class_docstr: A simple environment that returns zeros for observations and rewards.
class_docstr_tok: ["A","simple","environment","that","returns","zeros","for","observations","and","rewards","."]
code: def __init__(self, observation_shape, batch_size=1):
      observation_spec = tensor_spec.TensorSpec(
          shape=observation_shape, dtype=tf.float32, name="observation"
      )
      time_step_spec = ts.time_step_spec(observation_spec)
      super(ZerosEnvironment, self).__init__(
          time_step_spec=time_step_spec, batch_size=batch_size
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.bandits.environments import bandit_tf_environment
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
label_desc: Use image node_id 1 to create a new ZerosEnvironment object from inherited base classes: bandit_tf_environment with example: obj = ZerosEnvironment(observation_shape, batch_size)