[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

configs/_base_/models/3dssd.py

@@ -65,17 +65,16 @@ model = dict(
             type='SmoothL1Loss', reduction='sum', loss_weight=1.0),
         corner_loss=dict(
             type='SmoothL1Loss', reduction='sum', loss_weight=1.0),
-        vote_loss=dict(type='SmoothL1Loss', reduction='sum', loss_weight=1.0)))
-
-# model training and testing settings
-train_cfg = dict(
-    sample_mod='spec', pos_distance_thr=10.0, expand_dims_length=0.05)
-test_cfg = dict(
+        vote_loss=dict(type='SmoothL1Loss', reduction='sum', loss_weight=1.0)),
+    # model training and testing settings
+    train_cfg=dict(
+        sample_mod='spec', pos_distance_thr=10.0, expand_dims_length=0.05),
+    test_cfg=dict(
         nms_cfg=dict(type='nms', iou_thr=0.1),
         sample_mod='spec',
         score_thr=0.0,
         per_class_proposal=True,
-    max_output_num=100)
+        max_output_num=100))
 
 # optimizer
 # This schedule is mainly used by models on indoor dataset,

configs/_base_/models/cascade_mask_rcnn_r50_fpn.py

@@ -105,9 +105,9 @@ model = dict(
             conv_out_channels=256,
             num_classes=80,
             loss_mask=dict(
-                type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))))
-# model training and testing settings
-train_cfg = dict(
+                type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))),
+    # model training and testing settings
+    train_cfg=dict(
         rpn=dict(
             assigner=dict(
                 type='MaxIoUAssigner',
@@ -184,8 +184,8 @@ train_cfg = dict(
                 mask_size=28,
                 pos_weight=-1,
                 debug=False)
-    ])
-test_cfg = dict(
+        ]),
+    test_cfg=dict(
         rpn=dict(
             nms_across_levels=False,
             nms_pre=1000,
@@ -197,4 +197,4 @@ test_cfg = dict(
             score_thr=0.05,
             nms=dict(type='nms', iou_threshold=0.5),
             max_per_img=100,
-        mask_thr_binary=0.5))
+            mask_thr_binary=0.5)))

configs/_base_/models/centerpoint_01voxel_second_secfpn_nus.py

@@ -56,9 +56,9 @@ model = dict(
             type='SeparateHead', init_bias=-2.19, final_kernel=3),
         loss_cls=dict(type='GaussianFocalLoss', reduction='mean'),
         loss_bbox=dict(type='L1Loss', reduction='mean', loss_weight=0.25),
-        norm_bbox=True))
-# model training and testing settings
-train_cfg = dict(
+        norm_bbox=True),
+    # model training and testing settings
+    train_cfg=dict(
         pts=dict(
             grid_size=[1024, 1024, 40],
             voxel_size=voxel_size,
@@ -67,8 +67,8 @@ train_cfg = dict(
             gaussian_overlap=0.1,
             max_objs=500,
             min_radius=2,
-        code_weights=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]))
-test_cfg = dict(
+            code_weights=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2])),
+    test_cfg=dict(
         pts=dict(
             post_center_limit_range=[-61.2, -61.2, -10.0, 61.2, 61.2, 10.0],
             max_per_img=500,
@@ -80,4 +80,4 @@ test_cfg = dict(
             nms_type='rotate',
             pre_max_size=1000,
             post_max_size=83,
-        nms_thr=0.2))
+            nms_thr=0.2)))

configs/_base_/models/centerpoint_02pillar_second_secfpn_nus.py

@@ -55,9 +55,9 @@ model = dict(
             type='SeparateHead', init_bias=-2.19, final_kernel=3),
         loss_cls=dict(type='GaussianFocalLoss', reduction='mean'),
         loss_bbox=dict(type='L1Loss', reduction='mean', loss_weight=0.25),
-        norm_bbox=True))
-# model training and testing settings
-train_cfg = dict(
+        norm_bbox=True),
+    # model training and testing settings
+    train_cfg=dict(
         pts=dict(
             grid_size=[512, 512, 1],
             voxel_size=voxel_size,
@@ -66,8 +66,8 @@ train_cfg = dict(
             gaussian_overlap=0.1,
             max_objs=500,
             min_radius=2,
-        code_weights=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]))
-test_cfg = dict(
+            code_weights=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2])),
+    test_cfg=dict(
         pts=dict(
             post_center_limit_range=[-61.2, -61.2, -10.0, 61.2, 61.2, 10.0],
             max_per_img=500,
@@ -80,4 +80,4 @@ test_cfg = dict(
             nms_type='rotate',
             pre_max_size=1000,
             post_max_size=83,
-        nms_thr=0.2))
+            nms_thr=0.2)))

