class_docstr: Base class for actions sampler.
  
  Given a batch of distribution params(including mean and var), sample, clip and
  return [N, B, A] actions, where 'N' means num_samples, 'B' means batch_size,
  'A' means action_size.
class_docstr_tok: ["Base","class","for","actions","sampler",".","Given","a","batch","of","distribution","params","(","including","mean","and","var",")",",","sample",",","clip","and","return","[","N",",","B",",","A","]","actions",",","where","'N","'","means","num_samples",",","'","B","'","means","batch_size",",","'","A","'","means","action_size","."]
docstr: Samples and clips a batch of actions [N, B, A] with distribution params.
  
  Args:
    num_samples: Number of actions to sample each round.
    distribution_params: Distribution related parameters. The sampler will use
      it to sample actions.
    state: Nested state tensor constructed according to oberservation_spec of
      the task.
  
  Returns:
    actions: batch containing the full action vector
docstr_tok: ["Samples","and","clips","a","batch","of","actions","[","N",",","B",",","A","]","with","distribution","params",".","Args",":","num_samples",":","Number","of","actions","to","sample","each","round",".","distribution_params",":","Distribution","related","parameters",".","The","sampler","will","use","it","to","sample","actions",".","state",":","Nested","state","tensor","constructed","according","to","oberservation_spec","of","the","task",".","Returns",":","actions",":","batch","containing","the","full","action","vector"]
code: def sample_batch_and_clip(
      self, num_samples, distribution_params, state=None
  ):
      """Samples and clips a batch of actions [N, B, A] with distribution params.
  
      Args:
        num_samples: Number of actions to sample each round.
        distribution_params: Distribution related parameters. The sampler will use
          it to sample actions.
        state: Nested state tensor constructed according to oberservation_spec of
          the task.
  
      Returns:
        actions: batch containing the full action vector
      """
      raise NotImplementedError(
          "sample_batch_and_clip not implemented."
      )
  
file_path: agents/tf_agents/policies/samplers/qtopt_cem_actions_sampler.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
label_desc: Use image node_id 3 for calling the ActionsSampler obj's underlying member method code with example usage: obj.sample_batch_and_clip(num_samples, distribution_params, state) without return types