class_docstr: A Batch wraps a pyarrow.RecordBatch and provides caching functionality.
  
  This is useful when several different generators need to apply the same
  computation to the same input record batch. A CompositeCombinerStatsGenerator
  instantiates an InputBatch and then passes it to the add_input method of each
  constituent generator. This allows the constituent generators to reuse
  expensive operations that have already been computed by other constituents.
code: def __init__(self, record_batch: pa.RecordBatch):
      self._record_batch = record_batch
      self._cache = {}
  
file_path: data-validation/tensorflow_data_validation/statistics/generators/input_batch.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import pyarrow
  from tensorflow_data_validation import types
  from tfx_bsl.arrow import array_util
  from tfx_bsl.arrow import path
  from tfx_bsl.arrow import table_util
label_desc: Use image node_id 1 to create a new InputBatch object from inherited base classes: object with example: obj = InputBatch(record_batch)