Invalid JSON:Unexpected non-whitespace character after JSONat line 2, column 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"} | |
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