将子模块转换为普通目录

mmdetection3d @ c9541b0d

-Subproject commit c9541b0db89498fdea5cafd05b7b17f7b625b858

docker-hub/FlashOCC/Flashocc/mmdetection3d/.dev_scripts/gather_models.py

+# Copyright (c) OpenMMLab. All rights reserved.
+"""Script to gather benchmarked models and prepare them for upload.
+
+Usage:
+python gather_models.py ${root_path} ${out_dir}
+
+Example:
+python gather_models.py \
+work_dirs/pgd_r101_caffe_fpn_gn-head_3x4_4x_kitti-mono3d \
+work_dirs/pgd_r101_caffe_fpn_gn-head_3x4_4x_kitti-mono3d
+
+Note that before running the above command, rename the directory with the
+config name if you did not use the default directory name, create
+a corresponding directory 'pgd' under the above path and put the used config
+into it.
+"""
+
+import argparse
+import glob
+import json
+import shutil
+import subprocess
+from os import path as osp
+
+import mmcv
+import torch
+
+# build schedule look-up table to automatically find the final model
+SCHEDULES_LUT = {
+    '_1x_': 12,
+    '_2x_': 24,
+    '_20e_': 20,
+    '_3x_': 36,
+    '_4x_': 48,
+    '_24e_': 24,
+    '_6x_': 73,
+    '_50e_': 50,
+    '_80e_': 80,
+    '_100e_': 100,
+    '_150e_': 150,
+    '_200e_': 200,
+    '_250e_': 250,
+    '_400e_': 400
+}
+
+# TODO: add support for lyft dataset
+RESULTS_LUT = {
+    'coco': ['bbox_mAP', 'segm_mAP'],
+    'nus': ['pts_bbox_NuScenes/NDS', 'NDS'],
+    'kitti-3d-3class': ['KITTI/Overall_3D_moderate', 'Overall_3D_moderate'],
+    'kitti-3d-car': ['KITTI/Car_3D_moderate_strict', 'Car_3D_moderate_strict'],
+    'lyft': ['score'],
+    'scannet_seg': ['miou'],
+    's3dis_seg': ['miou'],
+    'scannet': ['mAP_0.50'],
+    'sunrgbd': ['mAP_0.50'],
+    'kitti-mono3d': [
+        'img_bbox/KITTI/Car_3D_AP40_moderate_strict',
+        'Car_3D_AP40_moderate_strict'
+    ],
+    'nus-mono3d': ['img_bbox_NuScenes/NDS', 'NDS']
+}
+
+
+def get_model_dataset(log_json_path):
+    for key in RESULTS_LUT:
+        if log_json_path.find(key) != -1:
+            return key
+
+
+def process_checkpoint(in_file, out_file):
+    checkpoint = torch.load(in_file, map_location='cpu')
+    # remove optimizer for smaller file size
+    if 'optimizer' in checkpoint:
+        del checkpoint['optimizer']
+    # if it is necessary to remove some sensitive data in checkpoint['meta'],
+    # add the code here.
+    torch.save(checkpoint, out_file)
+    sha = subprocess.check_output(['sha256sum', out_file]).decode()
+    final_file = out_file.rstrip('.pth') + '-{}.pth'.format(sha[:8])
+    subprocess.Popen(['mv', out_file, final_file])
+    return final_file
+
+
+def get_final_epoch(config):
+    if config.find('grid_rcnn') != -1 and config.find('2x') != -1:
+        # grid_rcnn 2x trains 25 epochs
+        return 25
+
+    for schedule_name, epoch_num in SCHEDULES_LUT.items():
+        if config.find(schedule_name) != -1:
+            return epoch_num
+
+
+def get_best_results(log_json_path):
+    dataset = get_model_dataset(log_json_path)
+    max_dict = dict()
+    max_memory = 0
+    with open(log_json_path, 'r') as f:
+        for line in f.readlines():
+            log_line = json.loads(line)
+            if 'mode' not in log_line.keys():
+                continue
+
+            # record memory and find best results & epochs
+            if log_line['mode'] == 'train' \
+                    and max_memory <= log_line['memory']:
+                max_memory = log_line['memory']
+
+            elif log_line['mode'] == 'val':
+                result_dict = {
+                    key: log_line[key]
+                    for key in RESULTS_LUT[dataset] if key in log_line
+                }
+                if len(max_dict) == 0:
+                    max_dict = result_dict
+                    max_dict['epoch'] = log_line['epoch']
+                elif all(
+                    [max_dict[key] <= result_dict[key]
+                     for key in result_dict]):
+                    max_dict.update(result_dict)
