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modify config param

This commit is contained in:
meixiaowei 2020-04-29 10:18:28 +08:00
parent 4fff5f442c
commit efe41902b8
4 changed files with 7 additions and 7 deletions
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4
example/resnet101_imagenet2012/README.md
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@ -51,8 +51,8 @@ Parameters for both training and evaluating can be set in config.py.
"image_height": 224, # image height
"image_width": 224, # image width
"save_checkpoint": True, # whether save checkpoint or not
"save_checkpoint_steps": 500, # the step interval between two checkpoints. By default, the last checkpoint will be saved after the last step
"keep_checkpoint_max": 40, # only keep the last keep_checkpoint_max checkpoint
"save_checkpoint_epochs": 1, # the epoch interval between two checkpoints. By default, the last checkpoint will be saved after the last epoch
"keep_checkpoint_max": 10, # only keep the last keep_checkpoint_max checkpoint
"save_checkpoint_path": "./", # path to save checkpoint relative to the executed path
"warmup_epochs": 0, # number of warmup epoch
"lr_decay_mode": "cosine" # decay mode for generating learning rate

4
example/resnet101_imagenet2012/config.py
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@ -28,8 +28,8 @@ config = ed({
"image_height": 224,
"image_width": 224,
"save_checkpoint": True,
"save_checkpoint_steps": 500,
"keep_checkpoint_max": 40,
"save_checkpoint_epochs": 1,
"keep_checkpoint_max": 10,
"save_checkpoint_path": "./",
"warmup_epochs": 0,
"lr_decay_mode": "cosine",

2
example/resnet101_imagenet2012/eval.py
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@ -54,7 +54,7 @@ if __name__ == '__main__':
if not args_opt.do_eval and args_opt.run_distribute:
context.set_auto_parallel_context(device_num=args_opt.device_num, parallel_mode=ParallelMode.DATA_PARALLEL,
mirror_mean=True, parameter_broadcast=True)
auto_parallel_context().set_all_reduce_fusion_split_indices([140])
auto_parallel_context().set_all_reduce_fusion_split_indices([180, 313])
init()
epoch_size = config.epoch_size

4
example/resnet101_imagenet2012/train.py
View File

@ -59,7 +59,7 @@ if __name__ == '__main__':
if not args_opt.do_eval and args_opt.run_distribute:
context.set_auto_parallel_context(device_num=args_opt.device_num, parallel_mode=ParallelMode.DATA_PARALLEL,
mirror_mean=True, parameter_broadcast=True)
auto_parallel_context().set_all_reduce_fusion_split_indices([140])
auto_parallel_context().set_all_reduce_fusion_split_indices([180, 313])
init()
epoch_size = config.epoch_size
@ -91,7 +91,7 @@ if __name__ == '__main__':
loss_cb = LossMonitor()
cb = [time_cb, loss_cb]
if config.save_checkpoint:
config_ck = CheckpointConfig(save_checkpoint_steps=config.save_checkpoint_steps,
config_ck = CheckpointConfig(save_checkpoint_steps=config.save_checkpoint_epochs*step_size,
keep_checkpoint_max=config.keep_checkpoint_max)
ckpt_cb = ModelCheckpoint(prefix="resnet", directory=config.save_checkpoint_path, config=config_ck)
cb += [ckpt_cb]