[Enhance] Move train_cfg test_cfg to model (#307)

* Move train_cfg/test_cfg to model

* Move train_cfg/test_cfg to model

* Move train_cfg/test_cfg to model

* Move train_cfg/test_cfg to model

* Move train_cfg/test_cfg to model

* Move train_cfg/test_cfg to model

* Move train_cfg/test_cfg to model

* Move train_cfg and test_cfg into model

* modify centerpoint configs

* Modify docs

* modify build_detector

* modify test_config_build_detector

* modify build_detector parameters

* Adopt the same strategy in build_detector

mmdet3d/apis/inference.py

@@ -30,7 +30,8 @@ def init_detector(config, checkpoint=None, device='cuda:0'):
         raise TypeError('config must be a filename or Config object, '
                         f'but got {type(config)}')
     config.model.pretrained = None
-    model = build_detector(config.model, test_cfg=config.test_cfg)
+    config.model.train_cfg = None
+    model = build_detector(config.model, test_cfg=config.get('test_cfg'))
     if checkpoint is not None:
         checkpoint = load_checkpoint(model, checkpoint)
         if 'CLASSES' in checkpoint['meta']:

mmdet3d/models/builder.py

+import warnings
+
 from mmdet.models.builder import (BACKBONES, DETECTORS, HEADS, LOSSES, NECKS,
                                   ROI_EXTRACTORS, SHARED_HEADS, build)
 from .registry import FUSION_LAYERS, MIDDLE_ENCODERS, VOXEL_ENCODERS
@@ -35,6 +37,14 @@ def build_loss(cfg):
 
 def build_detector(cfg, train_cfg=None, test_cfg=None):
     """Build detector."""
+    if train_cfg is not None or test_cfg is not None:
+        warnings.warn(
+            'train_cfg and test_cfg is deprecated, '
+            'please specify them in model', UserWarning)
+    assert cfg.get('train_cfg') is None or train_cfg is None, \
+        'train_cfg specified in both outer field and model field '
+    assert cfg.get('test_cfg') is None or test_cfg is None, \
+        'test_cfg specified in both outer field and model field '
     return build(cfg, DETECTORS, dict(train_cfg=train_cfg, test_cfg=test_cfg))
 
 

tests/test_models/test_detectors.py

@@ -62,8 +62,8 @@ def _get_detector_cfg(fname):
     import mmcv
     config = _get_config_module(fname)
     model = copy.deepcopy(config.model)
-    train_cfg = mmcv.Config(copy.deepcopy(config.train_cfg))
-    test_cfg = mmcv.Config(copy.deepcopy(config.test_cfg))
+    train_cfg = mmcv.Config(copy.deepcopy(config.model.train_cfg))
+    test_cfg = mmcv.Config(copy.deepcopy(config.model.test_cfg))
 
     model.update(train_cfg=train_cfg)
     model.update(test_cfg=test_cfg)

tests/test_models/test_forward.py

@@ -40,20 +40,17 @@ def _get_detector_cfg(fname):
     These are deep copied to allow for safe modification of parameters without
     influencing other tests.
     """
-    import mmcv
     config = _get_config_module(fname)
     model = copy.deepcopy(config.model)
-    train_cfg = mmcv.Config(copy.deepcopy(config.train_cfg))
-    test_cfg = mmcv.Config(copy.deepcopy(config.test_cfg))
-    return model, train_cfg, test_cfg
+    return model
 
 
 def _test_two_stage_forward(cfg_file):
-    model, train_cfg, test_cfg = _get_detector_cfg(cfg_file)
+    model = _get_detector_cfg(cfg_file)
     model['pretrained'] = None
 
     from mmdet.models import build_detector
-    detector = build_detector(model, train_cfg=train_cfg, test_cfg=test_cfg)
+    detector = build_detector(model)
 
     input_shape = (1, 3, 256, 256)
 
@@ -107,11 +104,11 @@ def _test_two_stage_forward(cfg_file):
 
 
 def _test_single_stage_forward(cfg_file):
-    model, train_cfg, test_cfg = _get_detector_cfg(cfg_file)
+    model = _get_detector_cfg(cfg_file)
     model['pretrained'] = None
 
     from mmdet.models import build_detector
-    detector = build_detector(model, train_cfg=train_cfg, test_cfg=test_cfg)
+    detector = build_detector(model)
 
     input_shape = (1, 3, 300, 300)
     mm_inputs = _demo_mm_inputs(input_shape)

tests/test_models/test_heads/test_heads.py

@@ -52,8 +52,8 @@ def _get_head_cfg(fname):
     import mmcv
     config = _get_config_module(fname)
     model = copy.deepcopy(config.model)
-    train_cfg = mmcv.Config(copy.deepcopy(config.train_cfg))
-    test_cfg = mmcv.Config(copy.deepcopy(config.test_cfg))
+    train_cfg = mmcv.Config(copy.deepcopy(config.model.train_cfg))
+    test_cfg = mmcv.Config(copy.deepcopy(config.model.test_cfg))
 
     bbox_head = model.bbox_head
     bbox_head.update(train_cfg=train_cfg)
@@ -70,8 +70,8 @@ def _get_rpn_head_cfg(fname):
     import mmcv
     config = _get_config_module(fname)
     model = copy.deepcopy(config.model)
-    train_cfg = mmcv.Config(copy.deepcopy(config.train_cfg))
-    test_cfg = mmcv.Config(copy.deepcopy(config.test_cfg))
+    train_cfg = mmcv.Config(copy.deepcopy(config.model.train_cfg))
+    test_cfg = mmcv.Config(copy.deepcopy(config.model.test_cfg))
 
