Fix training runtime bug

configs/kitti/dv_second_secfpn_6x8_80e_kitti-3d-car.py

@@ -194,7 +194,7 @@ log_config = dict(
 # yapf:enable
 # runtime settings
 total_epochs = 80
-dist_params = dict(backend='nccl', port=29511)
+dist_params = dict(backend='nccl')
 log_level = 'INFO'
 work_dir = './work_dirs/sec_secfpn_80e'
 load_from = None

mmdet3d/apis/train.py

@@ -2,11 +2,11 @@ import torch
 from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
 from mmcv.runner import DistSamplerSeedHook, Runner
 
+from mmdet3d.utils import get_root_logger
 from mmdet.apis.train import parse_losses
 from mmdet.core import (DistEvalHook, DistOptimizerHook, EvalHook,
                         Fp16OptimizerHook, build_optimizer)
 from mmdet.datasets import build_dataloader, build_dataset
-from mmdet.utils import get_root_logger
 
 
 def batch_processor(model, data, train_mode):

mmdet3d/core/optimizer/cocktail_constructor.py

 from mmcv.utils import build_from_cfg
 
+from mmdet3d.utils import get_root_logger
 from mmdet.core.optimizer import OPTIMIZER_BUILDERS, OPTIMIZERS
-from mmdet.utils import get_root_logger
 from .cocktail_optimizer import CocktailOptimizer
 
 

mmdet3d/datasets/pipelines/dbsampler.py

@@ -68,7 +68,7 @@ class DataBaseSampler(object):
             db_infos = pickle.load(f)
 
         # filter database infos
-        from mmdet.apis import get_root_logger
+        from mmdet3d.utils import get_root_logger
         logger = get_root_logger()
         for k, v in db_infos.items():
             logger.info(f'load {len(v)} {k} database infos')

mmdet3d/models/backbones/second.py

@@ -72,7 +72,7 @@ class SECOND(nn.Module):
 
     def init_weights(self, pretrained=None):
         if isinstance(pretrained, str):
-            from mmdet3d.apis import get_root_logger
+            from mmdet3d.utils import get_root_logger
             logger = get_root_logger()
             load_checkpoint(self, pretrained, strict=False, logger=logger)
 

mmdet3d/models/detectors/base.py

@@ -59,7 +59,7 @@ class BaseDetector(nn.Module, metaclass=ABCMeta):
 
     def init_weights(self, pretrained=None):
         if pretrained is not None:
-            from mmdet3d.apis import get_root_logger
+            from mmdet3d.utils import get_root_logger
             logger = get_root_logger()
             logger.info('load model from: {}'.format(pretrained))