text: # Copyright The PyTorch Lightning 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
  # limitations under the License.
  
  from abc import abstractmethod
  from typing import Sequence
  
  from torch.utils.data import DataLoader
  
  from pytorch_lightning.loops.base import Loop
  
  
  class DataLoaderLoop(Loop):
      """Base class to loop over all dataloaders"""
  
      @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.iteration_count
  
      @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.current_dataloader_idx >= self.num_dataloaders
  
      def reset(self) -> None:
          """Resets the internal state"""
          self.iteration_count = 0
  