class_docstr: A TFUniformReplayBuffer with batched adds and uniform sampling.
class_docstr_tok: ["A","TFUniformReplayBuffer","with","batched","adds","and","uniform","sampling","."]
docstr: Returns all the items in buffer, shape [batch_size, timestep, ...].
  
  Returns:
    All the items currently in the buffer.
docstr_tok: ["Returns","all","the","items","in","buffer",",","shape","[","batch_size",",","timestep",",","...","]",".","Returns",":","All","the","items","currently","in","the","buffer","."]
code: def _gather_all(self):
      """Returns all the items in buffer, shape [batch_size, timestep, ...].
  
      Returns:
        All the items currently in the buffer.
      """
      with tf.device(self._device), tf.name_scope(self._scope):
          with tf.name_scope("gather_all"):
              # Make ids, repeated over batch_size. Shape [batch_size, num_ids, ...].
              min_val, max_val = _valid_range_ids(
                  self._get_last_id(), self._max_length
              )
              ids = tf.range(min_val, max_val)
              ids = tf.stack([ids] * self._batch_size)
              rows = tf.math.mod(ids, self._max_length)
  
              # Make batch_offsets, shape [batch_size, 1], then add to rows.
              batch_offsets = tf.expand_dims(
                  tf.range(self._batch_size, dtype=tf.int64)
                  * self._max_length,
                  1,
              )
              rows += batch_offsets
  
              # Expected shape is [batch_size, max_length, ...].
              data = self._data_table.read(rows)
      return data
  
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 12 for calling the TFUniformReplayBuffer obj's underlying member method code with example usage: obj._gather_all() and returns: data