon_0_to_fp16 = const()[name = tensor("input_95_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_95_cast_fp16 = batch_norm(beta = input_95_beta_0_to_fp16, epsilon = input_95_epsilon_0_to_fp16, gamma = input_95_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_59_cast_fp16)[name = tensor("input_95_cast_fp16")]; tensor var_2224 = const()[name = tensor("op_2224"), val = tensor([1, 1])]; tensor var_2226 = const()[name = tensor("op_2226"), val = tensor([1, 1])]; tensor input_97_pad_type_0 = const()[name = tensor("input_97_pad_type_0"), val = tensor("custom")]; tensor input_97_pad_0 = const()[name = tensor("input_97_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_fc1_weight_to_fp16 = const()[name = tensor("layers_9_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259931200)))]; tensor layers_9_fc1_bias_to_fp16 = const()[name = tensor("layers_9_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264649856)))]; tensor input_97_cast_fp16 = conv(bias = layers_9_fc1_bias_to_fp16, dilations = var_2226, groups = var_2037, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = var_2224, weight = layers_9_fc1_weight_to_fp16, x = input_95_cast_fp16)[name = tensor("input_97_cast_fp16")]; tensor input_99_mode_0 = const()[name = tensor("input_99_mode_0"), val = tensor("EXACT")]; tensor input_99_cast_fp16 = gelu(mode = input_99_mode_0, x = input_97_cast_fp16)[name = tensor("input_99_cast_fp16")]; tensor var_2232 = const()[name = tensor("op_2232"), val = tensor([1, 1])]; tensor var_2234 = const()[name = tensor("op_2234"), val = tensor([1, 1])]; tensor hidden_states_21_pad_type_0 = const()[name = tensor("hidden_states_21_pad_type_0"), val = tensor("custom")]; tensor hidden_states_21_pad_0 = const()[name = tensor("hidden_states_21_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_9_fc2_weight_to_fp16 = const()[name = tensor("layers_9_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264656064)))]; tensor layers_9_fc2_bias_to_fp16 = const()[name = tensor("layers_9_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269374720)))]; tensor hidden_states_21_cast_fp16 = conv(bias = layers_9_fc2_bias_to_fp16, dilations = var_2234, groups = var_2037, pad = hidden_states_21_pad_0, pad_type = hidden_states_21_pad_type_0, strides = var_2232, weight = layers_9_fc2_weight_to_fp16, x = input_99_cast_fp16)[name = tensor("hidden_states_21_cast_fp16")]; tensor inputs_61_cast_fp16 = add(x = inputs_59_cast_fp16, y = hidden_states_21_cast_fp16)[name = tensor("inputs_61_cast_fp16")]; tensor var_2248 = const()[name = tensor("op_2248"), val = tensor(3)]; tensor var_2255 = const()[name = tensor("op_2255"), val = tensor(1)]; tensor var_2256 = const()[name = tensor("op_2256"), val = tensor(true)]; tensor var_2268 = const()[name = tensor("op_2268"), val = tensor([1])]; tensor channels_mean_61_cast_fp16 = reduce_mean(axes = var_2268, keep_dims = var_2256, x = inputs_61_cast_fp16)[name = tensor("channels_mean_61_cast_fp16")]; tensor zero_mean_61_cast_fp16 = sub(x = inputs_61_cast_fp16, y = channels_mean_61_cast_fp16)[name = tensor("zero_mean_61_cast_fp16")]; tensor zero_mean_sq_61_cast_fp16 = mul(x = zero_mean_61_cast_fp16, y = zero_mean_61_cast_fp16)[name = tensor("zero_mean_sq_61_cast_fp16")]; tensor var_2272 = const()[name = tensor("op_2272"), val = tensor([1])]; tensor var_2273_cast_fp16 = reduce_mean(axes = var_2272, keep_dims = var_2256, x = zero_mean_sq_61_cast_fp16)[name = tensor("op_2273_cast_fp16")]; tensor var_2274_to_fp16 = const()[name = tensor("op_2274_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2275_cast_fp16 = add(x = var_2273_cast_fp16, y = var_2274_to_fp16)[name = tensor("op_2275_cast_fp16")]; tensor denom_61_epsilon_0_to_fp16 = const()[name = tensor("denom_61_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_61_cast_fp16 = rsqrt(epsilon = denom_61_epsilon_0_to_fp16, x = var_2275_cast_fp16)[name = tensor("denom_61_cast_fp16")]; tensor out_61_cast_fp16 = mul(x = zero_mean_61_cast_fp16, y = denom_61_cast_fp16)[name = tensor("out_61_cast_fp16")]; tensor obj_141_gamma_0_to_fp16 = const()[name = tensor("obj_141_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269376320)))]; tensor obj_141_beta_0_to_fp16 = const()[name = tensor("obj_141_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269377920)))]; tensor obj_141_epsilon_0_to_fp16 = const()[name = tensor("obj_141_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_141_cast_fp16 = batch_norm(beta = obj_141_beta_0_to_fp16, epsilon = obj_141_epsilon_0_to_fp16, gamma = obj_141_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_61_cast_fp16)[name = tensor("obj_141_cast_fp16")]; tensor var_2290 = const()[name = tensor("op_2290"), val = tensor([1, 1])]; tensor var_2292 = const()[name = tensor("op_2292"), val = tensor([1, 1])]; tensor query_41_pad_type_0 = const()[name = tensor("query_41_pad_type_0"), val = tensor("custom")]; tensor query_41_pad_0 = const()[name = tensor("query_41_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269379520)))]; tensor layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270559232)))]; tensor query_41_cast_fp16 = conv(bias = layers_10_self_attn_q_proj_bias_to_fp16, dilations = var_2292, groups = var_2255, pad = query_41_pad_0, pad_type = query_41_pad_type_0, strides = var_2290, weight = layers_10_self_attn_q_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("query_41_cast_fp16")]; tensor var_2296 = const()[name = tensor("op_2296"), val = tensor([1, 1])]; tensor var_2298 = const()[name = tensor("op_2298"), val = tensor([1, 1])]; tensor current_key_21_pad_type_0 = const()[name = tensor("current_key_21_pad_type_0"), val = tensor("custom")]; tensor current_key_21_pad_0 = const()[name = tensor("current_key_21_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270560832)))]; tensor current_key_21_cast_fp16 = conv(dilations = var_2298, groups = var_2255, pad = current_key_21_pad_0, pad_type = current_key_21_pad_type_0, strides = var_2296, weight = layers_10_self_attn_k_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("current_key_21_cast_fp16")]; tensor var_2303 = const()[name = tensor("op_2303"), val = tensor([1, 1])]; tensor var_2305 = const()[name = tensor("op_2305"), val = tensor([1, 1])]; tensor current_value_21_pad_type_0 = const()[name = tensor("current_value_21_pad_type_0"), val = tensor("custom")]; tensor current_value_21_pad_0 = const()[name = tensor("current_value_21_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271740544)))]; tensor layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272920256)))]; tensor current_value_21_cast_fp16 = conv(bias = layers_10_self_attn_v_proj_bias_to_fp16, dilations = var_2305, groups = var_2255, pad = current_value_21_pad_0, pad_type = current_value_21_pad_type_0, strides = var_2303, weight = layers_10_self_attn_v_proj_weight_to_fp16, x = obj_141_cast_fp16)[name = tensor("current_value_21_cast_fp16")]; tensor var_2312_cast_fp16 = mul(x = current_key_21_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2312_cast_fp16")]; tensor var_2314_cast_fp16 = mul(x = var_63_cast_fp16_10, y = var_161_cast_fp16)[name = tensor("op_2314_cast_fp16")]; tensor