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27 lines
810 B
27 lines
810 B
from torch import optim
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from pydantic import BaseModel
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class BaseScheduler:
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"""
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Abstract base class for learning rate schedulers.
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Wraps a PyTorch LR scheduler and provides a unified interface.
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"""
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def __init__(self, optimizer: optim.Optimizer, params: BaseModel) -> None:
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self.scheduler: optim.lr_scheduler.LRScheduler | None = None
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def step(self) -> None:
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"""
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Performs a single scheduler step. This typically updates the learning rate
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based on the current epoch or step count.
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"""
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if self.scheduler is not None:
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self.scheduler.step()
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def get_last_lr(self) -> list[float]:
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"""
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Returns the most recent learning rate(s).
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"""
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return self.scheduler.get_last_lr() if self.scheduler else []
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