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@@ -34,3 +34,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 GenAD/no_hlc/20260213_082314.log.json filter=lfs diff=lfs merge=lfs -text
+DriveTransformer/goalpoint_1gpu/20260224_021525.log.json filter=lfs diff=lfs merge=lfs -text
+DriveTransformer/goalpoint_1gpu/20260302_071515.log filter=lfs diff=lfs merge=lfs -text
+DriveTransformer/goalpoint_1gpu/20260302_071515.log.json filter=lfs diff=lfs merge=lfs -text
+DriveTransformer/goalpoint_1gpu/train.log filter=lfs diff=lfs merge=lfs -text

DriveTransformer/goalpoint_1gpu/20260223_225608.log.json

@@ -0,0 +1 @@
+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}

DriveTransformer/goalpoint_1gpu/20260223_230843.log.json

@@ -0,0 +1 @@
+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}

DriveTransformer/goalpoint_1gpu/20260223_230908.log.json

@@ -0,0 +1 @@
+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}

DriveTransformer/goalpoint_1gpu/20260223_231013.log.json

@@ -0,0 +1 @@
+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}

DriveTransformer/goalpoint_1gpu/20260223_231057.log.json

@@ -0,0 +1 @@
+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}

DriveTransformer/goalpoint_1gpu/20260223_231151.log.json

@@ -0,0 +1 @@
+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}

DriveTransformer/goalpoint_1gpu/20260224_001423.log.json

@@ -0,0 +1,14 @@
+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}
+{"mode": "train", "epoch": 1, "iter": 50, "lr": 1e-05, "memory": 7284, "data_time": 0.12848, "loss_cls": 657.01774, "loss_bbox": 1.71262, "loss_traj": 4.03309, "loss_traj_cls": 0.09856, "loss_map_cls": 9.20249, "loss_map_pts": 5.19802, "loss_map_dir": 0.09459, "d0.loss_plan_l1_fix_time": 9.30642, "d0.loss_plan_l1_fix_dist": 3.13849, "d1.loss_plan_l1_fix_time": 9.75044, "d1.loss_plan_l1_fix_dist": 4.08195, "d2.loss_plan_l1_fix_time": 10.25692, "d2.loss_plan_l1_fix_dist": 5.54673, "d3.loss_plan_l1_fix_time": 10.84514, "d3.loss_plan_l1_fix_dist": 7.28534, "d4.loss_plan_l1_fix_time": 11.37837, "d4.loss_plan_l1_fix_dist": 9.82072, "d5.loss_plan_l1_fix_time": 11.97453, "d5.loss_plan_l1_fix_dist": 12.47565, "d6.loss_plan_l1_fix_time": 12.55222, "d6.loss_plan_l1_fix_dist": 14.96, "d0.loss_cls_all": 450.47849, "d0.loss_bbox_all": 1.63607, "d0.loss_cls": 450.47849, "d0.loss_bbox": 1.63607, "d1.loss_cls": 498.76385, "d1.loss_bbox": 1.61268, "d2.loss_cls": 493.99471, "d2.loss_bbox": 1.67709, "d3.loss_cls": 564.47956, "d3.loss_bbox": 1.67152, "d4.loss_cls": 529.9633, "d4.loss_bbox": 1.62845, "d5.loss_cls": 598.15416, "d5.loss_bbox": 1.71292, "d0.loss_traj_cls": 0.07253, "d0.loss_traj": 4.01002, "d1.loss_traj_cls": 0.06156, "d1.loss_traj": 4.0386, "d2.loss_traj_cls": 0.06451, "d2.loss_traj": 4.12676, "d3.loss_traj_cls": 0.11037, "d3.loss_traj": 4.09757, "d4.loss_traj_cls": 0.05513, "d4.loss_traj": 3.97019, "d5.loss_traj_cls": 0.06038, "d5.loss_traj": 4.01782, "d0.loss_map_cls_all": 6.96779, "d0.loss_map_pts_all": 4.86052, "d0.loss_map_dir_all": 0.09483, "d0.loss_map_cls": 6.96779, "d0.loss_map_pts": 4.86052, "d0.loss_map_dir": 0.09483, "d1.loss_map_cls": 6.28808, "d1.loss_map_pts": 4.89425, "d1.loss_map_dir": 0.09464, "d2.loss_map_cls": 6.99186, "d2.loss_map_pts": 4.94063, "d2.loss_map_dir": 0.09435, "d3.loss_map_cls": 9.52936, "d3.loss_map_pts": 4.97997, "d3.loss_map_dir": 0.09452, "d4.loss_map_cls": 9.53639, "d4.loss_map_pts": 5.04683, "d4.loss_map_dir": 0.09459, "d5.loss_map_cls": 9.54202, "d5.loss_map_pts": 5.12155, "d5.loss_map_dir": 0.09466, "loss": 4524.49282, "time": 0.74045}
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DriveTransformer/goalpoint_1gpu/20260224_002002.log.json

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+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}

DriveTransformer/goalpoint_1gpu/20260224_002248.log.json

@@ -0,0 +1,8 @@
+{"env_info": "MMCV: 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=2,\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=3,\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=3,\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=3,\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 = 2\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 = 60\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=96)\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=60)\nfp16 = dict(loss_scale=512.0)\nfind_unused_parameters = True\ncustom_hooks = [dict(type='CustomSetEpochInfoHook')]\ncumulative_iters = 96\ngpu_ids = range(0, 1)\n", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}
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DriveTransformer/goalpoint_1gpu/20260224_021525.log.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c15b908c1768e57b469d1161d31a35e8489616a0a419072f6879f753d8a072ac
+size 10949303

DriveTransformer/goalpoint_1gpu/20260226_120012.log.json

@@ -0,0 +1,22 @@
+{"env_info": "MMCV: 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", "seed": 0, "exp_name": "drivetransformer_goalpoint_1gpu.py"}
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DriveTransformer/goalpoint_1gpu/20260226_131720.log.json

