fix mask_fpn coverge, test=dygraph (#2015)

dygraph/ppdet/modeling/architectures/mask_rcnn.py

@@ -87,7 +87,7 @@ class MaskRCNN(BaseArch):
         # compute targets here when training
         rois = self.proposal(self.inputs, self.rpn_head_out, self.anchor_out)
         # BBox Head
-        bbox_feat, self.bbox_head_out, self.bbox_head_feat_func = self.bbox_head(
+        bbox_feat, self.bbox_head_out, bbox_head_feat_func = self.bbox_head(
             body_feats, rois, spatial_scale)
 
         rois_has_mask_int32 = None
@@ -108,7 +108,7 @@ class MaskRCNN(BaseArch):
         # Mask Head 
         self.mask_head_out = self.mask_head(
             self.inputs, body_feats, self.bboxes, bbox_feat,
-            rois_has_mask_int32, spatial_scale, self.bbox_head_feat_func)
+            rois_has_mask_int32, spatial_scale, bbox_head_feat_func)
 
     def get_loss(self, ):
         loss = {}

dygraph/tools/train.py

@@ -128,6 +128,16 @@ def run(FLAGS, cfg, place):
     # if sync_bn:
     #     model = paddle.nn.SyncBatchNorm.convert_sync_batchnorm(model)
 
+    # The parameter filter is temporary fix for training because of #28997
+    # in Paddle.
+    def no_grad(param):
+        if param.name.startswith("conv1_") or param.name.startswith("res2a_") \
+            or param.name.startswith("res2b_") or param.name.startswith("res2c_"):
+            return True
+
+    for param in filter(no_grad, model.parameters()):
+        param.stop_gradient = True
+
     # Parallel Model 
     if ParallelEnv().nranks > 1:
         model = paddle.DataParallel(model)