DriveTransformer/goalpoint_1gpu/20260226_122411.log.json

{"mmcv_version": "0.0.1", "config": "point_cloud_range = [-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]\nclass_names = [\n    'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',\n    'traffic_light', 'pedestrian', 'others'\n]\ndataset_type = 'B2D_DriveTransformer_GoalPoint_Dataset'\ndata_root = 'data/bench2drive'\ninput_modality = dict(\n    use_lidar=False,\n    use_camera=True,\n    use_radar=False,\n    use_map=False,\n    use_external=True)\nfile_client_args = dict(backend='disk')\ntrain_pipeline = [\n    dict(type='LoadMultiViewImageFromFiles', to_float32=True),\n    dict(type='ResizeCropFlipImage'),\n    dict(\n        type='NormalizeMultiviewImage',\n        mean=[123.675, 116.28, 103.53],\n        std=[58.395, 57.12, 57.375],\n        to_rgb=True),\n    dict(\n        type='LoadAnnotations3D',\n        with_bbox_3d=True,\n        with_label_3d=True,\n        with_attr_label=True),\n    dict(\n        type='CustomObjectRangeFilter',\n        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),\n    dict(\n        type='CustomObjectNameFilter',\n        classes=[\n            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',\n            'traffic_light', 'pedestrian', 'others'\n        ]),\n    dict(\n        type='TrajPreprocess',\n        pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n        with_ego_fix_dist=True,\n        ego_fut_offset_input=False,\n        assign_class_for_ego=False),\n    dict(\n        type='CustomFormatBundle3D',\n        class_names=[\n            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',\n            'traffic_light', 'pedestrian', 'others'\n        ],\n        with_ego=True,\n        collect_keys=[\n            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',\n            'ego_fut_classes'\n        ]),\n    dict(\n        type='CustomCollect3D',\n        keys=[\n            'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',\n            'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',\n            'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',\n            'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist', 'ego_fut_cmd',\n            'ego_lcf_feat', 'gt_attr_labels', 'prev_exists', 'index',\n            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',\n            'ego_fut_classes'\n        ])\n]\ntest_pipeline = [\n    dict(type='LoadMultiViewImageFromFiles', to_float32=True),\n    dict(type='ResizeCropFlipImage'),\n    dict(\n        type='NormalizeMultiviewImage',\n        mean=[123.675, 116.28, 103.53],\n        std=[58.395, 57.12, 57.375],\n        to_rgb=True),\n    dict(\n        type='LoadAnnotations3D',\n        with_bbox_3d=True,\n        with_label_3d=True,\n        with_attr_label=True),\n    dict(\n        type='CustomObjectRangeFilter',\n        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),\n    dict(\n        type='CustomObjectNameFilter',\n        classes=[\n            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',\n            'traffic_light', 'pedestrian', 'others'\n        ]),\n    dict(\n        type='TrajPreprocess',\n        pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n        with_ego_fix_dist=True,\n        ego_fut_offset_input=False,\n        assign_class_for_ego=False),\n    dict(\n        type='CustomFormatBundle3D',\n        class_names=[\n            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',\n            'traffic_light', 'pedestrian', 'others'\n        ],\n        with_ego=True,\n        collect_keys=[\n            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',\n            'ego_fut_classes'\n        ]),\n    dict(\n        type='CustomCollect3D',\n        keys=[\n            'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',\n            'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',\n            'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',\n            'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist', 'ego_fut_cmd',\n            'ego_lcf_feat', 'gt_attr_labels', 'prev_exists', 'index',\n            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',\n            'ego_fut_classes'\n        ])\n]\neval_pipeline = [\n    dict(\n        type='LoadPointsFromFile',\n        coord_type='LIDAR',\n        load_dim=5,\n        use_dim=5,\n        file_client_args=dict(backend='disk')),\n    dict(\n        type='LoadPointsFromMultiSweeps',\n        sweeps_num=10,\n        file_client_args=dict(backend='disk')),\n    dict(\n        type='DefaultFormatBundle3D',\n        class_names=[\n            'car', 'truck', 'trailer', 'bus', 'construction_vehicle',\n            'bicycle', 'motorcycle', 'pedestrian', 'traffic_cone', 'barrier'\n        ],\n        with_label=False),\n    dict(type='Collect3D', keys=['points'])\n]\ndata = dict(\n    samples_per_gpu=6,\n    workers_per_gpu=8,\n    train=dict(\n        type='B2D_DriveTransformer_GoalPoint_Dataset',\n        data_root='data/bench2drive',\n        ann_file='data/infos/b2d_infos_v1_train_drivetransformer_meta.pkl',\n        pipeline=[\n            dict(type='LoadMultiViewImageFromFiles', to_float32=True),\n            dict(type='ResizeCropFlipImage'),\n            dict(\n                type='NormalizeMultiviewImage',\n                mean=[123.675, 116.28, 103.53],\n                std=[58.395, 57.12, 57.375],\n                to_rgb=True),\n            dict(\n                type='LoadAnnotations3D',\n                with_bbox_3d=True,\n                with_label_3d=True,\n                with_attr_label=True),\n            dict(\n                type='CustomObjectRangeFilter',\n                point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),\n            dict(\n                type='CustomObjectNameFilter',\n                classes=[\n                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',\n                