I have an attention decoder whose forward function is as follows.
def forward(self, input, hidden, encoder_outputs):
embedded = self.embedding(input).view(1, 1, -1)
embedded = self.drop(embedded)
attn_weights = F.softmax(self.attn(torch.cat((embedded, hidden), 1)))
How can I print the shape of
embedded tensor inside the forward function? I checked, simple print() statement doesn’t work.
A print statement (
print(embedded.size())) should work. What do you mean when you say it doesn’t work (nothing happens?)
You can do
print(embedded.size()). Works for me even in the
The .size() solution didn’t work for me when I had created an embedding using nn.Embedding. However, just printing the embeddings does show me size at the end of it:
Hope this helps someone
does this return a tuple?
I saw it is torch.Size([19, 25, 2100])
torch.Size is essentially a tuple, and can do the same things
Use print(embedded) to see the shape, or embedded.eval()
If you want to see the content, embedded.weight will show you the tensor and if it requires grad.