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),
                [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),
                [num_updates, 1]))
    reset_op = tf.group([update_vals, update_logits])
    return reset_op
def reset ( self , entries_to_reset ) : 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 ) , [ 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 ) , [ num_updates , 1 ] ) ) reset_op = tf . group ( [ update_vals , update_logits ] ) return reset_op
Reset the entries in the memory.

    Args:
      entries_to_reset: a 1D tensor.
    Returns:
      the reset op.