configs/_base_/models/h3dnet.py

@@ -311,11 +311,11 @@ model = dict(
                 reduction='none',
                 loss_weight=5.0),
             primitive_center_loss=dict(
-                type='MSELoss', reduction='none', loss_weight=1.0))))
-
-# model training and testing settings
-train_cfg = dict(
-    rpn=dict(pos_distance_thr=0.3, neg_distance_thr=0.6, sample_mod='vote'),
+                type='MSELoss', reduction='none', loss_weight=1.0))),
+    # model training and testing settings
+    train_cfg=dict(
+        rpn=dict(
+            pos_distance_thr=0.3, neg_distance_thr=0.6, sample_mod='vote'),
         rpn_proposal=dict(use_nms=False),
         rcnn=dict(
             pos_distance_thr=0.3,
@@ -326,9 +326,8 @@ train_cfg = dict(
             mask_surface_threshold=0.3,
             label_surface_threshold=0.3,
             mask_line_threshold=0.3,
-        label_line_threshold=0.3))
-
-test_cfg = dict(
+            label_line_threshold=0.3)),
+    test_cfg=dict(
         rpn=dict(
             sample_mod='seed',
             nms_thr=0.25,
@@ -339,4 +338,4 @@ test_cfg = dict(
             sample_mod='seed',
             nms_thr=0.25,
             score_thr=0.05,
-        per_class_proposal=True))
+            per_class_proposal=True)))

configs/_base_/models/hv_pointpillars_fpn_lyft.py

@@ -17,6 +17,6 @@ model = dict(
         num_classes=9,
         anchor_generator=dict(
             ranges=[[-80, -80, -1.8, 80, 80, -1.8]], custom_values=[]),
-        bbox_coder=dict(type='DeltaXYZWLHRBBoxCoder', code_size=7)))
-# model training settings (based on nuScenes model settings)
-train_cfg = dict(pts=dict(code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]))
+        bbox_coder=dict(type='DeltaXYZWLHRBBoxCoder', code_size=7)),
+    # model training settings (based on nuScenes model settings)
+    train_cfg=dict(pts=dict(code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0])))

configs/_base_/models/hv_pointpillars_fpn_nus.py

@@ -70,9 +70,9 @@ model = dict(
             loss_weight=1.0),
         loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0),
         loss_dir=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)))
-# model training and testing settings
-train_cfg = dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)),
+    # model training and testing settings
+    train_cfg=dict(
         pts=dict(
             assigner=dict(
                 type='MaxIoUAssigner',
@@ -84,8 +84,8 @@ train_cfg = dict(
             allowed_border=0,
             code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2],
             pos_weight=-1,
-        debug=False))
-test_cfg = dict(
+            debug=False)),
+    test_cfg=dict(
         pts=dict(
             use_rotate_nms=True,
             nms_across_levels=False,
@@ -93,4 +93,4 @@ test_cfg = dict(
             nms_thr=0.2,
             score_thr=0.05,
             min_bbox_size=0,
-        max_num=500))
+            max_num=500)))

configs/_base_/models/hv_pointpillars_fpn_range100_lyft.py

@@ -17,6 +17,6 @@ model = dict(
         num_classes=9,
         anchor_generator=dict(
             ranges=[[-100, -100, -1.8, 100, 100, -1.8]], custom_values=[]),
-        bbox_coder=dict(type='DeltaXYZWLHRBBoxCoder', code_size=7)))
-# model training settings (based on nuScenes model settings)
-train_cfg = dict(pts=dict(code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]))
+        bbox_coder=dict(type='DeltaXYZWLHRBBoxCoder', code_size=7)),
+    # model training settings (based on nuScenes model settings)
+    train_cfg=dict(pts=dict(code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0])))

