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

configs/_base_/models/apcnet_r50-d8.py

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

configs/_base_/models/ccnet_r50-d8.py

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

configs/_base_/models/cgnet.py

@@ -29,7 +29,7 @@
                 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
-train_cfg = dict(sampler=None)
-test_cfg = dict(mode='whole')
+            ])),
+    # model training and testing settings
+    train_cfg=dict(sampler=None),
+    test_cfg=dict(mode='whole'))

configs/_base_/models/danet_r50-d8.py

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

configs/_base_/models/deeplabv3_r50-d8.py

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

configs/_base_/models/deeplabv3_unet_s5-d16.py

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

configs/_base_/models/deeplabv3plus_r50-d8.py

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

configs/_base_/models/dmnet_r50-d8.py

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

configs/_base_/models/dnl_r50-d8.py

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

configs/_base_/models/emanet_r50-d8.py

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

configs/_base_/models/encnet_r50-d8.py

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

configs/_base_/models/fast_scnn.py

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

configs/_base_/models/fcn_hr18.py

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

configs/_base_/models/fcn_r50-d8.py

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

configs/_base_/models/fcn_unet_s5-d16.py

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

configs/_base_/models/fpn_r50.py

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

configs/_base_/models/gcnet_r50-d8.py

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

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

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

configs/_base_/models/nonlocal_r50-d8.py

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

configs/_base_/models/ocrnet_hr18.py

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

configs/_base_/models/ocrnet_r50-d8.py

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

configs/_base_/models/pointrend_r50.py

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

configs/_base_/models/psanet_r50-d8.py

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

configs/_base_/models/pspnet_r50-d8.py

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

configs/_base_/models/pspnet_unet_s5-d16.py

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

configs/_base_/models/upernet_r50.py

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

configs/ann/ann_r50-d8_769x769_40k_cityscapes.py

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