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'\n                ]),\n            dict(\n                type='TrajPreprocess',\n                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n                with_ego_fix_dist=True,\n                ego_fut_offset_input=False,\n                assign_class_for_ego=False),\n            dict(\n                type='CustomFormatBundle3D',\n                class_names=[\n                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',\n                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'\n                ],\n                with_ego=True,\n                collect_keys=[\n                    'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n                    'ego_pose', 'ego_pose_inv', 'pad_shape',\n                    'gt_traj_fut_classes', 'ego_fut_classes'\n                ]),\n            dict(\n                type='CustomCollect3D',\n                keys=[\n                    'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',\n                    'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',\n                    'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',\n                    'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist',\n                    'ego_fut_cmd', 'ego_lcf_feat', 'gt_attr_labels',\n                    'prev_exists', 'index', 'lidar2img', 'cam_intrinsic',\n                    'cam_extrinsic', 'timestamp', 'ego_pose', 'ego_pose_inv',\n                    'pad_shape', 'gt_traj_fut_classes', 'ego_fut_classes'\n                ])\n        ],\n        classes=[\n            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',\n            'traffic_light', 'pedestrian', 'others'\n        ],\n        modality=dict(\n            use_lidar=False,\n            use_camera=True,\n            use_radar=False,\n            use_map=False,\n            use_external=True),\n        test_mode=False,\n        box_type_3d='LiDAR',\n        data_aug_conf=dict(\n            resize_lim=(0.64, 0.69),\n            final_dim=(384, 1056),\n            bot_pct_lim=(0.0, 0.0),\n            rot_lim=(-5.4, 5.4),\n            H=900,\n            W=1600,\n            rand_flip=True,\n            rot3d_range=[0, 0]),\n        name_mapping=dict({\n            'vehicle.bh.crossbike':\n            'bicycle',\n            'vehicle.diamondback.century':\n            'bicycle',\n            'vehicle.gazelle.omafiets':\n            'bicycle',\n            'vehicle.audi.etron':\n            'car',\n            'vehicle.chevrolet.impala':\n            'car',\n            'vehicle.dodge.charger_2020':\n            'car',\n            'vehicle.dodge.charger_police':\n            'car',\n            'vehicle.dodge.charger_police_2020':\n            'car',\n            'vehicle.lincoln.mkz_2017':\n            'car',\n            'vehicle.lincoln.mkz_2020':\n            'car',\n            'vehicle.mini.cooper_s_2021':\n            'car',\n            'vehicle.mercedes.coupe_2020':\n            'car',\n            'vehicle.ford.mustang':\n            'car',\n            'vehicle.nissan.patrol_2021':\n            'car',\n            'vehicle.audi.tt':\n            'car',\n            'vehicle.ford.crown':\n            'car',\n            'vehicle.tesla.model3':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/FordCrown/SM_FordCrown_parked.SM_FordCrown_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Charger/SM_ChargerParked.SM_ChargerParked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Lincoln/SM_LincolnParked.SM_LincolnParked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/MercedesCCC/SM_MercedesCCC_Parked.SM_MercedesCCC_Parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Mini2021/SM_Mini2021_parked.SM_Mini2021_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/NissanPatrol2021/SM_NissanPatrol2021_parked.SM_NissanPatrol2021_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/TeslaM3/SM_TeslaM3_parked.SM_TeslaM3_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/VolkswagenT2/SM_VolkswagenT2_2021_Parked.SM_VolkswagenT2_2021_Parked':\n            'van',\n            'vehicle.ford.ambulance':\n            'van',\n            'vehicle.carlamotors.firetruck':\n            'truck',\n            'traffic.speed_limit.30':\n            'traffic_sign',\n            'traffic.speed_limit.40':\n            'traffic_sign',\n            'traffic.speed_limit.50':\n            'traffic_sign',\n            'traffic.speed_limit.60':\n            'traffic_sign',\n            'traffic.speed_limit.90':\n            'traffic_sign',\n            'traffic.speed_limit.120':\n            'traffic_sign',\n            'traffic.stop':\n            'traffic_sign',\n            'traffic.yield':\n            'traffic_sign',\n            'traffic.traffic_light':\n            'traffic_light',\n            'static.prop.warningconstruction':\n            'traffic_cone',\n            'static.prop.warningaccident':\n            'traffic_cone',\n            'static.prop.trafficwarning':\n            'traffic_cone',\n            'static.prop.constructioncone':\n            'traffic_cone',\n            'walker.pedestrian.0001':\n            'pedestrian',\n            'walker.pedestrian.0003':\n            'pedestrian',\n            'walker.pedestrian.0004':\n            'pedestrian',\n            'walker.pedestrian.0005':\n            'pedestrian',\n            'walker.pedestrian.0007':\n            'pedestrian',\n            'walker.pedestrian.0010':\n            'pedestrian',\n            'walker.pedestrian.0013':\n            'pedestrian',\n            'walker.pedestrian.0014':\n            'pedestrian',\n            'walker.pedestrian.0015':\n            'pedestrian',\n            'walker.pedestrian.0016':\n            'pedestrian',\n            'walker.pedestrian.0017':\n            'pedestrian',\n            'walker.pedestrian.0018':\n            'pedestrian',\n            'walker.pedestrian.0019':\n            'pedestrian',\n            