code: def load_mnist(n_samples):
      """Load MNIST, shuffle the data, and return only n_samples."""
      mnist = fetch_openml("mnist_784", as_frame=False)
      X, y = shuffle(mnist.data, mnist.target, random_state=2)
      return X[:n_samples] / 255, y[:n_samples]
  
file_path: scikit-learn/examples/neighbors/approximate_nearest_neighbors.py
imports: import sys
  import joblib
  import numpy
  from scipy.sparse import csr_matrix
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.datasets import fetch_openml
  from sklearn.utils import shuffle
  import time
  from sklearn.manifold import TSNE
  from sklearn.neighbors import KNeighborsTransformer
  from sklearn.pipeline import make_pipeline
  import matplotlib.pyplot
  from matplotlib.ticker import NullFormatter
label_desc: Use image node_id 1 for calling a global function with example usage: load_mnist(n_samples) and returns: unknown,  y