From 0b1571476ad15ac723e23f8ee36155b35c98de57 Mon Sep 17 00:00:00 2001 From: Your Name Date: Wed, 23 Feb 2022 17:25:56 +0800 Subject: [PATCH] Add freeze_bn config Signed-off-by: Your Name --- resnet_training_yaml.yaml | 11 ++++++----- test.py | 24 ++++++++++++------------ 2 files changed, 18 insertions(+), 17 deletions(-) diff --git a/resnet_training_yaml.yaml b/resnet_training_yaml.yaml index 65c222a..1a79cfe 100644 --- a/resnet_training_yaml.yaml +++ b/resnet_training_yaml.yaml @@ -4,7 +4,7 @@ callback: monitor: eval_epoch_metric patience: 2 model_checkpoint: - every_n_epoch: 2 + every_n_epoch: 1 tensorboard: comment: '' log_dir: null @@ -23,20 +23,21 @@ logging: logging_dir: null logging_strategy: steps print_steps: null - save_strategy: steps metrics: metric: Accuracy train: - batch_size: 16 + batch_size: 256 dataloader_drop_last: false dataloader_num_workers: 0 - epoch_num: 16 + dataloader_pin_memory: true + epoch_num: 3 eval_steps: null eval_strategy: epoch + freeze_bn: true load_best_model_at_end: false - max_steps: -1 output_dir: ./output_dir overwrite_output_dir: true resume_from_checkpoint: null seed: 42 val_batch_size: -1 + freeze_bn: true diff --git a/test.py b/test.py index c4d2a6d..ee41a10 100644 --- a/test.py +++ b/test.py @@ -43,12 +43,12 @@ if __name__ == '__main__': # dump_default_yaml(yaml_path=yaml_path) training_config.load_from_yaml(yaml_path) - training_config.overwrite_output_dir=True - training_config.epoch_num=3 - training_config.batch_size=256 - training_config.device_str='cpu' - training_config.n_gpu=-1 - training_config.save_to_yaml(yaml_path) + # training_config.overwrite_output_dir=True + # training_config.epoch_num=3 + # training_config.batch_size=256 + # training_config.device_str='cpu' + # training_config.n_gpu=-1 + # training_config.save_to_yaml(yaml_path) # mnist_transform = transforms.Compose([transforms.ToTensor(), # RandomResizedCrop(224), @@ -59,8 +59,8 @@ if __name__ == '__main__': # training_config.output_dir = 'mnist_output' fake_transform = transforms.Compose([transforms.ToTensor(), RandomResizedCrop(224),]) - train_data = dataset('fake', size=1000, transform=fake_transform) - eval_data = dataset('fake', size=500, transform=fake_transform) + train_data = dataset('fake', size=100, transform=fake_transform) + eval_data = dataset('fake', size=10, transform=fake_transform) training_config.output_dir = 'fake_output' # trainer = op.setup_trainer() @@ -87,7 +87,7 @@ if __name__ == '__main__': # op.train(training_config, train_dataset=train_data, eval_dataset=eval_data, resume_checkpoint_path=training_config.output_dir + '/epoch_2') # op.save('./test_save') - # op.load('./test_save') - # new_out = op(towhee_img) - # - # assert (new_out[0]!=old_out[0]).all() + # op.load('./test_save')\ + + new_out = op(towhee_img) + assert (new_out.feature_vector==old_out.feature_vector).all()