def step(self, observation, **extra_feed):
        """
        Compute next action(s) given the observation(s)

        Parameters:
        ----------

        observation     observation data (either single or a batch)

        **extra_feed    additional data such as state or mask (names of the arguments should match the ones in constructor, see __init__)

        Returns:
        -------
        (action, value estimate, next state, negative log likelihood of the action under current policy parameters) tuple
        """

        a, v, state, neglogp = self._evaluate([self.action, self.vf, self.state, self.neglogp], observation, **extra_feed)
        if state.size == 0:
            state = None
        return a, v, state, neglogp
def step(self, observation, **extra_feed):
        """
        Compute next action(s) given the observation(s)

        Parameters:
        ----------

        observation     observation data (either single or a batch)

        **extra_feed    additional data such as state or mask (names of the arguments should match the ones in constructor, see __init__)

        Returns:
        -------
        (action, value estimate, next state, negative log likelihood of the action under current policy parameters) tuple
        """

        a, v, state, neglogp = self._evaluate([self.action, self.vf, self.state, self.neglogp], observation, **extra_feed)
        if state.size == 0:
            state = None
        return a, v, state, neglogp
def step ( self , observation , * * extra_feed ) : a , v , state , neglogp = self . _evaluate ( [ self . action , self . vf , self . state , self . neglogp ] , observation , * * extra_feed ) if state . size == 0 : state = None return a , v , state , neglogp
Compute next action(s) given the observation(s)

        Parameters:
        ----------

        observation     observation data (either single or a batch)

        **extra_feed    additional data such as state or mask (names of the arguments should match the ones in constructor, see __init__)

        Returns:
        -------
        (action, value estimate, next state, negative log likelihood of the action under current policy parameters) tuple
Compute next action ( s ) given the observation ( s )