mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
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26 lines
725 B
26 lines
725 B
2 years ago
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import torch
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import torch.nn as nn
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from torch.optim import Optimizer
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__all__ = ['Precision']
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class Precision:
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def __init__(self, precision_type: torch.dtype, grad_clipping_type: str, grad_clipping_value: float):
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self.precision_type = precision_type
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self.grad_clipping_type = grad_clipping_type
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self.grad_clipping_value = grad_clipping_value
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def setup_model(self, model: nn.Module) -> nn.Module:
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# TODO: implement this method
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pass
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def setup_optimizer(self, optimizer: Optimizer) -> Optimizer:
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# TODO: implement this method
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# inject grad clipping and unscale loss
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pass
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def scale_loss(self, loss: torch.Tensor) -> torch.Tensor:
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pass
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