在我的火炬模型中,最后一层是 a torch.nn.Sigmoid()
,损失是torch.nn.BCELoss
. 在训练步骤中,出现了以下错误:
RuntimeError: torch.nn.functional.binary_cross_entropy and torch.nn.BCELoss are unsafe to autocast.
Many models use a sigmoid layer right before the binary cross entropy layer.
In this case, combine the two layers using torch.nn.functional.binary_cross_entropy_with_logits
or torch.nn.BCEWithLogitsLoss. binary_cross_entropy_with_logits and BCEWithLogits are
safe to autocast.
但是,当在计算损失和反向传播时尝试重现此错误时,一切正常:
import torch
from torch import nn
# last layer
sigmoid = nn.Sigmoid()
# loss
bce_loss = nn.BCELoss()
# the true classes
true_cls = torch.tensor([
[0.],
[1.]])
# model prediction classes
pred_cls = sigmoid(
torch.tensor([
[0.4949],
[0.4824]],requires_grad=True)
)
pred_cls
# tensor([[0.6213],
# [0.6183]], grad_fn=<SigmoidBackward>)
out = bce_loss(pred_cls, true_cls)
out
# tensor(0.7258, grad_fn=<BinaryCrossEntropyBackward>)
out.backward()
我错过了什么?感谢您提供的任何帮助。