key_41_cast_fp16 = add(x = var_2312_cast_fp16, y = var_2314_cast_fp16)[name = tensor("key_41_cast_fp16")]; tensor var_2316_cast_fp16 = mul(x = current_value_21_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2316_cast_fp16")]; tensor var_2318_cast_fp16 = mul(x = var_78_cast_fp16_10, y = var_161_cast_fp16)[name = tensor("op_2318_cast_fp16")]; tensor value_41_cast_fp16 = add(x = var_2316_cast_fp16, y = var_2318_cast_fp16)[name = tensor("value_41_cast_fp16")]; tensor var_2321 = const()[name = tensor("op_2321"), val = tensor([1, 12, 64, -1])]; tensor var_2322_cast_fp16 = reshape(shape = var_2321, x = query_41_cast_fp16)[name = tensor("op_2322_cast_fp16")]; tensor var_2323_to_fp16 = const()[name = tensor("op_2323_to_fp16"), val = tensor(0x1p-3)]; tensor var_2324_cast_fp16 = mul(x = var_2322_cast_fp16, y = var_2323_to_fp16)[name = tensor("op_2324_cast_fp16")]; tensor var_2325 = const()[name = tensor("op_2325"), val = tensor([1, 12, 64, -1])]; tensor var_2326_cast_fp16 = reshape(shape = var_2325, x = key_41_cast_fp16)[name = tensor("op_2326_cast_fp16")]; tensor mh_w_61_transpose_x_0 = const()[name = tensor("mh_w_61_transpose_x_0"), val = tensor(true)]; tensor mh_w_61_transpose_y_0 = const()[name = tensor("mh_w_61_transpose_y_0"), val = tensor(false)]; tensor mh_w_61_cast_fp16 = matmul(transpose_x = mh_w_61_transpose_x_0, transpose_y = mh_w_61_transpose_y_0, x = var_2324_cast_fp16, y = var_2326_cast_fp16)[name = tensor("mh_w_61_cast_fp16")]; tensor mh_w_63_cast_fp16 = add(x = mh_w_61_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_63_cast_fp16")]; tensor var_2334_cast_fp16 = softmax(axis = var_2248, x = mh_w_63_cast_fp16)[name = tensor("op_2334_cast_fp16")]; tensor var_2335 = const()[name = tensor("op_2335"), val = tensor([1, 12, 64, -1])]; tensor var_2336_cast_fp16 = reshape(shape = var_2335, x = value_41_cast_fp16)[name = tensor("op_2336_cast_fp16")]; tensor attn_41_transpose_x_0 = const()[name = tensor("attn_41_transpose_x_0"), val = tensor(false)]; tensor attn_41_transpose_y_0 = const()[name = tensor("attn_41_transpose_y_0"), val = tensor(true)]; tensor attn_41_cast_fp16 = matmul(transpose_x = attn_41_transpose_x_0, transpose_y = attn_41_transpose_y_0, x = var_2336_cast_fp16, y = var_2334_cast_fp16)[name = tensor("attn_41_cast_fp16")]; tensor var_2339 = const()[name = tensor("op_2339"), val = tensor([1, 768, 1, -1])]; tensor input_101_cast_fp16 = reshape(shape = var_2339, x = attn_41_cast_fp16)[name = tensor("input_101_cast_fp16")]; tensor var_2343 = const()[name = tensor("op_2343"), val = tensor([1, 1])]; tensor var_2345 = const()[name = tensor("op_2345"), val = tensor([1, 1])]; tensor obj_147_pad_type_0 = const()[name = tensor("obj_147_pad_type_0"), val = tensor("custom")]; tensor obj_147_pad_0 = const()[name = tensor("obj_147_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272921856)))]; tensor layers_10_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274101568)))]; tensor obj_147_cast_fp16 = conv(bias = layers_10_self_attn_o_proj_bias_to_fp16, dilations = var_2345, groups = var_2255, pad = obj_147_pad_0, pad_type = obj_147_pad_type_0, strides = var_2343, weight = layers_10_self_attn_o_proj_weight_to_fp16, x = input_101_cast_fp16)[name = tensor("obj_147_cast_fp16")]; tensor inputs_63_cast_fp16 = add(x = inputs_61_cast_fp16, y = obj_147_cast_fp16)[name = tensor("inputs_63_cast_fp16")]; tensor var_2355 = const()[name = tensor("op_2355"), val = tensor([1])]; tensor channels_mean_63_cast_fp16 = reduce_mean(axes = var_2355, keep_dims = var_2256, x = inputs_63_cast_fp16)[name = tensor("channels_mean_63_cast_fp16")]; tensor zero_mean_63_cast_fp16 = sub(x = inputs_63_cast_fp16, y = channels_mean_63_cast_fp16)[name = tensor("zero_mean_63_cast_fp16")]; tensor zero_mean_sq_63_cast_fp16 = mul(x = zero_mean_63_cast_fp16, y = zero_mean_63_cast_fp16)[name = tensor("zero_mean_sq_63_cast_fp16")]; tensor var_2359 = const()[name = tensor("op_2359"), val = tensor([1])]; tensor var_2360_cast_fp16 = reduce_mean(axes = var_2359, keep_dims = var_2256, x = zero_mean_sq_63_cast_fp16)[name = tensor("op_2360_cast_fp16")]; tensor var_2361_to_fp16 = const()[name = tensor("op_2361_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2362_cast_fp16 = add(x = var_2360_cast_fp16, y = var_2361_to_fp16)[name = tensor("op_2362_cast_fp16")]; tensor denom_63_epsilon_0_to_fp16 = const()[name = tensor("denom_63_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_63_cast_fp16 = rsqrt(epsilon = denom_63_epsilon_0_to_fp16, x = var_2362_cast_fp16)[name = tensor("denom_63_cast_fp16")]; tensor out_63_cast_fp16 = mul(x = zero_mean_63_cast_fp16, y = denom_63_cast_fp16)[name = tensor("out_63_cast_fp16")]; tensor obj_149_gamma_0_to_fp16 = const()[name = tensor("obj_149_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274103168)))]; tensor obj_149_beta_0_to_fp16 = const()[name = tensor("obj_149_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274104768)))]; tensor obj_149_epsilon_0_to_fp16 = const()[name = tensor("obj_149_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_149_cast_fp16 = batch_norm(beta = obj_149_beta_0_to_fp16, epsilon = obj_149_epsilon_0_to_fp16, gamma = obj_149_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_63_cast_fp16)[name = tensor("obj_149_cast_fp16")]; tensor var_2377 = const()[name = tensor("op_2377"), val = tensor([1, 1])]; tensor var_2379 = const()[name = tensor("op_2379"), val = tensor([1, 1])]; tensor query_43_pad_type_0 = const()[name = tensor("query_43_pad_type_0"), val = tensor("custom")]; tensor query_43_pad_0 = const()[name = tensor("query_43_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274106368)))]; tensor layers_10_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275286080)))]; tensor query_43_cast_fp16 = conv(bias = layers_10_encoder_attn_q_proj_bias_to_fp16, dilations = var_2379, groups = var_2255, pad = query_43_pad_0, pad_type = query_43_pad_type_0, strides = var_2377, weight = layers_10_encoder_attn_q_proj_weight_to_fp16, x = obj_149_cast_fp16)[name = tensor("query_43_cast_fp16")]; tensor var_2383 = const()[name = tensor("op_2383"), val = tensor([1, 1])]; tensor var_2385 = const()[name = tensor("op_2385"), val = tensor([1, 1])]; tensor key_43_pad_type_0 = const()[name = tensor("key_43_pad_type_0"), val = tensor("custom")]; tensor key_43_pad_0 = const()[name = tensor("key_43_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(275287680)))]; tensor key_43_cast_fp16 = conv(dilations = var_2385, groups = var_2255, pad = key_43_pad_0, pad_type = key_43_pad_type_0, strides = var_2383, weight = layers_10_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_43_cast_fp16")]; tensor var_2390 = const()[name = tensor("op_2390"), val = tensor([1, 1])]; tensor var_2392 = const()[name = tensor("op_2392"), val = tensor([1, 1])]; tensor value_43_pad_type_0 = const()[name = tensor("value_43_pad_type_0"), val = tensor("custom")]; tensor value_43_pad_0 = const()[name = tensor("value_43_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276467392)))]; tensor layers_10_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277647104)))]; tensor value_43_cast_fp16 = conv(bias = layers_10_encoder_attn_v_proj_bias_to_fp16, dilations = var_2392, groups = var_2255, pad = value_43_pad_0, pad_type = value_43_pad_type_0, strides = var_2390, weight = layers_10_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_43_cast_fp16")]; tensor var_2396 = const()[name = tensor("op_2396"), val = tensor([1, 12, 64, -1])]; tensor var_2397_cast_fp16 = reshape(shape = var_2396, x = query_43_cast_fp16)[name = tensor("op_2397_cast_fp16")]; tensor var_2398_to_fp16 = const()[name = tensor("op_2398_to_fp16"), val = tensor(0x1p-3)]; tensor var_2399_cast_fp16 = mul(x = var_2397_cast_fp16, y = var_2398_to_fp16)[name = tensor("op_2399_cast_fp16")]; tensor var_2400 = const()[name = tensor("op_2400"), val = tensor([1, 12, 64, -1])]; tensor var_2401_cast_fp16 = reshape(shape = var_2400, x = key_43_cast_fp16)[name = tensor("op_2401_cast_fp16")]; tensor mh_w_65_transpose_x_0 = const()[name = tensor("mh_w_65_transpose_x_0"), val = tensor(true)]; tensor mh_w_65_transpose_y_0 = const()[name = tensor("mh_w_65_transpose_y_0"), val = tensor(false)]; tensor mh_w_65_cast_fp16 = matmul(transpose_x = mh_w_65_transpose_x_0, transpose_y = mh_w_65_transpose_y_0, x = var_2399_cast_fp16, y = var_2401_cast_fp16)[name = tensor("mh_w_65_cast_fp16")]; tensor obj_153_cast_fp16 = softmax(axis = var_2248, x = mh_w_65_cast_fp16)[name = tensor("obj_153_cast_fp16")]; tensor var_2405 = const()[name = tensor("op_2405"), val = tensor([1, 12, 64, -1])]; tensor var_2406_cast_fp16 = reshape(shape = var_2405, x = value_43_cast_fp16)[name = tensor("op_2406_cast_fp16")]; tensor attn_43_transpose_x_0 = const()[name = tensor("attn_43_transpose_x_0"), val = tensor(false)]; tensor attn_43_transpose_y_0 = const()[name = tensor("attn_43_transpose_y_0"), val = tensor(true)]; tensor attn_43_cast_fp16 = matmul(transpose_x = attn_43_transpose_x_0, transpose_y = attn_43_transpose_y_0, x = var_2406_cast_fp16, y = obj_153_cast_fp16)[name = tensor("attn_43_cast_fp16")]; tensor var_2409 = const()[name = tensor("op_2409"), val = tensor([1, 768, 1, -1])]; tensor input_103_cast_fp16 = reshape(shape = var_2409, x = attn_43_cast_fp16)[name = tensor("input_103_cast_fp16")]; tensor var_2413 = const()[name = tensor("op_2413"), val = tensor([1, 1])]; tensor var_2415 = const()[name = tensor("op_2415"), val = tensor([1, 1])]; tensor obj_151_pad_type_0 = const()[name = tensor("obj_151_pad_type_0"), val = tensor("custom")]; tensor obj_151_pad_0 = const()[name = tensor("obj_151_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_10_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277648704)))]; tensor layers_10_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_10_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278828416)))]; tensor obj_151_cast_fp16 = conv(bias = layers_10_encoder_attn_o_proj_bias_to_fp16, dilations = var_2415, groups = var_2255, pad = obj_151_pad_0, pad_type = obj_151_pad_type_0, strides = var_2413, weight = layers_10_encoder_attn_o_proj_weight_to_fp16, x = input_103_cast_fp16)[name = tensor("obj_151_cast_fp16")]; tensor inputs_65_cast_fp16 = add(x = inputs_63_cast_fp16, y = obj_151_cast_fp16)[name = tensor("inputs_65_cast_fp16")]; tensor var_2424 = const()[name = tensor("op_2424"), val = tensor([1])]; tensor channels_mean_65_cast_fp16 = reduce_mean(axes = var_2424, keep_dims = var_2256, x = inputs_65_cast_fp16)[name = tensor("channels_mean_65_cast_fp16")]; tensor zero_mean_65_cast_fp16 = sub(x = inputs_65_cast_fp16, y = channels_mean_65_cast_fp16)[name = tensor("zero_mean_65_cast_fp16")]; tensor zero_mean_sq_65_cast_fp16 = mul(x = zero_mean_65_cast_fp16, y = zero_mean_65_cast_fp16)[name = tensor("zero_mean_sq_65_cast_fp16")]; tensor var_2428 = const()[name = tensor("op_2428"), val = tensor([1])]; tensor var_2429_cast_fp16 = reduce_mean(axes = var_2428, keep_dims = var_2256, x = zero_mean_sq_65_cast_fp16)[name = tensor("op_2429_cast_fp16")]; tensor var_2430_to_fp16 = const()[name = tensor("op_2430_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2431_cast_fp16 = add(x = var_2429_cast_fp16, y = var_2430_to_fp16)[name = tensor("op_2431_cast_fp16")]; tensor denom_65_epsilon_0_to_fp16 = const()[name = tensor("denom_65_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_65_cast_fp16 = rsqrt(epsilon = denom_65_epsilon_0_to_fp16, x = var_2431_cast_fp16)[name = tensor("denom_65_cast_fp16")]; tensor out_65_cast_fp16 = mul(x = zero_mean_65_cast_fp16, y = denom_65_cast_fp16)[name = tensor("out_65_cast_fp16")]; tensor input_105_gamma_0_to_fp16 = const()[name = tensor("input_105_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278830016)))]; tensor input_105_beta_0_to_fp16 = const()[name = tensor("input_105_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278831616)))]; tensor input_105_epsilon_0_to_fp16 = const()[name = tensor("input_105_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_105_cast_fp16 = batch_norm(beta = input_105_beta_0_to_fp16, epsilon = input_105_epsilon_0_to_fp16, gamma = input_105_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_65_cast_fp16)[name = tensor("input_105_cast_fp16")]; tensor var_2442 = const()[name = tensor("op_2442"), val = tensor([1, 1])]; tensor var_2444 = const()[name = tensor("op_2444"), val = tensor([1, 1])]; tensor input_107_pad_type_0 = const()[name = tensor("input_107_pad_type_0"), val = tensor("custom")]; tensor input_107_pad_0 = const()[name = tensor("input_107_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_fc1_weight_to_fp16 = const()[name = tensor("layers_10_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278833216)))]; tensor layers_10_fc1_bias_to_fp16 = const()[name = tensor("layers_10_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283551872)))]; tensor input_107_cast_fp16 = conv(bias = layers_10_fc1_bias_to_fp16, dilations = var_2444, groups = var_2255, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = var_2442, weight = layers_10_fc1_weight_to_fp16, x = input_105_cast_fp16)[name = tensor("input_107_cast_fp16")]; tensor input_109_mode_0 = const()[name = tensor("input_109_mode_0"), val = tensor("EXACT")]; tensor input_109_cast_fp16 = gelu(mode = input_109_mode_0, x = input_107_cast_fp16)[name = tensor("input_109_cast_fp16")]; tensor var_2450 = const()[name = tensor("op_2450"), val = tensor([1, 1])]; tensor var_2452 = const()[name = tensor("op_2452"), val = tensor([1, 1])]; tensor hidden_states_23_pad_type_0 = const()[name = tensor("hidden_states_23_pad_type_0"), val = tensor("custom")]; tensor hidden_states_23_pad_0 = const()[name = tensor("hidden_states_23_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_10_fc2_weight_to_fp16 = const()[name = tensor("layers_10_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283558080)))]; tensor layers_10_fc2_bias_to_fp16 = const()[name = tensor("layers_10_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288276736)))]; tensor hidden_states_23_cast_fp16 = conv(bias = layers_10_fc2_bias_to_fp16, dilations = var_2452, groups = var_2255, pad = hidden_states_23_pad_0, pad_type = hidden_states_23_pad_type_0, strides = var_2450, weight = layers_10_fc2_weight_to_fp16, x = input_109_cast_fp16)[name = tensor("hidden_states_23_cast_fp16")]; tensor inputs_67_cast_fp16 = add(x = inputs_65_cast_fp16, y = hidden_states_23_cast_fp16)[name = tensor("inputs_67_cast_fp16")]; tensor var_2466 = const()[name = tensor("op_2466"), val = tensor(3)]; tensor var_2473 = const()[name = tensor("op_2473"), val = tensor(1)]; tensor var_2474 = const()[name = tensor("op_2474"), val = tensor(true)]; tensor var_2486 = const()[name = tensor("op_2486"), val = tensor([1])]; tensor channels_mean_67_cast_fp16 = reduce_mean(axes = var_2486, keep_dims = var_2474, x = inputs_67_cast_fp16)[name = tensor("channels_mean_67_cast_fp16")]; tensor zero_mean_67_cast_fp16 = sub(x = inputs_67_cast_fp16, y = channels_mean_67_cast_fp16)[name = tensor("zero_mean_67_cast_fp16")]; tensor zero_mean_sq_67_cast_fp16 = mul(x = zero_mean_67_cast_fp16, y = zero_mean_67_cast_fp16)[name = tensor("zero_mean_sq_67_cast_fp16")]; tensor var_2490 = const()[name = tensor("op_2490"), val = tensor([1])]; tensor var_2491_cast_fp16 = reduce_mean(axes = var_2490, keep_dims = var_2474, x = zero_mean_sq_67_cast_fp16)[name = tensor("op_2491_cast_fp16")]; tensor var_2492_to_fp16 = const()[name = tensor("op_2492_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2493_cast_fp16 = add(x = var_2491_cast_fp16, y = var_2492_to_fp16)[name = tensor("op_2493_cast_fp16")]; tensor denom_67_epsilon_0_to_fp16 = const()[name = tensor("denom_67_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_67_cast_fp16 = rsqrt(epsilon = denom_67_epsilon_0_to_fp16, x = var_2493_cast_fp16)[name = tensor("denom_67_cast_fp16")]; tensor out_67_cast_fp16 = mul(x = zero_mean_67_cast_fp16, y = denom_67_cast_fp16)[name = tensor("out_67_cast_fp16")]; tensor obj_155_gamma_0_to_fp16 = const()[name = tensor("obj_155_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288278336)))]; tensor obj_155_beta_0_to_fp16 = const()[name = tensor("obj_155_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288279936)))]; tensor obj_155_epsilon_0_to_fp16 = const()[name = tensor("obj_155_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_155_cast_fp16 = batch_norm(beta = obj_155_beta_0_to_fp16, epsilon = obj_155_epsilon_0_to_fp16, gamma = obj_155_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_67_cast_fp16)[name = tensor("obj_155_cast_fp16")]; tensor var_2508 = const()[name = tensor("op_2508"), val = tensor([1, 1])]; tensor var_2510 = const()[name = tensor("op_2510"), val = tensor([1, 1])]; tensor query_45_pad_type_0 = const()[name = tensor("query_45_pad_type_0"), val = tensor("custom")]; tensor query_45_pad_0 = const()[name = tensor("query_45_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288281536)))]; tensor layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289461248)))]; tensor query_45_cast_fp16 = conv(bias = layers_11_self_attn_q_proj_bias_to_fp16, dilations = var_2510, groups = var_2473, pad = query_45_pad_0, pad_type = query_45_pad_type_0, strides = var_2508, weight = layers_11_self_attn_q_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("query_45_cast_fp16")]; tensor var_2514 = const()[name = tensor("op_2514"), val = tensor([1, 1])]; tensor var_2516 = const()[name = tensor("op_2516"), val = tensor([1, 1])]; tensor current_key_pad_type_0 = const()[name = tensor("current_key_pad_type_0"), val = tensor("custom")]; tensor current_key_pad_0 = const()[name = tensor("current_key_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289462848)))]; tensor current_key_cast_fp16 = conv(dilations = var_2516, groups = var_2473, pad = current_key_pad_0, pad_type = current_key_pad_type_0, strides = var_2514, weight = layers_11_self_attn_k_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("current_key_cast_fp16")]; tensor var_2521 = const()[name = tensor("op_2521"), val = tensor([1, 1])]; tensor var_2523 = const()[name = tensor("op_2523"), val = tensor([1, 1])]; tensor current_value_pad_type_0 = const()[name = tensor("current_value_pad_type_0"), val = tensor("custom")]; tensor current_value_pad_0 = const()[name = tensor("current_value_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_self_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290642560)))]; tensor layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291822272)))]; tensor current_value_cast_fp16 = conv(bias = layers_11_self_attn_v_proj_bias_to_fp16, dilations = var_2523, groups = var_2473, pad = current_value_pad_0, pad_type = current_value_pad_type_0, strides = var_2521, weight = layers_11_self_attn_v_proj_weight_to_fp16, x = obj_155_cast_fp16)[name = tensor("current_value_cast_fp16")]; tensor var_2530_cast_fp16 = mul(x = current_key_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2530_cast_fp16")]; tensor var_2532_cast_fp16 = mul(x = var_63_cast_fp16_11, y = var_161_cast_fp16)[name = tensor("op_2532_cast_fp16")]; tensor key_45_cast_fp16 = add(x = var_2530_cast_fp16, y = var_2532_cast_fp16)[name = tensor("key_45_cast_fp16")]; tensor var_2534_cast_fp16 = mul(x = current_value_cast_fp16, y = var_158_cast_fp16)[name = tensor("op_2534_cast_fp16")]; tensor var_2536_cast_fp16 = mul(x = var_78_cast_fp16_11, y = var_161_cast_fp16)[name = tensor("op_2536_cast_fp16")]; tensor value_45_cast_fp16 = add(x = var_2534_cast_fp16, y = var_2536_cast_fp16)[name = tensor("value_45_cast_fp16")]; tensor var_2539 = const()[name = tensor("op_2539"), val = tensor([1, 12, 64, -1])]; tensor var_2540_cast_fp16 = reshape(shape = var_2539, x = query_45_cast_fp16)[name = tensor("op_2540_cast_fp16")]; tensor var_2541_to_fp16 = const()[name = tensor("op_2541_to_fp16"), val = tensor(0x1p-3)]; tensor var_2542_cast_fp16 = mul(x = var_2540_cast_fp16, y = var_2541_to_fp16)[name = tensor("op_2542_cast_fp16")]; tensor var_2543 = const()[name = tensor("op_2543"), val = tensor([1, 12, 64, -1])]; tensor var_2544_cast_fp16 = reshape(shape = var_2543, x = key_45_cast_fp16)[name = tensor("op_2544_cast_fp16")]; tensor mh_w_67_transpose_x_0 = const()[name = tensor("mh_w_67_transpose_x_0"), val = tensor(true)]; tensor mh_w_67_transpose_y_0 = const()[name = tensor("mh_w_67_transpose_y_0"), val = tensor(false)]; tensor mh_w_67_cast_fp16 = matmul(transpose_x = mh_w_67_transpose_x_0, transpose_y = mh_w_67_transpose_y_0, x = var_2542_cast_fp16, y = var_2544_cast_fp16)[name = tensor("mh_w_67_cast_fp16")]; tensor mh_w_69_cast_fp16 = add(x = mh_w_67_cast_fp16, y = var_179_cast_fp16)[name = tensor("mh_w_69_cast_fp16")]; tensor var_2552_cast_fp16 = softmax(axis = var_2466, x = mh_w_69_cast_fp16)[name = tensor("op_2552_cast_fp16")]; tensor var_2553 = const()[name = tensor("op_2553"), val = tensor([1, 12, 64, -1])]; tensor var_2554_cast_fp16 = reshape(shape = var_2553, x = value_45_cast_fp16)[name = tensor("op_2554_cast_fp16")]; tensor attn_45_transpose_x_0 = const()[name = tensor("attn_45_transpose_x_0"), val = tensor(false)]; tensor attn_45_transpose_y_0 = const()[name = tensor("attn_45_transpose_y_0"), val = tensor(true)]; tensor attn_45_cast_fp16 = matmul(transpose_x = attn_45_transpose_x_0, transpose_y = attn_45_transpose_y_0, x = var_2554_cast_fp16, y = var_2552_cast_fp16)[name = tensor("attn_45_cast_fp16")]; tensor var_2557 = const()[name = tensor("op_2557"), val = tensor([1, 768, 1, -1])]; tensor input_111_cast_fp16 = reshape(shape = var_2557, x = attn_45_cast_fp16)[name = tensor("input_111_cast_fp16")]; tensor var_2561 = const()[name = tensor("op_2561"), val = tensor([1, 1])]; tensor var_2563 = const()[name = tensor("op_2563"), val = tensor([1, 1])]; tensor obj_161_pad_type_0 = const()[name = tensor("obj_161_pad_type_0"), val = tensor("custom")]; tensor obj_161_pad_0 = const()[name = tensor("obj_161_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_self_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291823872)))]; tensor layers_11_self_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293003584)))]; tensor obj_161_cast_fp16 = conv(bias = layers_11_self_attn_o_proj_bias_to_fp16, dilations = var_2563, groups = var_2473, pad = obj_161_pad_0, pad_type = obj_161_pad_type_0, strides = var_2561, weight = layers_11_self_attn_o_proj_weight_to_fp16, x = input_111_cast_fp16)[name = tensor("obj_161_cast_fp16")]; tensor inputs_69_cast_fp16 = add(x = inputs_67_cast_fp16, y = obj_161_cast_fp16)[name = tensor("inputs_69_cast_fp16")]; tensor var_2573 = const()[name = tensor("op_2573"), val = tensor([1])]; tensor channels_mean_69_cast_fp16 = reduce_mean(axes = var_2573, keep_dims = var_2474, x = inputs_69_cast_fp16)[name = tensor("channels_mean_69_cast_fp16")]; tensor zero_mean_69_cast_fp16 = sub(x = inputs_69_cast_fp16, y = channels_mean_69_cast_fp16)[name = tensor("zero_mean_69_cast_fp16")]; tensor zero_mean_sq_69_cast_fp16 = mul(x = zero_mean_69_cast_fp16, y = zero_mean_69_cast_fp16)[name = tensor("zero_mean_sq_69_cast_fp16")]; tensor var_2577 = const()[name = tensor("op_2577"), val = tensor([1])]; tensor var_2578_cast_fp16 = reduce_mean(axes = var_2577, keep_dims = var_2474, x = zero_mean_sq_69_cast_fp16)[name = tensor("op_2578_cast_fp16")]; tensor var_2579_to_fp16 = const()[name = tensor("op_2579_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2580_cast_fp16 = add(x = var_2578_cast_fp16, y = var_2579_to_fp16)[name = tensor("op_2580_cast_fp16")]; tensor denom_69_epsilon_0_to_fp16 = const()[name = tensor("denom_69_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_69_cast_fp16 = rsqrt(epsilon = denom_69_epsilon_0_to_fp16, x = var_2580_cast_fp16)[name = tensor("denom_69_cast_fp16")]; tensor out_69_cast_fp16 = mul(x = zero_mean_69_cast_fp16, y = denom_69_cast_fp16)[name = tensor("out_69_cast_fp16")]; tensor obj_163_gamma_0_to_fp16 = const()[name = tensor("obj_163_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293005184)))]; tensor obj_163_beta_0_to_fp16 = const()[name = tensor("obj_163_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293006784)))]; tensor obj_163_epsilon_0_to_fp16 = const()[name = tensor("obj_163_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor obj_163_cast_fp16 = batch_norm(beta = obj_163_beta_0_to_fp16, epsilon = obj_163_epsilon_0_to_fp16, gamma = obj_163_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_69_cast_fp16)[name = tensor("obj_163_cast_fp16")]; tensor var_2595 = const()[name = tensor("op_2595"), val = tensor([1, 1])]; tensor var_2597 = const()[name = tensor("op_2597"), val = tensor([1, 1])]; tensor query_pad_type_0 = const()[name = tensor("query_pad_type_0"), val = tensor("custom")]; tensor query_pad_0 = const()[name = tensor("query_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_encoder_attn_q_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_q_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293008384)))]; tensor layers_11_encoder_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294188096)))]; tensor query_cast_fp16 = conv(bias = layers_11_encoder_attn_q_proj_bias_to_fp16, dilations = var_2597, groups = var_2473, pad = query_pad_0, pad_type = query_pad_type_0, strides = var_2595, weight = layers_11_encoder_attn_q_proj_weight_to_fp16, x = obj_163_cast_fp16)[name = tensor("query_cast_fp16")]; tensor var_2601 = const()[name = tensor("op_2601"), val = tensor([1, 1])]; tensor var_2603 = const()[name = tensor("op_2603"), val = tensor([1, 1])]; tensor key_pad_type_0 = const()[name = tensor("key_pad_type_0"), val = tensor("custom")]; tensor key_pad_0 = const()[name = tensor("key_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_encoder_attn_k_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_k_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294189696)))]; tensor key_cast_fp16 = conv(dilations = var_2603, groups = var_2473, pad = key_pad_0, pad_type = key_pad_type_0, strides = var_2601, weight = layers_11_encoder_attn_k_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("key_cast_fp16")]; tensor var_2608 = const()[name = tensor("op_2608"), val = tensor([1, 1])]; tensor var_2610 = const()[name = tensor("op_2610"), val = tensor([1, 1])]; tensor value_pad_type_0 = const()[name = tensor("value_pad_type_0"), val = tensor("custom")]; tensor value_pad_0 = const()[name = tensor("value_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_encoder_attn_v_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_v_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295369408)))]; tensor layers_11_encoder_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296549120)))]; tensor value_cast_fp16 = conv(bias = layers_11_encoder_attn_v_proj_bias_to_fp16, dilations = var_2610, groups = var_2473, pad = value_pad_0, pad_type = value_pad_type_0, strides = var_2608, weight = layers_11_encoder_attn_v_proj_weight_to_fp16, x = encoder_output_embeds)[name = tensor("value_cast_fp16")]; tensor var_2614 = const()[name = tensor("op_2614"), val = tensor([1, 12, 64, -1])]; tensor var_2615_cast_fp16 = reshape(shape = var_2614, x = query_cast_fp16)[name = tensor("op_2615_cast_fp16")]; tensor var_2616_to_fp16 = const()[name = tensor("op_2616_to_fp16"), val = tensor(0x1p-3)]; tensor var_2617_cast_fp16 = mul(x = var_2615_cast_fp16, y = var_2616_to_fp16)[name = tensor("op_2617_cast_fp16")]; tensor var_2618 = const()[name = tensor("op_2618"), val = tensor([1, 12, 64, -1])]; tensor var_2619_cast_fp16 = reshape(shape = var_2618, x = key_cast_fp16)[name = tensor("op_2619_cast_fp16")]; tensor mh_w_transpose_x_0 = const()[name = tensor("mh_w_transpose_x_0"), val = tensor(true)]; tensor mh_w_transpose_y_0 = const()[name = tensor("mh_w_transpose_y_0"), val = tensor(false)]; tensor mh_w_cast_fp16 = matmul(transpose_x = mh_w_transpose_x_0, transpose_y = mh_w_transpose_y_0, x = var_2617_cast_fp16, y = var_2619_cast_fp16)[name = tensor("mh_w_cast_fp16")]; tensor obj_167_cast_fp16 = softmax(axis = var_2466, x = mh_w_cast_fp16)[name = tensor("obj_167_cast_fp16")]; tensor var_2623 = const()[name = tensor("op_2623"), val = tensor([1, 12, 64, -1])]; tensor var_2624_cast_fp16 = reshape(shape = var_2623, x = value_cast_fp16)[name = tensor("op_2624_cast_fp16")]; tensor attn_transpose_x_0 = const()[name = tensor("attn_transpose_x_0"), val = tensor(false)]; tensor attn_transpose_y_0 = const()[name = tensor("attn_transpose_y_0"), val = tensor(true)]; tensor attn_cast_fp16 = matmul(transpose_x = attn_transpose_x_0, transpose_y = attn_transpose_y_0, x = var_2624_cast_fp16, y = obj_167_cast_fp16)[name = tensor("attn_cast_fp16")]; tensor var_2627 = const()[name = tensor("op_2627"), val = tensor([1, 768, 1, -1])]; tensor input_113_cast_fp16 = reshape(shape = var_2627, x = attn_cast_fp16)[name = tensor("input_113_cast_fp16")]; tensor var_2631 = const()[name = tensor("op_2631"), val = tensor([1, 1])]; tensor var_2633 = const()[name = tensor("op_2633"), val = tensor([1, 1])]; tensor obj_165_pad_type_0 = const()[name = tensor("obj_165_pad_type_0"), val = tensor("custom")]; tensor obj_165_pad_0 = const()[name = tensor("obj_165_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_encoder_attn_o_proj_weight_to_fp16 = const()[name = tensor("layers_11_encoder_attn_o_proj_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296550720)))]; tensor layers_11_encoder_attn_o_proj_bias_to_fp16 = const()[name = tensor("layers_11_encoder_attn_o_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297730432)))]; tensor obj_165_cast_fp16 = conv(bias = layers_11_encoder_attn_o_proj_bias_to_fp16, dilations = var_2633, groups = var_2473, pad = obj_165_pad_0, pad_type = obj_165_pad_type_0, strides = var_2631, weight = layers_11_encoder_attn_o_proj_weight_to_fp16, x = input_113_cast_fp16)[name = tensor("obj_165_cast_fp16")]; tensor inputs_71_cast_fp16 = add(x = inputs_69_cast_fp16, y = obj_165_cast_fp16)[name = tensor("inputs_71_cast_fp16")]; tensor var_2639 = const()[name = tensor("op_2639"), val = tensor([1])]; tensor channels_mean_71_cast_fp16 = reduce_mean(axes = var_2639, keep_dims = var_2474, x = inputs_71_cast_fp16)[name = tensor("channels_mean_71_cast_fp16")]; tensor zero_mean_71_cast_fp16 = sub(x = inputs_71_cast_fp16, y = channels_mean_71_cast_fp16)[name = tensor("zero_mean_71_cast_fp16")]; tensor zero_mean_sq_71_cast_fp16 = mul(x = zero_mean_71_cast_fp16, y = zero_mean_71_cast_fp16)[name = tensor("zero_mean_sq_71_cast_fp16")]; tensor var_2643 = const()[name = tensor("op_2643"), val = tensor([1])]; tensor var_2644_cast_fp16 = reduce_mean(axes = var_2643, keep_dims = var_2474, x = zero_mean_sq_71_cast_fp16)[name = tensor("op_2644_cast_fp16")]; tensor var_2645_to_fp16 = const()[name = tensor("op_2645_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2646_cast_fp16 = add(x = var_2644_cast_fp16, y = var_2645_to_fp16)[name = tensor("op_2646_cast_fp16")]; tensor denom_71_epsilon_0_to_fp16 = const()[name = tensor("denom_71_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_71_cast_fp16 = rsqrt(epsilon = denom_71_epsilon_0_to_fp16, x = var_2646_cast_fp16)[name = tensor("denom_71_cast_fp16")]; tensor out_71_cast_fp16 = mul(x = zero_mean_71_cast_fp16, y = denom_71_cast_fp16)[name = tensor("out_71_cast_fp16")]; tensor input_115_gamma_0_to_fp16 = const()[name = tensor("input_115_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297732032)))]; tensor input_115_beta_0_to_fp16 = const()[name = tensor("input_115_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297733632)))]; tensor input_115_epsilon_0_to_fp16 = const()[name = tensor("input_115_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_115_cast_fp16 = batch_norm(beta = input_115_beta_0_to_fp16, epsilon = input_115_epsilon_0_to_fp16, gamma = input_115_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_71_cast_fp16)[name = tensor("input_115_cast_fp16")]; tensor var_2657 = const()[name = tensor("op_2657"), val = tensor([1, 1])]; tensor var_2659 = const()[name = tensor("op_2659"), val = tensor([1, 1])]; tensor input_117_pad_type_0 = const()[name = tensor("input_117_pad_type_0"), val = tensor("custom")]; tensor input_117_pad_0 = const()[name = tensor("input_117_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_fc1_weight_to_fp16 = const()[name = tensor("layers_11_fc1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297735232)))]; tensor layers_11_fc1_bias_to_fp16 = const()[name = tensor("layers_11_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302453888)))]; tensor input_117_cast_fp16 = conv(bias = layers_11_fc1_bias_to_fp16, dilations = var_2659, groups = var_2473, pad = input_117_pad_0, pad_type = input_117_pad_type_0, strides = var_2657, weight = layers_11_fc1_weight_to_fp16, x = input_115_cast_fp16)[name = tensor("input_117_cast_fp16")]; tensor input_mode_0 = const()[name = tensor("input_mode_0"), val = tensor("EXACT")]; tensor input_cast_fp16 = gelu(mode = input_mode_0, x = input_117_cast_fp16)[name = tensor("input_cast_fp16")]; tensor var_2665 = const()[name = tensor("op_2665"), val = tensor([1, 1])]; tensor var_2667 = const()[name = tensor("op_2667"), val = tensor([1, 1])]; tensor hidden_states_25_pad_type_0 = const()[name = tensor("hidden_states_25_pad_type_0"), val = tensor("custom")]; tensor hidden_states_25_pad_0 = const()[name = tensor("hidden_states_25_pad_0"), val = tensor([0, 0, 0, 0])]; tensor layers_11_fc2_weight_to_fp16 = const()[name = tensor("layers_11_fc2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302460096)))]; tensor layers_11_fc2_bias_to_fp16 = const()[name = tensor("layers_11_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307178752)))]; tensor hidden_states_25_cast_fp16 = conv(bias = layers_11_fc2_bias_to_fp16, dilations = var_2667, groups = var_2473, pad = hidden_states_25_pad_0, pad_type = hidden_states_25_pad_type_0, strides = var_2665, weight = layers_11_fc2_weight_to_fp16, x = input_cast_fp16)[name = tensor("hidden_states_25_cast_fp16")]; tensor inputs_cast_fp16 = add(x = inputs_71_cast_fp16, y = hidden_states_25_cast_fp16)[name = tensor("inputs_cast_fp16")]; tensor var_2677 = const()[name = tensor("op_2677"), val = tensor(true)]; tensor var_2681 = const()[name = tensor("op_2681"), val = tensor([1])]; tensor channels_mean_cast_fp16 = reduce_mean(axes = var_2681, keep_dims = var_2677, x = inputs_cast_fp16)[name = tensor("channels_mean_cast_fp16")]; tensor zero_mean_cast_fp16 = sub(x = inputs_cast_fp16, y = channels_mean_cast_fp16)[name = tensor("zero_mean_cast_fp16")]; tensor zero_mean_sq_cast_fp16 = mul(x = zero_mean_cast_fp16, y = zero_mean_cast_fp16)[name = tensor("zero_mean_sq_cast_fp16")]; tensor var_2685 = const()[name = tensor("op_2685"), val = tensor([1])]; tensor var_2686_cast_fp16 = reduce_mean(axes = var_2685, keep_dims = var_2677, x = zero_mean_sq_cast_fp16)[name = tensor("op_2686_cast_fp16")]; tensor var_2687_to_fp16 = const()[name = tensor("op_2687_to_fp16"), val = tensor(0x1.5p-17)]; tensor var_2688_cast_fp16 = add(x = var_2686_cast_fp16, y = var_2687_to_fp16)[name = tensor("op_2688_cast_fp16")]; tensor denom_epsilon_0_to_fp16 = const()[name = tensor("denom_epsilon_0_to_fp16"), val = tensor(0x1p-24)]; tensor denom_cast_fp16 = rsqrt(epsilon = denom_epsilon_0_to_fp16, x = var_2688_cast_fp16)[name = tensor("denom_cast_fp16")]; tensor out_cast_fp16 = mul(x = zero_mean_cast_fp16, y = denom_cast_fp16)[name = tensor("out_cast_fp16")]; tensor hidden_states_gamma_0_to_fp16 = const()[name = tensor("hidden_states_gamma_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307180352)))]; tensor hidden_states_beta_0_to_fp16 = const()[name = tensor("hidden_states_beta_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307181952)))]; tensor hidden_states_epsilon_0_to_fp16 = const()[name = tensor("hidden_states_epsilon_0_to_fp16"), val = tensor(0x1.5p-17)]; tensor hidden_states_cast_fp16 = batch_norm(beta = hidden_states_beta_0_to_fp16, epsilon = hidden_states_epsilon_0_to_fp16, gamma = hidden_states_gamma_0_to_fp16, mean = obj_1_mean_0_to_fp16, variance = obj_1_variance_0_to_fp16, x = out_cast_fp16)[name = tensor("hidden_states_cast_fp16")]; tensor var_2698_axes_0 = const()[name = tensor("op_2698_axes_0"), val = tensor([2])]; tensor var_2698_cast_fp16 = squeeze(axes = var_2698_axes_0, x = hidden_states_cast_fp16)[name = tensor("op_2698_cast_fp16")]; tensor var_2701_perm_0 = const()[name = tensor("op_2701_perm_0"), val = tensor([0, 2, 1])]; tensor linear_0_bias_0_to_fp16 = const()[name = tensor("linear_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307183552)))]; tensor transpose_0 = transpose(perm = var_2701_perm_0, x = var_2698_cast_fp16)[name = tensor("transpose_0")]; tensor logits = linear(bias = linear_0_bias_0_to_fp16, weight = embed_tokens_weight_to_fp16, x = transpose_0)[name = tensor("linear_0_cast_fp16")]; tensor var_2705 = const()[name = tensor("op_2705"), val = tensor(1)]; tensor obj_171_interleave_0 = const()[name = tensor("obj_171_interleave_0"), val = tensor(false)]; tensor key_cache_updates = concat(axis = var_2705, interleave = obj_171_interleave_0, values = (current_key_1_cast_fp16, current_key_3_cast_fp16, current_key_5_cast_fp16, current_key_7_cast_fp16, current_key_9_cast_fp16, current_key_11_cast_fp16, current_key_13_cast_fp16, current_key_15_cast_fp16, current_key_17_cast_fp16, current_key_19_cast_fp16, current_key_21_cast_fp16, current_key_cast_fp16))[name = tensor("obj_171_cast_fp16")]; tensor var_2708 = const()[name = tensor("op_2708"), val = tensor(1)]; tensor obj_173_interleave_0 = const()[name = tensor("obj_173_interleave_0"), val = tensor(false)]; tensor value_cache_updates = concat(axis = var_2708, interleave = obj_173_interleave_0, values = (current_value_1_cast_fp16, current_value_3_cast_fp16, current_value_5_cast_fp16, current_value_7_cast_fp16, current_value_9_cast_fp16, current_value_11_cast_fp16, current_value_13_cast_fp16, current_value_15_cast_fp16, current_value_17_cast_fp16, current_value_19_cast_fp16, current_value_21_cast_fp16, current_value_cast_fp16))[name = tensor("obj_173_cast_fp16")]; tensor var_2719_begin_0 = const()[name = tensor("op_2719_begin_0"), val = tensor([0, 3, 0, 0])]; tensor var_2719_end_0 = const()[name = tensor("op_2719_end_0"), val = tensor([1, 4, 1, 1500])]; tensor var_2719_end_mask_0 = const()[name = tensor("op_2719_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2719_cast_fp16 = slice_by_index(begin = var_2719_begin_0, end = var_2719_end_0, end_mask = var_2719_end_mask_0, x = obj_83_cast_fp16)[name = tensor("op_2719_cast_fp16")]; tensor var_2722_begin_0 = const()[name = tensor("op_2722_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2722_end_0 = const()[name = tensor("op_2722_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2722_end_mask_0 = const()[name = tensor("op_2722_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2722_squeeze_mask_0 = const()[name = tensor("op_2722_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2722_cast_fp16 = slice_by_index(begin = var_2722_begin_0, end = var_2722_end_0, end_mask = var_2722_end_mask_0, squeeze_mask = var_2722_squeeze_mask_0, x = var_2719_cast_fp16)[name = tensor("op_2722_cast_fp16")]; tensor var_2737_begin_0 = const()[name = tensor("op_2737_begin_0"), val = tensor([0, 9, 0, 0])]; tensor var_2737_end_0 = const()[name = tensor("op_2737_end_0"), val = tensor([1, 10, 1, 1500])]; tensor var_2737_end_mask_0 = const()[name = tensor("op_2737_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2737_cast_fp16 = slice_by_index(begin = var_2737_begin_0, end = var_2737_end_0, end_mask = var_2737_end_mask_0, x = obj_83_cast_fp16)[name = tensor("op_2737_cast_fp16")]; tensor var_2740_begin_0 = const()[name = tensor("op_2740_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2740_end_0 = const()[name = tensor("op_2740_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2740_end_mask_0 = const()[name = tensor("op_2740_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2740_squeeze_mask_0 = const()[name = tensor("op_2740_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2740_cast_fp16 = slice_by_index(begin = var_2740_begin_0, end = var_2740_end_0, end_mask = var_2740_end_mask_0, squeeze_mask = var_2740_squeeze_mask_0, x = var_2737_cast_fp16)[name = tensor("op_2740_cast_fp16")]; tensor var_2755_begin_0 = const()[name = tensor("op_2755_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2755_end_0 = const()[name = tensor("op_2755_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2755_end_mask_0 = const()[name = tensor("op_2755_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2755_cast_fp16 = slice_by_index(begin = var_2755_begin_0, end = var_2755_end_0, end_mask = var_2755_end_mask_0, x = obj_125_cast_fp16)[name = tensor("op_2755_cast_fp16")]; tensor var_2758_begin_0 = const()[name = tensor("op_2758_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2758_end_0 = const()[name = tensor("op_2758_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2758_end_mask_0 = const()[name = tensor("op_2758_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2758_squeeze_mask_0 = const()[name = tensor("op_2758_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2758_cast_fp16 = slice_by_index(begin = var_2758_begin_0, end = var_2758_end_0, end_mask = var_2758_end_mask_0, squeeze_mask = var_2758_squeeze_mask_0, x = var_2755_cast_fp16)[name = tensor("op_2758_cast_fp16")]; tensor var_2773_begin_0 = const()[name = tensor("op_2773_begin_0"), val = tensor([0, 4, 0, 0])]; tensor var_2773_end_0 = const()[name = tensor("op_2773_end_0"), val = tensor([1, 5, 1, 1500])]; tensor var_2773_end_mask_0 = const()[name = tensor("op_2773_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2773_cast_fp16 = slice_by_index(begin = var_2773_begin_0, end = var_2773_end_0, end_mask = var_2773_end_mask_0, x = obj_125_cast_fp16)[name = tensor("op_2773_cast_fp16")]; tensor var_2776_begin_0 = const()[name = tensor("op_2776_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2776_end_0 = const()[name = tensor("op_2776_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2776_end_mask_0 = const()[name = tensor("op_2776_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2776_squeeze_mask_0 = const()[name = tensor("op_2776_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2776_cast_fp16 = slice_by_index(begin = var_2776_begin_0, end = var_2776_end_0, end_mask = var_2776_end_mask_0, squeeze_mask = var_2776_squeeze_mask_0, x = var_2773_cast_fp16)[name = tensor("op_2776_cast_fp16")]; tensor var_2791_begin_0 = const()[name = tensor("op_2791_begin_0"), val = tensor([0, 7, 0, 0])]; tensor var_2791_end_0 = const()[name = tensor("op_2791_end_0"), val = tensor([1, 8, 1, 1500])]; tensor var_2791_end_mask_0 = const()[name = tensor("op_2791_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2791_cast_fp16 = slice_by_index(begin = var_2791_begin_0, end = var_2791_end_0, end_mask = var_2791_end_mask_0, x = obj_125_cast_fp16)[name = tensor("op_2791_cast_fp16")]; tensor var_2794_begin_0 = const()[name = tensor("op_2794_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2794_end_0 = const()[name = tensor("op_2794_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2794_end_mask_0 = const()[name = tensor("op_2794_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2794_squeeze_mask_0 = const()[name = tensor("op_2794_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2794_cast_fp16 = slice_by_index(begin = var_2794_begin_0, end = var_2794_end_0, end_mask = var_2794_end_mask_0, squeeze_mask = var_2794_squeeze_mask_0, x = var_2791_cast_fp16)[name = tensor("op_2794_cast_fp16")]; tensor var_2809_begin_0 = const()[name = tensor("op_2809_begin_0"), val = tensor([0, 8, 0, 0])]; tensor var_2809_end_0 = const()[name = tensor("op_2809_end_0"), val = tensor([1, 9, 1, 1500])]; tensor var_2809_end_mask_0 = const()[name = tensor("op_2809_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2809_cast_fp16 = slice_by_index(begin = var_2809_begin_0, end = var_2809_end_0, end_mask = var_2809_end_mask_0, x = obj_125_cast_fp16)[name = tensor("op_2809_cast_fp16")]; tensor var_2812_begin_0 = const()[name = tensor("op_2812_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2812_end_0 = const()[name = tensor("op_2812_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2812_end_mask_0 = const()[name = tensor("op_2812_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2812_squeeze_mask_0 = const()[name = tensor("op_2812_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2812_cast_fp16 = slice_by_index(begin = var_2812_begin_0, end = var_2812_end_0, end_mask = var_2812_end_mask_0, squeeze_mask = var_2812_squeeze_mask_0, x = var_2809_cast_fp16)[name = tensor("op_2812_cast_fp16")]; tensor var_2827_begin_0 = const()[name = tensor("op_2827_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2827_end_0 = const()[name = tensor("op_2827_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2827_end_mask_0 = const()[name = tensor("op_2827_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2827_cast_fp16 = slice_by_index(begin = var_2827_begin_0, end = var_2827_end_0, end_mask = var_2827_end_mask_0, x = obj_139_cast_fp16)[name = tensor("op_2827_cast_fp16")]; tensor var_2830_begin_0 = const()[name = tensor("op_2830_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2830_end_0 = const()[name = tensor("op_2830_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2830_end_mask_0 = const()[name = tensor("op_2830_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2830_squeeze_mask_0 = const()[name = tensor("op_2830_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2830_cast_fp16 = slice_by_index(begin = var_2830_begin_0, end = var_2830_end_0, end_mask = var_2830_end_mask_0, squeeze_mask = var_2830_squeeze_mask_0, x = var_2827_cast_fp16)[name = tensor("op_2830_cast_fp16")]; tensor var_2845_begin_0 = const()[name = tensor("op_2845_begin_0"), val = tensor([0, 7, 0, 0])]; tensor var_2845_end_0 = const()[name = tensor("op_2845_end_0"), val = tensor([1, 8, 1, 1500])]; tensor var_2845_end_mask_0 = const()[name = tensor("op_2845_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2845_cast_fp16 = slice_by_index(begin = var_2845_begin_0, end = var_2845_end_0, end_mask = var_2845_end_mask_0, x = obj_139_cast_fp16)[name = tensor("op_2845_cast_fp16")]; tensor var_2848_begin_0 = const()[name = tensor("op_2848_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2848_end_0 = const()[name = tensor("op_2848_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2848_end_mask_0 = const()[name = tensor("op_2848_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2848_squeeze_mask_0 = const()[name = tensor("op_2848_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2848_cast_fp16 = slice_by_index(begin = var_2848_begin_0, end = var_2848_end_0, end_mask = var_2848_end_mask_0, squeeze_mask = var_2848_squeeze_mask_0, x = var_2845_cast_fp16)[name = tensor("op_2848_cast_fp16")]; tensor var_2863_begin_0 = const()[name = tensor("op_2863_begin_0"), val = tensor([0, 9, 0, 0])]; tensor var_2863_end_0 = const()[name = tensor("op_2863_end_0"), val = tensor([1, 10, 1, 1500])]; tensor var_2863_end_mask_0 = const()[name = tensor("op_2863_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2863_cast_fp16 = slice_by_index(begin = var_2863_begin_0, end = var_2863_end_0, end_mask = var_2863_end_mask_0, x = obj_139_cast_fp16)[name = tensor("op_2863_cast_fp16")]; tensor var_2866_begin_0 = const()[name = tensor("op_2866_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2866_end_0 = const()[name = tensor("op_2866_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2866_end_mask_0 = const()[name = tensor("op_2866_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2866_squeeze_mask_0 = const()[name = tensor("op_2866_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2866_cast_fp16 = slice_by_index(begin = var_2866_begin_0, end = var_2866_end_0, end_mask = var_2866_end_mask_0, squeeze_mask = var_2866_squeeze_mask_0, x = var_2863_cast_fp16)[name = tensor("op_2866_cast_fp16")]; tensor var_2881_begin_0 = const()[name = tensor("op_2881_begin_0"), val = tensor([0, 5, 0, 0])]; tensor var_2881_end_0 = const()[name = tensor("op_2881_end_0"), val = tensor([1, 6, 1, 1500])]; tensor var_2881_end_mask_0 = const()[name = tensor("op_2881_end_mask_0"), val = tensor([true, false, true, true])]; tensor var_2881_cast_fp16 = slice_by_index(begin = var_2881_begin_0, end = var_2881_end_0, end_mask = var_2881_end_mask_0, x = obj_153_cast_fp16)[name = tensor("op_2881_cast_fp16")]; tensor var_2884_begin_0 = const()[name = tensor("op_2884_begin_0"), val = tensor([0, 0, 0, 0])]; tensor var_2884_end_0 = const()[name = tensor("op_2884_end_0"), val = tensor([1, 1, 1, 1500])]; tensor var_2884_end_mask_0 = const()[name = tensor("op_2884_end_mask_0"), val = tensor([true, true, false, true])]; tensor var_2884_squeeze_mask_0 = const()[name = tensor("op_2884_squeeze_mask_0"), val = tensor([false, false, true, false])]; tensor var_2884_cast_fp16 = slice_by_index(begin = var_2884_begin_0, end = var_2884_end_0, end_mask = var_2884_end_mask_0, squeeze_mask = var_2884_squeeze_mask_0, x = var_2881_cast_fp16)[name = tensor("op_2884_cast_fp16")]; tensor var_2891 = const()[name = tensor("op_2891"), val = tensor(1)]; tensor var_2892_interleave_0 = const()[name = tensor("op_2892_interleave_0"), val = tensor(false)]; tensor var_2892_cast_fp16 = concat(axis = var_2891, interleave = var_2892_interleave_0, values = (var_2722_cast_fp16, var_2740_cast_fp16, var_2758_cast_fp16, var_2776_cast_fp16, var_2794_cast_fp16, var_2812_cast_fp16, var_2830_cast_fp16, var_2848_cast_fp16, var_2866_cast_fp16, var_2884_cast_fp16))[name = tensor("op_2892_cast_fp16")]; tensor var_2894 = const()[name = tensor("op_2894"), val = tensor([1])]; tensor var_2895 = const()[name = tensor("op_2895"), val = tensor(false)]; tensor alignment_heads_weights = reduce_mean(axes = var_2894, keep_dims = var_2895, x = var_2892_cast_fp16)[name = tensor("obj_cast_fp16")]; } -> (logits, key_cache_updates, value_cache_updates, alignment_heads_weights); }