code: # Copyright (c) Microsoft Corporation.
  # Licensed under the MIT license.
  
  from typing import List, Tuple, Union, Optional
  
  from overrides import overrides, EnforceOverrides
  from torch.utils.data.dataset import Dataset
  
  import torchvision
  from torchvision.transforms import transforms
  from torch.utils.data import ConcatDataset
  
  from archai.datasets.dataset_provider import DatasetProvider, register_dataset_provider, TrainTestDatasets
  from archai.common.config import Config
  from archai.common import utils
  
  
  class SvhnProvider(DatasetProvider):
      def __init__(self, conf_dataset:Config):
          super().__init__(conf_dataset)
          self._dataroot = utils.full_path(conf_dataset['dataroot'])
  
      @overrides
      def get_datasets(self, load_train:bool, load_test:bool,
                       transform_train, transform_test)->TrainTestDatasets:
          trainset, testset = None, None
  
          if load_train:
              trainset = torchvision.datasets.SVHN(root=self._dataroot, split='train',
                  download=True, transform=transform_train)
              extraset = torchvision.datasets.SVHN(root=self._dataroot, split='extra',
                  download=True, transform=transform_train)
              trainset = ConcatDataset([trainset, extraset])
          if load_test:
              testset = torchvision.datasets.SVHN(root=self._dataroot, split='test',
                  download=True, transform=transform_test)
  
          return trainset, testset
  
      @overrides
      def get_transforms(self)->tuple:
          MEAN = [0.4914, 0.4822, 0.4465]
          STD = [0.2023, 0.1994, 0.20100]
          transf = [
              transforms.RandomCrop(32, padding=4),
              transforms.RandomHorizontalFlip()
          ]
  
          normalize = [
              transforms.ToTensor(),
              transforms.Normalize(MEAN, STD)
          ]
  
          train_transform = transforms.Compose(transf + normalize)
          test_transform = transforms.Compose(normalize)
  
          return train_transform, test_transform
  
  register_dataset_provider('svhn', SvhnProvider)
apis: torch.utils.data.ConcatDataset