46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from abc import ABC, abstractmethod
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from tests.helpers.dataloaders import CustomInfDataloader, CustomNotImplementedErrorDataloader
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class TrainDataloaderVariations(ABC):
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@abstractmethod
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def dataloader(self, train: bool, *args, **kwargs):
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"""placeholder"""
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def train_dataloader(self):
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return self.dataloader(train=True)
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def train_dataloader__infinite(self):
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return CustomInfDataloader(self.dataloader(train=True))
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def train_dataloader__not_implemented_error(self):
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return CustomNotImplementedErrorDataloader(self.dataloader(train=True))
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def train_dataloader__zero_length(self):
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dataloader = self.dataloader(train=True)
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dataloader.dataset.data = dataloader.dataset.data[:0]
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dataloader.dataset.targets = dataloader.dataset.targets[:0]
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return dataloader
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def train_dataloader__multiple_mapping(self):
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"""Return a mapping loaders with different lengths"""
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return {
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'a': self.dataloader(train=True, num_samples=100),
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'b': self.dataloader(train=True, num_samples=50),
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}
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