| |
| import time |
| from typing import Optional, Sequence, Union |
|
|
| from mmengine.registry import HOOKS |
| from .hook import Hook |
|
|
| DATA_BATCH = Optional[Union[dict, tuple, list]] |
|
|
|
|
| @HOOKS.register_module() |
| class IterTimerHook(Hook): |
| """A hook that logs the time spent during iteration. |
| |
| E.g. ``data_time`` for loading data and ``time`` for a model train step. |
| """ |
|
|
| priority = 'NORMAL' |
|
|
| def __init__(self): |
| self.time_sec_tot = 0 |
| self.time_sec_test_val = 0 |
| self.start_iter = 0 |
|
|
| def before_train(self, runner) -> None: |
| """Synchronize the number of iterations with the runner after resuming |
| from checkpoints. |
| |
| Args: |
| runner: The runner of the training, validation or testing |
| process. |
| """ |
| self.start_iter = runner.iter |
|
|
| def _before_epoch(self, runner, mode: str = 'train') -> None: |
| """Record timestamp before start an epoch. |
| |
| Args: |
| runner (Runner): The runner of the training validation and |
| testing process. |
| mode (str): Current mode of runner. Defaults to 'train'. |
| """ |
| self.t = time.time() |
|
|
| def _after_epoch(self, runner, mode: str = 'train') -> None: |
| self.time_sec_test_val = 0 |
|
|
| def _before_iter(self, |
| runner, |
| batch_idx: int, |
| data_batch: DATA_BATCH = None, |
| mode: str = 'train') -> None: |
| """Calculating time for loading data and updating "data_time" |
| ``HistoryBuffer`` of ``runner.message_hub``. |
| |
| Args: |
| runner (Runner): The runner of the training, validation and |
| testing process. |
| batch_idx (int): The index of the current batch in the loop. |
| data_batch (dict or tuple or list, optional): Data from |
| dataloader. |
| mode (str): Current mode of runner. Defaults to 'train'. |
| """ |
| |
| runner.message_hub.update_scalar(f'{mode}/data_time', |
| time.time() - self.t) |
|
|
| def _after_iter(self, |
| runner, |
| batch_idx: int, |
| data_batch: DATA_BATCH = None, |
| outputs: Optional[Union[dict, Sequence]] = None, |
| mode: str = 'train') -> None: |
| """Calculating time for an iteration and updating "time" |
| ``HistoryBuffer`` of ``runner.message_hub``. |
| |
| Args: |
| runner (Runner): The runner of the training validation and |
| testing process. |
| batch_idx (int): The index of the current batch in the loop. |
| data_batch (dict or tuple or list, optional): Data from dataloader. |
| outputs (dict or sequence, optional): Outputs from model. |
| mode (str): Current mode of runner. Defaults to 'train'. |
| """ |
| |
| message_hub = runner.message_hub |
| message_hub.update_scalar(f'{mode}/time', time.time() - self.t) |
| self.t = time.time() |
| iter_time = message_hub.get_scalar(f'{mode}/time') |
| if mode == 'train': |
| self.time_sec_tot += iter_time.current() |
| |
| time_sec_avg = self.time_sec_tot / ( |
| runner.iter - self.start_iter + 1) |
| |
| eta_sec = time_sec_avg * (runner.max_iters - runner.iter - 1) |
| runner.message_hub.update_info('eta', eta_sec) |
| else: |
| if mode == 'val': |
| cur_dataloader = runner.val_dataloader |
| else: |
| cur_dataloader = runner.test_dataloader |
|
|
| self.time_sec_test_val += iter_time.current() |
| time_sec_avg = self.time_sec_test_val / (batch_idx + 1) |
| eta_sec = time_sec_avg * (len(cur_dataloader) - batch_idx - 1) |
| runner.message_hub.update_info('eta', eta_sec) |
|
|