'walker.pedestrian.0020':\n            'pedestrian',\n            'walker.pedestrian.0021':\n            'pedestrian',\n            'walker.pedestrian.0022':\n            'pedestrian',\n            'walker.pedestrian.0025':\n            'pedestrian',\n            'walker.pedestrian.0027':\n            'pedestrian',\n            'walker.pedestrian.0030':\n            'pedestrian',\n            'walker.pedestrian.0031':\n            'pedestrian',\n            'walker.pedestrian.0032':\n            'pedestrian',\n            'walker.pedestrian.0034':\n            'pedestrian',\n            'walker.pedestrian.0035':\n            'pedestrian',\n            'walker.pedestrian.0041':\n            'pedestrian',\n            'walker.pedestrian.0042':\n            'pedestrian',\n            'walker.pedestrian.0046':\n            'pedestrian',\n            'walker.pedestrian.0047':\n            'pedestrian',\n            'static.prop.dirtdebris01':\n            'others',\n            'static.prop.dirtdebris02':\n            'others'\n        }),\n        map_file='data/infos/b2d_map_infos.pkl',\n        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n        collect_keys=[\n            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',\n            'ego_fut_classes'\n        ],\n        polyline_points_num=20,\n        filter_empty_gt=False,\n        sub_seq_lenth=-1,\n        use_splited_data=True,\n        cache_lenth=7,\n        future_frames=6,\n        future_frames_ego_fix_time=30,\n        future_frames_ego_fix_dist=20,\n        sample_interval_ego_fut=1,\n        sample_interval=5,\n        fix_future_dis=1,\n        use_angle_as_dis_traj=True,\n        use_raw_goalpoint=False),\n    val=dict(\n        type='B2D_DriveTransformer_GoalPoint_Dataset',\n        ann_file='data/infos/b2d_infos_v1_val_drivetransformer_meta.pkl',\n        pipeline=[\n            dict(type='LoadMultiViewImageFromFiles', to_float32=True),\n            dict(type='ResizeCropFlipImage'),\n            dict(\n                type='NormalizeMultiviewImage',\n                mean=[123.675, 116.28, 103.53],\n                std=[58.395, 57.12, 57.375],\n                to_rgb=True),\n            dict(\n                type='LoadAnnotations3D',\n                with_bbox_3d=True,\n                with_label_3d=True,\n                with_attr_label=True),\n            dict(\n                type='CustomObjectRangeFilter',\n                point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),\n            dict(\n                type='CustomObjectNameFilter',\n                classes=[\n                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',\n                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'\n                ]),\n            dict(\n                type='TrajPreprocess',\n                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n                with_ego_fix_dist=True,\n                ego_fut_offset_input=False,\n                assign_class_for_ego=False),\n            dict(\n                type='CustomFormatBundle3D',\n                class_names=[\n                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',\n                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'\n                ],\n                with_ego=True,\n                collect_keys=[\n                    'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n                    'ego_pose', 'ego_pose_inv', 'pad_shape',\n                    'gt_traj_fut_classes', 'ego_fut_classes'\n                ]),\n            dict(\n                type='CustomCollect3D',\n                keys=[\n                    'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',\n                    'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',\n                    'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',\n                    'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist',\n                    'ego_fut_cmd', 'ego_lcf_feat', 'gt_attr_labels',\n                    'prev_exists', 'index', 'lidar2img', 'cam_intrinsic',\n                    'cam_extrinsic', 'timestamp', 'ego_pose', 'ego_pose_inv',\n                    'pad_shape', 'gt_traj_fut_classes', 'ego_fut_classes'\n                ])\n        ],\n        classes=[\n            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',\n            'traffic_light', 'pedestrian', 'others'\n        ],\n        modality=dict(\n            use_lidar=False,\n            use_camera=True,\n            use_radar=False,\n            use_map=False,\n            use_external=True),\n        test_mode=True,\n        box_type_3d='LiDAR',\n        data_root='data/bench2drive',\n        data_aug_conf=dict(\n            resize_lim=(0.64, 0.69),\n            final_dim=(384, 1056),\n            bot_pct_lim=(0.0, 0.0),\n            rot_lim=(-5.4, 5.4),\n            H=900,\n            W=1600,\n            rand_flip=True,\n            rot3d_range=[0, 0]),\n        name_mapping=dict({\n            'vehicle.bh.crossbike':\n            'bicycle',\n            'vehicle.diamondback.century':\n            'bicycle',\n            'vehicle.gazelle.omafiets':\n            'bicycle',\n            'vehicle.audi.etron':\n            'car',\n            'vehicle.chevrolet.impala':\n            'car',\n            'vehicle.dodge.charger_2020':\n            'car',\n            'vehicle.dodge.charger_police':\n            'car',\n            'vehicle.dodge.charger_police_2020':\n            'car',\n            'vehicle.lincoln.mkz_2017':\n            'car',\n            'vehicle.lincoln.mkz_2020':\n            'car',\n            'vehicle.mini.cooper_s_2021':\n            'car',\n            'vehicle.mercedes.coupe_2020':\n            'car',\n            'vehicle.ford.mustang':\n            'car',\n            'vehicle.nissan.patrol_2021':\n            'car',\n            'vehicle.audi.tt':\n            'car',\n            'vehicle.ford.crown':\n            