CrossEntropyLoss
类原型：
torch.nn.CrossEntropyLoss(weight=None,
size_average=None,
ignore_index=- 100,
reduce=None,
reduction='mean',
label_smoothing=0.0
)
这个criterion计算input和target之间的交叉熵损失。
It is useful when training a classification problem with C classes. If provided, the optional argument weight should be a 1D Tensor assigning weight to each of the classes. This is particularly useful when you have an unbalanced training set.
