[Docs] Update all the metafiles acoording to README (#2006)

* update centerpoint, dgcnn, fcos3d and free_anchor metafile

* check all metafile in configs

* update centerpoint, pointpillars and second yml

* rename PartA2 to parta2 in the name of config

* update metafile in nuimages

* update readme in nuimages

configs/pointpillars/pointpillars_hv_secfpn_sbn-all_8xb4-amp-2x_nus-3d.py

+_base_ = 'pointpillars_hv_secfpn_sbn-all_8xb4-2x_nus-3d.py'
+
+# schedule settings
+optim_wrapper = dict(type='AmpOptimWrapper', loss_scale=512.)

configs/regnet/metafile.yml

 Models:
   - Name: hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d
     In Collection: PointPillars
-    Config: configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d.py
+    Config: configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_8xb4-2x_nus-3d.py
     Metadata:
       Training Data: nuScenes
       Training Memory (GB): 16.4
@@ -16,9 +16,9 @@ Models:
           NDS: 55.2
     Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d_20200620_230334-53044f32.pth
 
-  - Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d
+  - Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_8xb4-2x_nus-3d
     In Collection: PointPillars
-    Config: configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py
+    Config: configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_8xb4-2x_nus-3d.py
     Metadata:
       Training Data: nuScenes
       Training Memory (GB): 17.3
@@ -33,9 +33,9 @@ Models:
           NDS: 56.4
     Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d_20200620_230239-c694dce7.pth
 
-  - Name: hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d
+  - Name: hv_pointpillars_regnet-1.6gf_fpn_sbn-all_8xb4-2x_nus-3d
     In Collection: PointPillars
-    Config: configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py
+    Config: configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_8xb4-2x_nus-3d.py
     Metadata:
       Training Data: nuScenes
       Training Memory (GB): 24.0

configs/second/metafile.yml

@@ -14,9 +14,9 @@ Collections:
       Version: v0.5.0
 
 Models:
-  - Name: hv_second_secfpn_6x8_80e_kitti-3d-car
+  - Name: second_hv_secfpn_8xb6-80e_kitti-3d-car
     In Collection: SECOND
-    Config: configs/second/hv_second_secfpn_6x8_80e_kitti-3d-car.py
+    Config: configs/second/second_hv_secfpn_8xb6-80e_kitti-3d-car.py
     Metadata:
       Training Data: KITTI
       Training Memory (GB): 5.4
@@ -28,9 +28,9 @@ Models:
           mAP: 79.07
     Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/second/hv_second_secfpn_6x8_80e_kitti-3d-car/hv_second_secfpn_6x8_80e_kitti-3d-car_20200620_230238-393f000c.pth
 
-  - Name: hv_second_secfpn_6x8_80e_kitti-3d-3class
+  - Name: second_hv_secfpn_8xb6-80e_kitti-3d-3class
     In Collection: SECOND
-    Config: configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py
+    Config: configs/second/second_hv_secfpn_8xb6-80e_kitti-3d-3class.py
     Metadata:
       Training Data: KITTI
       Training Memory (GB): 5.4
@@ -42,9 +42,9 @@ Models:
           mAP: 65.74
     Weights: https://download.openmmlab.com/mmdetection3d/v1.0.0_models/second/hv_second_secfpn_6x8_80e_kitti-3d-3class/hv_second_secfpn_6x8_80e_kitti-3d-3class_20210831_022017-ae782e87.pth
 
-  - Name: hv_second_secfpn_sbn_2x16_2x_waymoD5-3d-3class
+  - Name: second_hv_secfpn_sbn-all_16xb2-2x_waymoD5-3d-3class
     In Collection: SECOND
-    Config: configs/second/hv_second_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py
+    Config: configs/second/second_hv_secfpn_sbn-all_16xb2-2x_waymoD5-3d-3class.py
     Metadata:
       Training Data: Waymo
       Training Memory (GB): 8.12
@@ -58,9 +58,9 @@ Models:
           mAP@L2: 58.9
           mAPH@L2: 55.7
 
-  - Name: hv_second_secfpn_fp16_6x8_80e_kitti-3d-car
+  - Name: second_hv_secfpn_8xb6-amp-80e_kitti-3d-car
     In Collection: SECOND
-    Config: configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-car.py
+    Config: configs/second/hv_second_secfpn_8xb6-amp-80e_kitti-3d-car.py
     Metadata:
       Training Techniques:
         - AdamW
@@ -77,9 +77,9 @@ Models:
     Code:
       Version: v0.7.0
 