@@ -0,0 +1,19 @@
+{"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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+{"mode": "train", "epoch": 7, "iter": 800, "lr": 9e-05, "memory": 19865, "data_time": 0.03361, "loss_cls": 0.19547, "loss_bbox": 0.38967, "loss_traj": 0.61685, "loss_traj_cls": 0.00112, "loss_map_cls": 0.14804, "loss_map_pts": 0.70303, "loss_map_dir": 0.01204, "d0.loss_plan_l1_fix_time": 2.84766, "d0.loss_plan_l1_fix_dist": 0.475, "d1.loss_plan_l1_fix_time": 1.21864, "d1.loss_plan_l1_fix_dist": 0.20782, "d2.loss_plan_l1_fix_time": 1.20705, "d2.loss_plan_l1_fix_dist": 0.20468, "d3.loss_plan_l1_fix_time": 1.20526, "d3.loss_plan_l1_fix_dist": 0.21168, "d4.loss_plan_l1_fix_time": 1.20922, "d4.loss_plan_l1_fix_dist": 0.22302, "d5.loss_plan_l1_fix_time": 1.21408, "d5.loss_plan_l1_fix_dist": 0.23909, "d6.loss_plan_l1_fix_time": 1.21915, "d6.loss_plan_l1_fix_dist": 0.25869, "d0.loss_cls_all": 0.23764, "d0.loss_bbox_all": 0.45771, "d0.loss_cls": 0.23764, "d0.loss_bbox": 0.45771, "d1.loss_cls": 0.2249, "d1.loss_bbox": 0.42141, "d2.loss_cls": 0.21083, "d2.loss_bbox": 0.40158, "d3.loss_cls": 0.19967, "d3.loss_bbox": 0.39451, "d4.loss_cls": 0.19587, "d4.loss_bbox": 0.3888, "d5.loss_cls": 0.19467, "d5.loss_bbox": 0.38874, "d0.loss_traj_cls": 0.00011, "d0.loss_traj": 0.76496, "d1.loss_traj_cls": 0.00118, "d1.loss_traj": 0.66019, "d2.loss_traj_cls": 0.00181, "d2.loss_traj": 0.63173, "d3.loss_traj_cls": 0.00123, "d3.loss_traj": 0.62384, "d4.loss_traj_cls": 0.00126, "d4.loss_traj": 0.61858, "d5.loss_traj_cls": 0.00148, "d5.loss_traj": 0.61502, "d0.loss_map_cls_all": 0.21674, "d0.loss_map_pts_all": 1.47022, "d0.loss_map_dir_all": 0.01105, "d0.loss_map_cls": 0.21674, "d0.loss_map_pts": 1.47022, "d0.loss_map_dir": 0.01105, "d1.loss_map_cls": 0.18406, "d1.loss_map_pts": 0.98575, "d1.loss_map_dir": 0.01095, "d2.loss_map_cls": 0.16734, "d2.loss_map_pts": 0.79919, "d2.loss_map_dir": 0.01129, "d3.loss_map_cls": 0.16084, "d3.loss_map_pts": 0.73404, "d3.loss_map_dir": 0.01169, "d4.loss_map_cls": 0.1534, "d4.loss_map_pts": 0.71034, "d4.loss_map_dir": 0.01185, "d5.loss_map_cls": 0.14987, "d5.loss_map_pts": 0.70468, "d5.loss_map_dir": 0.012, "loss": 30.54368, "time": 0.77089, "grad_norm": 180.30732}
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+{"mode": "train", "epoch": 7, "iter": 900, "lr": 9e-05, "memory": 19865, "data_time": 0.03246, "loss_cls": 0.16039, "loss_bbox": 0.3351, "loss_traj": 0.5567, "loss_traj_cls": 0.00108, "loss_map_cls": 0.14605, "loss_map_pts": 0.68309, "loss_map_dir": 0.00984, "d0.loss_plan_l1_fix_time": 2.49499, "d0.loss_plan_l1_fix_dist": 0.40676, "d1.loss_plan_l1_fix_time": 1.09737, "d1.loss_plan_l1_fix_dist": 0.17121, "d2.loss_plan_l1_fix_time": 1.07587, "d2.loss_plan_l1_fix_dist": 0.18112, "d3.loss_plan_l1_fix_time": 1.0743, "d3.loss_plan_l1_fix_dist": 0.1971, "d4.loss_plan_l1_fix_time": 1.07783, "d4.loss_plan_l1_fix_dist": 0.2112, "d5.loss_plan_l1_fix_time": 1.08162, "d5.loss_plan_l1_fix_dist": 0.22237, "d6.loss_plan_l1_fix_time": 1.08632, "d6.loss_plan_l1_fix_dist": 0.2343, "d0.loss_cls_all": 0.19347, "d0.loss_bbox_all": 0.39423, "d0.loss_cls": 0.19347, "d0.loss_bbox": 0.39423, "d1.loss_cls": 0.18535, "d1.loss_bbox": 0.36137, "d2.loss_cls": 0.17396, "d2.loss_bbox": 0.34391, "d3.loss_cls": 0.16563, "d3.loss_bbox": 0.33745, "d4.loss_cls": 0.16011, "d4.loss_bbox": 0.33539, "d5.loss_cls": 0.16064, "d5.loss_bbox": 0.33396, "d0.loss_traj_cls": 9e-05, "d0.loss_traj": 0.7302, "d1.loss_traj_cls": 0.00116, "d1.loss_traj": 0.62254, "d2.loss_traj_cls": 0.00177, "d2.loss_traj": 0.57892, "d3.loss_traj_cls": 0.0012, "d3.loss_traj": 0.5673, "d4.loss_traj_cls": 0.00122, "d4.loss_traj": 0.55767, "d5.loss_traj_cls": 0.00141, "d5.loss_traj": 0.55469, "d0.loss_map_cls_all": 0.21249, "d0.loss_map_pts_all": 1.38512, "d0.loss_map_dir_all": 0.00968, "d0.loss_map_cls": 0.21249, "d0.loss_map_pts": 1.38512, "d0.loss_map_dir": 0.00968, "d1.loss_map_cls": 0.18423, "d1.loss_map_pts": 0.94759, "d1.loss_map_dir": 0.00935, "d2.loss_map_cls": 0.16847, "d2.loss_map_pts": 0.77617, "d2.loss_map_dir": 0.00946, "d3.loss_map_cls": 0.16015, "d3.loss_map_pts": 0.71481, "d3.loss_map_dir": 0.0096, "d4.loss_map_cls": 0.1524, "d4.loss_map_pts": 0.6901, "d4.loss_map_dir": 0.00972, "d5.loss_map_cls": 0.14815, "d5.loss_map_pts": 0.68309, "d5.loss_map_dir": 0.00972, "loss": 27.74352, "time": 0.74757, "grad_norm": 173.70888}

DriveTransformer/goalpoint_1gpu/20260302_065826.log.json

@@ -0,0 +1 @@
+{"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": 9, "iter": 355752, "time": "Sat Feb 28 10:41:11 2026", "hook_msgs": {"last_ckpt": "/home/Humble/Humble/EndtoEnd/Bench2DriveZoo/work_dirs/drivetransformer_goalpoint_1gpu/epoch_8.pth"}}

DriveTransformer/goalpoint_1gpu/20260302_071228.log.json

@@ -0,0 +1 @@
+{"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": 9, "iter": 355752, "time": "Sat Feb 28 10:41:11 2026", "hook_msgs": {"last_ckpt": "/home/Humble/Humble/EndtoEnd/Bench2DriveZoo/work_dirs/drivetransformer_goalpoint_1gpu/epoch_8.pth"}}

DriveTransformer/goalpoint_1gpu/20260302_071328.log.json

@@ -0,0 +1,2 @@
+{"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": 9, "iter": 355752, "time": "Sat Feb 28 10:41:11 2026", "hook_msgs": {"last_ckpt": "/home/Humble/Humble/EndtoEnd/Bench2DriveZoo/work_dirs/drivetransformer_goalpoint_1gpu/epoch_8.pth"}}
+{"mode": "train", "epoch": 10, "iter": 50, "lr": 7e-05, "memory": 19862, "data_time": 0.20962, "loss_cls": 0.11593, "loss_bbox": 0.3072, "loss_traj": 0.48392, "loss_traj_cls": 0.00202, "loss_map_cls": 0.12882, "loss_map_pts": 0.5999, "loss_map_dir": 0.007, "d0.loss_plan_l1_fix_time": 2.47242, "d0.loss_plan_l1_fix_dist": 0.37871, "d1.loss_plan_l1_fix_time": 0.86071, "d1.loss_plan_l1_fix_dist": 0.26848, "d2.loss_plan_l1_fix_time": 0.84022, "d2.loss_plan_l1_fix_dist": 0.21882, "d3.loss_plan_l1_fix_time": 0.83621, "d3.loss_plan_l1_fix_dist": 0.22214, "d4.loss_plan_l1_fix_time": 0.83909, "d4.loss_plan_l1_fix_dist": 0.20819, "d5.loss_plan_l1_fix_time": 0.84314, "d5.loss_plan_l1_fix_dist": 0.2493, "d6.loss_plan_l1_fix_time": 0.848, "d6.loss_plan_l1_fix_dist": 0.24196, "d0.loss_cls_all": 0.15553, "d0.loss_bbox_all": 0.37036, "d0.loss_cls": 0.15553, "d0.loss_bbox": 0.37036, "d1.loss_cls": 0.15043, "d1.loss_bbox": 0.33398, "d2.loss_cls": 0.14139, "d2.loss_bbox": 0.31416, "d3.loss_cls": 0.12609, "d3.loss_bbox": 0.30862, "d4.loss_cls": 0.11872, "d4.loss_bbox": 0.30886, "d5.loss_cls": 0.11713, "d5.loss_bbox": 0.30684, "d0.loss_traj_cls": 6e-05, "d0.loss_traj": 0.66307, "d1.loss_traj_cls": 0.00068, "d1.loss_traj": 0.55593, "d2.loss_traj_cls": 0.00089, "d2.loss_traj": 0.5135, "d3.loss_traj_cls": 0.0007, "d3.loss_traj": 0.49472, "d4.loss_traj_cls": 0.00086, "d4.loss_traj": 0.48748, "d5.loss_traj_cls": 0.00128, "d5.loss_traj": 0.48489, "d0.loss_map_cls_all": 0.21055, "d0.loss_map_pts_all": 1.20573, "d0.loss_map_dir_all": 0.00707, "d0.loss_map_cls": 0.21055, "d0.loss_map_pts": 1.20573, "d0.loss_map_dir": 0.00707, "d1.loss_map_cls": 0.17551, "d1.loss_map_pts": 0.86448, "d1.loss_map_dir": 0.00655, "d2.loss_map_cls": 0.15283, "d2.loss_map_pts": 0.70237, "d2.loss_map_dir": 0.00625, "d3.loss_map_cls": 0.14241, "d3.loss_map_pts": 0.63954, "d3.loss_map_dir": 0.00655, "d4.loss_map_cls": 0.13809, "d4.loss_map_pts": 0.61283, "d4.loss_map_dir": 0.00681, "d5.loss_map_cls": 0.13153, "d5.loss_map_pts": 0.60017, "d5.loss_map_dir": 0.00702, "loss": 24.49393, "time": 1.08184, "grad_norm": 89.64458}