'car',\n            'vehicle.tesla.model3':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/FordCrown/SM_FordCrown_parked.SM_FordCrown_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Charger/SM_ChargerParked.SM_ChargerParked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Lincoln/SM_LincolnParked.SM_LincolnParked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/MercedesCCC/SM_MercedesCCC_Parked.SM_MercedesCCC_Parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Mini2021/SM_Mini2021_parked.SM_Mini2021_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/NissanPatrol2021/SM_NissanPatrol2021_parked.SM_NissanPatrol2021_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/TeslaM3/SM_TeslaM3_parked.SM_TeslaM3_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/VolkswagenT2/SM_VolkswagenT2_2021_Parked.SM_VolkswagenT2_2021_Parked':\n            'van',\n            'vehicle.ford.ambulance':\n            'van',\n            'vehicle.carlamotors.firetruck':\n            'truck',\n            'traffic.speed_limit.30':\n            'traffic_sign',\n            'traffic.speed_limit.40':\n            'traffic_sign',\n            'traffic.speed_limit.50':\n            'traffic_sign',\n            'traffic.speed_limit.60':\n            'traffic_sign',\n            'traffic.speed_limit.90':\n            'traffic_sign',\n            'traffic.speed_limit.120':\n            'traffic_sign',\n            'traffic.stop':\n            'traffic_sign',\n            'traffic.yield':\n            'traffic_sign',\n            'traffic.traffic_light':\n            'traffic_light',\n            'static.prop.warningconstruction':\n            'traffic_cone',\n            'static.prop.warningaccident':\n            'traffic_cone',\n            'static.prop.trafficwarning':\n            'traffic_cone',\n            'static.prop.constructioncone':\n            'traffic_cone',\n            'walker.pedestrian.0001':\n            'pedestrian',\n            'walker.pedestrian.0003':\n            'pedestrian',\n            'walker.pedestrian.0004':\n            'pedestrian',\n            'walker.pedestrian.0005':\n            'pedestrian',\n            'walker.pedestrian.0007':\n            'pedestrian',\n            'walker.pedestrian.0010':\n            'pedestrian',\n            'walker.pedestrian.0013':\n            'pedestrian',\n            'walker.pedestrian.0014':\n            'pedestrian',\n            'walker.pedestrian.0015':\n            'pedestrian',\n            'walker.pedestrian.0016':\n            'pedestrian',\n            'walker.pedestrian.0017':\n            'pedestrian',\n            'walker.pedestrian.0018':\n            'pedestrian',\n            'walker.pedestrian.0019':\n            'pedestrian',\n            'walker.pedestrian.0020':\n            'pedestrian',\n            'walker.pedestrian.0021':\n            'pedestrian',\n            'walker.pedestrian.0022':\n            'pedestrian',\n            'walker.pedestrian.0025':\n            'pedestrian',\n            'walker.pedestrian.0027':\n            'pedestrian',\n            'walker.pedestrian.0030':\n            'pedestrian',\n            'walker.pedestrian.0031':\n            'pedestrian',\n            'walker.pedestrian.0032':\n            'pedestrian',\n            'walker.pedestrian.0034':\n            'pedestrian',\n            'walker.pedestrian.0035':\n            'pedestrian',\n            'walker.pedestrian.0041':\n            'pedestrian',\n            'walker.pedestrian.0042':\n            'pedestrian',\n            'walker.pedestrian.0046':\n            'pedestrian',\n            'walker.pedestrian.0047':\n            'pedestrian',\n            'static.prop.dirtdebris01':\n            'others',\n            'static.prop.dirtdebris02':\n            'others'\n        }),\n        map_file='data/infos/b2d_map_infos.pkl',\n        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n        collect_keys=[\n            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',\n            'ego_fut_classes'\n        ],\n        polyline_points_num=20,\n        filter_empty_gt=False,\n        use_splited_data=True,\n        cache_lenth=7,\n        future_frames=6,\n        future_frames_ego_fix_time=30,\n        future_frames_ego_fix_dist=20,\n        sample_interval_ego_fut=1,\n        sample_interval=5,\n        fix_future_dis=1,\n        use_angle_as_dis_traj=True,\n        use_raw_goalpoint=False),\n    test=dict(\n        type='B2D_DriveTransformer_GoalPoint_Dataset',\n        data_root='data/bench2drive',\n        ann_file='data/infos/b2d_infos_v1_val_drivetransformer_meta.pkl',\n        pipeline=[\n            dict(type='LoadMultiViewImageFromFiles', to_float32=True),\n            dict(type='ResizeCropFlipImage'),\n            dict(\n                type='NormalizeMultiviewImage',\n                mean=[123.675, 116.28, 103.53],\n                std=[58.395, 57.12, 57.375],\n                to_rgb=True),\n            dict(\n                type='LoadAnnotations3D',\n                with_bbox_3d=True,\n                with_label_3d=True,\n                with_attr_label=True),\n            dict(\n                type='CustomObjectRangeFilter',\n                point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),\n            dict(\n                type='CustomObjectNameFilter',\n                classes=[\n                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',\n                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'\n                ]),\n            dict(\n                type='TrajPreprocess',\n                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n                with_ego_fix_dist=True,\n                ego_fut_offset_input=False,\n                assign_class_for_ego=False),\n            dict(\n                type='CustomFormatBundle3D',\n                class_names=[\n                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',\n                