def test_parameters(self):
for tensor in self._model.parameters():
assert_not_nan(tensor)
assert_isfinite(tensor)
def test_forward(self):
test_array = torch.randn(*config["INPUT_DIM"])
pred = forward(self._model, test_array, self.device)
assert tuple(pred.shape) == config["OUTPUT_DIM"]
assert_isfinite(pred)
assert_not_nan(pred)
def test_forward(self):
test_array = torch.randn(1, 3, 256, 256)
pred = forward(self.model, test_array, self.device)
assert tuple(pred.shape) == (1, )
assert_isfinite(pred)
assert_not_nan(pred)