8000 ExponentialLR unexpectedly calls `step()` when init argument `last_epoch` is larger than -1 · Issue #102261 · pytorch/pytorch · GitHub
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ExponentialLR unexpectedly calls step() when init argument last_epoch is larger than -1 #102261

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yuxinyuan opened this issue May 25, 2023 · 2 comments · May be fixed by #149312
Open

ExponentialLR unexpectedly calls step() when init argument last_epoch is larger than -1 #102261

yuxinyuan opened this issue May 25, 2023 · 2 comments · May be fixed by #149312
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actionable module: LrScheduler module: optimizer Related to torch.optim triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module

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@yuxinyuan
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yuxinyuan commented May 25, 2023 •
edited by pytorch-bot bot
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🐛 Describe the bug

Currently, the init function of torch.optim.lr_scheduler._LRSchedule will call self.step() once. This causes a mismatch between the learning rate used by the optimizer and the closed_form_lr of ExponentialLR, when init argument last_epoch is larger than -1.

import torch

model = torch.nn.Linear(3, 3)
optim = torch.optim.AdamW(model.parameters())
sched = torch.optim.lr_scheduler.ExponentialLR(optim, gamma=0.999)

optim.step()
sched.step()
print("Optim & sched:")
print(optim.state_dict())
print(optim.param_groups[0]["lr"])
print(sched.state_dict())
print(sched._get_closed_form_lr())
print("")

# As if we are restoring from a checkpoint
optim2 = torch.optim.AdamW(model.parameters())
optim2.load_state_dict(optim.state_dict())
# Init scheduler with last_epoch=0
sched2 = torch.optim.lr_scheduler.ExponentialLR(optim2, gamma=0.999, last_epoch=0)

print("Optim2 & sched2:")
print(optim2.state_dict())
print(optim2.param_groups[0]["lr"])
print(sched2.state_dict())
print(sched2._get_closed_form_lr())
print("")

As the result shows, optim2 has lr 0.000998001, but the closed form lr of sched2 is 0.000999. This behavior causes confusion and inconsistency when one resumes training from a checkpoint.

Versions

Collecting environment information...
PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.6
ROCM used to build PyTorch: N/A

cc @vincentqb @jbschlosser @albanD @janeyx99 @crcrpar
@vadimkantorov vadimkantorov mentioned this issue May 25, 2023
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@soulitzer soulitzer added module: optimizer Related to torch.optim triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module module: LrScheduler labels May 25, 2023
@janeyx99
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We will accept a fix for this discrepancy to unblock checkpointing cases

This was referenced Mar 17, 2025
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@Vetti420
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Yes this causes also to step when we call .build in RLlib.

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