Method test_decollated

tests/data/utils/test_decollate.py:215–253

(self)

        self.assertEqual(out[1]["out"], 0)  # verify padding fill_value

    def test_decollated(self):
        test_case = {
            "image": torch.tensor([[[1, 2]], [[3, 4]]]),
            "meta": {"out": ["test", "test"]},
            PostFix.meta("image"): {"scl_slope": torch.Tensor((0.0, 0.0))},
            "loss": 0.85,
        }
        transform = Decollated(keys=["meta", PostFix.meta("image")], detach=False)
        out = transform(test_case)
        self.assertFalse("loss" in out)
        self.assertEqual(out[0]["meta"]["out"], "test")
        self.assertEqual(out[0][PostFix.meta("image")]["scl_slope"], 0.0)
        self.assertTrue(isinstance(out[0][PostFix.meta("image")]["scl_slope"], torch.Tensor))
        # decollate all data with keys=None
        transform = Decollated(keys=None, detach=True)
        out = transform(test_case)
        self.assertEqual(out[1]["loss"], 0.85)
        self.assertEqual(out[0]["meta"]["out"], "test")
        self.assertEqual(out[0][PostFix.meta("image")]["scl_slope"], 0.0)
        self.assertTrue(isinstance(out[0][PostFix.meta("image")]["scl_slope"], float))

        # test list input
        test_case = [
            torch.tensor([[[1, 2]], [[3, 4]]]),
            {"out": ["test", "test"]},
            {"scl_slope": torch.Tensor((0.0, 0.0))},
            {"out2": ["test1"]},
            0.85,
            [],
        ]
        transform = Decollated(keys=None, detach=False, fill_value=-1)
        out = transform(test_case)

        self.assertEqual(out[0][-2], 0.85)  # scalar replicates
        self.assertEqual(out[1][-2], 0.85)  # scalar replicates
        self.assertEqual(out[1][-3], -1)  # fill value for the dictionary item
        self.assertEqual(out[0][1]["out"], "test")
        self.assertEqual(out[0][2]["scl_slope"], 0.0)
        self.assertTrue(isinstance(out[0][2]["scl_slope"], torch.Tensor))


if __name__ == "__main__":