code: def test_itersamples_numpy():
      """Test that iterating over samples in a NumpyDataset works."""
      num_datapoints = 100
      num_features = 10
      num_tasks = 10
      # Generate data
      X = np.random.rand(num_datapoints, num_features)
      y = np.random.randint(2, size=(num_datapoints, num_tasks))
      w = np.random.randint(2, size=(num_datapoints, num_tasks))
      ids = np.array(["id"] * num_datapoints)
      dataset = dc.data.NumpyDataset(X, y, w, ids)
      for i, (sx, sy, sw, sid) in enumerate(dataset.itersamples()):
          np.testing.assert_array_equal(sx, X[i])
          np.testing.assert_array_equal(sy, y[i])
          np.testing.assert_array_equal(sw, w[i])
          np.testing.assert_array_equal(sid, ids[i])
  
imports: import random
  import math
  import unittest
  import os
  import numpy
  import pytest
  import deepchem
  import pandas
  import tempfile
label_desc: Use image node_id 13 for calling a global function with example usage: test_itersamples_numpy() without return types