[Improvement] Move train_cfg/test_cfg inside model (#341)

* [Improvement] Move train_cfg/test_cfg inside model

* fixed config dict

* fixed config dict

configs/_base_/models/ann_r50-d8.py

@@ -40,7 +40,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/apcnet_r50-d8.py

@@ -38,7 +38,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/ccnet_r50-d8.py

@@ -38,7 +38,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/cgnet.py

@@ -29,7 +29,7 @@ model = dict(
                 10.289121, 9.953208, 4.3097677, 9.490387, 7.674431, 9.396905,
                 10.347791, 6.3927646, 10.226669, 10.241062, 10.280587,
                 10.396974, 10.055647
-            ])))
+            ])),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict(sampler=None)
+    train_cfg=dict(sampler=None),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/danet_r50-d8.py

@@ -38,7 +38,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/deeplabv3_r50-d8.py

@@ -38,7 +38,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/deeplabv3_unet_s5-d16.py

@@ -44,7 +44,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='slide', crop_size=256, stride=170)
+    test_cfg=dict(mode='slide', crop_size=256, stride=170))

configs/_base_/models/deeplabv3plus_r50-d8.py

@@ -40,7 +40,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/dmnet_r50-d8.py

@@ -38,7 +38,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/dnl_r50-d8.py

@@ -40,7 +40,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/emanet_r50-d8.py

@@ -41,7 +41,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/encnet_r50-d8.py

@@ -42,7 +42,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/fast_scnn.py

@@ -51,8 +51,7 @@ model = dict(
             align_corners=False,
             loss_decode=dict(
                 type='CrossEntropyLoss', use_sigmoid=True, loss_weight=0.4)),
-    ])
+    ],
-
+    # model training and testing settings
-# model training and testing settings
+    train_cfg=dict(),
-train_cfg = dict()
+    test_cfg=dict(mode='whole'))
-test_cfg = dict(mode='whole')

configs/_base_/models/fcn_hr18.py

@@ -46,7 +46,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/fcn_r50-d8.py

@@ -39,7 +39,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/fcn_unet_s5-d16.py

@@ -45,7 +45,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='slide', crop_size=256, stride=170)
+    test_cfg=dict(mode='slide', crop_size=256, stride=170))

configs/_base_/models/fpn_r50.py

@@ -30,7 +30,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/gcnet_r50-d8.py

@@ -40,7 +40,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/lraspp_m-v3-d8.py

@@ -19,7 +19,7 @@ model = dict(
         act_cfg=dict(type='ReLU'),
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/nonlocal_r50-d8.py

@@ -40,7 +40,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/ocrnet_hr18.py

@@ -62,7 +62,7 @@ model = dict(
             align_corners=False,
             loss_decode=dict(
                 type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
-    ])
+    ],
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/ocrnet_r50-d8.py

@@ -41,7 +41,7 @@ model = dict(
             align_corners=False,
             loss_decode=dict(
                 type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))
-    ])
+    ],
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/pointrend_r50.py

@@ -45,12 +45,12 @@ model = dict(
             align_corners=False,
             loss_decode=dict(
                 type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))
-    ])
+    ],
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict(
+    train_cfg=dict(
-    num_points=2048, oversample_ratio=3, importance_sample_ratio=0.75)
+        num_points=2048, oversample_ratio=3, importance_sample_ratio=0.75),
-test_cfg = dict(
+    test_cfg=dict(
-    mode='whole',
+        mode='whole',
-    subdivision_steps=2,
+        subdivision_steps=2,
-    subdivision_num_points=8196,
+        subdivision_num_points=8196,
-    scale_factor=2)
+        scale_factor=2))

configs/_base_/models/psanet_r50-d8.py

@@ -43,7 +43,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/pspnet_r50-d8.py

@@ -38,7 +38,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/_base_/models/pspnet_unet_s5-d16.py

@@ -44,7 +44,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='slide', crop_size=256, stride=170)
+    test_cfg=dict(mode='slide', crop_size=256, stride=170))

configs/_base_/models/upernet_r50.py

@@ -38,7 +38,7 @@ model = dict(
         norm_cfg=norm_cfg,
         align_corners=False,
         loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)))
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-# model training and testing settings
+    # model training and testing settings
-train_cfg = dict()
+    train_cfg=dict(),
-test_cfg = dict(mode='whole')
+    test_cfg=dict(mode='whole'))

configs/ann/ann_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/ann/ann_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/apcnet/apcnet_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/apcnet/apcnet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/ccnet/ccnet_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/ccnet/ccnet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/danet/danet_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/danet/danet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/deeplabv3/deeplabv3_r50-d8_480x480_40k_pascal_context.py

