def test_ill_arg(self):
with self.assertRaises(ValueError):
ChannelSELayer(spatial_dims=1, in_channels=4, r=100)
def test_shape(self, input_param, input_data, expected_shape):
net = ChannelSELayer(**input_param)
net.eval()
with torch.no_grad():
result = net(input_data)
self.assertEqual(result.shape, expected_shape)
def test_shape(self, input_param, input_shape, expected_shape):
net = ChannelSELayer(**input_param)
with eval_mode(net):
result = net(torch.randn(input_shape))
self.assertEqual(result.shape, expected_shape)
def test_script(self):
input_param, input_shape, _ = TEST_CASES[0]
net = ChannelSELayer(**input_param)
test_data = torch.randn(input_shape)
test_script_save(net, test_data)
def test_script(self):
input_param, input_shape, _ = TEST_CASES[0]
net = ChannelSELayer(**input_param)
test_data = torch.randn(input_shape)
out_orig, out_reloaded = test_script_save(net, test_data)
assert torch.allclose(out_orig, out_reloaded)