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When using WarmupDecayLR, either
WarmupDecayLR
warmup_num_steps
1 / log(warmup_num_steps)
warmup_num_steps = max(2, warmup_num_steps)
Thank you.
Fix: #772
Error log from the test:
def __init__(self, optimizer: Optimizer, warmup_min_lr: float = 0.0, warmup_max_lr: float = 0.001, warmup_num_steps: int = 1000, last_batch_iteration: int = -1): self.optimizer = get_torch_optimizer(optimizer) self.min_lrs = self._format_param(self.optimizer, warmup_min_lr, "min_lr") self.max_lrs = self._format_param(self.optimizer, warmup_max_lr, "max_lr") self.delta_lrs = [big - small for big, small in zip(self.max_lrs, self.min_lrs)] self.warmup_num_steps = warmup_num_steps > self.inverse_log_warm_up = 1.0 / math.log(warmup_num_steps) E ZeroDivisionError: float division by zero DeepSpeed/deepspeed/runtime/lr_schedules.py:710: ZeroDivisionError
The text was updated successfully, but these errors were encountered:
Successfully merging a pull request may close this issue.
When using
WarmupDecayLR
, eitherwarmup_num_steps
is not 0 or 1, because it's a1 / log(warmup_num_steps)
Thank you.
Fix: #772
Error log from the test:
The text was updated successfully, but these errors were encountered: