    def _get_inputs(input_dim: int = 3) -> torch.tensor:
        """
        Provide different tensors as test cases.
        Yield:
            (torch.tensor): tensor as test case input.
        """
        # Prepare random tensor as test cases.
        shapes = (
            # Forward succeeded.
            (1, input_dim, 3, 7, 7),
            (1, input_dim, 5, 7, 7),
            (1, input_dim, 7, 7, 7),
            (2, input_dim, 3, 7, 7),
            (4, input_dim, 3, 7, 7),
            (8, input_dim, 3, 7, 7),
            (2, input_dim, 3, 7, 14),
            (2, input_dim, 3, 14, 7),
            (2, input_dim, 3, 14, 14),
            # Forward failed.
            (8, input_dim * 2, 3, 7, 7),
            (8, input_dim * 4, 5, 7, 7),
        )
        for shape in shapes:
            yield torch.rand(shape)
Provide different tensors as test cases.
Yield:
(torch.tensor): tensor as test case input.
tests/unittests/models/layers/test_resnet_basic_3d_module.py