#    Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
#    Licensed under the Apache License, Version 2.0 (the "License");
#    you may not use this file except in compliance with the License.
#    You may obtain a copy of the License at
#
#        http://www.apache.org/licenses/LICENSE-2.0
#
#    Unless required by applicable law or agreed to in writing, software
#    distributed under the License is distributed on an "AS IS" BASIS,
#    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#    See the License for the specific language governing permissions and
#    limitations under the License.

import torch


def maybe_to_torch(d):
    if isinstance(d, list):
        d = [maybe_to_torch(i) if not isinstance(i, torch.Tensor) else i for i in d]
    elif not isinstance(d, torch.Tensor):
        d = torch.from_numpy(d).float()
    return d


def to_cuda(data, non_blocking=True, gpu_id=0):
    if isinstance(data, list):
        data = [i.cuda(gpu_id, non_blocking=non_blocking) for i in data]
    else:
        data = data.cuda(gpu_id, non_blocking=non_blocking)
    return data