def _generate_output(
    batch_size: int = 2, n_views: int = 3, output_dim: int = 4, seed: int = 0
) -> List[Tensor]:
    """Returns a list of view representations.

    Example output:
        [
            torch.Tensor([img0_view0, img1_view0]),
            torch.Tensor([img0_view1, img1_view1])
        ]

    """
    torch.manual_seed(seed)
    out = []
    for _ in range(n_views):
        views = [torch.rand(output_dim) for _ in range(batch_size)]
        out.append(torch.stack(views))
    return out
Returns a list of view representations.

    Example output:
        [
            torch.Tensor([img0_view0, img1_view0]),
            torch.Tensor([img0_view1, img1_view1])
        ]

    
tests/loss/test_dino_loss.py