configs/_base_/models/hv_pointpillars_secfpn_kitti.py

@@ -52,9 +52,9 @@ model = dict(
             loss_weight=1.0),
         loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=2.0),
         loss_dir=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)))
-# model training and testing settings
-train_cfg = dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)),
+    # model training and testing settings
+    train_cfg=dict(
         assigner=[
             dict(  # for Pedestrian
                 type='MaxIoUAssigner',
@@ -80,12 +80,12 @@ train_cfg = dict(
         ],
         allowed_border=0,
         pos_weight=-1,
-    debug=False)
-test_cfg = dict(
+        debug=False),
+    test_cfg=dict(
         use_rotate_nms=True,
         nms_across_levels=False,
         nms_thr=0.01,
         score_thr=0.1,
         min_bbox_size=0,
         nms_pre=100,
-    max_num=50)
+        max_num=50))

configs/_base_/models/hv_pointpillars_secfpn_waymo.py

@@ -66,9 +66,9 @@ model = dict(
             loss_weight=1.0),
         loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0),
         loss_dir=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)))
-# model training and testing settings
-train_cfg = dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)),
+    # model training and testing settings
+    train_cfg=dict(
         pts=dict(
             assigner=[
                 dict(  # car
@@ -96,9 +96,8 @@ train_cfg = dict(
             allowed_border=0,
             code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
             pos_weight=-1,
-        debug=False))
-
-test_cfg = dict(
+            debug=False)),
+    test_cfg=dict(
         pts=dict(
             use_rotate_nms=True,
             nms_across_levels=False,
@@ -106,4 +105,4 @@ test_cfg = dict(
             nms_thr=0.25,
             score_thr=0.1,
             min_bbox_size=0,
-        max_num=500))
+            max_num=500)))

configs/_base_/models/hv_second_secfpn_kitti.py

@@ -48,9 +48,9 @@ model = dict(
             loss_weight=1.0),
         loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=2.0),
         loss_dir=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)))
-# model training and testing settings
-train_cfg = dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)),
+    # model training and testing settings
+    train_cfg=dict(
         assigner=[
             dict(  # for Pedestrian
                 type='MaxIoUAssigner',
@@ -76,12 +76,12 @@ train_cfg = dict(
         ],
         allowed_border=0,
         pos_weight=-1,
-    debug=False)
-test_cfg = dict(
+        debug=False),
+    test_cfg=dict(
         use_rotate_nms=True,
         nms_across_levels=False,
         nms_thr=0.01,
         score_thr=0.1,
         min_bbox_size=0,
         nms_pre=100,
-    max_num=50)
+        max_num=50))

configs/_base_/models/hv_second_secfpn_waymo.py

@@ -60,9 +60,9 @@ model = dict(
             loss_weight=1.0),
         loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0),
         loss_dir=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)))
-# model training and testing settings
-train_cfg = dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)),
+    # model training and testing settings
+    train_cfg=dict(
         assigner=[
             dict(  # car
                 type='MaxIoUAssigner',
@@ -89,13 +89,12 @@ train_cfg = dict(
         allowed_border=0,
         code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
         pos_weight=-1,
-    debug=False)
-
-test_cfg = dict(
+        debug=False),
+    test_cfg=dict(
         use_rotate_nms=True,
         nms_across_levels=False,
         nms_pre=4096,
         nms_thr=0.25,
         score_thr=0.1,
         min_bbox_size=0,
-    max_num=500)
+        max_num=500))

configs/_base_/models/mask_rcnn_r50_fpn.py

@@ -65,9 +65,9 @@ model = dict(
             conv_out_channels=256,
             num_classes=80,
             loss_mask=dict(
-                type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))))
-# model training and testing settings
-train_cfg = dict(
+                type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))),
+    # model training and testing settings
+    train_cfg=dict(
         rpn=dict(
             assigner=dict(
                 type='MaxIoUAssigner',
@@ -108,8 +108,8 @@ train_cfg = dict(
                 add_gt_as_proposals=True),
             mask_size=28,
             pos_weight=-1,
-        debug=False))
-test_cfg = dict(
+            debug=False)),
+    test_cfg=dict(
         rpn=dict(
             nms_across_levels=False,
             nms_pre=1000,
@@ -121,4 +121,4 @@ test_cfg = dict(
             score_thr=0.05,
             nms=dict(type='nms', iou_threshold=0.5),
             max_per_img=100,
-        mask_thr_binary=0.5))
+            mask_thr_binary=0.5)))