+                    max_dict['epoch'] = log_line['epoch']
+
+        max_dict['memory'] = max_memory
+        return max_dict
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='Gather benchmarked models')
+    parser.add_argument(
+        'root',
+        type=str,
+        help='root path of benchmarked models to be gathered')
+    parser.add_argument(
+        'out', type=str, help='output path of gathered models to be stored')
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = parse_args()
+    models_root = args.root
+    models_out = args.out
+    mmcv.mkdir_or_exist(models_out)
+
+    # find all models in the root directory to be gathered
+    raw_configs = list(mmcv.scandir('./configs', '.py', recursive=True))
+
+    # filter configs that is not trained in the experiments dir
+    used_configs = []
+    for raw_config in raw_configs:
+        if osp.exists(osp.join(models_root, raw_config)):
+            used_configs.append(raw_config)
+    print(f'Find {len(used_configs)} models to be gathered')
+
+    # find final_ckpt and log file for trained each config
+    # and parse the best performance
+    model_infos = []
+    for used_config in used_configs:
+        # get logs
+        log_json_path = glob.glob(osp.join(models_root, '*.log.json'))[0]
+        log_txt_path = glob.glob(osp.join(models_root, '*.log'))[0]
+        model_performance = get_best_results(log_json_path)
+        final_epoch = model_performance['epoch']
+        final_model = 'epoch_{}.pth'.format(final_epoch)
+        model_path = osp.join(models_root, final_model)
+
+        # skip if the model is still training
+        if not osp.exists(model_path):
+            print(f'Expected {model_path} does not exist!')
+            continue
+
+        if model_performance is None:
+            print(f'Obtained no performance for model {used_config}')
+            continue
+
+        model_time = osp.split(log_txt_path)[-1].split('.')[0]
+        model_infos.append(
+            dict(
+                config=used_config,
+                results=model_performance,
+                epochs=final_epoch,
+                model_time=model_time,
+                log_json_path=osp.split(log_json_path)[-1]))
+
+    # publish model for each checkpoint
+    publish_model_infos = []
+    for model in model_infos:
+        model_publish_dir = osp.join(models_out, model['config'].rstrip('.py'))
+        mmcv.mkdir_or_exist(model_publish_dir)
+
+        model_name = model['config'].split('/')[-1].rstrip(
+            '.py') + '_' + model['model_time']
+        publish_model_path = osp.join(model_publish_dir, model_name)
+        trained_model_path = osp.join(models_root,
+                                      'epoch_{}.pth'.format(model['epochs']))
+
+        # convert model
+        final_model_path = process_checkpoint(trained_model_path,
+                                              publish_model_path)
+
+        # copy log
+        shutil.copy(
+            osp.join(models_root, model['log_json_path']),
+            osp.join(model_publish_dir, f'{model_name}.log.json'))
+        shutil.copy(
+            osp.join(models_root, model['log_json_path'].rstrip('.json')),
+            osp.join(model_publish_dir, f'{model_name}.log'))
+
+        # copy config to guarantee reproducibility
+        config_path = model['config']
+        config_path = osp.join(
+            'configs',
+            config_path) if 'configs' not in config_path else config_path
+        target_cconfig_path = osp.split(config_path)[-1]
+        shutil.copy(config_path,
+                    osp.join(model_publish_dir, target_cconfig_path))
+
+        model['model_path'] = final_model_path
+        publish_model_infos.append(model)
+
+    models = dict(models=publish_model_infos)
+    print(f'Totally gathered {len(publish_model_infos)} models')
+    mmcv.dump(models, osp.join(models_out, 'model_info.json'))
+
+
+if __name__ == '__main__':
+    main()

