def _initialize_observation_space()

in gym_pusht/envs/pusht.py [0:0]


    def _initialize_observation_space(self):
        if self.obs_type == "state":
            # [agent_x, agent_y, block_x, block_y, block_angle]
            self.observation_space = spaces.Box(
                low=np.array([0, 0, 0, 0, 0]),
                high=np.array([512, 512, 512, 512, 2 * np.pi]),
                dtype=np.float64,
            )
        elif self.obs_type == "environment_state_agent_pos":
            self.observation_space = spaces.Dict(
                {
                    "environment_state": spaces.Box(
                        low=np.zeros(16),
                        high=np.full((16,), 512),
                        dtype=np.float64,
                    ),
                    "agent_pos": spaces.Box(
                        low=np.array([0, 0]),
                        high=np.array([512, 512]),
                        dtype=np.float64,
                    ),
                },
            )
        elif self.obs_type == "pixels":
            self.observation_space = spaces.Box(
                low=0, high=255, shape=(self.observation_height, self.observation_width, 3), dtype=np.uint8
            )
        elif self.obs_type == "pixels_agent_pos":
            self.observation_space = spaces.Dict(
                {
                    "pixels": spaces.Box(
                        low=0,
                        high=255,
                        shape=(self.observation_height, self.observation_width, 3),
                        dtype=np.uint8,
                    ),
                    "agent_pos": spaces.Box(
                        low=np.array([0, 0]),
                        high=np.array([512, 512]),
                        dtype=np.float64,
                    ),
                }
            )
        else:
            raise ValueError(
                f"Unknown obs_type {self.obs_type}. Must be one of [pixels, state, environment_state_agent_pos, "
                "pixels_agent_pos]"
            )