Why aren't torch.functional.sigmoid and torch.nn.functional.relu deprecated like torch.nn.functional.tanh?
Now when torch.autograd.Variable is merged with torch.tensor and obsolete, why did they deprecate some functions in torch.nn.functional but not others?  Namely, tanhis deprecated but not sigmoid or relu.

&gt;&gt;&gt; torch.__version__
'1.1.0'
&gt;&gt;&gt; u
tensor(2., grad_fn=&lt;MeanBackward0&gt;)
&gt;&gt;&gt; torch.nn.functional.tanh(u)
C:\Users\mlearning\AppData\Local\Continuum\anaconda3\lib\site-packages\torch\nn\functional.py:1374: UserWarning: nn.functional.tanh is deprecated. Use torch.tanh instead.
  warnings.warn("nn.functional.tanh is deprecated. Use torch.tanh instead.")
tensor(0.9640, grad_fn=&lt;TanhBackward&gt;)   
&gt;&gt;&gt; torch.nn.functional.sigmoid(u)
tensor(0.8808, grad_fn=&lt;SigmoidBackward&gt;)    
&gt;&gt;&gt; torch.nn.functional.relu(u)
tensor(2., grad_fn=&lt;ReluBackward0&gt;)


Is there any difference between torch.nn.functional.relu and torch.relu, or I can use them interchangeably?

You can check this thread where one of the few main PyTorch designers (actually a creator) set the directive.

You can also check the reasoning behind. Also, you may propose the same for the other 2 functions.

The other should deprecate as well.