docker-hub/FlashOCC/Flashocc/mmdetection3d/.dev_scripts/gen_benchmark_script.py

+import argparse
+import re
+from os import path as osp
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(
+        description='Generate benchmark training/testing scripts')
+    parser.add_argument(
+        '--input_file',
+        required=False,
+        type=str,
+        help='Input file containing the paths '
+        'of configs to be trained/tested.')
+    parser.add_argument(
+        '--output_file',
+        required=True,
+        type=str,
+        help='Output file containing the '
+        'commands to train/test selected models.')
+    parser.add_argument(
+        '--gpus_per_node',
+        type=int,
+        default=8,
+        help='GPUs per node config for slurm, '
+        'should be set according to your slurm environment')
+    parser.add_argument(
+        '--cpus_per_task',
+        type=int,
+        default=5,
+        help='CPUs per task config for slurm, '
+        'should be set according to your slurm environment')
+    parser.add_argument(
+        '--gpus',
+        type=int,
+        default=8,
+        help='Totally used num of GPUs config for slurm (in testing), '
+        'should be set according to your slurm environment')
+    parser.add_argument(
+        '--mode', type=str, default='train', help='Train or test')
+    parser.add_argument(
+        '--long_work_dir',
+        action='store_true',
+        help='Whether use full relative path of config as work dir')
+    parser.add_argument(
+        '--max_keep_ckpts',
+        type=int,
+        default=1,
+        help='The max number of checkpoints saved in training')
+    parser.add_argument(
+        '--full_log',
+        action='store_true',
+        help='Whether save full log in a file')
+
+    args = parser.parse_args()
+    return args
+
+
+args = parse_args()
+assert args.mode in ['train', 'test'], 'Currently we only support ' \
+    'automatically generating training or testing scripts.'
+
+config_paths = []
+
+if args.input_file is not None:
+    with open(args.input_file, 'r') as fi:
+        config_paths = fi.read().strip().split('\n')
+else:
+    while True:
+        print('Please type a config path and '
+              'press enter (press enter directly to exit):')
+        config_path = input()
+        if config_path != '':
+            config_paths.append(config_path)
+        else:
+            break
+
+script = '''PARTITION=$1
+CHECKPOINT_DIR=$2
+
+'''
+
+if args.mode == 'train':
+    for i, config_path in enumerate(config_paths):
+        root_dir = osp.dirname(osp.dirname(osp.abspath(__file__)))
+        if not osp.exists(osp.join(root_dir, config_path)):
+            print(f'Invalid config path (does not exist):\n{config_path}')
+            continue
+
+        config_name = config_path.split('/')[-1][:-3]
+        match_obj = re.match(r'^.*_[0-9]+x([0-9]+)_.*$', config_name)
+        if match_obj is None:
+            print(f'Invalid config path (no GPU num in '
+                  f'config name):\n{config_path}')
+            continue
+
+        gpu_num = int(match_obj.group(1))
+        work_dir_name = config_path if args.long_work_dir else config_name
+
+        script += f"echo '{config_path}' &\n"
+        if args.full_log:
+            script += f'mkdir -p $CHECKPOINT_DIR/{work_dir_name}\n'
+
+        # training commands
+        script += f'GPUS={gpu_num} GPUS_PER_NODE={args.gpus_per_node} ' \
+                  f'CPUS_PER_TASK={args.cpus_per_task} ' \
+                  f'./tools/slurm_train.sh $PARTITION {config_name} ' \
+                  f'{config_path} \\\n'
+        script += f'$CHECKPOINT_DIR/{work_dir_name} --cfg-options ' \
+                  f'checkpoint_config.max_keep_ckpts=' \
+                  f'{args.max_keep_ckpts} \\\n' \
+
+        # if output full log, redirect stdout and stderr to
+        # another log file in work dir
+        if args.full_log:
+            script += f'2>&1|tee $CHECKPOINT_DIR/{work_dir_name}' \
+                      f'/FULL_LOG.txt &\n'
+        else:
+            script += '>/dev/null &\n'
+
+        if i != len(config_paths) - 1:
+            script += '\n'
+
+        print(f'Successfully generated script for {config_name}')
+
+    with open(args.output_file, 'w') as fo:
+        fo.write(script)
+
+elif args.mode == 'test':
+    for i, config_path in enumerate(config_paths):
+        root_dir = osp.dirname(osp.dirname(osp.abspath(__file__)))
+        if not osp.exists(osp.join(root_dir, config_path)):
+            print(f'Invalid config path (does not exist):\n{config_path}')
+            continue
+
+        config_name = config_path.split('/')[-1][:-3]
+
+        tasks = {
+            'scannet_seg', 'scannet', 's3dis_seg', 'sunrgbd', 'kitti', 'nus',
+            'lyft', 'waymo'
+        }
+        eval_option = None
+        for task in tasks:
+            if task in config_name:
+                eval_option = task
+                break
+        if eval_option is None:
+            print(f'Invalid config path (invalid task):\n{config_path}')
+            continue
+
+        work_dir_name = config_path if args.long_work_dir else config_name
+
+        script += f"echo '{config_path}' &\n"
+        if args.full_log:
+            script += f'mkdir -p $CHECKPOINT_DIR/{work_dir_name}\n'
+
+        # training commands
+        script += f'GPUS={args.gpus} GPUS_PER_NODE={args.gpus_per_node} ' \
+                  f'CPUS_PER_TASK={args.cpus_per_task} ' \
+                  f'./tools/slurm_test.sh $PARTITION {config_name} ' \
+                  f'{config_path} \\\n'
+        script += f'$CHECKPOINT_DIR/{work_dir_name}/latest.pth ' \
+
+        if eval_option in ['scannet_seg', 's3dis_seg']:
+            script += '--eval mIoU \\\n'
+        elif eval_option in ['scannet', 'sunrgbd', 'kitti', 'nus']:
+            script += '--eval map \\\n'
+        elif eval_option in ['lyft']:
+            script += f'--format-only --eval-options jsonfile_prefix=' \
+                      f'$CHECKPOINT_DIR/{work_dir_name}/results_challenge ' \
+                      f'csv_savepath=$CHECKPOINT_DIR/{work_dir_name}/' \
+                      f'results_challenge.csv \\\n'
+        elif eval_option in ['waymo']:
+            script += f'--eval waymo --eval-options pklfile_prefix=' \
+                      f'$CHECKPOINT_DIR/{work_dir_name}/kitti_results ' \
+                      f'submission_prefix=$CHECKPOINT_DIR/{work_dir_name}/' \
+                      f'kitti_results \\\n'
+
+        # if output full log, redirect stdout and stderr to
+        # another log file in work dir
+        if args.full_log:
+            script += f'2>&1|tee $CHECKPOINT_DIR/{work_dir_name}' \
+                      f'/FULL_LOG.txt &\n'
+        else:
+            script += '>/dev/null &\n'
+
+        if i != len(config_paths) - 1:
+            script += '\n'
+
+        print(f'Successfully generated script for {config_name}')
+
+    with open(args.output_file, 'w') as fo:
+        fo.write(script)

