Conv1d
类原型:
torch.nn.Conv1d(
in_channels,
out_channels,
kernel_size,
stride=1,
padding=0,
dilation=1,
groups=1,
bias=True,
padding_mode='zeros',
device=None,
dtype=None
)
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.
待补充:
https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html?highlight=crossen#torch.nn.CrossEntropyLoss
最后
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