DriveTransformer/goalpoint_1gpu/20260302_071515.log

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+oid sha256:a40e899338cc7bafc4df9e36f9b7d9b3410c9dde8740badc90a2364f27458737
+size 18492763

DriveTransformer/goalpoint_1gpu/20260302_071515.log.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:64c1a029f6c13edf4e5c2be107abe85684617482aacad06a98e77a47b76121b4
+size 19951009

DriveTransformer/goalpoint_1gpu/drivetransformer_goalpoint_1gpu.py

@@ -0,0 +1,1327 @@
+point_cloud_range = [-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]
+class_names = [
+    'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',
+    'traffic_light', 'pedestrian', 'others'
+]
+dataset_type = 'B2D_DriveTransformer_GoalPoint_Dataset'
+data_root = 'data/bench2drive'
+input_modality = dict(
+    use_lidar=False,
+    use_camera=True,
+    use_radar=False,
+    use_map=False,
+    use_external=True)
+file_client_args = dict(backend='disk')
+train_pipeline = [
+    dict(type='LoadMultiViewImageFromFiles', to_float32=True),
+    dict(type='ResizeCropFlipImage'),
+    dict(
+        type='NormalizeMultiviewImage',
+        mean=[123.675, 116.28, 103.53],
+        std=[58.395, 57.12, 57.375],
+        to_rgb=True),
+    dict(
+        type='LoadAnnotations3D',
+        with_bbox_3d=True,
+        with_label_3d=True,
+        with_attr_label=True),
+    dict(
+        type='CustomObjectRangeFilter',
+        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),
+    dict(
+        type='CustomObjectNameFilter',
+        classes=[
+            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',
+            'traffic_light', 'pedestrian', 'others'
+        ]),
+    dict(
+        type='TrajPreprocess',
+        pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+        with_ego_fix_dist=True,
+        ego_fut_offset_input=False,
+        assign_class_for_ego=False),
+    dict(
+        type='CustomFormatBundle3D',
+        class_names=[
+            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',
+            'traffic_light', 'pedestrian', 'others'
+        ],
+        with_ego=True,
+        collect_keys=[
+            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',
+            'ego_fut_classes'
+        ]),
+    dict(
+        type='CustomCollect3D',
+        keys=[
+            'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',
+            'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',
+            'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',
+            'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist', 'ego_fut_cmd',
+            'ego_lcf_feat', 'gt_attr_labels', 'prev_exists', 'index',
+            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',
+            'ego_fut_classes'
+        ])
+]
+test_pipeline = [
+    dict(type='LoadMultiViewImageFromFiles', to_float32=True),
+    dict(type='ResizeCropFlipImage'),
+    dict(
+        type='NormalizeMultiviewImage',
+        mean=[123.675, 116.28, 103.53],
+        std=[58.395, 57.12, 57.375],
+        to_rgb=True),
+    dict(
+        type='LoadAnnotations3D',
+        with_bbox_3d=True,
+        with_label_3d=True,
+        with_attr_label=True),
+    dict(
+        type='CustomObjectRangeFilter',
+        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),
+    dict(
+        type='CustomObjectNameFilter',
+        classes=[
+            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',
+            'traffic_light', 'pedestrian', 'others'
+        ]),
+    dict(
+        type='TrajPreprocess',
+        pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+        with_ego_fix_dist=True,
+        ego_fut_offset_input=False,
+        assign_class_for_ego=False),
+    dict(
+        type='CustomFormatBundle3D',
+        class_names=[
+            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',
+            'traffic_light', 'pedestrian', 'others'
+        ],
+        with_ego=True,
+        collect_keys=[
+            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',
+            'ego_fut_classes'
+        ]),
+    dict(
+        type='CustomCollect3D',
+        keys=[
+            'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',
+            'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',
+            'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',
+            'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist', 'ego_fut_cmd',
+            'ego_lcf_feat', 'gt_attr_labels', 'prev_exists', 'index',
+            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',
+            'ego_fut_classes'
+        ])
+]
+eval_pipeline = [
+    dict(
+        type='LoadPointsFromFile',
+        coord_type='LIDAR',
+        load_dim=5,
+        use_dim=5,
+        file_client_args=dict(backend='disk')),
+    dict(
+        type='LoadPointsFromMultiSweeps',
+        sweeps_num=10,
+        file_client_args=dict(backend='disk')),
+    dict(
+        type='DefaultFormatBundle3D',
+        class_names=[
+            'car', 'truck', 'trailer', 'bus', 'construction_vehicle',
+            'bicycle', 'motorcycle', 'pedestrian', 'traffic_cone', 'barrier'
+        ],
+        with_label=False),
+    dict(type='Collect3D', keys=['points'])
+]
+data = dict(
+    samples_per_gpu=6,
+    workers_per_gpu=8,
+    train=dict(
+        type='B2D_DriveTransformer_GoalPoint_Dataset',
+        data_root='data/bench2drive',
+        ann_file='data/infos/b2d_infos_v1_train_drivetransformer_meta.pkl',
+        pipeline=[
+            dict(type='LoadMultiViewImageFromFiles', to_float32=True),
+            dict(type='ResizeCropFlipImage'),
+            dict(
+                type='NormalizeMultiviewImage',
+                mean=[123.675, 116.28, 103.53],
+                std=[58.395, 57.12, 57.375],
+                to_rgb=True),
+            dict(
+                type='LoadAnnotations3D',
+                with_bbox_3d=True,
+                with_label_3d=True,
+                with_attr_label=True),
+            dict(
+                type='CustomObjectRangeFilter',
+                point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),
+            dict(
+                type='CustomObjectNameFilter',
+                classes=[
+                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',
+                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'
+                ]),
+            dict(
+                type='TrajPreprocess',
+                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+                with_ego_fix_dist=True,
+                ego_fut_offset_input=False,
+                assign_class_for_ego=False),
+            dict(
+                type='CustomFormatBundle3D',
+                class_names=[
+                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',
+                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'
+                ],
+                with_ego=True,
+                collect_keys=[
+                    'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+                    'ego_pose', 'ego_pose_inv', 'pad_shape',
+                    'gt_traj_fut_classes', 'ego_fut_classes'
+                ]),
+            dict(
+                type='CustomCollect3D',
+                keys=[
+                    'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',
+                    'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',
+                    'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',
+                    'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist',
+                    'ego_fut_cmd', 'ego_lcf_feat', 'gt_attr_labels',
+                    'prev_exists', 'index', 'lidar2img', 'cam_intrinsic',
+                    'cam_extrinsic', 'timestamp', 'ego_pose', 'ego_pose_inv',
+                    'pad_shape', 'gt_traj_fut_classes', 'ego_fut_classes'
+                ])
+        ],
