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# 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
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