@@ -4,6 +4,7 @@ _base_ = [
     '../_base_/schedules/schedule_40k.py'
 ]
 model = dict(
-    decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60))
+    decode_head=dict(num_classes=60),
-test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
+    auxiliary_head=dict(num_classes=60),
+    test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
 optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)

configs/deeplabv3/deeplabv3_r50-d8_480x480_80k_pascal_context.py

@@ -4,6 +4,7 @@ _base_ = [
     '../_base_/schedules/schedule_80k.py'
 ]
 model = dict(
-    decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60))
+    decode_head=dict(num_classes=60),
-test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
+    auxiliary_head=dict(num_classes=60),
+    test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
 optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)

configs/deeplabv3/deeplabv3_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/deeplabv3plus/deeplabv3plus_r50-d8_480x480_40k_pascal_context.py

@@ -4,6 +4,7 @@ _base_ = [
     '../_base_/schedules/schedule_40k.py'
 ]
 model = dict(
-    decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60))
+    decode_head=dict(num_classes=60),
-test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
+    auxiliary_head=dict(num_classes=60),
+    test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
 optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)

configs/deeplabv3plus/deeplabv3plus_r50-d8_480x480_80k_pascal_context.py

@@ -4,6 +4,7 @@ _base_ = [
     '../_base_/schedules/schedule_80k.py'
 ]
 model = dict(
-    decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60))
+    decode_head=dict(num_classes=60),
-test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
+    auxiliary_head=dict(num_classes=60),
+    test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
 optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)

configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/dmnet/dmnet_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/dmnet/dmnet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/dnlnet/dnl_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/dnlnet/dnl_r50-d8_769x769_80k_cityscapes.py

@@ -5,8 +5,8 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
 optimizer = dict(
     paramwise_cfg=dict(
         custom_keys=dict(theta=dict(wd_mult=0.), phi=dict(wd_mult=0.))))

configs/emanet/emanet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/encnet/encnet_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/encnet/encnet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/fcn/fcn_r50-d8_480x480_40k_pascal_context.py

@@ -2,6 +2,7 @@ _base_ = [
     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_context.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-model = dict(decode_head=dict(num_classes=60))
+model = dict(
-test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
+    decode_head=dict(num_classes=60),
+    test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
 optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)

configs/fcn/fcn_r50-d8_480x480_80k_pascal_context.py

@@ -2,6 +2,7 @@ _base_ = [
     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_context.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
 ]
-model = dict(decode_head=dict(num_classes=60))
+model = dict(
-test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
+    decode_head=dict(num_classes=60),
+    test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
 optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)

configs/fcn/fcn_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/fcn/fcn_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/gcnet/gcnet_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/gcnet/gcnet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/hrnet/fcn_hr18_480x480_40k_pascal_context.py

@@ -2,6 +2,7 @@ _base_ = [
     '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-model = dict(decode_head=dict(num_classes=60))
+model = dict(
-test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
+    decode_head=dict(num_classes=60),
+    test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
 optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)

configs/hrnet/fcn_hr18_480x480_80k_pascal_context.py

@@ -2,6 +2,7 @@ _base_ = [
     '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
 ]
-model = dict(decode_head=dict(num_classes=60))
+model = dict(
-test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
+    decode_head=dict(num_classes=60),
+    test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
 optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)

configs/nonlocal_net/nonlocal_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/nonlocal_net/nonlocal_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/psanet/psanet_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/psanet/psanet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/pspnet/pspnet_r50-d8_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/pspnet/pspnet_r50-d8_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py

