mirror of https://github.com/alibaba/EasyCV.git
84 lines
3.2 KiB
Python
84 lines
3.2 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from mmcv import runner
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from mmcv.runner import HOOKS
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from mmcv.runner.hooks.lr_updater import (CosineAnnealingLrUpdaterHook,
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annealing_cos)
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@HOOKS.register_module()
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class StepFixCosineAnnealingLrUpdaterHook(CosineAnnealingLrUpdaterHook):
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def get_warmup_lr(self, cur_iters):
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def _get_warmup_lr(cur_iters, regular_lr):
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if self.warmup == 'constant':
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warmup_lr = [_lr * self.warmup_ratio for _lr in regular_lr]
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elif self.warmup == 'linear':
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k = (1 - cur_iters / self.warmup_iters)
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warmup_lr = [_lr * (1 - k) for _lr in regular_lr]
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elif self.warmup == 'exp':
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k = self.warmup_ratio**(1 - cur_iters / self.warmup_iters)
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warmup_lr = [_lr * k for _lr in regular_lr]
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return warmup_lr
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if isinstance(self.regular_lr, dict):
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lr_groups = {}
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for key, regular_lr in self.regular_lr.items():
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lr_groups[key] = _get_warmup_lr(cur_iters, regular_lr)
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return lr_groups
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else:
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return _get_warmup_lr(cur_iters, self.regular_lr)
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def get_lr(self, runner, base_lr):
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if self.by_epoch:
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progress = runner.epoch
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max_progress = runner.max_epochs
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# Delete warmup epochs
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if self.warmup is not None:
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progress = progress - self.warmup_iters // len(
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runner.data_loader)
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max_progress = max_progress - self.warmup_iters // len(
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runner.data_loader)
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else:
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progress = runner.iter
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max_progress = runner.max_iters
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# Delete warmup iters
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if self.warmup is not None:
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progress = progress - self.warmup_iters
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max_progress = max_progress - self.warmup_iters
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if self.min_lr_ratio is not None:
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target_lr = base_lr * self.min_lr_ratio
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else:
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target_lr = self.min_lr
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return annealing_cos(base_lr, target_lr, progress / max_progress)
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@HOOKS.register_module()
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class CosineAnnealingWarmupByEpochLrUpdaterHook(CosineAnnealingLrUpdaterHook):
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def before_train_iter(self, runner: 'runner.BaseRunner'):
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cur_iter = runner.iter
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epoch_len = len(runner.data_loader)
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assert isinstance(self.warmup_iters, int)
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if not self.by_epoch:
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self.regular_lr = self.get_regular_lr(runner)
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if self.warmup is None or cur_iter >= self.warmup_iters:
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self._set_lr(runner, self.regular_lr)
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else:
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if cur_iter % epoch_len == 0:
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warmup_lr = self.get_warmup_lr(cur_iter)
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self._set_lr(runner, warmup_lr)
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elif self.by_epoch:
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if self.warmup is None or cur_iter > self.warmup_iters:
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return
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elif cur_iter == self.warmup_iters:
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self._set_lr(runner, self.regular_lr)
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else:
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if cur_iter % epoch_len == 0:
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warmup_lr = self.get_warmup_lr(cur_iter)
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self._set_lr(runner, warmup_lr)
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