class_docstr: A container that holds info about partial batches for `predict()`.
docstr: Calculate and cache the amount of padding required for a batch.
code: def update_mask(self, padding_mask, dataset_batch):
      """Calculate and cache the amount of padding required for a batch."""
      original_batch_size = self.get_real_batch_size(dataset_batch)
      missing_count = self.padded_batch_size - original_batch_size
      mask = backend.concatenate(
          [
              array_ops.ones(original_batch_size),
              array_ops.zeros(missing_count),
          ],
          axis=0,
      )
      return backend.concatenate([padding_mask, mask], axis=0)
  
file_path: tensorflow-upstream/tensorflow/python/keras/engine/partial_batch_padding_handler.py
imports: import numpy
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.keras import backend
  from tensorflow.python.ops import array_ops
  from tensorflow.python.util import nest
label_desc: Use image node_id 3 for calling the PartialBatchPaddingHandler obj's underlying member method code with example usage: obj.update_mask(padding_mask, dataset_batch) and returns: backend