So, basically as I am not very experienced, do I have to initialize N and K with some random integers? And I have already done this loop state in my later part like this -
for epoch in range(epochs):
  
  running_loss = 0
  model.train()
  for images, labels in dataloader_train:
    
    #steps += 1
    images, labels = images.to(device), labels.to(device)
    
    optimizer.zero_grad()
    
    output = model.forward(images)
    p = torch.nn.functional.softmax(output, dim=1)
    prediction = torch.argmax(p, dim=1)
    #loss = torch.nn.functional.nll_loss(torch.log(p), y)
    loss = criterion(output, labels)
    loss.backward()
    optimizer.step()
    
    running_loss += loss.item()

so here in the first cell, where I have written my dataloader code, I have to write like this -
all_label = torch.zeros(N,K)
for i,(image, labels) in enumerate(dataloader_test):
      all_label[i]=labels
label_binarize(all_label)

am I right? Thanks.