# coding=utf-8
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import oneflow as flow
from oneflow import nn
[docs]class ParallelCrossEntropyLoss(nn.Module):
"""This criterion acts like :class:`~flow.nn.CrossEntropyLoss` except it will
execute distributed cross entropy loss computation cross different GPUs.
"""
[docs] def forward(self, logits: flow.Tensor, target: flow.Tensor):
"""Function for the distributed cross entropy.
Args:
logits (flow.Tensor): vocab_parallel_logits with shape
(batch_size, seq_length, vocab_size) and sbp signature is [S(0), S(2)].
target (flow.Tensor): target with shape (batch_size, seq_length) and
sbp signature is [S(0), B].
"""
assert logits.ndim == 3
assert target.ndim == 2
assert logits.shape[0:2] == target.shape
target = target.to_global(placement=logits.placement)
# Change -1 in target to 0 because sparse_softmax_cross_entropy don't accept -1
target = target * (target >= 0)
lm_loss = flow._C.sparse_softmax_cross_entropy(
logits.view(-1, logits.shape[-1]),
target.view(-1),
)
return lm_loss