class_docstr: Continuous Gaussian actions sampler.
  
  Supports nested action_spec with 1d continuous actions.
  
  Given a batch of distribution params(including mean and var), sample and
  return [B, N, A] actions, where 'B' means batch_size, 'N' means num_samples,
  'A' means action_size.
code: def __init__(
      self,
      action_spec,
      sample_clippers=None,
      sample_rejecters=None,
      max_rejection_iterations=10,
      support_integer=False,
  ):
      super(GaussianActionsSampler, self).__init__(
          action_spec, sample_clippers
      )
  
      self._sample_rejecters = sample_rejecters
      self._max_rejection_iterations = tf.constant(
          max_rejection_iterations
      )
  
      self._support_integer = support_integer
      if not support_integer:
          for flat_action_spec in tf.nest.flatten(action_spec):
              if flat_action_spec.dtype.is_integer:
                  raise ValueError(
                      "Only continuous action is supported by this "
                      "sampler. The action_spec: {} contains discrete "
                      "action".format(action_spec)
                  )
              if flat_action_spec.shape.rank > 1:
                  raise ValueError(
                      "Only 1d action is supported by this sampler. "
                      "The action_spec: {} contains action whose rank > 1."
                      "Consider coverting it into multiple 1d "
                      "actions.".format(action_spec)
                  )
  
file_path: agents/tf_agents/policies/samplers/qtopt_cem_actions_sampler_continuous.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gin
  import tensorflow
  import tensorflow_probability
  from tf_agents.policies.samplers import qtopt_cem_actions_sampler
  from tf_agents.specs import tensor_spec
  from tf_agents.utils import common
label_desc: Use image node_id 1 to create a new GaussianActionsSampler object from inherited base classes: qtopt_cem_actions_sampler with example: obj = GaussianActionsSampler(action_spec, sample_clippers, sample_rejecters, max_rejection_iterations, support_integer)