+        classes=[
+            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',
+            'traffic_light', 'pedestrian', 'others'
+        ],
+        modality=dict(
+            use_lidar=False,
+            use_camera=True,
+            use_radar=False,
+            use_map=False,
+            use_external=True),
+        test_mode=False,
+        box_type_3d='LiDAR',
+        data_aug_conf=dict(
+            resize_lim=(0.64, 0.69),
+            final_dim=(384, 1056),
+            bot_pct_lim=(0.0, 0.0),
+            rot_lim=(-5.4, 5.4),
+            H=900,
+            W=1600,
+            rand_flip=True,
+            rot3d_range=[0, 0]),
+        name_mapping=dict({
+            'vehicle.bh.crossbike':
+            'bicycle',
+            'vehicle.diamondback.century':
+            'bicycle',
+            'vehicle.gazelle.omafiets':
+            'bicycle',
+            'vehicle.audi.etron':
+            'car',
+            'vehicle.chevrolet.impala':
+            'car',
+            'vehicle.dodge.charger_2020':
+            'car',
+            'vehicle.dodge.charger_police':
+            'car',
+            'vehicle.dodge.charger_police_2020':
+            'car',
+            'vehicle.lincoln.mkz_2017':
+            'car',
+            'vehicle.lincoln.mkz_2020':
+            'car',
+            'vehicle.mini.cooper_s_2021':
+            'car',
+            'vehicle.mercedes.coupe_2020':
+            'car',
+            'vehicle.ford.mustang':
+            'car',
+            'vehicle.nissan.patrol_2021':
+            'car',
+            'vehicle.audi.tt':
+            'car',
+            'vehicle.ford.crown':
+            'car',
+            'vehicle.tesla.model3':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/FordCrown/SM_FordCrown_parked.SM_FordCrown_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Charger/SM_ChargerParked.SM_ChargerParked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Lincoln/SM_LincolnParked.SM_LincolnParked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/MercedesCCC/SM_MercedesCCC_Parked.SM_MercedesCCC_Parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Mini2021/SM_Mini2021_parked.SM_Mini2021_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/NissanPatrol2021/SM_NissanPatrol2021_parked.SM_NissanPatrol2021_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/TeslaM3/SM_TeslaM3_parked.SM_TeslaM3_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/VolkswagenT2/SM_VolkswagenT2_2021_Parked.SM_VolkswagenT2_2021_Parked':
+            'van',
+            'vehicle.ford.ambulance':
+            'van',
+            'vehicle.carlamotors.firetruck':
+            'truck',
+            'traffic.speed_limit.30':
+            'traffic_sign',
+            'traffic.speed_limit.40':
+            'traffic_sign',
+            'traffic.speed_limit.50':
+            'traffic_sign',
+            'traffic.speed_limit.60':
+            'traffic_sign',
+            'traffic.speed_limit.90':
+            'traffic_sign',
+            'traffic.speed_limit.120':
+            'traffic_sign',
+            'traffic.stop':
+            'traffic_sign',
+            'traffic.yield':
+            'traffic_sign',
+            'traffic.traffic_light':
+            'traffic_light',
+            'static.prop.warningconstruction':
+            'traffic_cone',
+            'static.prop.warningaccident':
+            'traffic_cone',
+            'static.prop.trafficwarning':
+            'traffic_cone',
+            'static.prop.constructioncone':
+            'traffic_cone',
+            'walker.pedestrian.0001':
+            'pedestrian',
+            'walker.pedestrian.0003':
+            'pedestrian',
+            'walker.pedestrian.0004':
+            'pedestrian',
+            'walker.pedestrian.0005':
+            'pedestrian',
+            'walker.pedestrian.0007':
+            'pedestrian',
+            'walker.pedestrian.0010':
+            'pedestrian',
+            'walker.pedestrian.0013':
+            'pedestrian',
+            'walker.pedestrian.0014':
+            'pedestrian',
+            'walker.pedestrian.0015':
+            'pedestrian',
+            'walker.pedestrian.0016':
+            'pedestrian',
+            'walker.pedestrian.0017':
+            'pedestrian',
+            'walker.pedestrian.0018':
+            'pedestrian',
+            'walker.pedestrian.0019':
+            'pedestrian',
+            'walker.pedestrian.0020':
+            'pedestrian',
+            'walker.pedestrian.0021':
+            'pedestrian',
+            'walker.pedestrian.0022':
+            'pedestrian',
+            'walker.pedestrian.0025':
+            'pedestrian',
+            'walker.pedestrian.0027':
+            'pedestrian',
+            'walker.pedestrian.0030':
+            'pedestrian',
+            'walker.pedestrian.0031':
+            'pedestrian',
+            'walker.pedestrian.0032':
+            'pedestrian',
+            'walker.pedestrian.0034':
+            'pedestrian',
+            'walker.pedestrian.0035':
+            'pedestrian',
+            'walker.pedestrian.0041':
+            'pedestrian',
+            'walker.pedestrian.0042':
+            'pedestrian',
+            'walker.pedestrian.0046':
+            'pedestrian',
+            'walker.pedestrian.0047':
+            'pedestrian',
+            'static.prop.dirtdebris01':
+            'others',
+            'static.prop.dirtdebris02':
+            'others'
+        }),
+        map_file='data/infos/b2d_map_infos.pkl',
+        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+        collect_keys=[
+            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',
+            'ego_fut_classes'
+        ],
+        polyline_points_num=20,
+        filter_empty_gt=False,
+        sub_seq_lenth=-1,
+        use_splited_data=True,
+        cache_lenth=7,
+        future_frames=6,
+        future_frames_ego_fix_time=30,
+        future_frames_ego_fix_dist=20,
+        sample_interval_ego_fut=1,
+        sample_interval=5,
+        fix_future_dis=1,
+        use_angle_as_dis_traj=True,
+        use_raw_goalpoint=False),
+    val=dict(
+        type='B2D_DriveTransformer_GoalPoint_Dataset',
+        ann_file='data/infos/b2d_infos_v1_val_drivetransformer_meta.pkl',
+        pipeline=[
+            dict(type='LoadMultiViewImageFromFiles', to_float32=True),
+            dict(type='ResizeCropFlipImage'),
+            dict(
+                type='NormalizeMultiviewImage',
+                mean=[123.675, 116.28, 103.53],
+                std=[58.395, 57.12, 57.375],
+                to_rgb=True),
+            dict(
+                type='LoadAnnotations3D',
+                with_bbox_3d=True,
+                with_label_3d=True,
+                with_attr_label=True),
+            dict(
+                type='CustomObjectRangeFilter',
+                point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),
+            dict(
+                type='CustomObjectNameFilter',
+                classes=[
+                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',
+                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'
+                ]),
+            dict(
+                type='TrajPreprocess',
+                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+                with_ego_fix_dist=True,
+                ego_fut_offset_input=False,
+                assign_class_for_ego=False),
+            dict(
+                type='CustomFormatBundle3D',
+                class_names=[
+                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',
+                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'
+                ],
+                with_ego=True,
+                collect_keys=[
+                    'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+                    'ego_pose', 'ego_pose_inv', 'pad_shape',
+                    'gt_traj_fut_classes', 'ego_fut_classes'