configs/_base_/models/votenet.py

@@ -62,8 +62,12 @@ model = dict(
         size_res_loss=dict(
             type='SmoothL1Loss', reduction='sum', loss_weight=10.0 / 3.0),
         semantic_loss=dict(
-            type='CrossEntropyLoss', reduction='sum', loss_weight=1.0)))
-# model training and testing settings
-train_cfg = dict(pos_distance_thr=0.3, neg_distance_thr=0.6, sample_mod='vote')
-test_cfg = dict(
-    sample_mod='seed', nms_thr=0.25, score_thr=0.05, per_class_proposal=True)
+            type='CrossEntropyLoss', reduction='sum', loss_weight=1.0)),
+    # model training and testing settings
+    train_cfg=dict(
+        pos_distance_thr=0.3, neg_distance_thr=0.6, sample_mod='vote'),
+    test_cfg=dict(
+        sample_mod='seed',
+        nms_thr=0.25,
+        score_thr=0.05,
+        per_class_proposal=True))

configs/benchmark/hv_PartA2_secfpn_4x8_cyclic_80e_pcdet_kitti-3d-3class.py

@@ -111,9 +111,9 @@ model = dict(
                 type='CrossEntropyLoss',
                 use_sigmoid=True,
                 reduction='sum',
-                loss_weight=1.0))))
-# model training and testing settings
-train_cfg = dict(
+                loss_weight=1.0))),
+    # model training and testing settings
+    train_cfg=dict(
         rpn=dict(
             assigner=[
                 dict(  # for Pedestrian
@@ -152,21 +152,24 @@ train_cfg = dict(
             assigner=[
                 dict(  # for Pedestrian
                     type='MaxIoUAssigner',
-                iou_calculator=dict(type='BboxOverlaps3D', coordinate='lidar'),
+                    iou_calculator=dict(
+                        type='BboxOverlaps3D', coordinate='lidar'),
                     pos_iou_thr=0.55,
                     neg_iou_thr=0.55,
                     min_pos_iou=0.55,
                     ignore_iof_thr=-1),
                 dict(  # for Cyclist
                     type='MaxIoUAssigner',
-                iou_calculator=dict(type='BboxOverlaps3D', coordinate='lidar'),
+                    iou_calculator=dict(
+                        type='BboxOverlaps3D', coordinate='lidar'),
                     pos_iou_thr=0.55,
                     neg_iou_thr=0.55,
                     min_pos_iou=0.55,
                     ignore_iof_thr=-1),
                 dict(  # for Car
                     type='MaxIoUAssigner',
-                iou_calculator=dict(type='BboxOverlaps3D', coordinate='lidar'),
+                    iou_calculator=dict(
+                        type='BboxOverlaps3D', coordinate='lidar'),
                     pos_iou_thr=0.55,
                     neg_iou_thr=0.55,
                     min_pos_iou=0.55,
@@ -182,8 +185,8 @@ train_cfg = dict(
                 add_gt_as_proposals=False,
                 return_iou=True),
             cls_pos_thr=0.75,
-        cls_neg_thr=0.25))
-test_cfg = dict(
+            cls_neg_thr=0.25)),
+    test_cfg=dict(
         rpn=dict(
             nms_pre=1024,
             nms_post=100,
@@ -192,7 +195,10 @@ test_cfg = dict(
             score_thr=0,
             use_rotate_nms=True),
         rcnn=dict(
-        use_rotate_nms=True, use_raw_score=True, nms_thr=0.01, score_thr=0.3))
+            use_rotate_nms=True,
+            use_raw_score=True,
+            nms_thr=0.01,
+            score_thr=0.3)))
 
