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import torch
from realesrgan.archs.discriminator_arch import UNetDiscriminatorSN
def test_unetdiscriminatorsn():
"""Test arch: UNetDiscriminatorSN."""
# model init and forward (cpu)
net = UNetDiscriminatorSN(num_in_ch=3, num_feat=4, skip_connection=True)
img = torch.rand((1, 3, 32, 32), dtype=torch.float32)
output = net(img)
assert output.shape == (1, 1, 32, 32)
# model init and forward (gpu)
if torch.cuda.is_available():
net.cuda()
output = net(img.cuda())
assert output.shape == (1, 1, 32, 32)
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