+                ]),
+            dict(
+                type='CustomCollect3D',
+                keys=[
+                    'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',
+                    'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',
+                    'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',
+                    'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist',
+                    'ego_fut_cmd', 'ego_lcf_feat', 'gt_attr_labels',
+                    'prev_exists', 'index', 'lidar2img', 'cam_intrinsic',
+                    'cam_extrinsic', 'timestamp', 'ego_pose', 'ego_pose_inv',
+                    'pad_shape', 'gt_traj_fut_classes', 'ego_fut_classes'
+                ])
+        ],
+        classes=[
+            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',
+            'traffic_light', 'pedestrian', 'others'
+        ],
+        modality=dict(
+            use_lidar=False,
+            use_camera=True,
+            use_radar=False,
+            use_map=False,
+            use_external=True),
+        test_mode=True,
+        box_type_3d='LiDAR',
+        data_root='data/bench2drive',
+        data_aug_conf=dict(
+            resize_lim=(0.64, 0.69),
+            final_dim=(384, 1056),
+            bot_pct_lim=(0.0, 0.0),
+            rot_lim=(-5.4, 5.4),
+            H=900,
+            W=1600,
+            rand_flip=True,
+            rot3d_range=[0, 0]),
+        name_mapping=dict({
+            'vehicle.bh.crossbike':
+            'bicycle',
+            'vehicle.diamondback.century':
+            'bicycle',
+            'vehicle.gazelle.omafiets':
+            'bicycle',
+            'vehicle.audi.etron':
+            'car',
+            'vehicle.chevrolet.impala':
+            'car',
+            'vehicle.dodge.charger_2020':
+            'car',
+            'vehicle.dodge.charger_police':
+            'car',
+            'vehicle.dodge.charger_police_2020':
+            'car',
+            'vehicle.lincoln.mkz_2017':
+            'car',
+            'vehicle.lincoln.mkz_2020':
+            'car',
+            'vehicle.mini.cooper_s_2021':
+            'car',
+            'vehicle.mercedes.coupe_2020':
+            'car',
+            'vehicle.ford.mustang':
+            'car',
+            'vehicle.nissan.patrol_2021':
+            'car',
+            'vehicle.audi.tt':
+            'car',
+            'vehicle.ford.crown':
+            'car',
+            'vehicle.tesla.model3':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/FordCrown/SM_FordCrown_parked.SM_FordCrown_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Charger/SM_ChargerParked.SM_ChargerParked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Lincoln/SM_LincolnParked.SM_LincolnParked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/MercedesCCC/SM_MercedesCCC_Parked.SM_MercedesCCC_Parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Mini2021/SM_Mini2021_parked.SM_Mini2021_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/NissanPatrol2021/SM_NissanPatrol2021_parked.SM_NissanPatrol2021_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/TeslaM3/SM_TeslaM3_parked.SM_TeslaM3_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/VolkswagenT2/SM_VolkswagenT2_2021_Parked.SM_VolkswagenT2_2021_Parked':
+            'van',
+            'vehicle.ford.ambulance':
+            'van',
+            'vehicle.carlamotors.firetruck':
+            'truck',
+            'traffic.speed_limit.30':
+            'traffic_sign',
+            'traffic.speed_limit.40':
+            'traffic_sign',
+            'traffic.speed_limit.50':
+            'traffic_sign',
+            'traffic.speed_limit.60':
+            'traffic_sign',
+            'traffic.speed_limit.90':
+            'traffic_sign',
+            'traffic.speed_limit.120':
+            'traffic_sign',
+            'traffic.stop':
+            'traffic_sign',
+            'traffic.yield':
+            'traffic_sign',
+            'traffic.traffic_light':
+            'traffic_light',
+            'static.prop.warningconstruction':
+            'traffic_cone',
+            'static.prop.warningaccident':
+            'traffic_cone',
+            'static.prop.trafficwarning':
+            'traffic_cone',
+            'static.prop.constructioncone':
+            'traffic_cone',
+            'walker.pedestrian.0001':
+            'pedestrian',
+            'walker.pedestrian.0003':
+            'pedestrian',
+            'walker.pedestrian.0004':
+            'pedestrian',
+            'walker.pedestrian.0005':
+            'pedestrian',
+            'walker.pedestrian.0007':
+            'pedestrian',
+            'walker.pedestrian.0010':
+            'pedestrian',
+            'walker.pedestrian.0013':
+            'pedestrian',
+            'walker.pedestrian.0014':
+            'pedestrian',
+            'walker.pedestrian.0015':
+            'pedestrian',
+            'walker.pedestrian.0016':
+            'pedestrian',
+            'walker.pedestrian.0017':
+            'pedestrian',
+            'walker.pedestrian.0018':
+            'pedestrian',
+            'walker.pedestrian.0019':
+            'pedestrian',
+            'walker.pedestrian.0020':
+            'pedestrian',
+            'walker.pedestrian.0021':
+            'pedestrian',
+            'walker.pedestrian.0022':
+            'pedestrian',
+            'walker.pedestrian.0025':
+            'pedestrian',
+            'walker.pedestrian.0027':
+            'pedestrian',
+            'walker.pedestrian.0030':
+            'pedestrian',
+            'walker.pedestrian.0031':
+            'pedestrian',
+            'walker.pedestrian.0032':
+            'pedestrian',
+            'walker.pedestrian.0034':
+            'pedestrian',
+            'walker.pedestrian.0035':
+            'pedestrian',
+            'walker.pedestrian.0041':
+            'pedestrian',
+            'walker.pedestrian.0042':
+            'pedestrian',
+            'walker.pedestrian.0046':
+            'pedestrian',
+            'walker.pedestrian.0047':
+            'pedestrian',
+            'static.prop.dirtdebris01':
+            'others',
+            'static.prop.dirtdebris02':
+            'others'
+        }),
+        map_file='data/infos/b2d_map_infos.pkl',
+        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+        collect_keys=[
+            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',
+            'ego_fut_classes'
+        ],
+        polyline_points_num=20,
+        filter_empty_gt=False,
+        use_splited_data=True,
+        cache_lenth=7,
+        future_frames=6,
+        future_frames_ego_fix_time=30,
+        future_frames_ego_fix_dist=20,
+        sample_interval_ego_fut=1,
+        sample_interval=5,
+        fix_future_dis=1,
+        use_angle_as_dis_traj=True,
+        use_raw_goalpoint=False),
+    test=dict(
+        type='B2D_DriveTransformer_GoalPoint_Dataset',
+        data_root='data/bench2drive',
+        ann_file='data/infos/b2d_infos_v1_val_drivetransformer_meta.pkl',
+        pipeline=[
+            dict(type='LoadMultiViewImageFromFiles', to_float32=True),
+            dict(type='ResizeCropFlipImage'),
+            dict(
+                type='NormalizeMultiviewImage',
+                mean=[123.675, 116.28, 103.53],
+                std=[58.395, 57.12, 57.375],
+                to_rgb=True),
+            dict(
+                type='LoadAnnotations3D',
+                with_bbox_3d=True,
+                with_label_3d=True,
+                with_attr_label=True),
+            dict(
+                type='CustomObjectRangeFilter',
+                point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),
+            dict(
+                type='CustomObjectNameFilter',
+                classes=[
+                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',
+                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'
