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# Copyright (c) 2020 Huawei Technologies Co., Ltd.
# Licensed under CC BY-NC-SA 4.0 (Attribution-NonCommercial-ShareAlike 4.0 International) (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
#
# The code is released for academic research use only. For commercial use, please contact Huawei Technologies Co., Ltd.
# 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.
#
# This file contains content licensed by https://github.com/xinntao/BasicSR/blob/master/LICENSE/LICENSE
'''create dataset and dataloader'''
import logging
import torch
import torch.utils.data
def create_dataloader(dataset, dataset_opt, opt=None, sampler=None):
phase = dataset_opt.get('phase', 'test')
if phase == 'train':
gpu_ids = opt.get('gpu_ids', None)
gpu_ids = gpu_ids if gpu_ids else []
num_workers = dataset_opt['n_workers'] * len(gpu_ids)
batch_size = dataset_opt['batch_size']
shuffle = True
return torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=shuffle,
num_workers=num_workers, sampler=sampler, drop_last=True,
pin_memory=False)
else:
return torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False, num_workers=1,
pin_memory=True)
def create_dataset(dataset_opt):
print(dataset_opt)
mode = dataset_opt['mode']
if mode == 'LRHR_PKL':
from data.LRHR_PKL_dataset import LRHR_PKLDataset as D
else:
raise NotImplementedError('Dataset [{:s}] is not recognized.'.format(mode))
dataset = D(dataset_opt)
logger = logging.getLogger('base')
logger.info('Dataset [{:s} - {:s}] is created.'.format(dataset.__class__.__name__,
dataset_opt['name']))
return dataset
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