def _tick(self, ret_val):
self._ctr -= 1
if self._ctr == 0:
self._stage += 1
if self._hp.action_bound:
ret_val['actions'] = truncate_movement(ret_val['actions'][None], self._hp)[0]
return ret_val
def _process(self, actions):
if self._hp.discrete_gripper:
actions = discretize_gripper(actions, self._hp.discrete_gripper)
if self._hp.action_bound:
actions = truncate_movement(actions, self._hp)
actions = np.repeat(actions, self._hp.repeat, axis=0)
return actions
def _default_sampler(self, mean, sigma, M):
actions = np.random.multivariate_normal(mean, sigma, M)
actions = actions.reshape(M, self._hp.nactions, self._adim)
if self._hp.action_bound:
actions = truncate_movement(actions, self._hp)
actions = np.repeat(actions, self._hp.repeat, axis=1)
return actions
def sample_actions(self, mean, sigma, hp, M):
actions = np.random.multivariate_normal(mean, sigma, M)
actions = actions.reshape(M, self.naction_steps, self.adim)
if hp.discrete_ind != None:
actions = discretize(actions, M, self.naction_steps,
hp.discrete_ind)
if hp.action_bound:
actions = truncate_movement(actions, hp)
actions = np.repeat(actions, hp.repeat, axis=1)
if hp.add_zero_action:
actions[0] = 0
return actions