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.
docstr: Returns a boolean mask of rows which are null in all provided paths.
  
  All provided paths must correspond to array of the same length.
  
  Args:
    *paths: Any number of paths for which to compute the all null mask.
  
  Returns:
    A boolean numpy array of shape (N,), where N is the size of all arrays
    referenced by paths.
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code: def all_null_mask(self, *paths: types.FeaturePath) -> np.ndarray:
      """Returns a boolean mask of rows which are null in all provided paths.
  
      All provided paths must correspond to array of the same length.
  
      Args:
        *paths: Any number of paths for which to compute the all null mask.
  
      Returns:
        A boolean numpy array of shape (N,), where N is the size of all arrays
        referenced by paths.
      """
      key = ("all_null_mask",) + paths
      if key in self._cache:
          return self._cache[key]
      if not paths:
          raise ValueError("Paths cannot be empty.")
      mask = self.null_mask(paths[0])
      for path in paths[1:]:
          path_mask = self.null_mask(path)
          if mask.size != path_mask.size:
              raise ValueError(
                  "All array lengths must be equal. "
                  "other_null_mask.size != null_mask({}).size "
                  "({} != {}).".format(path, mask.size, path_mask.size)
              )
          mask = mask & path_mask
      self._cache[key] = mask
      return mask
  
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 4 for calling the InputBatch obj's underlying member method code with example usage: obj.all_null_mask() and returns: mask, self