def step()

in env_utils.py [0:0]

• 35 lines of code
• 6 McCabe index (conditional complexity)

    def step(self, action):
        frame, reward, done, _ = self.gym_env.step(action.item())

        self.episode_step += 1
        episode_step = self.episode_step

        self.episode_return += reward
        episode_return = self.episode_return

        if done and reward > 0:
            self.episode_win[0][0] = 1
        else:
            self.episode_win[0][0] = 0
        episode_win = self.episode_win

        if done:
            if self.fix_seed:
                self.gym_env.seed(seed=self.env_seed)
            frame = self.gym_env.reset()
            self.episode_return = torch.zeros(1, 1)
            self.episode_step = torch.zeros(1, 1, dtype=torch.int32)
            self.episode_win = torch.zeros(1, 1, dtype=torch.int32)

        frame = _format_observation(frame)
        reward = torch.tensor(reward).view(1, 1)
        done = torch.tensor(done).view(1, 1)

        if self.gym_env.carrying:
            carried_col, carried_obj = torch.LongTensor([[COLOR_TO_IDX[self.gym_env.carrying.color]]]), torch.LongTensor([[OBJECT_TO_IDX[self.gym_env.carrying.type]]])
        else:
            carried_col, carried_obj = torch.LongTensor([[5]]), torch.LongTensor([[1]])

        return dict(
            frame=frame,
            reward=reward,
            done=done,
            episode_return=episode_return,
            episode_step = episode_step,
            episode_win = episode_win,
            carried_col = carried_col,
            carried_obj = carried_obj
            )