I am learning RNN with pytorch from this github.
Pytorch RNN Tutorial 1
I’m a little bit confused, because the code didn’t show result of the training. Only show the accuracy. Now I want to show image that output from model.
I try to save image from output, but the result I get is a compressed representation (below is the image I got from output of the model)

# Train the model
total_step = len(train_loader)
for epoch in range(num_epochs):
    for i, (images, labels) in enumerate(train_loader):
        images = images.reshape(-1, sequence_length, input_size).to(device)
        labels = labels.to(device)

        # Forward pass
        outputs = model(images)
        loss = criterion(outputs, labels)

        # Backward and optimize
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()

        if (i+1) % 100 == 0:
            print ('Epoch [{}/{}], Step [{}/{}], Loss: {:.4f}' 
                    .format(epoch+1, num_epochs, i+1, total_step, loss.item()))

I am trying to show the image of the output by adding this cod
plt.imshow(outputs.reshape(28, 28))

But I got this error
RuntimeError: shape '[28, 28]' is invalid for input of size 1000

So, I assume that the output is 1000 size. but I want it to show as a mnist image (784 size (28*28)).