@@ -3,5 +3,5 @@ _base_ = [
     '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py',
     '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(128, 128), stride=(85, 85))
+model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
 evaluation = dict(metric='mDice')

configs/unet/deeplabv3_unet_s5-d16_128x128_40k_stare.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/stare.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(128, 128), stride=(85, 85))
+model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
 evaluation = dict(metric='mDice')

configs/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/hrf.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(256, 256), stride=(170, 170))
+model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170)))
 evaluation = dict(metric='mDice')

configs/unet/deeplabv3_unet_s5-d16_64x64_40k_drive.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/drive.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(64, 64), stride=(42, 42))
+model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42)))
 evaluation = dict(metric='mDice')

configs/unet/fcn_unet_s5-d16_128x128_40k_chase_db1.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/chase_db1.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(128, 128), stride=(85, 85))
+model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
 evaluation = dict(metric='mDice')

configs/unet/fcn_unet_s5-d16_128x128_40k_stare.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/stare.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(128, 128), stride=(85, 85))
+model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
 evaluation = dict(metric='mDice')

configs/unet/fcn_unet_s5-d16_256x256_40k_hrf.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/hrf.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(256, 256), stride=(170, 170))
+model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170)))
 evaluation = dict(metric='mDice')

configs/unet/fcn_unet_s5-d16_64x64_40k_drive.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/drive.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(64, 64), stride=(42, 42))
+model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42)))
 evaluation = dict(metric='mDice')

configs/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1.py

@@ -3,5 +3,5 @@ _base_ = [
     '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py',
     '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(128, 128), stride=(85, 85))
+model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
 evaluation = dict(metric='mDice')

configs/unet/pspnet_unet_s5-d16_128x128_40k_stare.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/stare.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(128, 128), stride=(85, 85))
+model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
 evaluation = dict(metric='mDice')

configs/unet/pspnet_unet_s5-d16_256x256_40k_hrf.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/hrf.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(256, 256), stride=(170, 170))
+model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170)))
 evaluation = dict(metric='mDice')

configs/unet/pspnet_unet_s5-d16_64x64_40k_drive.py

@@ -2,5 +2,5 @@ _base_ = [
     '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/drive.py',
     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
 ]
-test_cfg = dict(crop_size=(64, 64), stride=(42, 42))
+model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42)))
 evaluation = dict(metric='mDice')

configs/upernet/upernet_r50_769x769_40k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

configs/upernet/upernet_r50_769x769_80k_cityscapes.py

@@ -5,5 +5,5 @@ _base_ = [
 ]
 model = dict(
     decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True))
+    auxiliary_head=dict(align_corners=True),
-test_cfg = dict(mode='slide', crop_size=(769, 769), stride=(513, 513))
+    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))

mmseg/apis/inference.py

@@ -27,7 +27,8 @@ def init_segmentor(config, checkpoint=None, device='cuda:0'):
         raise TypeError('config must be a filename or Config object, '
                         'but got {}'.format(type(config)))
     config.model.pretrained = None
-    model = build_segmentor(config.model, test_cfg=config.test_cfg)
+    config.model.train_cfg = None
+    model = build_segmentor(config.model, test_cfg=config.get('test_cfg'))
     if checkpoint is not None:
         checkpoint = load_checkpoint(model, checkpoint, map_location='cpu')
         model.CLASSES = checkpoint['meta']['CLASSES']

mmseg/models/builder.py

@@ -1,3 +1,5 @@
+import warnings
+
 from mmcv.utils import Registry, build_from_cfg
 from torch import nn
 
@@ -53,4 +55,12 @@ def build_loss(cfg):
 
 def build_segmentor(cfg, train_cfg=None, test_cfg=None):
     """Build segmentor."""
+    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, SEGMENTORS, dict(train_cfg=train_cfg, test_cfg=test_cfg))

tests/test_config.py

@@ -45,8 +45,6 @@ def test_config_build_segmentor():
         config_mod = Config.fromfile(config_fpath)
 
         config_mod.model
-        config_mod.train_cfg
-        config_mod.test_cfg
         print('Building segmentor, config_fpath = {!r}'.format(config_fpath))
 
         # Remove pretrained keys to allow for testing in an offline environment
@@ -54,10 +52,7 @@ def test_config_build_segmentor():
             config_mod.model['pretrained'] = None
 
         print('building {}'.format(config_fname))
-        segmentor = build_segmentor(
+        segmentor = build_segmentor(config_mod.model)
-            config_mod.model,
-            train_cfg=config_mod.train_cfg,
-            test_cfg=config_mod.test_cfg)
         assert segmentor is not None
 
         head_config = config_mod.model['decode_head']

tests/test_models/test_forward.py

@@ -76,12 +76,9 @@ def _get_segmentor_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))
+    return model
-    test_cfg = mmcv.Config(copy.deepcopy(config.test_cfg))
-    return model, train_cfg, test_cfg
 