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'\n                ],\n                with_ego=True,\n                collect_keys=[\n                    'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n                    'ego_pose', 'ego_pose_inv', 'pad_shape',\n                    'gt_traj_fut_classes', 'ego_fut_classes'\n                ]),\n            dict(\n                type='CustomCollect3D',\n                keys=[\n                    'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',\n                    'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',\n                    'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',\n                    'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist',\n                    'ego_fut_cmd', 'ego_lcf_feat', 'gt_attr_labels',\n                    'prev_exists', 'index', 'lidar2img', 'cam_intrinsic',\n                    'cam_extrinsic', 'timestamp', 'ego_pose', 'ego_pose_inv',\n                    'pad_shape', 'gt_traj_fut_classes', 'ego_fut_classes'\n                ])\n        ],\n        classes=[\n            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',\n            'traffic_light', 'pedestrian', 'others'\n        ],\n        modality=dict(\n            use_lidar=False,\n            use_camera=True,\n            use_radar=False,\n            use_map=False,\n            use_external=True),\n        test_mode=True,\n        box_type_3d='LiDAR',\n        data_aug_conf=dict(\n            resize_lim=(0.64, 0.69),\n            final_dim=(384, 1056),\n            bot_pct_lim=(0.0, 0.0),\n            rot_lim=(-5.4, 5.4),\n            H=900,\n            W=1600,\n            rand_flip=True,\n            rot3d_range=[0, 0]),\n        name_mapping=dict({\n            'vehicle.bh.crossbike':\n            'bicycle',\n            'vehicle.diamondback.century':\n            'bicycle',\n            'vehicle.gazelle.omafiets':\n            'bicycle',\n            'vehicle.audi.etron':\n            'car',\n            'vehicle.chevrolet.impala':\n            'car',\n            'vehicle.dodge.charger_2020':\n            'car',\n            'vehicle.dodge.charger_police':\n            'car',\n            'vehicle.dodge.charger_police_2020':\n            'car',\n            'vehicle.lincoln.mkz_2017':\n            'car',\n            'vehicle.lincoln.mkz_2020':\n            'car',\n            'vehicle.mini.cooper_s_2021':\n            'car',\n            'vehicle.mercedes.coupe_2020':\n            'car',\n            'vehicle.ford.mustang':\n            'car',\n            'vehicle.nissan.patrol_2021':\n            'car',\n            'vehicle.audi.tt':\n            'car',\n            'vehicle.ford.crown':\n            'car',\n            'vehicle.tesla.model3':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/FordCrown/SM_FordCrown_parked.SM_FordCrown_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Charger/SM_ChargerParked.SM_ChargerParked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Lincoln/SM_LincolnParked.SM_LincolnParked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/MercedesCCC/SM_MercedesCCC_Parked.SM_MercedesCCC_Parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Mini2021/SM_Mini2021_parked.SM_Mini2021_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/NissanPatrol2021/SM_NissanPatrol2021_parked.SM_NissanPatrol2021_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/TeslaM3/SM_TeslaM3_parked.SM_TeslaM3_parked':\n            'car',\n            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/VolkswagenT2/SM_VolkswagenT2_2021_Parked.SM_VolkswagenT2_2021_Parked':\n            'van',\n            'vehicle.ford.ambulance':\n            'van',\n            'vehicle.carlamotors.firetruck':\n            'truck',\n            'traffic.speed_limit.30':\n            'traffic_sign',\n            'traffic.speed_limit.40':\n            'traffic_sign',\n            'traffic.speed_limit.50':\n            'traffic_sign',\n            'traffic.speed_limit.60':\n            'traffic_sign',\n            'traffic.speed_limit.90':\n            'traffic_sign',\n            'traffic.speed_limit.120':\n            'traffic_sign',\n            'traffic.stop':\n            'traffic_sign',\n            'traffic.yield':\n            'traffic_sign',\n            'traffic.traffic_light':\n            'traffic_light',\n            'static.prop.warningconstruction':\n            'traffic_cone',\n            'static.prop.warningaccident':\n            'traffic_cone',\n            'static.prop.trafficwarning':\n            'traffic_cone',\n            'static.prop.constructioncone':\n            'traffic_cone',\n            'walker.pedestrian.0001':\n            'pedestrian',\n            'walker.pedestrian.0003':\n            'pedestrian',\n            'walker.pedestrian.0004':\n            'pedestrian',\n            'walker.pedestrian.0005':\n            'pedestrian',\n            'walker.pedestrian.0007':\n            'pedestrian',\n            'walker.pedestrian.0010':\n            'pedestrian',\n            'walker.pedestrian.0013':\n            'pedestrian',\n            'walker.pedestrian.0014':\n            'pedestrian',\n            'walker.pedestrian.0015':\n            'pedestrian',\n            'walker.pedestrian.0016':\n            'pedestrian',\n            'walker.pedestrian.0017':\n            'pedestrian',\n            'walker.pedestrian.0018':\n            'pedestrian',\n            'walker.pedestrian.0019':\n            'pedestrian',\n            'walker.pedestrian.0020':\n            'pedestrian',\n            'walker.pedestrian.0021':\n            'pedestrian',\n            'walker.pedestrian.0022':\n            'pedestrian',\n            'walker.pedestrian.0025':\n            'pedestrian',\n            'walker.pedestrian.0027':\n            'pedestrian',\n            'walker.pedestrian.0030':\n            'pedestrian',\n            'walker.pedestrian.0031':\n            