[Refactor] move model.pretrained to model.backbone.init_cfg (open-mmlab#5370)

* [Refactor] move model pretrained to backbone init_cfg

* fix some bug and add a test unit

* add

* fix bug

* fix priority

* fix bug

* delete test backbone init cfg

* fix potential bug

* fix potential bug

* add detectors test unit

* fix logic

* add test unit

* fix

Author: BIGWangYuDong

configs/_base_/models/cascade_mask_rcnn_r50_fpn.py

@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='CascadeRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

configs/_base_/models/cascade_rcnn_r50_fpn.py

@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='CascadeRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

configs/_base_/models/fast_rcnn_r50_fpn.py

@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='FastRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

configs/_base_/models/faster_rcnn_r50_caffe_c4.py

@@ -2,7 +2,6 @@
 norm_cfg = dict(type='BN', requires_grad=False)
 model = dict(
     type='FasterRCNN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -13,7 +12,10 @@
         frozen_stages=1,
         norm_cfg=norm_cfg,
         norm_eval=True,
-        style='caffe'),
+        style='caffe',
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
     rpn_head=dict(
         type='RPNHead',
         in_channels=1024,

configs/_base_/models/faster_rcnn_r50_caffe_dc5.py

@@ -2,7 +2,6 @@
 norm_cfg = dict(type='BN', requires_grad=False)
 model = dict(
     type='FasterRCNN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -13,7 +12,10 @@
         frozen_stages=1,
         norm_cfg=norm_cfg,
         norm_eval=True,
-        style='caffe'),
+        style='caffe',
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
     rpn_head=dict(
         type='RPNHead',
         in_channels=2048,

configs/_base_/models/faster_rcnn_r50_fpn.py

@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='FasterRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

configs/_base_/models/mask_rcnn_r50_caffe_c4.py

@@ -2,7 +2,6 @@
 norm_cfg = dict(type='BN', requires_grad=False)
 model = dict(
     type='MaskRCNN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -13,7 +12,10 @@
         frozen_stages=1,
         norm_cfg=norm_cfg,
         norm_eval=True,
-        style='caffe'),
+        style='caffe',
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
     rpn_head=dict(
         type='RPNHead',
         in_channels=1024,

configs/_base_/models/mask_rcnn_r50_fpn.py

@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='MaskRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

configs/_base_/models/retinanet_r50_fpn.py

@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='RetinaNet',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

configs/_base_/models/rpn_r50_caffe_c4.py

@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='RPN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -12,7 +11,10 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=False),
         norm_eval=True,
-        style='caffe'),
+        style='caffe',
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
     neck=None,
     rpn_head=dict(
         type='RPNHead',