 
 def test_pspnet_forward():
@@ -212,12 +209,12 @@ def _convert_batchnorm(module):
        _check_input_dim)
 @patch('torch.distributed.get_world_size', get_world_size)
 def _test_encoder_decoder_forward(cfg_file):
-    model, train_cfg, test_cfg = _get_segmentor_cfg(cfg_file)
+    model = _get_segmentor_cfg(cfg_file)
     model['pretrained'] = None
-    test_cfg['mode'] = 'whole'
+    model['test_cfg']['mode'] = 'whole'
 
     from mmseg.models import build_segmentor
-    segmentor = build_segmentor(model, train_cfg=train_cfg, test_cfg=test_cfg)
+    segmentor = build_segmentor(model)
 
     if isinstance(segmentor.decode_head, nn.ModuleList):
         num_classes = segmentor.decode_head[-1].num_classes

tests/test_models/test_segmentor.py

@@ -1,6 +1,6 @@
-import mmcv
 import numpy as np
 import torch
+from mmcv import ConfigDict
 from torch import nn
 
 from mmseg.models import BACKBONES, HEADS, build_segmentor
@@ -123,31 +123,33 @@ def _segmentor_forward_train_test(segmentor):
 def test_encoder_decoder():
 
     # test 1 decode head, w.o. aux head
-    cfg = dict(
+
+    cfg = ConfigDict(
         type='EncoderDecoder',
         backbone=dict(type='ExampleBackbone'),
-        decode_head=dict(type='ExampleDecodeHead'))
+        decode_head=dict(type='ExampleDecodeHead'),
-    test_cfg = mmcv.Config(dict(mode='whole'))
+        train_cfg=None,
-    segmentor = build_segmentor(cfg, train_cfg=None, test_cfg=test_cfg)
+        test_cfg=dict(mode='whole'))
+    segmentor = build_segmentor(cfg)
     _segmentor_forward_train_test(segmentor)
 
     # test slide mode
-    test_cfg = mmcv.Config(dict(mode='slide', crop_size=(3, 3), stride=(2, 2)))
+    cfg.test_cfg = ConfigDict(mode='slide', crop_size=(3, 3), stride=(2, 2))
-    segmentor = build_segmentor(cfg, train_cfg=None, test_cfg=test_cfg)
+    segmentor = build_segmentor(cfg)
     _segmentor_forward_train_test(segmentor)
 
     # test 1 decode head, 1 aux head
-    cfg = dict(
+    cfg = ConfigDict(
         type='EncoderDecoder',
         backbone=dict(type='ExampleBackbone'),
         decode_head=dict(type='ExampleDecodeHead'),
         auxiliary_head=dict(type='ExampleDecodeHead'))
-    test_cfg = mmcv.Config(dict(mode='whole'))
+    cfg.test_cfg = ConfigDict(mode='whole')
-    segmentor = build_segmentor(cfg, train_cfg=None, test_cfg=test_cfg)
+    segmentor = build_segmentor(cfg)
     _segmentor_forward_train_test(segmentor)
 
     # test 1 decode head, 2 aux head
-    cfg = dict(
+    cfg = ConfigDict(
         type='EncoderDecoder',
         backbone=dict(type='ExampleBackbone'),
         decode_head=dict(type='ExampleDecodeHead'),
@@ -155,15 +157,15 @@ def test_encoder_decoder():
             dict(type='ExampleDecodeHead'),
             dict(type='ExampleDecodeHead')
         ])
-    test_cfg = mmcv.Config(dict(mode='whole'))
+    cfg.test_cfg = ConfigDict(mode='whole')
-    segmentor = build_segmentor(cfg, train_cfg=None, test_cfg=test_cfg)
+    segmentor = build_segmentor(cfg)
     _segmentor_forward_train_test(segmentor)
 
 
 def test_cascade_encoder_decoder():
 
     # test 1 decode head, w.o. aux head
-    cfg = dict(
+    cfg = ConfigDict(
         type='CascadeEncoderDecoder',
         num_stages=2,
         backbone=dict(type='ExampleBackbone'),
@@ -171,17 +173,17 @@ def test_cascade_encoder_decoder():
             dict(type='ExampleDecodeHead'),
             dict(type='ExampleCascadeDecodeHead')
         ])
-    test_cfg = mmcv.Config(dict(mode='whole'))
+    cfg.test_cfg = ConfigDict(mode='whole')
-    segmentor = build_segmentor(cfg, train_cfg=None, test_cfg=test_cfg)
+    segmentor = build_segmentor(cfg)
     _segmentor_forward_train_test(segmentor)
 
