Merge branch 'PaddlePaddle:develop' into develop

README.md

@@ -43,7 +43,7 @@ The goal of Paddle Serving is to provide high-performance, flexible and easy-to-
 <h2 align="center">Tutorial and Papers</h2>
 
 
-- AIStudio tutorial(Chinese) : [Paddle Serving服务化部署框架](https://www.paddlepaddle.org.cn/tutorials/projectdetail/2538249)
+- AIStudio tutorial(Chinese) : [Paddle Serving服务化部署框架](https://www.paddlepaddle.org.cn/tutorials/projectdetail/3946013)
 - AIStudio OCR practice(Chinese) : [基于PaddleServing的OCR服务化部署实战](https://aistudio.baidu.com/aistudio/projectdetail/3630726)
 - Video tutorial(Chinese) : [深度学习服务化部署-以互联网应用为例](https://aistudio.baidu.com/aistudio/course/introduce/19084)
 - Edge AI solution(Chinese) : [基于Paddle Serving&百度智能边缘BIE的边缘AI解决方案](https://mp.weixin.qq.com/s/j0EVlQXaZ7qmoz9Fv96Yrw)

README_CN.md

@@ -41,7 +41,7 @@ Paddle Serving依托深度学习框架PaddlePaddle旨在帮助深度学习开发
 
 <h2 align="center">教程与论文</h2>
 
-- AIStudio 使用教程 : [Paddle Serving服务化部署框架](https://www.paddlepaddle.org.cn/tutorials/projectdetail/2538249)
+- AIStudio 使用教程 : [Paddle Serving服务化部署框架](https://www.paddlepaddle.org.cn/tutorials/projectdetail/3946013)
 - AIStudio OCR实战 : [基于PaddleServing的OCR服务化部署实战](https://aistudio.baidu.com/aistudio/projectdetail/3630726)
 - 视频教程 : [深度学习服务化部署-以互联网应用为例](https://aistudio.baidu.com/aistudio/course/introduce/19084)
 - 边缘AI 解决方案 : [基于Paddle Serving&百度智能边缘BIE的边缘AI解决方案](https://mp.weixin.qq.com/s/j0EVlQXaZ7qmoz9Fv96Yrw)

cmake/paddlepaddle.cmake

@@ -30,7 +30,7 @@ message( "WITH_GPU = ${WITH_GPU}")
 # Paddle Version should be one of:
 # latest: latest develop build
 # version number like 1.5.2
-SET(PADDLE_VERSION "2.3.0-rc0")
+SET(PADDLE_VERSION "2.3.0")
 if (WITH_GPU)
     message("CUDA: ${CUDA_VERSION}, CUDNN_MAJOR_VERSION: ${CUDNN_MAJOR_VERSION}")
     # cuda 11.0 is not supported, 11.2 would be added.

python/paddle_serving_app/local_predict.py

@@ -93,7 +93,9 @@ class LocalPredictor(object):
                           use_ascend_cl=False,
                           min_subgraph_size=3,
                           dynamic_shape_info={},
-                          use_calib=False):
+                          use_calib=False,
+                          collect_shape_range_info="",
+                          tuned_dynamic_shape_info=""):
         """
         Load model configs and create the paddle predictor by Paddle Inference API.
    
@@ -160,12 +162,14 @@ class LocalPredictor(object):
             "use_trt:{}, use_lite:{}, use_xpu:{}, precision:{}, use_calib:{}, "
             "use_mkldnn:{}, mkldnn_cache_capacity:{}, mkldnn_op_list:{}, "
             "mkldnn_bf16_op_list:{}, use_feed_fetch_ops:{}, "
-            "use_ascend_cl:{}, min_subgraph_size:{}, dynamic_shape_info:{}".
+            "use_ascend_cl:{}, min_subgraph_size:{}, dynamic_shape_info:{},"
+            "collect_shape_range_info:{},tuned_dynamic_shape_info:{}".
             format(model_path, use_gpu, gpu_id, use_profile, thread_num,
                    mem_optim, ir_optim, use_trt, use_lite, use_xpu, precision,
                    use_calib, use_mkldnn, mkldnn_cache_capacity, mkldnn_op_list,
                    mkldnn_bf16_op_list, use_feed_fetch_ops, use_ascend_cl,
-                   min_subgraph_size, dynamic_shape_info))
+                   min_subgraph_size, dynamic_shape_info,
+                   collect_shape_range_info,tuned_dynamic_shape_info))
 
