mirror of https://github.com/hpcaitech/ColossalAI
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35 lines
851 B
35 lines
851 B
import torch.nn as nn
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class ModelWrapper(nn.Module):
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"""
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A wrapper class to define the common interface used by booster.
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Args:
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module (nn.Module): The model to be wrapped.
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"""
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def __init__(self, module: nn.Module) -> None:
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super().__init__()
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self.module = module
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def unwrap(self):
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"""
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Unwrap the model to return the original model for checkpoint saving/loading.
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"""
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if isinstance(self.module, ModelWrapper):
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return self.module.unwrap()
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return self.module
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def forward(self, *args, **kwargs):
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return self.module(*args, **kwargs)
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class AMPModelMixin:
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"""This mixin class defines the interface for AMP training."""
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def update_master_params(self):
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"""
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Update the master parameters for AMP training.
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"""
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