From b5bc0cca453b51a8ce63e47e6cd349b83f43805d Mon Sep 17 00:00:00 2001 From: ykxia Date: Fri, 25 Nov 2022 14:55:18 +0800 Subject: [PATCH] =?UTF-8?q?SSD-Resnet50V1-FPN=5FID1463=5Ffor=5FTensorFlow?= =?UTF-8?q?=E9=80=82=E9=85=8DRT2.0+=E4=BA=8C=E8=BF=9B=E5=88=B6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../models/research/object_detection/model_main_rt.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/TensorFlow/built-in/cv/detection/SSD-Resnet50V1-FPN_ID1463_for_TensorFlow/models/research/object_detection/model_main_rt.py b/TensorFlow/built-in/cv/detection/SSD-Resnet50V1-FPN_ID1463_for_TensorFlow/models/research/object_detection/model_main_rt.py index 46bcfb668..aa1dab728 100644 --- a/TensorFlow/built-in/cv/detection/SSD-Resnet50V1-FPN_ID1463_for_TensorFlow/models/research/object_detection/model_main_rt.py +++ b/TensorFlow/built-in/cv/detection/SSD-Resnet50V1-FPN_ID1463_for_TensorFlow/models/research/object_detection/model_main_rt.py @@ -123,7 +123,7 @@ def main(unused_argv): model_dir = (FLAGS.model_dir if (get_npu_rank_id() == 0) else None) config = tf.estimator.RunConfig(model_dir=model_dir, session_config=session_config) - train_and_eval_dict = model_lib.create_estimator_and_inputs(run_config=config, eval_count=FLAGS.eval_count, hparams=model_hparams.create_hparams(FLAGS.hparams_overrides), pipeline_config_path=FLAGS.pipeline_config_path, train_steps=FLAGS.num_train_steps, sample_1_of_n_eval_examples=FLAGS.sample_1_of_n_eval_examples, sample_1_of_n_eval_on_train_examples=FLAGS.sample_1_of_n_eval_on_train_examples) + train_and_eval_dict = model_lib_rt.create_estimator_and_inputs(run_config=config, eval_count=FLAGS.eval_count, hparams=model_hparams.create_hparams(FLAGS.hparams_overrides), pipeline_config_path=FLAGS.pipeline_config_path, train_steps=FLAGS.num_train_steps, sample_1_of_n_eval_examples=FLAGS.sample_1_of_n_eval_examples, sample_1_of_n_eval_on_train_examples=FLAGS.sample_1_of_n_eval_on_train_examples) estimator = train_and_eval_dict['estimator'] train_input_fn = train_and_eval_dict['train_input_fn'] eval_input_fns = train_and_eval_dict['eval_input_fns'] @@ -142,7 +142,7 @@ def main(unused_argv): #else: # model_lib.continuous_eval(estimator, FLAGS.checkpoint_dir, input_fn, train_steps, name) else: - (train_spec, eval_specs) = model_lib.create_train_and_eval_specs(train_input_fn, eval_input_fns, eval_on_train_input_fn, predict_input_fn, train_steps, eval_on_train_data=False) + (train_spec, eval_specs) = model_lib_rt.create_train_and_eval_specs(train_input_fn, eval_input_fns, eval_on_train_input_fn, predict_input_fn, train_steps, eval_on_train_data=False) ##################################NPU_modify add################################### if FLAGS.check_loss_scale: train_hooks = [NpuEmptyHook(), DLLoggerHook((get_rank_size() * train_and_eval_dict['train_batch_size']), get_npu_rank_id()),_LogSessionRunHook()] -- Gitee