'pedestrian',\n            'walker.pedestrian.0032':\n            'pedestrian',\n            'walker.pedestrian.0034':\n            'pedestrian',\n            'walker.pedestrian.0035':\n            'pedestrian',\n            'walker.pedestrian.0041':\n            'pedestrian',\n            'walker.pedestrian.0042':\n            'pedestrian',\n            'walker.pedestrian.0046':\n            'pedestrian',\n            'walker.pedestrian.0047':\n            'pedestrian',\n            'static.prop.dirtdebris01':\n            'others',\n            'static.prop.dirtdebris02':\n            'others'\n        }),\n        map_file='data/infos/b2d_map_infos.pkl',\n        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n        collect_keys=[\n            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',\n            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',\n            'ego_fut_classes'\n        ],\n        polyline_points_num=20,\n        filter_empty_gt=False,\n        use_splited_data=True,\n        cache_lenth=7,\n        future_frames=6,\n        future_frames_ego_fix_time=30,\n        future_frames_ego_fix_dist=20,\n        sample_interval_ego_fut=1,\n        sample_interval=5,\n        fix_future_dis=1,\n        use_angle_as_dis_traj=True,\n        use_raw_goalpoint=False),\n    shuffler_sampler=dict(type='InfiniteGroupEachSampleInBatchSampler'),\n    nonshuffler_sampler=dict(type='DistributedSampler'))\nevaluation = dict(\n    interval=24,\n    pipeline=[\n        dict(\n            type='LoadPointsFromFile',\n            coord_type='LIDAR',\n            load_dim=5,\n            use_dim=5,\n            file_client_args=dict(backend='disk')),\n        dict(\n            type='LoadPointsFromMultiSweeps',\n            sweeps_num=10,\n            file_client_args=dict(backend='disk')),\n        dict(\n            type='DefaultFormatBundle3D',\n            class_names=[\n                'car', 'truck', 'trailer', 'bus', 'construction_vehicle',\n                'bicycle', 'motorcycle', 'pedestrian', 'traffic_cone',\n                'barrier'\n            ],\n            with_label=False),\n        dict(type='Collect3D', keys=['points'])\n    ])\ncheckpoint_config = dict(interval=1)\nlog_config = dict(\n    interval=50,\n    hooks=[dict(type='TextLoggerHook'),\n           dict(type='TensorboardLoggerHook')])\ndist_params = dict(backend='nccl')\nlog_level = 'INFO'\nwork_dir = './work_dirs/drivetransformer_goalpoint_1gpu'\nload_from = None\nresume_from = None\nworkflow = [('train', 1)]\nplugin = True\nplugin_dir = 'adzoo/drivetransformer/mmdet3d_plugin/'\nvoxel_size = [0.15, 0.15, 4]\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)\nNameMapping = dict({\n    'vehicle.bh.crossbike':\n    'bicycle',\n    'vehicle.diamondback.century':\n    'bicycle',\n    'vehicle.gazelle.omafiets':\n    'bicycle',\n    'vehicle.audi.etron':\n    'car',\n    'vehicle.chevrolet.impala':\n    'car',\n    'vehicle.dodge.charger_2020':\n    'car',\n    'vehicle.dodge.charger_police':\n    'car',\n    'vehicle.dodge.charger_police_2020':\n    'car',\n    'vehicle.lincoln.mkz_2017':\n    'car',\n    'vehicle.lincoln.mkz_2020':\n    'car',\n    'vehicle.mini.cooper_s_2021':\n    'car',\n    'vehicle.mercedes.coupe_2020':\n    'car',\n    'vehicle.ford.mustang':\n    'car',\n    'vehicle.nissan.patrol_2021':\n    'car',\n    'vehicle.audi.tt':\n    'car',\n    'vehicle.ford.crown':\n    'car',\n    'vehicle.tesla.model3':\n    'car',\n    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/FordCrown/SM_FordCrown_parked.SM_FordCrown_parked':\n    'car',\n    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Charger/SM_ChargerParked.SM_ChargerParked':\n    'car',\n    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Lincoln/SM_LincolnParked.SM_LincolnParked':\n    'car',\n    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/MercedesCCC/SM_MercedesCCC_Parked.SM_MercedesCCC_Parked':\n    'car',\n    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Mini2021/SM_Mini2021_parked.SM_Mini2021_parked':\n    'car',\n    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/NissanPatrol2021/SM_NissanPatrol2021_parked.SM_NissanPatrol2021_parked':\n    'car',\n    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/TeslaM3/SM_TeslaM3_parked.SM_TeslaM3_parked':\n    'car',\n    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/VolkswagenT2/SM_VolkswagenT2_2021_Parked.SM_VolkswagenT2_2021_Parked':\n    'van',\n    'vehicle.ford.ambulance':\n    'van',\n    'vehicle.carlamotors.firetruck':\n    'truck',\n    'traffic.speed_limit.30':\n    'traffic_sign',\n    'traffic.speed_limit.40':\n    'traffic_sign',\n    'traffic.speed_limit.50':\n    'traffic_sign',\n    'traffic.speed_limit.60':\n    'traffic_sign',\n    'traffic.speed_limit.90':\n    'traffic_sign',\n    'traffic.speed_limit.120':\n    'traffic_sign',\n    'traffic.stop':\n    'traffic_sign',\n    'traffic.yield':\n    'traffic_sign',\n    'traffic.traffic_light':\n    'traffic_light',\n    'static.prop.warningconstruction':\n    'traffic_cone',\n    'static.prop.warningaccident':\n    'traffic_cone',\n    'static.prop.trafficwarning':\n    'traffic_cone',\n    'static.prop.constructioncone':\n    'traffic_cone',\n    'walker.pedestrian.0001':\n    'pedestrian',\n    'walker.pedestrian.0003':\n    'pedestrian',\n    'walker.pedestrian.0004':\n    'pedestrian',\n    'walker.pedestrian.0005':\n    'pedestrian',\n    'walker.pedestrian.0007':\n    'pedestrian',\n    'walker.pedestrian.0010':\n    'pedestrian',\n    'walker.pedestrian.0013':\n    'pedestrian',\n    'walker.pedestrian.0014':\n    'pedestrian',\n    'walker.pedestrian.0015':\n    'pedestrian',\n    'walker.pedestrian.0016':\n    'pedestrian',\n    'walker.pedestrian.0017':\n    'pedestrian',\n    'walker.pedestrian.0018':\n    'pedestrian',\n    'walker.pedestrian.0019':\n    'pedestrian',\n    'walker.pedestrian.0020':\n    'pedestrian',\n    'walker.pedestrian.0021':\n    'pedestrian',\n    