     rpn_head = model.rpn_head
     rpn_head.update(train_cfg=train_cfg.rpn)
@@ -88,8 +88,8 @@ def _get_roi_head_cfg(fname):
     import mmcv
     config = _get_config_module(fname)
     model = copy.deepcopy(config.model)
-    train_cfg = mmcv.Config(copy.deepcopy(config.train_cfg))
-    test_cfg = mmcv.Config(copy.deepcopy(config.test_cfg))
+    train_cfg = mmcv.Config(copy.deepcopy(config.model.train_cfg))
+    test_cfg = mmcv.Config(copy.deepcopy(config.model.test_cfg))
 
     roi_head = model.roi_head
     roi_head.update(train_cfg=train_cfg.rcnn)
@@ -106,8 +106,8 @@ def _get_pts_bbox_head_cfg(fname):
     import mmcv
     config = _get_config_module(fname)
     model = copy.deepcopy(config.model)
-    train_cfg = mmcv.Config(copy.deepcopy(config.train_cfg.pts))
-    test_cfg = mmcv.Config(copy.deepcopy(config.test_cfg.pts))
+    train_cfg = mmcv.Config(copy.deepcopy(config.model.train_cfg.pts))
+    test_cfg = mmcv.Config(copy.deepcopy(config.model.test_cfg.pts))
 
     pts_bbox_head = model.pts_bbox_head
     pts_bbox_head.update(train_cfg=train_cfg)
@@ -124,8 +124,8 @@ def _get_vote_head_cfg(fname):
     import mmcv
     config = _get_config_module(fname)
     model = copy.deepcopy(config.model)
-    train_cfg = mmcv.Config(copy.deepcopy(config.train_cfg))
-    test_cfg = mmcv.Config(copy.deepcopy(config.test_cfg))
+    train_cfg = mmcv.Config(copy.deepcopy(config.model.train_cfg))
+    test_cfg = mmcv.Config(copy.deepcopy(config.model.test_cfg))
 
     vote_head = model.bbox_head
     vote_head.update(train_cfg=train_cfg)

tests/test_runtime/test_apis.py

@@ -51,7 +51,8 @@ def test_single_gpu_test():
     if not torch.cuda.is_available():
         pytest.skip('test requires GPU and torch+cuda')
     cfg = _get_config_module('votenet/votenet_16x8_sunrgbd-3d-10class.py')
-    model = build_detector(cfg.model, train_cfg=None, test_cfg=cfg.test_cfg)
+    cfg.model.train_cfg = None
+    model = build_detector(cfg.model, test_cfg=cfg.get('test_cfg'))
     dataset_cfg = cfg.data.test
     dataset_cfg.data_root = './tests/data/sunrgbd'
     dataset_cfg.ann_file = 'tests/data/sunrgbd/sunrgbd_infos.pkl'

tests/test_runtime/test_config.py

@@ -38,18 +38,15 @@ def test_config_build_detector():
         config_mod = Config.fromfile(config_fpath)
 
         config_mod.model
-        config_mod.train_cfg
-        config_mod.test_cfg
+        config_mod.model.train_cfg
+        config_mod.model.test_cfg
         print('Building detector, config_fpath = {!r}'.format(config_fpath))
 
         # Remove pretrained keys to allow for testing in an offline environment
         if 'pretrained' in config_mod.model:
             config_mod.model['pretrained'] = None
 
-        detector = build_detector(
-            config_mod.model,
-            train_cfg=config_mod.train_cfg,
-            test_cfg=config_mod.test_cfg)
+        detector = build_detector(config_mod.model)
         assert detector is not None
 
         if 'roi_head' in config_mod.model.keys():

tools/benchmark.py

@@ -48,7 +48,8 @@ def main():
         shuffle=False)
 
     # build the model and load checkpoint
-    model = build_detector(cfg.model, train_cfg=None, test_cfg=cfg.test_cfg)
+    cfg.model.train_cfg = None
+    model = build_detector(cfg.model, test_cfg=cfg.get('test_cfg'))
     fp16_cfg = cfg.get('fp16', None)
     if fp16_cfg is not None:
         wrap_fp16_model(model)

tools/convert_votenet_checkpoints.py

@@ -77,7 +77,10 @@ def main():
     checkpoint = torch.load(args.checkpoint)
     cfg = parse_config(checkpoint['meta']['config'])
     # Build the model and load checkpoint
-    model = build_detector(cfg.model, train_cfg=None, test_cfg=cfg.test_cfg)
+    model = build_detector(
+        cfg.model,
+        train_cfg=cfg.get('train_cfg'),
+        test_cfg=cfg.get('test_cfg'))
     orig_ckpt = checkpoint['state_dict']
     converted_ckpt = orig_ckpt.copy()
 

tools/test.py

@@ -111,7 +111,8 @@ def main():
         shuffle=False)
 
     # build the model and load checkpoint
-    model = build_detector(cfg.model, train_cfg=None, test_cfg=cfg.test_cfg)
+    cfg.model.train_cfg = None
+    model = build_detector(cfg.model, test_cfg=cfg.get('test_cfg'))
     fp16_cfg = cfg.get('fp16', None)
     if fp16_cfg is not None:
         wrap_fp16_model(model)

tools/train.py

@@ -136,7 +136,10 @@ def main():
     meta['seed'] = args.seed
 
     model = build_detector(
-        cfg.model, train_cfg=cfg.train_cfg, test_cfg=cfg.test_cfg)
+        cfg.model,
+        train_cfg=cfg.get('train_cfg'),
+        test_cfg=cfg.get('test_cfg'))
+
     logger.info(f'Model:\n{model}')
     datasets = [build_dataset(cfg.data.train)]
     if len(cfg.workflow) == 2: