class_docstr: A TFUniformReplayBuffer with batched adds and uniform sampling.
class_docstr_tok: ["A","TFUniformReplayBuffer","with","batched","adds","and","uniform","sampling","."]
docstr: Return op that resets the contents of replay buffer.
  
  Args:
    clear_all_variables: boolean indicating if all variables should be
      cleared. By default, table contents will be unlinked from replay buffer,
      but values are unmodified for efficiency. Set `clear_all_variables=True`
      to reset all variables including Table contents.
  
  Returns:
    op that clears or unlinks the replay buffer contents.
docstr_tok: ["Return","op","that","resets","the","contents","of","replay","buffer",".","Args",":","clear_all_variables",":","boolean","indicating","if","all","variables","should","be","cleared",".","By","default",",","table","contents","will","be","unlinked","from","replay","buffer",",","but","values","are","unmodified","for","efficiency",".","Set","`","clear_all_variables=True","`","to","reset","all","variables","including","Table","contents",".","Returns",":","op","that","clears","or","unlinks","the","replay","buffer","contents","."]
code: def _clear(self, clear_all_variables=False):
      """Return op that resets the contents of replay buffer.
  
      Args:
        clear_all_variables: boolean indicating if all variables should be
          cleared. By default, table contents will be unlinked from replay buffer,
          but values are unmodified for efficiency. Set `clear_all_variables=True`
          to reset all variables including Table contents.
  
      Returns:
        op that clears or unlinks the replay buffer contents.
      """
      table_vars = (
          self._data_table.variables() + self._id_table.variables()
      )
  
      def _init_vars():
          assignments = [self._last_id.assign(-1)]
          if clear_all_variables:
              assignments += [
                  v.assign(tf.zeros_like(v)) for v in table_vars
              ]
          return tf.group(*assignments, name="clear")
  
      return self._last_id_cs.execute(_init_vars)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import gin
  import numpy
  import tensorflow
  from tf_agents.replay_buffers import replay_buffer
  from tf_agents.replay_buffers import table
  from tf_agents.specs import tensor_spec
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 13 for calling the TFUniformReplayBuffer obj's underlying member method code with example usage: obj._clear(clear_all_variables) and returns: self, tf