In my encoder decoder model ,output of encoder when goes to decoder it gives this error.
Code is-
torch.set_default_tensor_type('torch.cuda.FloatTensor')
model=GRUNet()
n_epochs = 50
model=model.cuda()
valid_loss_min = np.Inf # track change in validation loss
model.train()
train_loss = 0.0
for epoch in range(1, n_epochs+1):
print("ALL ABOUT LOSS--------",(train_loss/len(images)),"----------/n")
train_loss = 0.0
for i in range(len(im)):
data=im[i].cuda()
tar=targ[i].cuda()
optimizer.zero_grad()
# forward pass: compute predicted outputs by passing inputs to the model
loss = criterion(model(data), tar)
loss.backward()
optimizer.step()
# update training loss
train_loss += loss.item()*data.size(0)