Jul 09, 2017 · You should do self.threshold = nn.Parameter(torch.rand(1)). All parameters of a nn.Module must be nn.Parameter s otherwise they won’t appear when you call .parameters() and won’t move when you call .cuda() (which is your problem here).
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09.07.2017 · You should do self.threshold = nn.Parameter(torch.rand(1)). All parameters of a nn.Module must be nn.Parameter s otherwise they won’t appear when you call .parameters() and won’t move when you call .cuda() (which is your problem here).
28.05.2021 · When using sigmoid function in PyTorch as our activation function, for example it is connected to the last layer of the model as the output of binary classification. After all, sigmoid can compress the value between 0-1, we only need to set a threshold, for example 0.5 and you can divide the value into two categories.
Transcript: This video will show you how to specify a PyTorch tensor's maximum value threshold by using the torch.clamp operation. First, we import PyTorch.
May 28, 2021 · When using sigmoid function in PyTorch as our activation function, for example it is connected to the last layer of the model as the output of binary classification. After all, sigmoid can compress the value between 0-1, we only need to set a threshold, for example 0.5 and you can divide the value into two categories.