class_docstr: DataLoaderOperation
class_docstr_tok: ["DataLoaderOperation"]
code: def execute(self, batch_size: int, shuffle: bool):
      train_loader = torch.utils.data.DataLoader(
          datasets.MNIST(
              "data",
              train=True,
              download=True,
              transform=transforms.Compose(
                  [
                      transforms.ToTensor(),
                      transforms.Normalize((0.1307,), (0.3081,)),
                  ]
              ),
          ),
          batch_size=batch_size,
          shuffle=shuffle,
      )
      test_loader = torch.utils.data.DataLoader(
          datasets.MNIST(
              "data",
              train=False,
              transform=transforms.Compose(
                  [
                      transforms.ToTensor(),
                      transforms.Normalize((0.1307,), (0.3081,)),
                  ]
              ),
          ),
          batch_size=1000,
          shuffle=False,
      )
      self.train_data = train_loader
      self.test_data = test_loader
  
imports: import urllib.request
  from typing import Any
  import torch
  import torch.utils.data
  from nebullvm.operations.base import Operation
  from torchvision import datasets, transforms
label_desc: Use image node_id 3 for calling the MNISTDataLoaderOperation obj's underlying member method code with example usage: obj.execute(batch_size, shuffle) without return types