Cherry pick remove actual shape (#3620)

* remove actual_shape

* change version to 1.5 in yolov3

PaddleCV/PaddleDetection/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):

PaddleCV/PaddleDetection/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
 

PaddleCV/yolov3/README.md

@@ -42,7 +42,7 @@
 
 **安装[PaddlePaddle](https://github.com/PaddlePaddle/Paddle)：**
 
-在当前目录下运行样例代码需要PadddlePaddle Fluid的v.1.4或以上的版本。如果你的运行环境中的PaddlePaddle低于此版本，请根据[安装文档](http://paddlepaddle.org/documentation/docs/zh/1.4/beginners_guide/install/index_cn.html)中的说明来更新PaddlePaddle。
+在当前目录下运行样例代码需要PadddlePaddle Fluid的v.1.5或以上的版本。如果你的运行环境中的PaddlePaddle低于此版本，请根据[安装文档](http://paddlepaddle.org/documentation/docs/zh/1.5/beginners_guide/install/index_cn.html)中的说明来更新PaddlePaddle。
 
 ### 数据准备
 

PaddleCV/yolov3/README_en.md

@@ -28,7 +28,7 @@ We also recommend users to take a look at the  [IPython Notebook demo](https:/
 
 **Install [PaddlePaddle](https://github.com/PaddlePaddle/Paddle):**
 
-Running sample code in this directory requires PaddelPaddle Fluid v.1.4 and later. If the PaddlePaddle on your device is lower than this version, please follow the instructions in [installation document](http://www.paddlepaddle.org/documentation/docs/en/1.4/beginners_guide/install/index_en.html) and make an update.
+Running sample code in this directory requires PaddelPaddle Fluid v.1.5 and later. If the PaddlePaddle on your device is lower than this version, please follow the instructions in [installation document](http://www.paddlepaddle.org/documentation/docs/en/1.5/beginners_guide/install/index_en.html) and make an update.
 
 **Install the [COCO-API](https://github.com/cocodataset/cocoapi):**
 

PaddleCV/yolov3/infer.py

@@ -70,7 +70,8 @@ def infer():
         im_shape = data[0][2]
         outputs = exe.run(fetch_list=[v.name for v in fetch_list],
                           feed=feeder.feed(data),
-                          return_numpy=False)
+                          return_numpy=False,
+                          use_program_cache=True)
         bboxes = np.array(outputs[0])
         if bboxes.shape[1] != 6:
             print("No object found in {}".format(image_name))

PaddleCV/yolov3/models/yolov3.py

@@ -68,17 +68,8 @@ def yolo_detection_block(input, channel, is_test=True, name=None):
 
 
 def upsample(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