(self, is_terminal)
return np.array(self._get_table_state(normalization_sum=normalization_sum) \
                        + self._get_player_states_all_players(normalization_sum=normalization_sum) \
                        + self._get_board_state()
                        , dtype=np.float32)
This function can be useful for manually setting the environment to a desired state and then getting the
        formatted observation from it without actually stepping it.

        Args:
            is_terminal (bool): Whether the last env.step() call returned that it is done or not

        Returns:
            np.ndarray: current observation as returned by the last env.step() call.
This function can be useful for manually setting the environment to a desired state and then getting the
        formatted observation from it without actually stepping it.
This function can be useful for manually setting the environment to a desired state and then getting the formatted observation from it without actually stepping it .
def get_current_obs(self, is_terminal):
        """
        This function can be useful for manually setting the environment to a desired state and then getting the
        formatted observation from it without actually stepping it.

        Args:
            is_terminal (bool): Whether the last env.step() call returned that it is done or not

        Returns:
            np.ndarray: current observation as returned by the last env.step() call.

        """
        if is_terminal:
            return np.zeros(shape=self.observation_space.shape, dtype=np.float32)  # terminal is all zero
        normalization_sum = float(sum([s.starting_stack_this_episode for s in self.seats])) / self.N_SEATS
        return np.array(self._get_table_state(normalization_sum=normalization_sum) \
                        + self._get_player_states_all_players(normalization_sum=normalization_sum) \
                        + self._get_board_state()
                        , dtype=np.float32)
def get_current_obs ( self , is_terminal ) : if is_terminal : return np . zeros ( shape = self . observation_space . shape , dtype = np . float32 ) # terminal is all zero normalization_sum = float ( sum ( [ s . starting_stack_this_episode for s in self . seats ] ) ) / self . N_SEATS return np . array ( self . _get_table_state ( normalization_sum = normalization_sum ) + self . _get_player_states_all_players ( normalization_sum = normalization_sum ) + self . _get_board_state ( ) , dtype = np . float32 )