towhee.trainer.callback.ProgressBarCallBack¶
- class towhee.trainer.callback.ProgressBarCallBack(total_epoch_num: int, train_dataloader: DataLoader)[source]¶
Bases:
Callback
ProgressBarCallBack is intended to print a progress bar to visualize current training progress. The tqdm is used as the progress bar backend.
- Parameters:
total_epoch_num (int) – Epoch numbers expected to run.
train_dataloader (torch.utils.data.DataLoader) – training dataloader for tqdm to warp.
Methods
Hook function invoked before every batch calculation.
Hook function invoked after every batch calculation.
Hook function invoked before each epoch.
Hook function invoked after each epoch.
Hook function invoked before every batch calculation in evaluate stage.
Hook function invoked after every batch calculation in evaluate stage.
Hook function invoked before evaluate stage.
Hook function invoked after evaluate stage.
Hook function invoked before train stage.
Hook function invoked before every batch calculation in train stage.
Hook function invoked before train stage.
Hook function invoked after train stage.
Set the model to callback.
Set the optimizer to callback.
Set the trainercontrol to callback.
- on_batch_begin(batch: Tuple, logs: Dict) None ¶
Hook function invoked before every batch calculation.
- Parameters:
batch (Tuple) – The data batch to calculate.
logs (Dict) – Kv store to save and load info.
- on_batch_end(batch: Tuple, logs: Dict) None ¶
Hook function invoked after every batch calculation.
- Parameters:
batch (Tuple) – The data batch to calculate.
logs (Dict) – Kv store to save and load info.
- on_epoch_begin(epochs: int, logs: Dict) None [source]¶
Hook function invoked before each epoch.
- Parameters:
epochs (int) – Epoch index.
logs (Dict) – Kv store to save and load info.
- on_epoch_end(epochs: int, logs: Dict) None ¶
Hook function invoked after each epoch.
- Parameters:
epochs (int) – Epoch index.
logs (Dict) – Kv store to save and load info.
- on_eval_batch_begin(batch: Tuple, logs: Dict) None ¶
Hook function invoked before every batch calculation in evaluate stage.
- Parameters:
batch (Tuple) – The data batch to calculate.
logs (Dict) – Kv store to save and load info.
- on_eval_batch_end(batch: Tuple, logs: Dict) None [source]¶
Hook function invoked after every batch calculation in evaluate stage.
- Parameters:
batch (Tuple) – The data batch to calculate.
logs (Dict) – Kv store to save and load info.
- on_eval_begin(logs: Dict) None ¶
Hook function invoked before evaluate stage.
- Parameters:
logs (Dict) – Kv store to save and load info.
- on_eval_end(logs: Dict) None ¶
Hook function invoked after evaluate stage.
- Parameters:
logs (Dict) – Kv store to save and load info.
- on_train_batch_begin(batch: Tuple, logs: Dict) None ¶
Hook function invoked before train stage.
- Parameters:
logs (Dict) – Kv store to save and load info.
- on_train_batch_end(batch: Tuple, logs: Dict) None [source]¶
Hook function invoked before every batch calculation in train stage.
- Parameters:
batch (Tuple) – The data batch to calculate.
logs (Dict) – Kv store to save and load info.
- on_train_begin(logs: Dict) None ¶
Hook function invoked before train stage.
- Parameters:
logs (Dict) – Kv store to save and load info.
- on_train_end(logs: Dict) None ¶
Hook function invoked after train stage.
- Parameters:
logs (Dict) – Kv store to save and load info.
- set_model(model: Module) None ¶
Set the model to callback.
- Parameters:
model (torch.nn.Module) – The model which callback can operate.
- set_optimizer(optimizer: Optimizer) None ¶
Set the optimizer to callback.
- Parameters:
optimizer (torch.optim.Optimizer) – The optimizer which callback can operate.
- set_trainercontrol(trainercontrol: TrainerControl) None ¶
Set the trainercontrol to callback.
- Parameters:
trainercontrol (towhee.trainer.callback.TrainerControl) – The trainercontrol which callback can operate.