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","."]
docstr: Reset policy.
  
  Args:
      do_resets (None or list[bool]): Vectorized policy states to reset.
  
  Raises:
      ValueError: If do_resets has length greater than 1.
docstr_tok: ["Reset","policy",".","Args",":","do_resets","(","None","or","list","[","bool","]",")",":","Vectorized","policy","states","to","reset",".","Raises",":","ValueError",":","If","do_resets","has","length","greater","than","1","."]
code: def reset(self, do_resets=None):
      """Reset policy.
  
      Args:
          do_resets (None or list[bool]): Vectorized policy states to reset.
  
      Raises:
          ValueError: If do_resets has length greater than 1.
  
      """
      if do_resets is None:
          do_resets = [True]
      if len(do_resets) > 1:
          raise ValueError(
              "FixedPolicy does not support more than one "
              "action at a time."
          )
      self._indices[0] = 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 2 for calling the FixedPolicy obj's underlying member method code with example usage: obj.reset(do_resets) without return types