class_docstr: Implements the Memory module.
  
  Based on Neural Turing Machines: arXiv:1410.5401 [cs.NE]
class_docstr_tok: ["Implements","the","Memory","module",".","Based","on","Neural","Turing","Machines",":","arXiv:1410.5401","[","cs.NE","]"]
docstr: Reset the entries in the memory.
  
  Args:
    entries_to_reset: a 1D tensor.
  Returns:
    the reset op.
docstr_tok: ["Reset","the","entries","in","the","memory",".","Args",":","entries_to_reset",":","a","1D","tensor",".","Returns",":","the","reset","op","."]
code: def reset(self, entries_to_reset):
      """Reset the entries in the memory.
  
      Args:
        entries_to_reset: a 1D tensor.
      Returns:
        the reset op.
      """
      num_updates = tf.size(entries_to_reset)
      update_vals = tf.scatter_update(
          self.mem_vals,
          entries_to_reset,
          tf.tile(
              tf.expand_dims(
                  tf.fill([self.memory_size, self.val_depth], 0.0), 0
              ),
              [num_updates, 1, 1],
          ),
      )
      update_logits = tf.scatter_update(
          self.mean_logits,
          entries_to_reset,
          tf.tile(
              tf.expand_dims(tf.fill([self.memory_size], 0.0), 0),
              [num_updates, 1],
          ),
      )
      reset_op = tf.group([update_vals, update_logits])
      return reset_op
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import common_layers
  import tensorflow.compat.v1
label_desc: Use image node_id 9 for calling the TransformerMemory obj's underlying member method code with example usage: obj.reset(entries_to_reset) and returns: reset_op