please set 'STRIDE_IN_1X1' to be 'False' when backbone uses GN (#465)

* make pixel indexes 0-based for bounding box in pascal voc dataset

* replacing all instances of torch.distributed.deprecated with torch.distributed

* replacing all instances of torch.distributed.deprecated with torch.distributed

* add GroupNorm

* add GroupNorm -- sort out yaml files

* use torch.nn.GroupNorm instead, replace 'use_gn' with 'conv_block' and use 'BaseStem'&'Bottleneck' to simply codes

* modification on 'group_norm' and 'conv_with_kaiming_uniform' function

* modification on yaml files in configs/gn_baselines/ and reduce the amount of indentation and code duplication

* use 'kaiming_uniform' to initialize resnet, disable gn after fc layer, and add dilation into ResNetHead

* agnostic-regression for bbox

* please set 'STRIDE_IN_1X1' to be 'False' when backbone use GN

configs/gn_baselines/e2e_faster_rcnn_R_50_FPN_1x_gn.yaml

@@ -10,6 +10,7 @@ MODEL:
     CONV_BODY: "R-50-FPN"
     OUT_CHANNELS: 256
   RESNETS: # use GN for backbone
+    STRIDE_IN_1X1: False
     TRANS_FUNC: "BottleneckWithGN"
     STEM_FUNC: "StemWithGN"
   FPN:

configs/gn_baselines/e2e_faster_rcnn_R_50_FPN_Xconv1fc_1x_gn.yaml

@@ -10,6 +10,7 @@ MODEL:
     CONV_BODY: "R-50-FPN"
     OUT_CHANNELS: 256
   RESNETS: # use GN for backbone
+    STRIDE_IN_1X1: False
     TRANS_FUNC: "BottleneckWithGN"
     STEM_FUNC: "StemWithGN"
   FPN:
@@ -47,4 +48,4 @@ SOLVER:
   MAX_ITER: 90000
   IMS_PER_BATCH: 16
 TEST:
-  IMS_PER_BATCH: 8
+  IMS_PER_BATCH: 8

configs/gn_baselines/e2e_mask_rcnn_R_50_FPN_1x_gn.yaml

@@ -10,6 +10,7 @@ MODEL:
     CONV_BODY: "R-50-FPN"
     OUT_CHANNELS: 256
   RESNETS: # use GN for backbone
+    STRIDE_IN_1X1: False
     TRANS_FUNC: "BottleneckWithGN"
     STEM_FUNC: "StemWithGN"
   FPN:
@@ -56,4 +57,4 @@ SOLVER:
   MAX_ITER: 90000
   IMS_PER_BATCH: 16
 TEST:
-  IMS_PER_BATCH: 8
+  IMS_PER_BATCH: 8

configs/gn_baselines/e2e_mask_rcnn_R_50_FPN_Xconv1fc_1x_gn.yaml

@@ -10,6 +10,7 @@ MODEL:
     CONV_BODY: "R-50-FPN"
     OUT_CHANNELS: 256
   RESNETS: # use GN for backbone
+    STRIDE_IN_1X1: False
     TRANS_FUNC: "BottleneckWithGN"
     STEM_FUNC: "StemWithGN"
   FPN:
@@ -58,4 +59,4 @@ SOLVER:
   MAX_ITER: 90000
   IMS_PER_BATCH: 16
 TEST:
-  IMS_PER_BATCH: 8
+  IMS_PER_BATCH: 8

configs/gn_baselines/scratch_e2e_faster_rcnn_R_50_FPN_3x_gn.yaml

@@ -11,6 +11,7 @@ MODEL:
     OUT_CHANNELS: 256
     FREEZE_CONV_BODY_AT: 0 # finetune all layers
   RESNETS: # use GN for backbone
+    STRIDE_IN_1X1: False
     TRANS_FUNC: "BottleneckWithGN"
     STEM_FUNC: "StemWithGN"
   FPN:
@@ -46,4 +47,4 @@ SOLVER:
   MAX_ITER: 270000
   IMS_PER_BATCH: 16
 TEST:
-  IMS_PER_BATCH: 8
+  IMS_PER_BATCH: 8

configs/gn_baselines/scratch_e2e_faster_rcnn_R_50_FPN_Xconv1fc_3x_gn.yaml

@@ -11,6 +11,7 @@ MODEL:
     OUT_CHANNELS: 256
     FREEZE_CONV_BODY_AT: 0 # finetune all layers
   RESNETS: # use GN for backbone
+    STRIDE_IN_1X1: False
     TRANS_FUNC: "BottleneckWithGN"
     STEM_FUNC: "StemWithGN"
   FPN:
@@ -48,4 +49,4 @@ SOLVER:
   MAX_ITER: 270000
   IMS_PER_BATCH: 16
 TEST:
-  IMS_PER_BATCH: 8
+  IMS_PER_BATCH: 8

configs/gn_baselines/scratch_e2e_mask_rcnn_R_50_FPN_3x_gn.yaml

@@ -11,6 +11,7 @@ MODEL:
     OUT_CHANNELS: 256
     FREEZE_CONV_BODY_AT: 0 # finetune all layers
   RESNETS: # use GN for backbone
+    STRIDE_IN_1X1: False
     TRANS_FUNC: "BottleneckWithGN"
     STEM_FUNC: "StemWithGN"
   FPN:

configs/gn_baselines/scratch_e2e_mask_rcnn_R_50_FPN_Xconv1fc_3x_gn.yaml

@@ -11,6 +11,7 @@ MODEL:
     OUT_CHANNELS: 256
     FREEZE_CONV_BODY_AT: 0 # finetune all layers
   RESNETS: # use GN for backbone
+    STRIDE_IN_1X1: False
     TRANS_FUNC: "BottleneckWithGN"
     STEM_FUNC: "StemWithGN"
   FPN:
@@ -59,4 +60,4 @@ SOLVER:
   MAX_ITER: 270000
   IMS_PER_BATCH: 16
 TEST:
-  IMS_PER_BATCH: 8
+  IMS_PER_BATCH: 8