Any different between model(input) and model.forward(input)

1 
class MyModel(nn.Module):
    def __init__(self, cuda, word_dim, tag_dim, mem_dim, criterion):
        super(MyModel, self).__init__()
   
    def forward(input):
         .. # do something
         return output

model = MyModel()

Is there any different if I called

model.forward(input)

rather than

model(input)

Because only when I call model.forward(input), IDE (in this case, Pycharm) suggest me argument for forward function.

12 Likes
2

You should avoid calling Module.forward.
The difference is that all the hooks are dispatched in the __call__ function, so if you call .forward and have hooks in your model, the hooks won’t have any effect

17 Likes
3

But who/what exactly calls the .forward() function? is it the init()? In my case I am being told in error that the .forward is not getting all the arguments it needs, but I am not able to figure out where in the control flow its getting lost.

2 Likes
4

As @fmassa said, forward is called in the .__call__ function. Have a look at the line of code.

8 Likes
5

What so you mean by the “hooks”?

6 Likes
6

Just avoiding using forward directly doesn’t really solve the issue that it breaks IDE support. One potential solution could be this Solution to different forward for train and inference + IDE support for forward args . Here I just wrapped nn.Module to allow a forward method with both hooks and IDE support is retained.

7

I haven’t use “hooks” yet, but it is like event trigger.

8

Hello from 6 years later, here is a link targetting the commit instead of the main branch, showing the right line (as i suppose) pytorch/torch/nn/modules/module.py at d564ecb4a515e34184c976617f57b2eb01665660 · pytorch/pytorch · GitHub