docker-hub/FlashOCC/Flashocc/mmdetection3d/.dev_scripts/linter.sh

+yapf -r -i mmdet3d/ configs/ tests/ tools/
+isort mmdet3d/ configs/ tests/ tools/
+flake8 .

docker-hub/FlashOCC/Flashocc/mmdetection3d/.dev_scripts/test_benchmark.sh

+PARTITION=$1
+CHECKPOINT_DIR=$2
+
+echo 'configs/3dssd/3dssd_4x4_kitti-3d-car.py' &
+mkdir -p $CHECKPOINT_DIR/configs/3dssd/3dssd_4x4_kitti-3d-car.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION 3dssd_4x4_kitti-3d-car configs/3dssd/3dssd_4x4_kitti-3d-car.py \
+$CHECKPOINT_DIR/configs/3dssd/3dssd_4x4_kitti-3d-car.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/3dssd/3dssd_4x4_kitti-3d-car.py/FULL_LOG.txt &
+
+echo 'configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py' &
+mkdir -p $CHECKPOINT_DIR/configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py \
+$CHECKPOINT_DIR/configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py/FULL_LOG.txt &
+
+echo 'configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py \
+$CHECKPOINT_DIR/configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py/FULL_LOG.txt &
+
+echo 'configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py \
+$CHECKPOINT_DIR/configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py/FULL_LOG.txt &
+
+echo 'configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py' &
+mkdir -p $CHECKPOINT_DIR/configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION groupfree3d_8x4_scannet-3d-18class-L6-O256 configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py \
+$CHECKPOINT_DIR/configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py/FULL_LOG.txt &
+
+echo 'configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION h3dnet_3x8_scannet-3d-18class configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py \
+$CHECKPOINT_DIR/configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py/FULL_LOG.txt &
+
+echo 'configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py \
+$CHECKPOINT_DIR/configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py/FULL_LOG.txt &
+
+echo 'configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION imvotenet_stage2_16x8_sunrgbd-3d-10class configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py \
+$CHECKPOINT_DIR/configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py/FULL_LOG.txt &
+
+echo 'configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py' &
+mkdir -p $CHECKPOINT_DIR/configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION imvoxelnet_4x8_kitti-3d-car configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py \
+$CHECKPOINT_DIR/configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py/FULL_LOG.txt &
+
+echo 'configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py \
+$CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py/latest.pth --eval mIoU \
+2>&1|tee $CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py/FULL_LOG.txt &
+
+echo 'configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py \
+$CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py/FULL_LOG.txt &
+
+echo 'configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py \
+$CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py/latest.pth --format-only --eval-options jsonfile_prefix=$CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py/results_challenge csv_savepath=$CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py/results_challenge.csv \
+2>&1|tee $CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py/FULL_LOG.txt &
+
+echo 'configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py \
+$CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py/latest.pth --eval waymo --eval-options pklfile_prefix=$CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py/kitti_results submission_prefix=$CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py/kitti_results \
+2>&1|tee $CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py \
+$CHECKPOINT_DIR/configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py/FULL_LOG.txt &
+
+echo 'configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION hv_second_secfpn_6x8_80e_kitti-3d-3class configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py \
+$CHECKPOINT_DIR/configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py/latest.pth --format-only --eval-options jsonfile_prefix=$CHECKPOINT_DIR/configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py/results_challenge csv_savepath=$CHECKPOINT_DIR/configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py/results_challenge.csv \
+2>&1|tee $CHECKPOINT_DIR/configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py/FULL_LOG.txt &
+
+echo 'configs/votenet/votenet_8x8_scannet-3d-18class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/votenet/votenet_8x8_scannet-3d-18class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_test.sh $PARTITION votenet_8x8_scannet-3d-18class configs/votenet/votenet_8x8_scannet-3d-18class.py \
+$CHECKPOINT_DIR/configs/votenet/votenet_8x8_scannet-3d-18class.py/latest.pth --eval map \
+2>&1|tee $CHECKPOINT_DIR/configs/votenet/votenet_8x8_scannet-3d-18class.py/FULL_LOG.txt &

docker-hub/FlashOCC/Flashocc/mmdetection3d/.dev_scripts/train_benchmark.sh

+PARTITION=$1
+CHECKPOINT_DIR=$2
+
+echo 'configs/3dssd/3dssd_4x4_kitti-3d-car.py' &
+mkdir -p $CHECKPOINT_DIR/configs/3dssd/3dssd_4x4_kitti-3d-car.py
+GPUS=4 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION 3dssd_4x4_kitti-3d-car configs/3dssd/3dssd_4x4_kitti-3d-car.py \
+$CHECKPOINT_DIR/configs/3dssd/3dssd_4x4_kitti-3d-car.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/3dssd/3dssd_4x4_kitti-3d-car.py/FULL_LOG.txt &
+
+echo 'configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py' &
+mkdir -p $CHECKPOINT_DIR/configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py \
+$CHECKPOINT_DIR/configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py/FULL_LOG.txt &
+
+echo 'configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py \
+$CHECKPOINT_DIR/configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py/FULL_LOG.txt &
+
+echo 'configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py \
+$CHECKPOINT_DIR/configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py/FULL_LOG.txt &
+
+echo 'configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py' &
+mkdir -p $CHECKPOINT_DIR/configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py
+GPUS=4 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION groupfree3d_8x4_scannet-3d-18class-L6-O256 configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py \
+$CHECKPOINT_DIR/configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py/FULL_LOG.txt &
+
+echo 'configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION h3dnet_3x8_scannet-3d-18class configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py \
+$CHECKPOINT_DIR/configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py/FULL_LOG.txt &
+
+echo 'configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py
+GPUS=4 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py \
+$CHECKPOINT_DIR/configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py/FULL_LOG.txt &
+
+echo 'configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION imvotenet_stage2_16x8_sunrgbd-3d-10class configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py \
+$CHECKPOINT_DIR/configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py/FULL_LOG.txt &
+
+echo 'configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py' &
+mkdir -p $CHECKPOINT_DIR/configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION imvoxelnet_4x8_kitti-3d-car configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py \
+$CHECKPOINT_DIR/configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py/FULL_LOG.txt &
+
+echo 'configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py
+GPUS=2 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py \
+$CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_80e_s3dis_seg-3d-13class.py/FULL_LOG.txt &
+
+echo 'configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py
+GPUS=2 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py \
+$CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/pointnet2/pointnet2_msg_16x2_cosine_250e_scannet_seg-3d-20class.py/FULL_LOG.txt &
+
+echo 'configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py \
+$CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py/FULL_LOG.txt &
+
+echo 'configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py
+GPUS=16 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py \
+$CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py \
+$CHECKPOINT_DIR/configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py/FULL_LOG.txt &
+
+echo 'configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION hv_second_secfpn_6x8_80e_kitti-3d-3class configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py \
+$CHECKPOINT_DIR/configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py/FULL_LOG.txt &
+
+echo 'configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py' &
+mkdir -p $CHECKPOINT_DIR/configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py
+GPUS=16 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py \
+$CHECKPOINT_DIR/configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py/FULL_LOG.txt &
+
+echo 'configs/votenet/votenet_8x8_scannet-3d-18class.py' &
+mkdir -p $CHECKPOINT_DIR/configs/votenet/votenet_8x8_scannet-3d-18class.py
+GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=5 ./tools/slurm_train.sh $PARTITION votenet_8x8_scannet-3d-18class configs/votenet/votenet_8x8_scannet-3d-18class.py \
+$CHECKPOINT_DIR/configs/votenet/votenet_8x8_scannet-3d-18class.py --cfg-options checkpoint_config.max_keep_ckpts=1 \
+2>&1|tee $CHECKPOINT_DIR/configs/votenet/votenet_8x8_scannet-3d-18class.py/FULL_LOG.txt &

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/CODE_OF_CONDUCT.md

+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, sex characteristics, gender identity and expression,
+level of experience, education, socio-economic status, nationality, personal
+appearance, race, religion, or sexual identity and orientation.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+- Using welcoming and inclusive language
+- Being respectful of differing viewpoints and experiences
+- Gracefully accepting constructive criticism
+- Focusing on what is best for the community
+- Showing empathy towards other community members
+
+Examples of unacceptable behavior by participants include:
+
+- The use of sexualized language or imagery and unwelcome sexual attention or
+  advances
+- Trolling, insulting/derogatory comments, and personal or political attacks
+- Public or private harassment
+- Publishing others' private information, such as a physical or electronic
+  address, without explicit permission
+- Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned to this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project e-mail
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the project team at chenkaidev@gmail.com. All
+complaints will be reviewed and investigated and will result in a response that
+is deemed necessary and appropriate to the circumstances. The project team is
+obligated to maintain confidentiality with regard to the reporter of an incident.
+Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
+
+For answers to common questions about this code of conduct, see
+https://www.contributor-covenant.org/faq
+
+[homepage]: https://www.contributor-covenant.org

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/CONTRIBUTING.md

+We appreciate all contributions to improve MMDetection3D. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmcv/blob/master/CONTRIBUTING.md) in MMCV for more details about the contributing guideline.