+                ]),
+            dict(
+                type='TrajPreprocess',
+                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+                with_ego_fix_dist=True,
+                ego_fut_offset_input=False,
+                assign_class_for_ego=False),
+            dict(
+                type='CustomFormatBundle3D',
+                class_names=[
+                    'car', 'van', 'truck', 'bicycle', 'traffic_sign',
+                    'traffic_cone', 'traffic_light', 'pedestrian', 'others'
+                ],
+                with_ego=True,
+                collect_keys=[
+                    'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+                    'ego_pose', 'ego_pose_inv', 'pad_shape',
+                    'gt_traj_fut_classes', 'ego_fut_classes'
+                ]),
+            dict(
+                type='CustomCollect3D',
+                keys=[
+                    'gt_bboxes_3d', 'gt_labels_3d', 'img', 'ego_his_trajs',
+                    'fut_valid_flag_fix_time', 'ego_fut_trajs_fix_time',
+                    'ego_fut_masks_fix_time', 'fut_valid_flag_fix_dist',
+                    'ego_fut_trajs_fix_dist', 'ego_fut_masks_fix_dist',
+                    'ego_fut_cmd', 'ego_lcf_feat', 'gt_attr_labels',
+                    'prev_exists', 'index', 'lidar2img', 'cam_intrinsic',
+                    'cam_extrinsic', 'timestamp', 'ego_pose', 'ego_pose_inv',
+                    'pad_shape', 'gt_traj_fut_classes', 'ego_fut_classes'
+                ])
+        ],
+        classes=[
+            'car', 'van', 'truck', 'bicycle', 'traffic_sign', 'traffic_cone',
+            'traffic_light', 'pedestrian', 'others'
+        ],
+        modality=dict(
+            use_lidar=False,
+            use_camera=True,
+            use_radar=False,
+            use_map=False,
+            use_external=True),
+        test_mode=True,
+        box_type_3d='LiDAR',
+        data_aug_conf=dict(
+            resize_lim=(0.64, 0.69),
+            final_dim=(384, 1056),
+            bot_pct_lim=(0.0, 0.0),
+            rot_lim=(-5.4, 5.4),
+            H=900,
+            W=1600,
+            rand_flip=True,
+            rot3d_range=[0, 0]),
+        name_mapping=dict({
+            'vehicle.bh.crossbike':
+            'bicycle',
+            'vehicle.diamondback.century':
+            'bicycle',
+            'vehicle.gazelle.omafiets':
+            'bicycle',
+            'vehicle.audi.etron':
+            'car',
+            'vehicle.chevrolet.impala':
+            'car',
+            'vehicle.dodge.charger_2020':
+            'car',
+            'vehicle.dodge.charger_police':
+            'car',
+            'vehicle.dodge.charger_police_2020':
+            'car',
+            'vehicle.lincoln.mkz_2017':
+            'car',
+            'vehicle.lincoln.mkz_2020':
+            'car',
+            'vehicle.mini.cooper_s_2021':
+            'car',
+            'vehicle.mercedes.coupe_2020':
+            'car',
+            'vehicle.ford.mustang':
+            'car',
+            'vehicle.nissan.patrol_2021':
+            'car',
+            'vehicle.audi.tt':
+            'car',
+            'vehicle.ford.crown':
+            'car',
+            'vehicle.tesla.model3':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/FordCrown/SM_FordCrown_parked.SM_FordCrown_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Charger/SM_ChargerParked.SM_ChargerParked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Lincoln/SM_LincolnParked.SM_LincolnParked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/MercedesCCC/SM_MercedesCCC_Parked.SM_MercedesCCC_Parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Mini2021/SM_Mini2021_parked.SM_Mini2021_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/NissanPatrol2021/SM_NissanPatrol2021_parked.SM_NissanPatrol2021_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/TeslaM3/SM_TeslaM3_parked.SM_TeslaM3_parked':
+            'car',
+            '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/VolkswagenT2/SM_VolkswagenT2_2021_Parked.SM_VolkswagenT2_2021_Parked':
+            'van',
+            'vehicle.ford.ambulance':
+            'van',
+            'vehicle.carlamotors.firetruck':
+            'truck',
+            'traffic.speed_limit.30':
+            'traffic_sign',
+            'traffic.speed_limit.40':
+            'traffic_sign',
+            'traffic.speed_limit.50':
+            'traffic_sign',
+            'traffic.speed_limit.60':
+            'traffic_sign',
+            'traffic.speed_limit.90':
+            'traffic_sign',
+            'traffic.speed_limit.120':
+            'traffic_sign',
+            'traffic.stop':
+            'traffic_sign',
+            'traffic.yield':
+            'traffic_sign',
+            'traffic.traffic_light':
+            'traffic_light',
+            'static.prop.warningconstruction':
+            'traffic_cone',
+            'static.prop.warningaccident':
+            'traffic_cone',
+            'static.prop.trafficwarning':
+            'traffic_cone',
+            'static.prop.constructioncone':
+            'traffic_cone',
+            'walker.pedestrian.0001':
+            'pedestrian',
+            'walker.pedestrian.0003':
+            'pedestrian',
+            'walker.pedestrian.0004':
+            'pedestrian',
+            'walker.pedestrian.0005':
+            'pedestrian',
+            'walker.pedestrian.0007':
+            'pedestrian',
+            'walker.pedestrian.0010':
+            'pedestrian',
+            'walker.pedestrian.0013':
+            'pedestrian',
+            'walker.pedestrian.0014':
+            'pedestrian',
+            'walker.pedestrian.0015':
+            'pedestrian',
+            'walker.pedestrian.0016':
+            'pedestrian',
+            'walker.pedestrian.0017':
+            'pedestrian',
+            'walker.pedestrian.0018':
+            'pedestrian',
+            'walker.pedestrian.0019':
+            'pedestrian',
+            'walker.pedestrian.0020':
+            'pedestrian',
+            'walker.pedestrian.0021':
+            'pedestrian',
+            'walker.pedestrian.0022':
+            'pedestrian',
+            'walker.pedestrian.0025':
+            'pedestrian',
+            'walker.pedestrian.0027':
+            'pedestrian',
+            'walker.pedestrian.0030':
+            'pedestrian',
+            'walker.pedestrian.0031':
+            'pedestrian',
+            'walker.pedestrian.0032':
+            'pedestrian',
+            'walker.pedestrian.0034':
+            'pedestrian',
+            'walker.pedestrian.0035':
+            'pedestrian',
+            'walker.pedestrian.0041':
+            'pedestrian',
+            'walker.pedestrian.0042':
+            'pedestrian',
+            'walker.pedestrian.0046':
+            'pedestrian',
+            'walker.pedestrian.0047':
+            'pedestrian',
+            'static.prop.dirtdebris01':
+            'others',
+            'static.prop.dirtdebris02':
+            'others'
+        }),
+        map_file='data/infos/b2d_map_infos.pkl',
+        point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+        collect_keys=[
+            'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp',
+            'ego_pose', 'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes',
+            'ego_fut_classes'
+        ],
+        polyline_points_num=20,
+        filter_empty_gt=False,
+        use_splited_data=True,
+        cache_lenth=7,
+        future_frames=6,
+        future_frames_ego_fix_time=30,
+        future_frames_ego_fix_dist=20,
+        sample_interval_ego_fut=1,
+        sample_interval=5,
+        fix_future_dis=1,
+        use_angle_as_dis_traj=True,
+        use_raw_goalpoint=False),
+    shuffler_sampler=dict(type='InfiniteGroupEachSampleInBatchSampler'),
+    nonshuffler_sampler=dict(type='DistributedSampler'))
+evaluation = dict(
+    interval=24,
+    pipeline=[
+        dict(
+            type='LoadPointsFromFile',
+            coord_type='LIDAR',
+            load_dim=5,
+            use_dim=5,
+            file_client_args=dict(backend='disk')),
+        dict(
+            type='LoadPointsFromMultiSweeps',
+            sweeps_num=10,
+            file_client_args=dict(backend='disk')),
+        dict(
+            type='DefaultFormatBundle3D',
+            class_names=[
+                'car', 'truck', 'trailer', 'bus', 'construction_vehicle',
+                'bicycle', 'motorcycle', 'pedestrian', 'traffic_cone',
+                'barrier'
+            ],
+            with_label=False),
+        dict(type='Collect3D', keys=['points'])
+    ])
+checkpoint_config = dict(interval=1)
+log_config = dict(
+    interval=50,
+    hooks=[dict(type='TextLoggerHook'),
+           dict(type='TensorboardLoggerHook')])
+dist_params = dict(backend='nccl')
+log_level = 'INFO'
+work_dir = './work_dirs/drivetransformer_goalpoint_1gpu'
+load_from = None
+resume_from = './work_dirs/drivetransformer_goalpoint_1gpu/epoch_12.pth'
+workflow = [('train', 1)]
+plugin = True
+plugin_dir = 'adzoo/drivetransformer/mmdet3d_plugin/'
+voxel_size = [0.15, 0.15, 4]
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+NameMapping = dict({
+    'vehicle.bh.crossbike':
+    'bicycle',
+    'vehicle.diamondback.century':
+    'bicycle',
+    'vehicle.gazelle.omafiets':
+    'bicycle',
+    'vehicle.audi.etron':
+    'car',
+    'vehicle.chevrolet.impala':
+    'car',
+    'vehicle.dodge.charger_2020':
+    'car',
+    'vehicle.dodge.charger_police':
+    'car',
+    'vehicle.dodge.charger_police_2020':
+    'car',
+    'vehicle.lincoln.mkz_2017':
+    'car',
+    'vehicle.lincoln.mkz_2020':
+    'car',
+    'vehicle.mini.cooper_s_2021':
+    'car',
+    'vehicle.mercedes.coupe_2020':
+    'car',
+    'vehicle.ford.mustang':
+    'car',
+    'vehicle.nissan.patrol_2021':
+    'car',
+    'vehicle.audi.tt':
+    'car',
+    'vehicle.ford.crown':
+    'car',
+    'vehicle.tesla.model3':
+    'car',
+    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/FordCrown/SM_FordCrown_parked.SM_FordCrown_parked':
+    'car',
+    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Charger/SM_ChargerParked.SM_ChargerParked':
+    'car',
+    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Lincoln/SM_LincolnParked.SM_LincolnParked':
+    'car',
+    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/MercedesCCC/SM_MercedesCCC_Parked.SM_MercedesCCC_Parked':
+    'car',
+    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/Mini2021/SM_Mini2021_parked.SM_Mini2021_parked':
+    'car',
+    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/NissanPatrol2021/SM_NissanPatrol2021_parked.SM_NissanPatrol2021_parked':
+    'car',
+    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/TeslaM3/SM_TeslaM3_parked.SM_TeslaM3_parked':
+    'car',
+    '/Game/Carla/Static/Car/4Wheeled/ParkedVehicles/VolkswagenT2/SM_VolkswagenT2_2021_Parked.SM_VolkswagenT2_2021_Parked':
+    'van',
+    'vehicle.ford.ambulance':
+    'van',
+    'vehicle.carlamotors.firetruck':
+    'truck',
+    'traffic.speed_limit.30':
+    'traffic_sign',
+    'traffic.speed_limit.40':
+    'traffic_sign',
+    'traffic.speed_limit.50':
+    'traffic_sign',
+    'traffic.speed_limit.60':
+    'traffic_sign',
+    'traffic.speed_limit.90':
+    'traffic_sign',
+    'traffic.speed_limit.120':
+    'traffic_sign',
+    'traffic.stop':
+    'traffic_sign',
+    'traffic.yield':
+    'traffic_sign',
+    'traffic.traffic_light':
+    'traffic_light',
+    'static.prop.warningconstruction':
+    'traffic_cone',
+    'static.prop.warningaccident':
+    'traffic_cone',
+    'static.prop.trafficwarning':
+    'traffic_cone',
+    'static.prop.constructioncone':
+    'traffic_cone',
+    'walker.pedestrian.0001':
+    'pedestrian',
+    'walker.pedestrian.0003':
+    'pedestrian',
+    'walker.pedestrian.0004':
+    'pedestrian',
+    'walker.pedestrian.0005':
+    'pedestrian',
+    'walker.pedestrian.0007':
+    'pedestrian',
+    'walker.pedestrian.0010':
+    'pedestrian',
+    'walker.pedestrian.0013':
+    'pedestrian',
+    'walker.pedestrian.0014':
+    'pedestrian',
+    'walker.pedestrian.0015':
+    'pedestrian',
+    'walker.pedestrian.0016':
+    'pedestrian',
+    'walker.pedestrian.0017':
+    'pedestrian',
+    'walker.pedestrian.0018':
+    'pedestrian',
+    'walker.pedestrian.0019':
+    'pedestrian',
+    'walker.pedestrian.0020':
+    'pedestrian',
+    'walker.pedestrian.0021':
+    'pedestrian',
+    'walker.pedestrian.0022':
+    'pedestrian',
+    'walker.pedestrian.0025':
+    'pedestrian',
+    'walker.pedestrian.0027':
+    'pedestrian',
+    'walker.pedestrian.0030':
+    'pedestrian',
+    'walker.pedestrian.0031':
+    'pedestrian',
+    'walker.pedestrian.0032':
+    'pedestrian',
+    'walker.pedestrian.0034':
+    'pedestrian',
+    'walker.pedestrian.0035':
+    'pedestrian',
+    'walker.pedestrian.0041':
+    'pedestrian',
+    'walker.pedestrian.0042':
+    'pedestrian',
+    'walker.pedestrian.0046':
+    'pedestrian',
+    'walker.pedestrian.0047':
+    'pedestrian',
+    'static.prop.dirtdebris01':
+    'others',
+    'static.prop.dirtdebris02':
+    'others'
+})
+collect_keys = [
+    'lidar2img', 'cam_intrinsic', 'cam_extrinsic', 'timestamp', 'ego_pose',
+    'ego_pose_inv', 'pad_shape', 'gt_traj_fut_classes', 'ego_fut_classes'
+]
+num_classes = 9
+map_classes = [
+    'Broken', 'Solid', 'SolidSolid', 'Center', 'TrafficLight', 'StopSign'
+]
+map_fixed_ptsnum_per_gt_line = 20
+map_fixed_ptsnum_per_pred_line = 20
+map_eval_use_same_gt_sample_num_flag = True
+map_num_classes = 6
+agent_query_num_vec = 900
+agent_num_topk_sift = 900
+agent_num_propagated = 50
+map_query_num_vec = 100
+map_num_topk_sift = 100
+map_num_propagated = 50
+memory_len_frame = 10
+num_mode = 6
+num_gpus = 1
+batch_size = 6
+num_iters_per_epoch = 1041
+data_aug_conf = dict(
+    resize_lim=(0.64, 0.69),
+    final_dim=(384, 1056),
+    bot_pct_lim=(0.0, 0.0),
+    rot_lim=(-5.4, 5.4),
+    H=900,
+    W=1600,
+    rand_flip=True,
+    rot3d_range=[0, 0])
+_dim_ = 512
+queue_length = 1
+total_epochs = 24
+dropout = 0.1
+model = dict(
+    type='DriveTransformer',
+    use_grid_mask=False,
+    pretrained=dict(img='./ckpts/resnet50-19c8e357.pth'),
+    img_backbone=dict(
+        type='ResNet',
+        depth=50,
+        num_stages=4,
+        out_indices=(3, ),
+        frozen_stages=1,
+        norm_cfg=dict(type='BN', requires_grad=False),
+        norm_eval=True,
+        style='pytorch'),
+    img_neck=dict(
+        type='FPN',
+        in_channels=[2048],
+        out_channels=512,
+        start_level=0,
+        add_extra_convs='on_output',
+        num_outs=1,
+        relu_before_extra_convs=True),
+    pts_bbox_head=dict(
+        type='DriveTransformerlHead',
+        ego_lcf_feat_idx=[0, 1, 2, 3, 4, 5, 6, 7, 8],
+        ego_command_dim=128,
+        img_stride=32,
+        embed_dims=512,
+        num_reg_fcs=2,
+        num_cls_fcs=2,
+        agent_num_propagated=50,
+        map_num_propagated=50,
+        memory_len_frame=10,
+        agent_num_query=900,
+        agent_num_query_sifted=900,
+        fut_mode=6,
+        fut_ego_mode=1,
+        fut_ts=6,
+        fut_ego_fix_dist=True,
+        fut_ts_ego_fix_dist=20,
+        fut_ts_ego_fix_time=30,
+        num_classes=9,
+        code_size=10,
+        map_num_query=100,
+        map_num_query_sifted=100,
+        map_num_classes=6,
+        map_num_pts_per_vec=20,
+        map_num_pts_per_gt_vec=20,
+        map_query_embed_type='instance_pts',
+        map_transform_method='minmax',
+        map_gt_shift_pts_pattern='v2',
+        map_dir_interval=1,
+        map_code_size=2,
+        map_code_weights=[1.0, 1.0, 1.0, 1.0],
+        sync_cls_avg_factor=True,
+        with_box_refine=True,
+        LID=True,
+        with_ego_pos=True,
+        position_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+        depth_start=1,
