code: def load_data():
      X, _ = datasets.fetch_openml(
          "mnist_784", version=1, return_X_y=True
      )
      X = (X / 255.0).astype(np.float32)
  
      np.random.shuffle(X)
      x_train_2d, x_test_2d = X[:60000], X[60000:]
      x_train_4d = x_train_2d.reshape((60000, 28, 28, 1))
      x_test_4d = x_test_2d.reshape((10000, 28, 28, 1))
  
      return x_train_4d, x_test_4d
  
imports: import numpy
  from sklearn import datasets
  import matplotlib.pyplot
  from neupy.layers import *
  from neupy import algorithms
label_desc: Use image node_id 1 for calling a global function with example usage: load_data() and returns: x_train_4d,  x_test_4d