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/ISSUE_TEMPLATE/config.yml

+blank_issues_enabled: false

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/ISSUE_TEMPLATE/error-report.md

+---
+name: Error report
+about: Create a report to help us improve
+title: ''
+labels: ''
+assignees: ''
+---
+
+Thanks for your error report and we appreciate it a lot.
+
+**Checklist**
+
+1. I have searched related issues but cannot get the expected help.
+2. The bug has not been fixed in the latest version.
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**Reproduction**
+
+1. What command or script did you run?
+
+```
+A placeholder for the command.
+```
+
+2. Did you make any modifications on the code or config? Did you understand what you have modified?
+3. What dataset did you use?
+
+**Environment**
+
+1. Please run `python mmdet3d/utils/collect_env.py` to collect necessary environment information and paste it here.
+2. You may add addition that may be helpful for locating the problem, such as
+   - How you installed PyTorch \[e.g., pip, conda, source\]
+   - Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
+
+**Error traceback**
+If applicable, paste the error trackback here.
+
+```
+A placeholder for trackback.
+```
+
+**Bug fix**
+If you have already identified the reason, you can provide the information here. If you are willing to create a PR to fix it, please also leave a comment here and that would be much appreciated!

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/ISSUE_TEMPLATE/feature_request.md

+---
+name: Feature request
+about: Suggest an idea for this project
+title: ''
+labels: ''
+assignees: ''
+---
+
+**Describe the feature**
+
+**Motivation**
+A clear and concise description of the motivation of the feature.
+Ex1. It is inconvenient when \[....\].
+Ex2. There is a recent paper \[....\], which is very helpful for \[....\].
+
+**Related resources**
+If there is an official code release or third-party implementations, please also provide the information here, which would be very helpful.
+
+**Additional context**
+Add any other context or screenshots about the feature request here.
+If you would like to implement the feature and create a PR, please leave a comment here and that would be much appreciated.

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/ISSUE_TEMPLATE/general_questions.md

+---
+name: General questions
+about: Ask general questions to get help
+title: ''
+labels: ''
+assignees: ''
+---

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/ISSUE_TEMPLATE/reimplementation_questions.md

+---
+name: Reimplementation Questions
+about: Ask about questions during model reimplementation
+title: ''
+labels: reimplementation
+assignees: ''
+---
+
+**Notice**
+
+There are several common situations in the reimplementation issues as below
+
+1. Reimplement a model in the model zoo using the provided configs
+2. Reimplement a model in the model zoo on other dataset (e.g., custom datasets)
+3. Reimplement a custom model but all the components are implemented in MMDetection3D
+4. Reimplement a custom model with new modules implemented by yourself
+
+There are several things to do for different cases as below.
+
+- For case 1 & 3, please follow the steps in the following sections thus we could help to quick identify the issue.
+- For case 2 & 4, please understand that we are not able to do much help here because we usually do not know the full code and the users should be responsible to the code they write.
+- One suggestion for case 2 & 4 is that the users should first check whether the bug lies in the self-implemted code or the original code. For example, users can first make sure that the same model runs well on supported datasets. If you still need help, please describe what you have done and what you obtain in the issue, and follow the steps in the following sections and try as clear as possible so that we can better help you.
+
+**Checklist**
+
+1. I have searched related issues but cannot get the expected help.
+2. The issue has not been fixed in the latest version.
+
+**Describe the issue**
+
+A clear and concise description of what the problem you meet and what have you done.
+
+**Reproduction**
+
+1. What command or script did you run?
+
+```
+A placeholder for the command.
+```
+
+2. What config dir you run?
+
+```
+A placeholder for the config.
+```
+
+3. Did you make any modifications on the code or config? Did you understand what you have modified?
+4. What dataset did you use?
+
+**Environment**
+
+1. Please run `python mmdet3d/utils/collect_env.py` to collect necessary environment information and paste it here.
+2. You may add addition that may be helpful for locating the problem, such as
+   - How you installed PyTorch \[e.g., pip, conda, source\]
+   - Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
+
+**Results**
+
+If applicable, paste the related results here, e.g., what you expect and what you get.
+
+```
+A placeholder for results comparison
+```
+
+**Issue fix**
+
+If you have already identified the reason, you can provide the information here. If you are willing to create a PR to fix it, please also leave a comment here and that would be much appreciated!

