content: #  Copyright (c) ZenML GmbH 2022. All Rights Reserved.
  #
  #  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:
  #
  #       https://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 typing import Tuple
  
  from torch.utils.data import DataLoader
  from torchvision import datasets
  from torchvision.transforms import ToTensor
  from typing_extensions import Annotated
  
  from zenml import step
  
  
  @step
  def importer_mnist() -> Tuple[
      Annotated[DataLoader, "train_dataloader"],
      Annotated[DataLoader, "test_dataloader"],
  ]:
      """Download the Fashion MNIST dataset."""
      # Download training data from open datasets.
      training_data = datasets.FashionMNIST(
          root="data",
          train=True,
          download=True,
          transform=ToTensor(),
      )
  
      # Download test data from open datasets.
      test_data = datasets.FashionMNIST(
          root="data",
          train=False,
          download=True,
          transform=ToTensor(),
      )
      batch_size = 64
  
      # Create dataloaders.
      train_dataloader = DataLoader(training_data, batch_size=batch_size)
      test_dataloader = DataLoader(test_data, batch_size=batch_size)
  
      return train_dataloader, test_dataloader
  