class_docstr: Policy that performs a fixed sequence of actions.
  
  Args:
      env_spec (garage.envs.env_spec.EnvSpec): Environment specification.
      scripted_actions (list[np.ndarray] or np.ndarray): Sequence of actions
          to perform.
      agent_infos (list[dict[str, np.ndarray]] or None): Sequence of
          agent_infos to produce.
class_docstr_tok: ["Policy","that","performs","a","fixed","sequence","of","actions",".","Args",":","env_spec","(","garage.envs.env_spec.EnvSpec",")",":","Environment","specification",".","scripted_actions","(","list","[","np.ndarray","]","or","np.ndarray",")",":","Sequence","of","actions","to","perform",".","agent_infos","(","list","[","dict","[","str",",","np.ndarray","]","]","or","None",")",":","Sequence","of","agent_infos","to","produce","."]
code: def __init__(self, env_spec, scripted_actions, agent_infos=None):
      if agent_infos is None:
          agent_infos = [{}] * len(scripted_actions)
      self._env_spec = env_spec
      self._scripted_actions = scripted_actions
      self._agent_infos = agent_infos
      self._indices = [0]
  
file_path: garage/src/garage/np/policies/fixed_policy.py
imports: import numpy
  from garage.np.policies.policy import Policy
label_desc: Use image node_id 1 to create a new FixedPolicy object from inherited base classes: Policy with example: obj = FixedPolicy(env_spec, scripted_actions, agent_infos)