54 lines
1.7 KiB
Python
54 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 abstractmethod
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from typing import Sequence
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from torch.utils.data import DataLoader
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from pytorch_lightning.loops.base import Loop
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class DataLoaderLoop(Loop):
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"""Base class to loop over all dataloaders"""
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@property
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@abstractmethod
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def dataloaders(self) -> Sequence[DataLoader]:
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"""Returns the dataloaders to loop over"""
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@property
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def current_dataloader_idx(self) -> int:
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"""Returns the index of the current dataloader"""
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return self.iteration_count
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@property
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def current_dataloader(self) -> DataLoader:
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"""Returns the current dataloader"""
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return self.dataloaders[self.current_dataloader_idx]
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@property
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def num_dataloaders(self) -> int:
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"""Returns the number of dataloaders present"""
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return len(self.dataloaders) if self.dataloaders is not None else 0
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@property
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def done(self) -> bool:
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"""Returns whether all dataloaders have been processed"""
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return self.current_dataloader_idx >= self.num_dataloaders
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def reset(self) -> None:
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"""Resets the internal state"""
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self.iteration_count = 0
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