def prune_layer(
    layer: Union[nn.Linear, Conv1D], index: torch.LongTensor, dim: Optional[int] = None
) -> Union[nn.Linear, Conv1D]:
    """
    Prune a Conv1D or linear layer to keep only entries in index.

    Used to remove heads.

    Args:
        layer (`Union[torch.nn.Linear, Conv1D]`): The layer to prune.
        index (`torch.LongTensor`): The indices to keep in the layer.
        dim (`int`, *optional*): The dimension on which to keep the indices.

    Returns:
        `torch.nn.Linear` or [`~pytorch_utils.Conv1D`]: The pruned layer as a new layer with `requires_grad=True`.
    """
    if isinstance(layer, nn.Linear):
        return prune_linear_layer(layer, index, dim=0 if dim is None else dim)
    elif isinstance(layer, Conv1D):
        return prune_conv1d_layer(layer, index, dim=1 if dim is None else dim)
    else:
        raise ValueError(f"Can't prune layer of class {layer.__class__}")

    Prune a Conv1D or linear layer to keep only entries in index.

    Used to remove heads.

    Args:
        layer (`Union[torch.nn.Linear, Conv1D]`): The layer to prune.
        index (`torch.LongTensor`): The indices to keep in the layer.
        dim (`int`, *optional*): The dimension on which to keep the indices.

    Returns:
        `torch.nn.Linear` or [`~pytorch_utils.Conv1D`]: The pruned layer as a new layer with `requires_grad=True`.
    
dpkd/transformers/src/transformers/pytorch_utils.py