The batch size is set to 1. A large part of it happens when I call my network (Model), before even getting to the forward pass:
In the debugging window:
y = Model(x)
-> Class Model(Module):
def init(self):
# some initializations
def forward (self, input):
# A large part of memory have been used before the forward pass. Here
tensor = torch.max(input, dim=2, keepdim=False)