'walker.pedestrian.0022':\n    'pedestrian',\n    'walker.pedestrian.0025':\n    'pedestrian',\n    'walker.pedestrian.0027':\n    'pedestrian',\n    'walker.pedestrian.0030':\n    'pedestrian',\n    'walker.pedestrian.0031':\n    'pedestrian',\n    'walker.pedestrian.0032':\n    'pedestrian',\n    'walker.pedestrian.0034':\n    'pedestrian',\n    'walker.pedestrian.0035':\n    'pedestrian',\n    'walker.pedestrian.0041':\n    'pedestrian',\n    'walker.pedestrian.0042':\n    'pedestrian',\n    'walker.pedestrian.0046':\n    'pedestrian',\n    'walker.pedestrian.0047':\n    'pedestrian',\n    'static.prop.dirtdebris01':\n    'others',\n    'static.prop.dirtdebris02':\n    'others'\n})\ncollect_keys = [\n    'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp', 'ego_pose',\n    'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes', 'ego_fut_classes'\n]\nnum_classes = 9\nmap_classes = [\n    'Broken', 'Solid', 'SolidSolid', 'Center', 'TrafficLight', 'StopSign'\n]\nmap_fixed_ptsnum_per_gt_line = 20\nmap_fixed_ptsnum_per_pred_line = 20\nmap_eval_use_same_gt_sample_num_flag = True\nmap_num_classes = 6\nagent_query_num_vec = 900\nagent_num_topk_sift = 900\nagent_num_propagated = 50\nmap_query_num_vec = 100\nmap_num_topk_sift = 100\nmap_num_propagated = 50\nmemory_len_frame = 10\nnum_mode = 6\nnum_gpus = 1\nbatch_size = 6\nnum_iters_per_epoch = 1041\ndata_aug_conf = dict(\n    resize_lim=(0.64, 0.69),\n    final_dim=(384, 1056),\n    bot_pct_lim=(0.0, 0.0),\n    rot_lim=(-5.4, 5.4),\n    H=900,\n    W=1600,\n    rand_flip=True,\n    rot3d_range=[0, 0])\n_dim_ = 512\nqueue_length = 1\ntotal_epochs = 24\ndropout = 0.1\nmodel = dict(\n    type='DriveTransformer',\n    use_grid_mask=False,\n    pretrained=dict(img='./ckpts/resnet50-19c8e357.pth'),\n    img_backbone=dict(\n        type='ResNet',\n        depth=50,\n        num_stages=4,\n        out_indices=(3, ),\n        frozen_stages=1,\n        norm_cfg=dict(type='BN', requires_grad=False),\n        norm_eval=True,\n        style='pytorch'),\n    img_neck=dict(\n        type='FPN',\n        in_channels=[2048],\n        out_channels=512,\n        start_level=0,\n        add_extra_convs='on_output',\n        num_outs=1,\n        relu_before_extra_convs=True),\n    pts_bbox_head=dict(\n        type='DriveTransformerlHead',\n        ego_lcf_feat_idx=[0, 1, 2, 3, 4, 5, 6, 7, 8],\n        ego_command_dim=128,\n        img_stride=32,\n        embed_dims=512,\n        num_reg_fcs=2,\n        num_cls_fcs=2,\n        agent_num_propagated=50,\n        map_num_propagated=50,\n        memory_len_frame=10,\n        agent_num_query=900,\n        agent_num_query_sifted=900,\n        fut_mode=6,\n        fut_ego_mode=1,\n        fut_ts=6,\n        fut_ego_fix_dist=True,\n        fut_ts_ego_fix_dist=20,\n        fut_ts_ego_fix_time=30,\n        num_classes=9,\n        code_size=10,\n        map_num_query=100,\n        map_num_query_sifted=100,\n        map_num_classes=6,\n        map_num_pts_per_vec=20,\n        map_num_pts_per_gt_vec=20,\n        map_query_embed_type='instance_pts',\n        map_transform_method='minmax',\n        map_gt_shift_pts_pattern='v2',\n        map_dir_interval=1,\n        map_code_size=2,\n        map_code_weights=[1.0, 1.0, 1.0, 1.0],\n        sync_cls_avg_factor=True,\n        with_box_refine=True,\n        LID=True,\n        with_ego_pos=True,\n        position_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n        depth_start=1,\n        depth_step=0.8,\n        depth_num=64,\n        agent_prep_decoder=dict(\n            type='DriveTransformerPreDecoder',\n            num_layers=1,\n            return_intermediate=False,\n            transformerlayers=dict(\n                type='DriveTransformerPreDecoderLayer',\n                attn_cfgs=[\n                    dict(\n                        type='AttentionLayer',\n                        embed_dims=512,\n                        head_dim=64,\n                        attn_drop=0.1),\n                    dict(\n                        type='AttentionLayer',\n                        embed_dims=512,\n                        head_dim=64,\n                        attn_drop=0.1)\n                ],\n                ffn_cfgs=dict(\n                    type='SwiGLULayer',\n                    embed_dims=512,\n                    feedforward_channels=2048,\n                    ffn_drop=0.1),\n                with_cp=False,\n                operation_order=('cross_attn', 'norm', 'self_attn', 'norm',\n                                 'ffn', 'norm'))),\n        map_prep_decoder=dict(\n            type='DriveTransformerPreDecoder',\n            num_layers=1,\n            return_intermediate=False,\n            transformerlayers=dict(\n                type='DriveTransformerPreDecoderLayer',\n                attn_cfgs=[\n                    dict(\n                        type='AttentionLayer',\n                        embed_dims=512,\n                        head_dim=64,\n                        attn_drop=0.1),\n                    dict(\n                        type='AttentionLayer',\n                        embed_dims=512,\n                        head_dim=64,\n                        attn_drop=0.1)\n                ],\n                ffn_cfgs=dict(\n                    type='SwiGLULayer',\n                    embed_dims=512,\n                    feedforward_channels=2048,\n                    ffn_drop=0.1),\n                with_cp=False,\n                operation_order=('cross_attn', 'norm', 'self_attn', 'norm',\n                                 'ffn', 'norm'))),\n        transformer=dict(\n            type='DriveTransformerWrapper',\n            embed_dims=512,\n            decoder=dict(\n                type='DriveTransformerDecoder',\n                num_layers=6,\n                fut_mode=6,\n                agent_num_query=900,\n                map_num_query=100,\n                map_num_pts_per_vec=20,\n                return_intermediate=True,\n                