What about this…
result = None
input_downsampled = input
for i in range(3):
       if result is None:
            result = self.forward(model, input_downsampled)
       else:
            result = torch.cat([model, self.forward(model, input_downsampled)])
       if i != (2):
            input_downsampled = self.downsample(input_downsampled)
return result

The tensorflow code you posted returns a list. How is this list used? If it is used as a list of tensors and not as a tensor itself, then the code you posted should do the job just fine.