 # dataset settings
 dataset_type = 'KittiDataset'

configs/benchmark/hv_pointpillars_secfpn_3x8_100e_det3d_kitti-3d-car.py

@@ -50,9 +50,9 @@ model = dict(
             loss_weight=1.0),
         loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=2.0),
         loss_dir=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)))
-# model training and testing settings
-train_cfg = dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)),
+    # model training and testing settings
+    train_cfg=dict(
         assigner=dict(
             type='MaxIoUAssigner',
             iou_calculator=dict(type='BboxOverlapsNearest3D'),
@@ -62,15 +62,15 @@ train_cfg = dict(
             ignore_iof_thr=-1),
         allowed_border=0,
         pos_weight=-1,
-    debug=False)
-test_cfg = dict(
+        debug=False),
+    test_cfg=dict(
         use_rotate_nms=True,
         nms_across_levels=False,
         nms_thr=0.01,
         score_thr=0.1,
         min_bbox_size=0,
         nms_pre=100,
-    max_num=50)
+        max_num=50))
 
 # dataset settings
 dataset_type = 'KittiDataset'

configs/benchmark/hv_pointpillars_secfpn_4x8_80e_pcdet_kitti-3d-3class.py

@@ -63,9 +63,8 @@ model = dict(
         loss_dir=dict(
             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2),
     ),
-)
-# model training and testing settings
-train_cfg = dict(
+    # model training and testing settings
+    train_cfg=dict(
         assigner=[
             dict(  # for Pedestrian
                 type='MaxIoUAssigner',
@@ -91,15 +90,15 @@ train_cfg = dict(
         ],
         allowed_border=0,
         pos_weight=-1,
-    debug=False)
-test_cfg = dict(
+        debug=False),
+    test_cfg=dict(
         use_rotate_nms=True,
         nms_across_levels=False,
         nms_thr=0.01,
         score_thr=0.1,
         min_bbox_size=0,
         nms_pre=100,
-    max_num=50)
+        max_num=50))
 
 # dataset settings
 dataset_type = 'KittiDataset'

configs/benchmark/hv_second_secfpn_4x8_80e_pcdet_kitti-3d-3class.py

@@ -52,9 +52,9 @@ model = dict(
             loss_weight=1.0),
         loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=2.0),
         loss_dir=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)))
-# model training and testing settings
-train_cfg = dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.2)),
+    # model training and testing settings
+    train_cfg=dict(
         assigner=[
             dict(  # for Pedestrian
                 type='MaxIoUAssigner',
@@ -80,15 +80,15 @@ train_cfg = dict(
         ],
         allowed_border=0,
         pos_weight=-1,
-    debug=False)
-test_cfg = dict(
+        debug=False),
+    test_cfg=dict(
         use_rotate_nms=True,
         nms_across_levels=False,
         nms_thr=0.01,
         score_thr=0.1,
         min_bbox_size=0,
         nms_pre=100,
-    max_num=50)
+        max_num=50))
 
 # dataset settings
 dataset_type = 'KittiDataset'

configs/centerpoint/README.md

@@ -47,10 +47,11 @@ For example, we change `centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic
 _base_ = './centerpoint_0075voxel_second_secfpn_circlenms' \
          '_4x8_cyclic_20e_nus.py'
 
-test_cfg = dict(
+model = dict(
+    test_cfg=dict(
         pts=dict(
             use_rotate_nms=True,
-        max_num=83))
+            max_num=83)))
 
 point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
 file_client_args = dict(backend='disk')

configs/centerpoint/centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py

@@ -16,16 +16,14 @@ model = dict(
     pts_middle_encoder=dict(sparse_shape=[41, 1440, 1440]),
     pts_bbox_head=dict(
         bbox_coder=dict(
-            voxel_size=voxel_size[:2], pc_range=point_cloud_range[:2])))
-
-train_cfg = dict(
+            voxel_size=voxel_size[:2], pc_range=point_cloud_range[:2])),
+    train_cfg=dict(
         pts=dict(
             grid_size=[1440, 1440, 40],
             voxel_size=voxel_size,
-        point_cloud_range=point_cloud_range))
-
-test_cfg = dict(
-    pts=dict(voxel_size=voxel_size[:2], pc_range=point_cloud_range[:2]))
+            point_cloud_range=point_cloud_range)),
+    test_cfg=dict(
+        pts=dict(voxel_size=voxel_size[:2], pc_range=point_cloud_range[:2])))
 
 dataset_type = 'NuScenesDataset'
 data_root = 'data/nuscenes/'