remove actual_shape in resize_nearest and use_progam_cache in yolov3/infer.py (#3617)

* remove actual_shape

* add fpn fix

ppdet/modeling/anchor_heads/yolo_head.py

@@ -148,18 +148,8 @@ class YOLOv3Head(object):
         return route, tip
 
     def _upsample(self, input, scale=2, name=None):
-        # get dynamic upsample output shape
-        shape_nchw = fluid.layers.shape(input)
-        shape_hw = fluid.layers.slice(
-            shape_nchw, axes=[0], starts=[2], ends=[4])
-        shape_hw.stop_gradient = True
-        in_shape = fluid.layers.cast(shape_hw, dtype='int32')
-        out_shape = in_shape * scale
-        out_shape.stop_gradient = True
-
-        # reisze by actual_shape
         out = fluid.layers.resize_nearest(
-            input=input, scale=scale, actual_shape=out_shape, name=name)
+            input=input, scale=float(scale), name=name)
         return out
 
     def _parse_anchors(self, anchors):

ppdet/modeling/backbones/fpn.py

@@ -87,13 +87,8 @@ class FPN(object):
                     learning_rate=2.,
                     regularizer=L2Decay(0.)),
                 name=lateral_name)
-        shape = fluid.layers.shape(upper_output)
-        shape_hw = fluid.layers.slice(shape, axes=[0], starts=[2], ends=[4])
-        out_shape_ = shape_hw * 2
-        out_shape = fluid.layers.cast(out_shape_, dtype='int32')
-        out_shape.stop_gradient = True
         topdown = fluid.layers.resize_nearest(
-            upper_output, scale=2., actual_shape=out_shape, name=topdown_name)
+            upper_output, scale=2., name=topdown_name)
 
         return lateral + topdown