code: def get_mnist_data():
      _X_train, _Y_train, X_test, Y_test = fetch_mnist()
      BS = 32
      num_classes = 10
      X = Tensor(X_test[0:BS].astype(np.float32))
      Y = np.zeros((BS, num_classes), np.float32)
      Y[range(BS), Y_test[0:BS]] = -1.0 * num_classes
      return X, Tensor(Y)
  
file_path: tinygrad/test/models/test_end2end.py
imports: import torch
  from torch import nn
  import unittest
  import numpy
  from tinygrad.nn.state import get_parameters, get_state_dict
  from tinygrad.nn import optim, Linear, Conv2d, BatchNorm2d
  from tinygrad.tensor import Tensor
  from extra.datasets import fetch_mnist
  from tinygrad.helpers import CI
label_desc: Use image node_id 2 for calling a global function with example usage: get_mnist_data() and returns: X,  Tensor