[Fix] Fix RegNet pretrained weight loading (#889)

* Fix regnet pretrained weight loading

* Remove unused file

configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py

 _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
 
 model = dict(
-    pretrained=dict(pts='open-mmlab://regnetx_1.6gf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch='regnetx_1.6gf',
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_1.6gf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py

 _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
 
 model = dict(
-    pretrained=dict(pts='open-mmlab://regnetx_1.6gf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch='regnetx_1.6gf',
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_1.6gf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py

 _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
 
 model = dict(
-    pretrained=dict(pts='open-mmlab://regnetx_3.2gf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch='regnetx_3.2gf',
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_3.2gf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py

 _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
 
 model = dict(
-    pretrained=dict(pts='open-mmlab://regnetx_3.2gf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch='regnetx_3.2gf',
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_3.2gf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/free_anchor/hv_pointpillars_regnet-400mf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py

 _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
 
 model = dict(
-    pretrained=dict(pts='open-mmlab://regnetx_400mf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch='regnetx_400mf',
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_400mf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py

@@ -7,11 +7,12 @@ _base_ = [
 # model settings
 model = dict(
     type='MVXFasterRCNN',
-    pretrained=dict(pts='open-mmlab://regnetx_1.6gf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch='regnetx_1.6gf',
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_1.6gf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d.py

@@ -7,11 +7,12 @@ _base_ = [
 # model settings
 model = dict(
     type='MVXFasterRCNN',
-    pretrained=dict(pts='open-mmlab://regnetx_400mf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch=dict(w0=24, wa=24.48, wm=2.54, group_w=16, depth=22, bot_mul=1.0),
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_400mf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py

@@ -7,11 +7,12 @@ _base_ = [
 # model settings
 model = dict(
     type='MVXFasterRCNN',
-    pretrained=dict(pts='open-mmlab://regnetx_400mf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch=dict(w0=24, wa=24.48, wm=2.54, group_w=16, depth=22, bot_mul=1.0),
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_400mf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_range100_2x8_2x_lyft-3d.py

@@ -7,11 +7,12 @@ _base_ = [
 # model settings
 model = dict(
     type='MVXFasterRCNN',
-    pretrained=dict(pts='open-mmlab://regnetx_400mf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch=dict(w0=24, wa=24.48, wm=2.54, group_w=16, depth=22, bot_mul=1.0),
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_400mf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_1x16_2x_lyft-3d.py

@@ -2,11 +2,12 @@ _base_ = './hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py'
 # model settings
 model = dict(
     type='MVXFasterRCNN',
-    pretrained=dict(pts='open-mmlab://regnetx_400mf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch=dict(w0=24, wa=24.48, wm=2.54, group_w=16, depth=22, bot_mul=1.0),
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_400mf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d.py

@@ -2,11 +2,12 @@ _base_ = './hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d.py'
 # model settings
 model = dict(
     type='MVXFasterRCNN',
-    pretrained=dict(pts='open-mmlab://regnetx_400mf'),
     pts_backbone=dict(
         _delete_=True,
         type='NoStemRegNet',
         arch=dict(w0=24, wa=24.48, wm=2.54, group_w=16, depth=22, bot_mul=1.0),
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://regnetx_400mf'),
         out_indices=(1, 2, 3),
         frozen_stages=-1,
         strides=(1, 2, 2, 2),

mmdet3d/models/detectors/mvx_two_stage.py

@@ -96,7 +96,7 @@ class MVXTwoStageDetector(Base3DDetector):
                     type='Pretrained', checkpoint=img_pretrained)
 
         if self.with_pts_backbone:
-            if img_pretrained is not None:
+            if pts_pretrained is not None:
                 warnings.warn('DeprecationWarning: pretrained is a deprecated \
                     key, please consider using init_cfg')
                 self.pts_backbone.init_cfg = dict(