mirror of https://github.com/hpcaitech/ColossalAI
29 lines
952 B
Python
29 lines
952 B
Python
from torch import nn
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from torch.nn.modules.loss import *
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from torch.nn.modules.loss import _Loss
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from colossalai.nn.layer.utils import get_tensor_parallel_mode
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from .loss_2d import CrossEntropyLoss2D
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from .loss_2p5d import CrossEntropyLoss2p5D
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from .loss_3d import CrossEntropyLoss3D
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_parallel_cross_entropy = {
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'2d': CrossEntropyLoss2D,
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'2.5d': CrossEntropyLoss2p5D,
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'3d': CrossEntropyLoss3D
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}
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class CrossEntropyLoss(_Loss):
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def __init__(self, reduction: bool = True, *args, **kwargs):
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super().__init__()
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tensor_parallel = get_tensor_parallel_mode()
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if tensor_parallel in ['None', '1d']:
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reduction = 'mean' if reduction else 'none'
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self.loss = nn.CrossEntropyLoss(reduction=reduction, *args, **kwargs)
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else:
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self.loss = _parallel_cross_entropy[tensor_parallel](reduction=reduction, *args, **kwargs)
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def forward(self, *args):
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return self.loss(*args)
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