class_docstr: ArrowDatasetTest
class_docstr_tok: ["ArrowDatasetTest"]
docstr: Test batch_size that divides an Arrow record batch into
  partial batches and leaves remainder data
code: def test_batch_with_partials_and_remainder(self):
      """Test batch_size that divides an Arrow record batch into
      partial batches and leaves remainder data
      """
      import tensorflow_io.arrow as arrow_io
  
      num_batches = 3
      batch_size = len(self.scalar_data[0]) + 1
  
      single_batch_data = TruthData(
          self.scalar_data, self.scalar_dtypes, self.scalar_shapes
      )
  
      batch = self.make_record_batch(single_batch_data)
      batches = [batch] * num_batches
  
      truth_data = TruthData(
          [d * num_batches for d in single_batch_data.data],
          single_batch_data.output_types,
          single_batch_data.output_shapes,
      )
  
      # Batches should divide input and leave a remainder
      self.assertNotEqual(len(truth_data.data[0]) % batch_size, 0)
  
      dataset = arrow_io.ArrowDataset.from_record_batches(
          batches,
          truth_data.output_types,
          truth_data.output_shapes,
          batch_size=batch_size,
      )
  
      self.run_test_case(dataset, truth_data, batch_size=batch_size)
  
imports: from collections import namedtuple
  import io
  import os
  import socket
  import tempfile
  import threading
  import pytest
  import pyarrow
  import numpy.testing
  import tensorflow
  import tensorflow_io
label_desc: Use image node_id 24 for calling the ArrowDatasetTest obj's underlying member method code with example usage: obj.test_batch_with_partials_and_remainder() without return types