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36 lines
1.3 KiB
36 lines
1.3 KiB
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 colossalai.context import Config
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from .torch_amp import TorchAMPOptimizer, TorchAMPModel, TorchAMPLoss
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from typing import Optional
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def convert_to_torch_amp(model: nn.Module,
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optimizer: Optimizer,
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criterion: Optional[_Loss] = None,
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amp_config: Optional[Config] = None):
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"""A helper function to wrap training components with Torch AMP modules
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:param model: your model object
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:type model: :class:`torch.nn.Module`
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:param optimizer: your optimizer object
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:type optimizer: :class:`torch.optim.Optimizer`
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:param criterion: your loss function object
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:type criterion: :class:`torch.nn.modules.loss._Loss`, optional
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:param amp_config: configuration for different amp modes
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:type amp_config: :class:`colossalai.context.Config` or dict, optional
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:return: (model, optimizer, criterion)
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:rtype: Tuple
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"""
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model = TorchAMPModel(model)
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if amp_config is None:
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amp_config = dict()
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optimizer = TorchAMPOptimizer(optimizer, **amp_config)
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if criterion:
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criterion = TorchAMPLoss(criterion)
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return model, optimizer, criterion
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__all__ = ['convert_to_torch_amp', 'TorchAMPModel', 'TorchAMPLoss', 'TorchAMPOptimizer']
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