test_image_rnn.py

dataiter = iter(trainloader)
images, labels = dataiter.next()
model = ImageRNN(BATCH_SIZE, N_STEPS, N_INPUTS, N_NEURONS, N_OUTPUTS)
logits = model(images.view(-1, 28,28))
print(logits[0:10])

### output
'''
tensor([[-0.0197,  0.0082,  0.0248,  0.0758, -0.0110,  0.0521, -0.0261,  0.0217,
         -0.0083,  0.0866],
        [-0.0214,  0.0173,  0.0255,  0.0715, -0.0092,  0.0486, -0.0253,  0.0214,
         -0.0141,  0.0909],
        ...
        [-0.0187,  0.0199,  0.0317,  0.0743, -0.0061,  0.0488, -0.0273,  0.0223,
         -0.0152,  0.0881],
        [ 0.0012,  0.0542,  0.0261,  0.0561, -0.0549,  0.0510,  0.0108,  0.0414,
         -0.0394,  0.0897]], grad_fn=<SliceBackward>)
'''