mirror of https://github.com/hpcaitech/ColossalAI
33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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from .amp_type import AMP_TYPE
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from colossalai.context import Config
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import torch.nn as nn
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from torch.optim import Optimizer
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from torch.nn.modules.loss import _Loss
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from .torch_amp import convert_to_torch_amp
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from .apex_amp import convert_to_apex_amp
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from .naive_amp import convert_to_naive_amp
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def convert_to_amp(model: nn.Module,
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optimizer: Optimizer,
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criterion: _Loss,
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mode: AMP_TYPE,
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amp_config: Config = None):
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assert isinstance(mode, AMP_TYPE), \
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f'expected the argument mode be AMP_TYPE, but got {type(mode)}'
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if amp_config is None:
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amp_config = Config()
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if mode == AMP_TYPE.TORCH:
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model, optimizer, criterion = convert_to_torch_amp(model, optimizer, criterion, amp_config)
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elif mode == AMP_TYPE.APEX:
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model, optimizer = convert_to_apex_amp(model, optimizer, amp_config)
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elif mode == AMP_TYPE.NAIVE:
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model, optimizer = convert_to_naive_amp(model, optimizer, amp_config)
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return model, optimizer, criterion
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