-  - Name: hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class
+  - Name: second_hv_secfpn_8xb6-amp-80e_kitti-3d-3class
     In Collection: SECOND
-    Config: configs/second/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py
+    Config: configs/second/hv_second_secfpn_8xb6-amp-80e_kitti-3d-3class.py
     Metadata:
       Training Techniques:
         - AdamW

configs/second/second_hv_secfpn_8xb6-amp-80e_kitti-3d-3class.py

+_base_ = 'second_hv_secfpn_8xb6-80e_kitti-3d-3class.py'
+
+# schedule settings
+optim_wrapper = dict(type='AmpOptimWrapper', loss_scale=512.)

configs/second/second_hv_secfpn_8xb6-amp-80e_kitti-3d-car.py

+_base_ = 'second_hv_secfpn_8xb6-80e_kitti-3d-car.py'
+
+# schedule settings
+optim_wrapper = dict(type='AmpOptimWrapper', loss_scale=512.)

configs/smoke/metafile.yml

@@ -17,9 +17,9 @@ Collections:
       Version: v1.0.0
 
 Models:
-  - Name: smoke_dla34_pytorch_dlaneck_gn-all_8x4_6x_kitti-mono3d
+  - Name: smoke_dla34_pytorch_dlaneck_gn-all_4xb8-6x_kitti-mono3d
     In Collection: SMOKE
-    Config: configs/smoke/smoke_dla34_pytorch_dlaneck_gn-all_8x4_6x_kitti-mono3d.py
+    Config: configs/smoke/smoke_dla34_pytorch_dlaneck_gn-all_4xb8-6x_kitti-mono3d.py
     Metadata:
       Training Memory (GB): 9.6
     Results:

configs/ssn/metafile.yml

@@ -15,7 +15,7 @@ Collections:
       Version: v0.7.0
 
 Models:
-  - Name: hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d
+  - Name: hv_ssn_secfpn_sbn-all_16xb2-2x_nus-3d
     In Collection: SSN
     Config: configs/ssn/ssn_hv_secfpn_sbn-all_16xb2-2x_nus-3d.py
     Metadata:
@@ -29,7 +29,7 @@ Models:
           NDS: 54.44
     Weights: https://download.openmmlab.com/mmdetection3d/v1.0.0_models/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d/hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d_20210830_101351-51915986.pth
 
-  - Name: hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d
+  - Name: hv_ssn_regnet-400mf_secfpn_sbn-all_16xb2-2x_nus-3d
     In Collection: SSN
     Config: configs/ssn/ssn_hv_regnet-400mf_secfpn_sbn-all_16xb2-2x_nus-3d.py
     Metadata:
@@ -43,7 +43,7 @@ Models:
           NDS: 58.24
     Weights: https://download.openmmlab.com/mmdetection3d/v1.0.0_models/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d_20210829_210615-361e5e04.pth
 
-  - Name: hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d
+  - Name: hv_ssn_secfpn_sbn-all_16xb2-2x_lyft-3d
     In Collection: SSN
     Config: configs/ssn/ssn_hv_secfpn_sbn-all_16xb2-2x_lyft-3d.py
     Metadata:
@@ -57,9 +57,9 @@ Models:
           Public Score: 17.5
     Weights: https://download.openmmlab.com/mmdetection3d/v1.0.0_models/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d_20210822_134731-46841b41.pth
 
-  - Name: hv_ssn_regnet-400mf_secfpn_sbn-all_1x16_2x_lyft-3d
+  - Name: hv_ssn_regnet-400mf_secfpn_sbn-all_16xb1-2x_lyft-3d
     In Collection: SSN
-    Config: configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_1x16_2x_lyft-3d.py
+    Config: configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_16xb1-2x_lyft-3d.py
     Metadata:
       Training Data: Lyft
       Training Memory (GB): 7.4

tests/test_models/test_detectors/test_parta2.py

@@ -17,7 +17,7 @@ class TestPartA2(unittest.TestCase):
         DefaultScope.get_instance('test_parta2', scope_name='mmdet3d')
         setup_seed(0)
         parta2_cfg = get_detector_cfg(
-            'parta2/PartA2_hv_secfpn_8xb2-cyclic-80e_kitti-3d-3class.py')
+            'parta2/parta2_hv_secfpn_8xb2-cyclic-80e_kitti-3d-3class.py')
         model = MODELS.build(parta2_cfg)
         num_gt_instance = 2
         packed_inputs = create_detector_inputs(num_gt_instance=num_gt_instance)