code: def test_load_npy_range(self) -> None:
      num_rows = 10
      start_row = 2
      num_rows_to_select = 4
      with self._create_dataset_npys(
          num_rows=num_rows,
          generate_sparse=False,
          generate_labels=False,
      ) as (dense_path,):
          full = np.load(dense_path)
          partial = BinaryCriteoUtils.load_npy_range(
              dense_path,
              start_row=start_row,
              num_rows=num_rows_to_select,
          )
          np.testing.assert_array_equal(
              full[start_row : start_row + num_rows_to_select], partial
          )
  
imports: import contextlib
  import math
  import os
  import random
  import tempfile
  from typing import Any, Dict, List, Optional
  import numpy
  from torch.utils.data import DataLoader
  from torchrec.datasets.criteo import BinaryCriteoUtils, CAT_FEATURE_COUNT, criteo_kaggle, criteo_terabyte, InMemoryBinaryCriteoIterDataPipe, INT_FEATURE_COUNT
  from torchrec.datasets.test_utils.criteo_test_utils import CriteoTest
  from torchrec.datasets.utils import Batch
label_desc: Use image node_id 4 for calling the TestBinaryCriteoUtils obj's underlying member method code with example usage: obj.test_load_npy_range() without return types