You could create an own layer for that:
class PrintLayer(nn.Module):
def __init__(self):
super(PrintLayer, self).__init__()
def forward(self, x):
# Do your print / debug stuff here
print(x)
return x
model = nn.Sequential(
nn.Linear(1, 5),
PrintLayer(), # Add Print layer for debug
nn.ReLU(),
nn.Linear(5,1),
nn.LogSigmoid(),
)
x = Variable(torch.randn(10, 1))
output = model(x)
I hope this helps!