def METHOD_NAME(
    shape: Tuple[int], data: List[torch.Tensor], input_name: str, channel_axis: int
) -> torch.Tensor:
    blob = torch.zeros(shape, dtype=data[0].dtype)
    for j, idx in enumerate(np.ndindex(blob.shape[channel_axis])):
        index = tuple(slice(None) if i != channel_axis else idx for i in range(blob.ndim))
        blob[index] = data[j]
    return blob