embed_dims=512,\n                refine=True,\n                transformerlayers=dict(\n                    type='DriveTransformerDecoderLayer',\n                    agent_query_num=900,\n                    map_query_num=100,\n                    memory_len_frame=10,\n                    agent_num_propagated=50,\n                    map_num_propagated=50,\n                    map_pts_per_vec=20,\n                    feedforward_channels=2048,\n                    ffn_dropout=0.1,\n                    with_cp=False,\n                    attn_cfgs=[\n                        dict(\n                            type='AttentionLayer',\n                            embed_dims=512,\n                            head_dim=64,\n                            attn_drop=0.1,\n                            layer_scale=0.01),\n                        dict(\n                            type='AttentionLayer',\n                            embed_dims=512,\n                            head_dim=64,\n                            attn_drop=0.1,\n                            layer_scale=0.01),\n                        dict(\n                            type='AttentionLayer',\n                            embed_dims=512,\n                            head_dim=64,\n                            attn_drop=0.1,\n                            no_wq=True)\n                    ],\n                    ffn_cfgs=dict(\n                        type='SwiGLULayer',\n                        embed_dims=512,\n                        feedforward_channels=2048,\n                        ffn_drop=0.1),\n                    operation_order=('task_self_attn', 'norm',\n                                     'temporal_cross_attn', 'norm',\n                                     'sensor_cross_attn', 'norm', 'ffn',\n                                     'norm')))),\n        bbox_coder=dict(\n            type='CustomNMSFreeCoder',\n            post_center_range=[-20, -35, -10.0, 20, 35, 10.0],\n            pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n            max_num=100,\n            voxel_size=[0.15, 0.15, 4],\n            num_classes=9),\n        loss_cls=dict(\n            type='FocalLoss',\n            use_sigmoid=True,\n            gamma=2.0,\n            alpha=0.25,\n            loss_weight=2.0),\n        loss_bbox=dict(type='L1Loss', loss_weight=0.25),\n        loss_traj=dict(type='L1Loss', loss_weight=0.2),\n        loss_traj_cls=dict(\n            type='FocalLoss',\n            use_sigmoid=True,\n            gamma=2.0,\n            alpha=0.5,\n            loss_weight=0.2),\n        map_bbox_coder=dict(\n            type='MapNMSFreeCoder',\n            post_center_range=[-20, -35, -20, -35, 20, 35, 20, 35],\n            pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n            max_num=50,\n            voxel_size=[0.15, 0.15, 4],\n            num_classes=6),\n        loss_map_cls=dict(\n            type='FocalLoss',\n            use_sigmoid=True,\n            gamma=2.0,\n            alpha=0.25,\n            loss_weight=2.0),\n        loss_map_pts=dict(type='PtsL1Loss', loss_weight=1.0),\n        loss_map_dir=dict(type='PtsDirCosLoss', loss_weight=0.005),\n        loss_plan_reg_fix_time=dict(type='L1Loss', loss_weight=3.5),\n        loss_plan_reg_fix_dist=dict(type='L1Loss', loss_weight=10.0),\n        loss_plan_cls=dict(\n            type='FocalLoss',\n            use_sigmoid=True,\n            gamma=4.0,\n            alpha=0.5,\n            loss_weight=20.0)),\n    train_cfg=dict(\n        pts=dict(\n            grid_size=[512, 512, 1],\n            voxel_size=[0.15, 0.15, 4],\n            point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],\n            out_size_factor=4,\n            assigner=dict(\n                type='HungarianAssigner3D',\n                cls_cost=dict(\n                    type='FocalLossCost', weight=2.0, gamma=2.0, alpha=0.25),\n                reg_cost=dict(type='BBox3DL1Cost', weight=0.25),\n                iou_cost=dict(type='IoUCost', weight=0.0),\n                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),\n            map_assigner=dict(\n                type='MapHungarianAssigner3D',\n                cls_cost=dict(\n                    type='FocalLossCost', weight=2.0, gamma=2.0, alpha=0.25),\n                reg_cost=dict(\n                    type='BBoxL1Cost', weight=0.0, box_format='xywh'),\n                iou_cost=dict(type='IoUCost', iou_mode='giou', weight=0.0),\n                pts_cost=dict(type='OrderedPtsL1Cost', weight=1.0),\n                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]))))\ninfo_root = 'data/infos'\nmap_root = 'data/bench2drive/maps'\nmap_file = 'data/infos/b2d_map_infos.pkl'\nann_file_train = 'data/infos/b2d_infos_v1_train_drivetransformer_meta.pkl'\nann_file_val = 'data/infos/b2d_infos_v1_val_drivetransformer_meta.pkl'\nann_file_test = 'data/infos/b2d_infos_v1_val_drivetransformer_meta.pkl'\noptimizer = dict(type='AdamW', lr=0.0001, weight_decay=0.01)\noptimizer_config = dict(\n    grad_clip=dict(max_norm=35, norm_type=2),\n    type='GradientCumulativeFp16OptimizerHook',\n    cumulative_iters=32)\nlr_config = dict(\n    policy='CosineAnnealing',\n    warmup='linear',\n    warmup_iters=1000,\n    warmup_ratio=0.1,\n    min_lr_ratio=0.01)\nrunner = dict(type='EpochBasedRunner', max_epochs=24)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 32\ngpu_ids = range(0, 1)\n", "CLASSES": ["car", "van", "truck", "bicycle", "traffic_sign", "traffic_cone", "traffic_light", "pedestrian", "others"], "PALETTE": null, "env_info": "MMCV: 0.0.1", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py", "fp16": {"loss_scaler": {"scale": 512.0, "growth_factor": 2.0, "backoff_factor": 0.5, "growth_interval": 2000, "_growth_tracker": 0}}, "epoch": 6, "iter": 237168, "time": "Thu Feb 26 07:15:52 2026", "hook_msgs": {"last_ckpt": "/home/Humble/Humble/EndtoEnd/Bench2DriveZoo/work_dirs/drivetransformer_goalpoint_1gpu/epoch_5.pth"}}
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