activation.py

import torch

x = torch.rand(10)
print(x)

> tensor([0.2791, 0.7676, 0.5146, 0.5865, 0.5029, 0.5618, 0.2659, 0.9412, 0.4960,
        0.1228])
        
# apply softmax
torch.softmax(x, dim=0)

> tensor([0.0778, 0.1268, 0.0984, 0.1058, 0.0973, 0.1032, 0.0768, 0.1508, 0.0966,
        0.0665])
        
# apply sigmoid
torch.sigmoid(x)

> tensor([0.5693, 0.6830, 0.6259, 0.6426, 0.6231, 0.6369, 0.5661, 0.7193, 0.6215,
        0.5307])
        
# apply relu
torch.relu(x)

> tensor([0.2791, 0.7676, 0.5146, 0.5865, 0.5029, 0.5618, 0.2659, 0.9412, 0.4960,
        0.1228])