     # test slide mode
-    test_cfg = mmcv.Config(dict(mode='slide', crop_size=(3, 3), stride=(2, 2)))
+    cfg.test_cfg = ConfigDict(mode='slide', crop_size=(3, 3), stride=(2, 2))
-    segmentor = build_segmentor(cfg, train_cfg=None, test_cfg=test_cfg)
+    segmentor = build_segmentor(cfg)
     _segmentor_forward_train_test(segmentor)
 
     # test 1 decode head, 1 aux head
-    cfg = dict(
+    cfg = ConfigDict(
         type='CascadeEncoderDecoder',
         num_stages=2,
         backbone=dict(type='ExampleBackbone'),
@@ -190,12 +192,12 @@ def test_cascade_encoder_decoder():
             dict(type='ExampleCascadeDecodeHead')
         ],
         auxiliary_head=dict(type='ExampleDecodeHead'))
-    test_cfg = mmcv.Config(dict(mode='whole'))
+    cfg.test_cfg = ConfigDict(mode='whole')
-    segmentor = build_segmentor(cfg, train_cfg=None, test_cfg=test_cfg)
+    segmentor = build_segmentor(cfg)
     _segmentor_forward_train_test(segmentor)
 
     # test 1 decode head, 2 aux head
-    cfg = dict(
+    cfg = ConfigDict(
         type='CascadeEncoderDecoder',
         num_stages=2,
         backbone=dict(type='ExampleBackbone'),
@@ -207,6 +209,6 @@ def test_cascade_encoder_decoder():
             dict(type='ExampleDecodeHead'),
             dict(type='ExampleDecodeHead')
         ])
-    test_cfg = mmcv.Config(dict(mode='whole'))
+    cfg.test_cfg = ConfigDict(mode='whole')
-    segmentor = build_segmentor(cfg, train_cfg=None, test_cfg=test_cfg)
+    segmentor = build_segmentor(cfg)
     _segmentor_forward_train_test(segmentor)

tools/benchmark.py

@@ -40,7 +40,8 @@ def main():
         shuffle=False)
 
     # build the model and load checkpoint
-    model = build_segmentor(cfg.model, train_cfg=None, test_cfg=cfg.test_cfg)
+    cfg.model.train_cfg = None
+    model = build_segmentor(cfg.model, test_cfg=cfg.get('test_cfg'))
     load_checkpoint(model, args.checkpoint, map_location='cpu')
 
     model = MMDataParallel(model, device_ids=[0])

tools/get_flops.py

@@ -33,7 +33,9 @@ def main():
     cfg = Config.fromfile(args.config)
     cfg.model.pretrained = None
     model = build_segmentor(
-        cfg.model, train_cfg=cfg.train_cfg, test_cfg=cfg.test_cfg).cuda()
+        cfg.model,
+        train_cfg=cfg.get('train_cfg'),
+        test_cfg=cfg.get('test_cfg')).cuda()
     model.eval()
 
     if hasattr(model, 'forward_dummy'):

tools/pytorch2onnx.py

@@ -181,8 +181,9 @@ if __name__ == '__main__':
     cfg.model.pretrained = None
 
     # build the model and load checkpoint
+    cfg.model.train_cfg = None
     segmentor = build_segmentor(
-        cfg.model, train_cfg=None, test_cfg=cfg.test_cfg)
+        cfg.model, train_cfg=None, test_cfg=cfg.get('test_cfg'))
     # convert SyncBN to BN
     segmentor = _convert_batchnorm(segmentor)
 

tools/test.py

@@ -110,7 +110,8 @@ def main():
         shuffle=False)
 
     # build the model and load checkpoint
-    model = build_segmentor(cfg.model, train_cfg=None, test_cfg=cfg.test_cfg)
+    cfg.model.train_cfg = None
+    model = build_segmentor(cfg.model, test_cfg=cfg.get('test_cfg'))
     checkpoint = load_checkpoint(model, args.checkpoint, map_location='cpu')
     model.CLASSES = checkpoint['meta']['CLASSES']
     model.PALETTE = checkpoint['meta']['PALETTE']

tools/train.py

@@ -128,7 +128,9 @@ def main():
     meta['exp_name'] = osp.basename(args.config)
 
     model = build_segmentor(
-        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(model)