code: def assert_correct_incr(
      i, batch_start, batch_stop, n, chunk_size, n_samples_seen
  ):
      if batch_stop != n:
          assert (i + 1) * chunk_size == n_samples_seen
      else:
          assert (
              i * chunk_size + (batch_stop - batch_start)
              == n_samples_seen
          )
  
file_path: mars/mars/learn/preprocessing/tests/test_data.py
imports: import pytest
  from sklearn.datasets import load_iris
  from sklearn.utils import gen_batches
  from sklearn.utils._testing import assert_array_almost_equal, assert_allclose
  from ....None import tensor
  from ..None import MinMaxScaler, minmax_scale
label_desc: Use image node_id 1 for calling a global function with example usage: assert_correct_incr(i, batch_start, batch_stop, n, chunk_size, n_samples_seen) without return types