occant_baselines/rl/occant_exp_trainer.py [90:142]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - self.envs = None if config is not None: logger.info(f"config: {config}") def _synchronize_configs(self, config): r"""Matches configs for different parts of the model as well as the simulator. """ config.defrost() config.RL.ANS.PLANNER.nplanners = config.NUM_PROCESSES config.RL.ANS.MAPPER.thresh_explored = config.RL.ANS.thresh_explored config.RL.ANS.pyt_random_seed = config.PYT_RANDOM_SEED config.RL.ANS.OCCUPANCY_ANTICIPATOR.pyt_random_seed = config.PYT_RANDOM_SEED # Compute the EGO_PROJECTION options based on the # depth sensor information and agent parameters. map_size = config.RL.ANS.MAPPER.map_size map_scale = config.RL.ANS.MAPPER.map_scale min_depth = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.MIN_DEPTH max_depth = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.MAX_DEPTH hfov = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.HFOV width = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.WIDTH height = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.HEIGHT hfov_rad = np.radians(float(hfov)) vfov_rad = 2 * np.arctan((height / width) * np.tan(hfov_rad / 2.0)) vfov = np.degrees(vfov_rad).item() camera_height = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.POSITION[1] height_thresholds = [0.2, 1.5] # Set the EGO_PROJECTION options ego_proj_config = config.RL.ANS.OCCUPANCY_ANTICIPATOR.EGO_PROJECTION ego_proj_config.local_map_shape = (2, map_size, map_size) ego_proj_config.map_scale = map_scale ego_proj_config.min_depth = min_depth ego_proj_config.max_depth = max_depth ego_proj_config.hfov = hfov ego_proj_config.vfov = vfov ego_proj_config.camera_height = camera_height ego_proj_config.height_thresholds = height_thresholds config.RL.ANS.OCCUPANCY_ANTICIPATOR.EGO_PROJECTION = ego_proj_config # Set the GT anticipation options wall_fov = config.RL.ANS.OCCUPANCY_ANTICIPATOR.GP_ANTICIPATION.wall_fov config.TASK_CONFIG.TASK.GT_EGO_MAP_ANTICIPATED.WALL_FOV = wall_fov config.TASK_CONFIG.TASK.GT_EGO_MAP_ANTICIPATED.MAP_SIZE = map_size config.TASK_CONFIG.TASK.GT_EGO_MAP_ANTICIPATED.MAP_SCALE = map_scale config.TASK_CONFIG.TASK.GT_EGO_MAP_ANTICIPATED.MAX_SENSOR_RANGE = -1 # Set the correct image scaling values config.RL.ANS.MAPPER.image_scale_hw = config.RL.ANS.image_scale_hw config.RL.ANS.LOCAL_POLICY.image_scale_hw = config.RL.ANS.image_scale_hw # Set the agent dynamics for the local policy config.RL.ANS.LOCAL_POLICY.AGENT_DYNAMICS.forward_step = ( config.TASK_CONFIG.SIMULATOR.FORWARD_STEP_SIZE ) config.RL.ANS.LOCAL_POLICY.AGENT_DYNAMICS.turn_angle = ( config.TASK_CONFIG.SIMULATOR.TURN_ANGLE ) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - occant_baselines/rl/occant_nav_trainer.py [61:113]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - self.envs = None if config is not None: logger.info(f"config: {config}") def _synchronize_configs(self, config): r"""Matches configs for different parts of the model as well as the simulator. """ config.defrost() config.RL.ANS.PLANNER.nplanners = config.NUM_PROCESSES config.RL.ANS.MAPPER.thresh_explored = config.RL.ANS.thresh_explored config.RL.ANS.pyt_random_seed = config.PYT_RANDOM_SEED config.RL.ANS.OCCUPANCY_ANTICIPATOR.pyt_random_seed = config.PYT_RANDOM_SEED # Compute the EGO_PROJECTION options based on the # depth sensor information and agent parameters. map_size = config.RL.ANS.MAPPER.map_size map_scale = config.RL.ANS.MAPPER.map_scale min_depth = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.MIN_DEPTH max_depth = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.MAX_DEPTH hfov = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.HFOV width = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.WIDTH height = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.HEIGHT hfov_rad = np.radians(float(hfov)) vfov_rad = 2 * np.arctan((height / width) * np.tan(hfov_rad / 2.0)) vfov = np.degrees(vfov_rad).item() camera_height = config.TASK_CONFIG.SIMULATOR.DEPTH_SENSOR.POSITION[1] height_thresholds = [0.2, 1.5] # Set the EGO_PROJECTION options ego_proj_config = config.RL.ANS.OCCUPANCY_ANTICIPATOR.EGO_PROJECTION ego_proj_config.local_map_shape = (2, map_size, map_size) ego_proj_config.map_scale = map_scale ego_proj_config.min_depth = min_depth ego_proj_config.max_depth = max_depth ego_proj_config.hfov = hfov ego_proj_config.vfov = vfov ego_proj_config.camera_height = camera_height ego_proj_config.height_thresholds = height_thresholds config.RL.ANS.OCCUPANCY_ANTICIPATOR.EGO_PROJECTION = ego_proj_config # Set the GT anticipation options wall_fov = config.RL.ANS.OCCUPANCY_ANTICIPATOR.GP_ANTICIPATION.wall_fov config.TASK_CONFIG.TASK.GT_EGO_MAP_ANTICIPATED.WALL_FOV = wall_fov config.TASK_CONFIG.TASK.GT_EGO_MAP_ANTICIPATED.MAP_SIZE = map_size config.TASK_CONFIG.TASK.GT_EGO_MAP_ANTICIPATED.MAP_SCALE = map_scale config.TASK_CONFIG.TASK.GT_EGO_MAP_ANTICIPATED.MAX_SENSOR_RANGE = -1 # Set the correct image scaling values config.RL.ANS.MAPPER.image_scale_hw = config.RL.ANS.image_scale_hw config.RL.ANS.LOCAL_POLICY.image_scale_hw = config.RL.ANS.image_scale_hw # Set the agent dynamics for the local policy config.RL.ANS.LOCAL_POLICY.AGENT_DYNAMICS.forward_step = ( config.TASK_CONFIG.SIMULATOR.FORWARD_STEP_SIZE ) config.RL.ANS.LOCAL_POLICY.AGENT_DYNAMICS.turn_angle = ( config.TASK_CONFIG.SIMULATOR.TURN_ANGLE ) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -