def get_action(self, obs):
    '\n\t\t\tQueries an action from the actor network, should be called from rollout.\n\n\t\t\tParameters:\n\t\t\t\tobs - the observation at the current timestep\n\n\t\t\tReturn:\n\t\t\t\taction - the action to take, as a numpy array\n\t\t\t\tlog_prob - the log probability of the selected action in the distribution\n\t\t'
    mean = self.actor(obs)
    dist = MultivariateNormal(mean, self.cov_mat)
    action = dist.sample()
    log_prob = dist.log_prob(action)
    return (action.detach().numpy(), log_prob.detach())
Queries an action from the actor network, should be called from rollout.

Parameters:
        obs - the observation at the current timestep

Return:
        action - the action to take, as a numpy array
        log_prob - the log probability of the selected action in the distribution
def get_action(self, obs):
    '\n\t\t\tQueries an action from the actor network, should be called from rollout.\n\n\t\t\tParameters:\n\t\t\t\tobs - the observation at the current timestep\n\n\t\t\tReturn:\n\t\t\t\taction - the action to take, as a numpy array\n\t\t\t\tlog_prob - the log probability of the selected action in the distribution\n\t\t'
    mean = self.actor(obs)
    dist = MultivariateNormal(mean, self.cov_mat)
    action = dist.sample()
    log_prob = dist.log_prob(action)
    return (action.detach().numpy(), log_prob.detach())