Source code for pytorch_lightning.loops.dataloader.dataloader_loop
# Copyright The Lightning AI team.
#
# 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
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from abc import abstractmethod
from typing import Any, Sequence
from torch.utils.data import DataLoader
from pytorch_lightning.loops.loop import Loop
from pytorch_lightning.trainer.progress import DataLoaderProgress
[docs]class DataLoaderLoop(Loop):
"""Base class to loop over all dataloaders."""
def __init__(self) -> None:
super().__init__()
self.dataloader_progress = DataLoaderProgress()
@property
@abstractmethod
def dataloaders(self) -> Sequence[DataLoader]:
"""Returns the dataloaders to loop over."""
@property
def current_dataloader_idx(self) -> int:
"""Returns the index of the current dataloader."""
return self.dataloader_progress.current.ready - 1
@property
def current_dataloader(self) -> DataLoader:
"""Returns the current dataloader."""
return self.dataloaders[self.current_dataloader_idx]
@property
def num_dataloaders(self) -> int:
"""Returns the number of dataloaders present."""
return len(self.dataloaders) if self.dataloaders is not None else 0
@property
def done(self) -> bool:
"""Returns whether all dataloaders have been processed."""
return self.dataloader_progress.current.completed >= self.num_dataloaders
[docs] def reset(self) -> None:
"""Resets the internal state."""
if not self.restarting:
self.dataloader_progress.reset_on_run()
else:
self.dataloader_progress.reset_on_restart()
[docs] def on_advance_start(self, *args: Any, **kwargs: Any) -> None:
self.dataloader_progress.increment_ready()