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/pull_request_template.md

+Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers.
+
+## Motivation
+
+Please describe the motivation of this PR and the goal you want to achieve through this PR.
+
+## Modification
+
+Please briefly describe what modification is made in this PR.
+
+## BC-breaking (Optional)
+
+Does the modification introduce changes that break the back-compatibility of the downstream repos?
+If so, please describe how it breaks the compatibility and how the downstream projects should modify their code to keep compatibility with this PR.
+
+## Use cases (Optional)
+
+If this PR introduces a new feature, it is better to list some use cases here, and update the documentation.
+
+## Checklist
+
+1. Pre-commit or other linting tools are used to fix the potential lint issues.
+2. The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
+3. If the modification has potential influence on downstream projects, this PR should be tested with downstream projects.
+4. The documentation has been modified accordingly, like docstring or example tutorials.

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/workflows/build.yml

+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: build
+
+on:
+  push:
+    paths-ignore:
+      - ".dev_scripts/**"
+      - ".github/**.md"
+      - "demo/**"
+      - "docker/**"
+      - "tools/**"
+
+  pull_request:
+    paths-ignore:
+      - ".dev_scripts/**"
+      - ".github/**.md"
+      - "demo/**"
+      - "docker/**"
+      - "tools/**"
+      - "docs/**"
+      - "docs_zh-CN/**"
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  build:
+    env:
+      FORCE_CUDA: 1
+      CUDA_ARCH: ${{matrix.cuda_arch}}
+    runs-on: ubuntu-18.04
+    container:
+      image: pytorch/pytorch:1.6.0-cuda10.1-cudnn7-devel
+
+    strategy:
+      matrix:
+        python-version: [3.6, 3.7]
+        torch: [1.5.0+cu101, 1.6.0+cu101, 1.7.0+cu101, 1.8.0+cu101]
+        include:
+          - torch: 1.5.0+cu101
+            torch_version: torch1.5
+            torchvision: 0.6.0+cu101
+            mmcv_link: "torch1.5.0"
+            cuda_arch: "7.0"
+          - torch: 1.6.0+cu101
+            torch_version: torch1.6
+            mmcv_link: "torch1.6.0"
+            torchvision: 0.7.0+cu101
+            cuda_arch: "7.0"
+          - torch: 1.7.0+cu101
+            torch_version: torch1.7
+            mmcv_link: "torch1.7.0"
+            torchvision: 0.8.1+cu101
+            cuda_arch: "7.0"
+          - torch: 1.8.0+cu101
+            torch_version: torch1.8
+            mmcv_link: "torch1.8.0"
+            torchvision: 0.9.0+cu101
+            cuda_arch: "7.0"
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Fetch GPG keys
+        run: |
+          apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
+          apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
+      - name: Install system dependencies
+        run: |
+          apt-get update && apt-get install -y ffmpeg libsm6 git ninja-build libglib2.0-0 libsm6 libxrender-dev python${{matrix.python-version}}-dev
+          apt-get clean
+          rm -rf /var/lib/apt/lists/*
+      - name: Install PyTorch
+        run: python -m pip install numpy==1.19.5 torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Install mmdet3d dependencies
+        run: |
+          python -m pip install mmcv-full==1.6.0 -f https://download.openmmlab.com/mmcv/dist/cu101/${{matrix.torch_version}}/index.html
+          python -m pip install mmdet
+          python -m pip install mmsegmentation
+          python -m pip install -r requirements.txt
+      - name: Build and install
+        run: |
+          rm -rf .eggs
+          python setup.py check -m -s
+          TORCH_CUDA_ARCH_LIST=${CUDA_ARCH} python setup.py build_ext --inplace
+      - name: Run unittests and generate coverage report
+        run: |
+          coverage run --branch --source mmdet3d -m pytest tests/
+          coverage xml
+          coverage report -m
+      # Only upload coverage report for python3.7 && pytorch1.5
+      - name: Upload coverage to Codecov
+        if: ${{matrix.torch == '1.5.0+cu101' && matrix.python-version == '3.7'}}
+        uses: codecov/codecov-action@v1.0.10
+        with:
+          file: ./coverage.xml
+          flags: unittests
+          env_vars: OS,PYTHON
+          name: codecov-umbrella
+          fail_ci_if_error: false
+
+  build_windows:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [windows-2022]
+        python: [3.8]
+        platform: [cpu]
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python }}
+      - name: Upgrade pip
+        run: python -m pip install pip --upgrade --user
+      - name: Install PyTorch
+        # As a complement to Linux CI, we test on PyTorch LTS version
+        run: pip install torch==1.8.2+${{ matrix.platform }} torchvision==0.9.2+${{ matrix.platform }} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
+      - name: Install mmdet3d dependencies
+        run: |
+          pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8/index.html --only-binary mmcv-full
+          python -m pip install mmdet
+          python -m pip install mmsegmentation
+          python -m pip install -r requirements/build.txt -r requirements/runtime.txt -r requirements/tests.txt
+      - name: Build and install
+        run: pip install -e .
+      - name: Run unittests and generate coverage report
+        run: coverage run --branch --source mmdet3d -m pytest tests/
+      - name: Generate coverage report
+        run: |
+          coverage xml
+          coverage report -m
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v2
+        with:
+          file: ./coverage.xml
+          flags: unittests
+          env_vars: OS,PYTHON
+          name: codecov-umbrella
+          fail_ci_if_error: false