         self.feed_names_ = [var.alias_name for var in model_conf.feed_var]
         self.fetch_names_ = [var.alias_name for var in model_conf.fetch_var]
@@ -213,6 +217,8 @@ class LocalPredictor(object):
             if mkldnn_op_list is not None:
                 config.set_mkldnn_op(mkldnn_op_list)
         # set gpu
+        if collect_shape_range_info != "":
+            config.collect_shape_range_info(collect_shape_range_info)
         if not use_gpu:
             config.disable_gpu()
         else:
@@ -226,6 +232,9 @@ class LocalPredictor(object):
                     use_static=False,
                     use_calib_mode=use_calib)
 
+                if tuned_dynamic_shape_info != "":
+                    config.enable_tuned_tensorrt_dynamic_shape(tuned_dynamic_shape_info, True)
+
                 @ErrorCatch
                 @ParamChecker
                 def dynamic_shape_info_helper(dynamic_shape_info:lambda dynamic_shape_info: check_dynamic_shape_info(dynamic_shape_info)):
@@ -235,7 +244,7 @@ class LocalPredictor(object):
                     print("dynamic_shape_info configure error, it should contain [min_input_shape', 'max_input_shape', 'opt_input_shape' {}".format(resp.err_msg))
                     kill_stop_process_by_pid("kill", os.getpgid(os.getpid()))
 
-                if len(dynamic_shape_info):
+                if len(dynamic_shape_info) and tuned_dynamic_shape_info == "":
                     config.set_trt_dynamic_shape_info(
                         dynamic_shape_info['min_input_shape'],
                         dynamic_shape_info['max_input_shape'],

python/pipeline/local_service_handler.py

@@ -53,7 +53,9 @@ class LocalServiceHandler(object):
                  mkldnn_bf16_op_list=None,
                  min_subgraph_size=3,
                  dynamic_shape_info={},
-                 use_calib=False):
+                 use_calib=False,
+                 collect_shape_range_info="",
+                 tuned_dynamic_shape_info=""):
         """
         Initialization of localservicehandler
 
@@ -99,6 +101,8 @@ class LocalServiceHandler(object):
         self.min_subgraph_size = 3
         self.dynamic_shape_info = {}
         self._use_calib = False
+        self.collect_shape_range_info = ""
+        self.tuned_dynamic_shape_info = ""
 
         if device_type == -1:
             # device_type is not set, determined by `devices`, 
@@ -179,6 +183,8 @@ class LocalServiceHandler(object):
         self._mkldnn_op_list = mkldnn_op_list
         self._mkldnn_bf16_op_list = mkldnn_bf16_op_list
         self._use_calib = use_calib
+        self.collect_shape_range_info = collect_shape_range_info
+        self.tuned_dynamic_shape_info = tuned_dynamic_shape_info
 
         _LOGGER.info(
             "Models({}) will be launched by device {}. use_gpu:{}, "
@@ -187,14 +193,16 @@ class LocalServiceHandler(object):
             "client_type:{}, fetch_names:{}, precision:{}, use_calib:{}, "
             "use_mkldnn:{}, mkldnn_cache_capacity:{}, mkldnn_op_list:{}, "
             "mkldnn_bf16_op_list:{}, use_ascend_cl:{}, min_subgraph_size:{},"
-            "is_set_dynamic_shape_info:{}".format(
+            "is_set_dynamic_shape_info:{},collect_shape_range_info:{},"
+            "tuned_dynamic_shape_info:{}".format(
                 model_config, self._device_name, self._use_gpu, self._use_trt,
                 self._use_lite, self._use_xpu, device_type, self._devices, self.
                 _mem_optim, self._ir_optim, self._use_profile, self._thread_num,
                 self._client_type, self._fetch_names, self._precision, self.
                 _use_calib, self._use_mkldnn, self._mkldnn_cache_capacity, self.
                 _mkldnn_op_list, self._mkldnn_bf16_op_list, self._use_ascend_cl,
-                self.min_subgraph_size, bool(len(self.dynamic_shape_info))))
+                self.min_subgraph_size, bool(len(self.dynamic_shape_info)),
+                self.collect_shape_range_info, self.tuned_dynamic_shape_info))
 