+        depth_step=0.8,
+        depth_num=64,
+        agent_prep_decoder=dict(
+            type='DriveTransformerPreDecoder',
+            num_layers=1,
+            return_intermediate=False,
+            transformerlayers=dict(
+                type='DriveTransformerPreDecoderLayer',
+                attn_cfgs=[
+                    dict(
+                        type='AttentionLayer',
+                        embed_dims=512,
+                        head_dim=64,
+                        attn_drop=0.1),
+                    dict(
+                        type='AttentionLayer',
+                        embed_dims=512,
+                        head_dim=64,
+                        attn_drop=0.1)
+                ],
+                ffn_cfgs=dict(
+                    type='SwiGLULayer',
+                    embed_dims=512,
+                    feedforward_channels=2048,
+                    ffn_drop=0.1),
+                with_cp=False,
+                operation_order=('cross_attn', 'norm', 'self_attn', 'norm',
+                                 'ffn', 'norm'))),
+        map_prep_decoder=dict(
+            type='DriveTransformerPreDecoder',
+            num_layers=1,
+            return_intermediate=False,
+            transformerlayers=dict(
+                type='DriveTransformerPreDecoderLayer',
+                attn_cfgs=[
+                    dict(
+                        type='AttentionLayer',
+                        embed_dims=512,
+                        head_dim=64,
+                        attn_drop=0.1),
+                    dict(
+                        type='AttentionLayer',
+                        embed_dims=512,
+                        head_dim=64,
+                        attn_drop=0.1)
+                ],
+                ffn_cfgs=dict(
+                    type='SwiGLULayer',
+                    embed_dims=512,
+                    feedforward_channels=2048,
+                    ffn_drop=0.1),
+                with_cp=False,
+                operation_order=('cross_attn', 'norm', 'self_attn', 'norm',
+                                 'ffn', 'norm'))),
+        transformer=dict(
+            type='DriveTransformerWrapper',
+            embed_dims=512,
+            decoder=dict(
+                type='DriveTransformerDecoder',
+                num_layers=6,
+                fut_mode=6,
+                agent_num_query=900,
+                map_num_query=100,
+                map_num_pts_per_vec=20,
+                return_intermediate=True,
+                embed_dims=512,
+                refine=True,
+                transformerlayers=dict(
+                    type='DriveTransformerDecoderLayer',
+                    agent_query_num=900,
+                    map_query_num=100,
+                    memory_len_frame=10,
+                    agent_num_propagated=50,
+                    map_num_propagated=50,
+                    map_pts_per_vec=20,
+                    feedforward_channels=2048,
+                    ffn_dropout=0.1,
+                    with_cp=False,
+                    attn_cfgs=[
+                        dict(
+                            type='AttentionLayer',
+                            embed_dims=512,
+                            head_dim=64,
+                            attn_drop=0.1,
+                            layer_scale=0.01),
+                        dict(
+                            type='AttentionLayer',
+                            embed_dims=512,
+                            head_dim=64,
+                            attn_drop=0.1,
+                            layer_scale=0.01),
+                        dict(
+                            type='AttentionLayer',
+                            embed_dims=512,
+                            head_dim=64,
+                            attn_drop=0.1,
+                            no_wq=True)
+                    ],
+                    ffn_cfgs=dict(
+                        type='SwiGLULayer',
+                        embed_dims=512,
+                        feedforward_channels=2048,
+                        ffn_drop=0.1),
+                    operation_order=('task_self_attn', 'norm',
+                                     'temporal_cross_attn', 'norm',
+                                     'sensor_cross_attn', 'norm', 'ffn',
+                                     'norm')))),
+        bbox_coder=dict(
+            type='CustomNMSFreeCoder',
+            post_center_range=[-20, -35, -10.0, 20, 35, 10.0],
+            pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+            max_num=100,
+            voxel_size=[0.15, 0.15, 4],
+            num_classes=9),
+        loss_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=2.0,
+            alpha=0.25,
+            loss_weight=2.0),
+        loss_bbox=dict(type='L1Loss', loss_weight=0.25),
+        loss_traj=dict(type='L1Loss', loss_weight=0.2),
+        loss_traj_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=2.0,
+            alpha=0.5,
+            loss_weight=0.2),
+        map_bbox_coder=dict(
+            type='MapNMSFreeCoder',
+            post_center_range=[-20, -35, -20, -35, 20, 35, 20, 35],
+            pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+            max_num=50,
+            voxel_size=[0.15, 0.15, 4],
+            num_classes=6),
+        loss_map_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=2.0,
+            alpha=0.25,
+            loss_weight=2.0),
+        loss_map_pts=dict(type='PtsL1Loss', loss_weight=1.0),
+        loss_map_dir=dict(type='PtsDirCosLoss', loss_weight=0.005),
+        loss_plan_reg_fix_time=dict(type='L1Loss', loss_weight=3.5),
+        loss_plan_reg_fix_dist=dict(type='L1Loss', loss_weight=10.0),
+        loss_plan_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=4.0,
+            alpha=0.5,
+            loss_weight=20.0)),
+    train_cfg=dict(
+        pts=dict(
+            grid_size=[512, 512, 1],
+            voxel_size=[0.15, 0.15, 4],
+            point_cloud_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0],
+            out_size_factor=4,
+            assigner=dict(
+                type='HungarianAssigner3D',
+                cls_cost=dict(
+                    type='FocalLossCost', weight=2.0, gamma=2.0, alpha=0.25),
+                reg_cost=dict(type='BBox3DL1Cost', weight=0.25),
+                iou_cost=dict(type='IoUCost', weight=0.0),
+                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]),
+            map_assigner=dict(
+                type='MapHungarianAssigner3D',
+                cls_cost=dict(
+                    type='FocalLossCost', weight=2.0, gamma=2.0, alpha=0.25),
+                reg_cost=dict(
+                    type='BBoxL1Cost', weight=0.0, box_format='xywh'),
+                iou_cost=dict(type='IoUCost', iou_mode='giou', weight=0.0),
+                pts_cost=dict(type='OrderedPtsL1Cost', weight=1.0),
+                pc_range=[-15.0, -30.0, -2.0, 15.0, 30.0, 2.0]))))
+info_root = 'data/infos'
+map_root = 'data/bench2drive/maps'
+map_file = 'data/infos/b2d_map_infos.pkl'
+ann_file_train = 'data/infos/b2d_infos_v1_train_drivetransformer_meta.pkl'
+ann_file_val = 'data/infos/b2d_infos_v1_val_drivetransformer_meta.pkl'
+ann_file_test = 'data/infos/b2d_infos_v1_val_drivetransformer_meta.pkl'
+optimizer = dict(type='AdamW', lr=0.0001, weight_decay=0.01)
+optimizer_config = dict(
+    grad_clip=dict(max_norm=35, norm_type=2),
+    type='GradientCumulativeFp16OptimizerHook',
+    cumulative_iters=32)
+lr_config = dict(
+    policy='CosineAnnealing',
+    warmup='linear',
+    warmup_iters=1000,
+    warmup_ratio=0.1,
+    min_lr_ratio=0.01)
+runner = dict(type='EpochBasedRunner', max_epochs=24)
+fp16 = dict(loss_scale=512.0)
+find_unused_parameters = True
+custom_hooks = [dict(type='CustomSetEpochInfoHook')]
+cumulative_iters = 32
+gpu_ids = range(0, 1)

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