create wrapper submodule for compute block to use in to_backend

Summary: Refactoring generate_proposals logic in Caffe2RPN to a separate method, allowing running it separately from the RPN head.

Reviewed By: wat3rBro

Differential Revision: D24627425

fbshipit-source-id: cda2637b87089dcd30348c9ede97e48bdde9bf48

Author: mortzur

detectron2/export/c10.py

@@ -162,12 +162,9 @@ def _set_tensor_mode(self, v):
 
 
 class Caffe2RPN(Caffe2Compatible, rpn.RPN):
-    def forward(self, images, features, gt_instances=None):
-        assert not self.training
-
-        features = [features[f] for f in self.in_features]
-        objectness_logits_pred, anchor_deltas_pred = self.rpn_head(features)
-
+    def _generate_proposals(
+        self, images, objectness_logits_pred, anchor_deltas_pred, gt_instances=None
+    ):
         assert isinstance(images, ImageList)
         if self.tensor_mode:
             im_info = images.image_sizes
@@ -248,6 +245,17 @@ def forward(self, images, features, gt_instances=None):
         proposals = self.c2_postprocess(im_info, rpn_rois, rpn_roi_probs, self.tensor_mode)
         return proposals, {}
 
+    def forward(self, images, features, gt_instances=None):
+        assert not self.training
+        features = [features[f] for f in self.in_features]
+        objectness_logits_pred, anchor_deltas_pred = self.rpn_head(features)
+        return self._generate_proposals(
+            images,
+            objectness_logits_pred,
+            anchor_deltas_pred,
+            gt_instances,
+        )
+
     @staticmethod
     def c2_postprocess(im_info, rpn_rois, rpn_roi_probs, tensor_mode):
         proposals = InstancesList(