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/workflows/deploy.yml

+name: deploy
+
+on: push
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  build-n-publish:
+    runs-on: ubuntu-18.04
+    if: startsWith(github.event.ref, 'refs/tags')
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.7
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.7
+      - name: Install torch
+        run: pip install torch
+      - name: Build MMDet3D
+        run: python setup.py sdist
+      - name: Publish distribution to PyPI
+        run: |
+          pip install twine
+          twine upload dist/* -u __token__ -p ${{ secrets.pypi_password }}

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/workflows/lint.yml

+name: lint
+
+on: [push, pull_request]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  lint:
+    runs-on: ubuntu-18.04
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.7
+        uses: actions/setup-python@v1
+        with:
+          python-version: 3.7
+      - name: Install linting dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install flake8==3.8.3 isort==5.10.1 yapf==v0.30.0 interrogate
+      - name: Lint with flake8
+        run: flake8 .
+      - name: Lint with isort
+        run: isort --recursive --check-only --diff mmdet3d/ tests/ examples/
+      - name: Format python codes with yapf
+        run: yapf -r -d mmdet3d/ tests/ examples/
+      - name: Check docstring
+        run: interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --exclude mmdet3d/ops --ignore-regex "__repr__" --fail-under 95 mmdet3d

docker-hub/FlashOCC/Flashocc/mmdetection3d/.github/workflows/test_mim.yml

+name: test-mim
+
+on:
+  push:
+    paths:
+      - 'model-index.yml'
+      - 'configs/**'
+
+  pull_request:
+    paths:
+      - 'model-index.yml'
+      - 'configs/**'
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  build_cpu:
+    runs-on: ubuntu-18.04
+    strategy:
+      matrix:
+        python-version: [3.7]
+        torch: [1.8.0]
+        include:
+          - torch: 1.8.0
+            torch_version: torch1.8
+            torchvision: 0.9.0
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Upgrade pip
+        run: pip install pip --upgrade
+      - name: Install Pillow
+        run: pip install Pillow==6.2.2
+        if: ${{matrix.torchvision == '0.4.2'}}
+      - name: Install PyTorch
+        run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Install openmim
+        run: pip install openmim
+      - name: Build and install
+        run: rm -rf .eggs && mim install -e .
+      - name: test commands of mim
+        run: mim search mmdet3d

docker-hub/FlashOCC/Flashocc/mmdetection3d/.gitignore

+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+*.ipynb
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/en/_build/
+docs/zh_cn/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+# cython generated cpp
+data
+.vscode
+.idea
+
+# custom
+*.pkl
+*.pkl.json
+*.log.json
+work_dirs/
+exps/
+*~
+mmdet3d/.mim
+
+# Pytorch
+*.pth
+
+# demo
+*.jpg
+*.png
+data/s3dis/Stanford3dDataset_v1.2_Aligned_Version/
+data/scannet/scans/
+data/sunrgbd/OFFICIAL_SUNRGBD/
+*.obj
+*.ply
+
+# Waymo evaluation
+mmdet3d/core/evaluation/waymo_utils/compute_detection_metrics_main

docker-hub/FlashOCC/Flashocc/mmdetection3d/.pre-commit-config.yaml

+repos:
+  - repo: https://github.com/PyCQA/flake8
+    rev: 3.8.3
+    hooks:
+      - id: flake8
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.10.1
+    hooks:
+      - id: isort
+  - repo: https://github.com/pre-commit/mirrors-yapf
+    rev: v0.30.0
+    hooks:
+      - id: yapf
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v3.1.0
+    hooks:
+      - id: trailing-whitespace
+      - id: check-yaml
+      - id: end-of-file-fixer
+      - id: requirements-txt-fixer
+      - id: double-quote-string-fixer
+      - id: check-merge-conflict
+      - id: fix-encoding-pragma
+        args: ["--remove"]
+      - id: mixed-line-ending
+        args: ["--fix=lf"]
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.1.0
+    hooks:
+      - id: codespell
+  - repo: https://github.com/executablebooks/mdformat
+    rev: 0.7.9
+    hooks:
+      - id: mdformat
+        args: [ "--number" ]
+        additional_dependencies:
+          - mdformat-openmmlab
+          - mdformat_frontmatter
+          - linkify-it-py
+  - repo: https://github.com/myint/docformatter
+    rev: v1.3.1
+    hooks:
+      - id: docformatter
+        args: ["--in-place", "--wrap-descriptions", "79"]
+  - repo: https://github.com/open-mmlab/pre-commit-hooks
+    rev: v0.2.0  # Use the ref you want to point at
+    hooks:
+      - id: check-algo-readme
+      - id: check-copyright
+        args: ["mmdet3d"]  # replace the dir_to_check with your expected directory to check