     def get_fetch_list(self):
         return self._fetch_names
@@ -254,7 +262,9 @@ class LocalServiceHandler(object):
                 use_ascend_cl=self._use_ascend_cl,
                 min_subgraph_size=self.min_subgraph_size,
                 dynamic_shape_info=self.dynamic_shape_info,
-                use_calib=self._use_calib)
+                use_calib=self._use_calib,
+                collect_shape_range_info=self.collect_shape_range_info,
+                tuned_dynamic_shape_info=self.tuned_dynamic_shape_info)
         return self._local_predictor_client
 
     def get_client_config(self):

python/pipeline/operator.py

@@ -121,6 +121,8 @@ class Op(object):
         self._succ_close_op = False
         self.dynamic_shape_info = {}
         self.set_dynamic_shape_info()
+        self.collect_shape_range_info = ""
+        self.tuned_dynamic_shape_info = ""
 
     def set_dynamic_shape_info(self):
         """
@@ -235,6 +237,14 @@ class Op(object):
                         "mkldnn_bf16_op_list")
                     self.min_subgraph_size = local_service_conf.get(
                         "min_subgraph_size")
+                    self.collect_shape_range_info = local_service_conf.get(
+                        "collect_shape_range_info")
+                    self.tuned_dynamic_shape_info = local_service_conf.get(
+                        "tuned_dynamic_shape_info")
+                    if self.collect_shape_range_info is None:
+                        self.collect_shape_range_info = ""
+                    if self.tuned_dynamic_shape_info is None:
+                        self.tuned_dynamic_shape_info = ""
 
                     if self.model_config is None:
                         self.with_serving = False
@@ -259,7 +269,9 @@ class Op(object):
                                 mkldnn_bf16_op_list=self.mkldnn_bf16_op_list,
                                 min_subgraph_size=self.min_subgraph_size,
                                 dynamic_shape_info=self.dynamic_shape_info,
-                                use_calib=self.use_calib)
+                                use_calib=self.use_calib,
+                                collect_shape_range_info=self.collect_shape_range_info,
+                                tuned_dynamic_shape_info=self.tuned_dynamic_shape_info)
                             service_handler.prepare_server()  # get fetch_list
                             serivce_ports = service_handler.get_port_list()
                             self._server_endpoints = [
@@ -290,7 +302,9 @@ class Op(object):
                                 mkldnn_bf16_op_list=self.mkldnn_bf16_op_list,
                                 min_subgraph_size=self.min_subgraph_size,
                                 dynamic_shape_info=self.dynamic_shape_info,
-                                use_calib=self.use_calib)
+                                use_calib=self.use_calib,
+                                collect_shape_range_info=self.collect_shape_range_info,
+                                tuned_dynamic_shape_info=self.tuned_dynamic_shape_info)
                             if self._client_config is None:
                                 self._client_config = service_handler.get_client_config(
                                 )
@@ -1387,7 +1401,9 @@ class Op(object):
                     mkldnn_bf16_op_list=mkldnn_bf16_op_list,
                     min_subgraph_size=min_subgraph_size,
                     dynamic_shape_info=dynamic_shape_info,
-                    use_calib=use_calib)
+                    use_calib=use_calib,
+                    collect_shape_range_info=self.collect_shape_range_info,
+                    tuned_dynamic_shape_info=self.tuned_dynamic_shape_info)
 
                 _LOGGER.info("Init cuda env in process {}".format(
                     concurrency_idx))

python/pipeline/pipeline_server.py

@@ -261,6 +261,8 @@ class PipelineServer(object):
                 "use_mkldnn": False,
                 "mkldnn_cache_capacity": 0,
                 "min_subgraph_size": 3,
+                "collect_shape_range_info": "",
+                "tuned_dynamic_shape_info": "",
             },
         }
         for op in self._used_op:
@@ -422,6 +424,8 @@ class ServerYamlConfChecker(object):
             "use_mkldnn": False,
             "mkldnn_cache_capacity": 0,
             "min_subgraph_size": 3,
+            "collect_shape_range_info": "",
+            "tuned_dynamic_shape_info": "",
         }
         conf_type = {
             "model_config": str,
@@ -438,6 +442,8 @@ class ServerYamlConfChecker(object):
             "mkldnn_op_list": list,
             "mkldnn_bf16_op_list": list,
             "min_subgraph_size": int,
+            "collect_shape_range_info": str,
+            "tuned_dynamic_shape_info": str,
         }
         conf_qualification = {"thread_num": (">=", 1), }
         ServerYamlConfChecker.check_conf(conf, default_conf, conf_type,