fix trt

deploy/cpp_infer/src/ocr_cls.cpp

@@ -112,8 +112,11 @@ void Classifier::LoadModel(const std::string &model_dir) {
         precision = paddle_infer::Config::Precision::kInt8;
       }
       config.EnableTensorRtEngine(1 << 20, 10, 3, precision, false, false);
-      config.CollectShapeRangeInfo("./trt_shape.txt");
-      config.EnableTunedTensorRtDynamicShape("./trt_shape.txt", true);
+      if (!Utility::PathExists("./trt_cls_shape.txt")){
+        config.CollectShapeRangeInfo("./trt_cls_shape.txt");
+      } else { 
+        config.EnableTunedTensorRtDynamicShape("./trt_cls_shape.txt", true);
+      }
     }
   } else {
     config.DisableGpu();

deploy/cpp_infer/src/ocr_det.cpp

@@ -33,8 +33,11 @@ void DBDetector::LoadModel(const std::string &model_dir) {
         precision = paddle_infer::Config::Precision::kInt8;
       }
       config.EnableTensorRtEngine(1 << 30, 1, 20, precision, false, false);
-      config.CollectShapeRangeInfo("./trt_shape.txt");
-      config.EnableTunedTensorRtDynamicShape("./trt_shape.txt", true);
+      if (!Utility::PathExists("./trt_det_shape.txt")){
+        config.CollectShapeRangeInfo("./trt_det_shape.txt");
+      } else { 
+        config.EnableTunedTensorRtDynamicShape("./trt_det_shape.txt", true);
+      }
       
     }
   } else {

deploy/cpp_infer/src/ocr_rec.cpp

@@ -147,9 +147,11 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
       if (this->precision_ == "int8") {
         precision = paddle_infer::Config::Precision::kInt8;
       }
-      config.EnableTensorRtEngine(1 << 20, 10, 15, precision, false, false);
-      config.CollectShapeRangeInfo("./trt_shape.txt");
-      config.EnableTunedTensorRtDynamicShape("./trt_shape.txt", true);
+      if (!Utility::PathExists("./trt_rec_shape.txt")){
+        config.CollectShapeRangeInfo("./trt_rec_shape.txt");
+      } else { 
+        config.EnableTunedTensorRtDynamicShape("./trt_rec_shape.txt", true);
+      }
       
     }
   } else {

tools/infer/utility.py

@@ -228,19 +228,18 @@ def create_predictor(args, mode, logger):
                     use_calib_mode=False)
 
                 # collect shape
-                if args.shape_info_filename is not None:
-                    if not os.path.exists(args.shape_info_filename):
-                        config.collect_shape_range_info(
-                            args.shape_info_filename)
+                trt_shape_f = f"{os.path.dirname(args.shape_info_filename)}/{mode}_{os.path.basename(args.shape_info_filename)}"
+                if trt_shape_f is not None:
+                    if not os.path.exists(trt_shape_f):
+                        config.collect_shape_range_info(trt_shape_f)
                         logger.info(
-                            f"collect dynamic shape info into : {args.shape_info_filename}"
+                            f"collect dynamic shape info into : {trt_shape_f}"
                         )
                     else:
                         logger.info(
-                            f"dynamic shape info file( {args.shape_info_filename} ) already exists, not need to generate again."
+                            f"dynamic shape info file( {trt_shape_f} ) already exists, not need to generate again."
                         )
-                    config.enable_tuned_tensorrt_dynamic_shape(
-                        args.shape_info_filename, True)
+                    config.enable_tuned_tensorrt_dynamic_shape(trt_shape_f, True)
                 else:
                     logger.info(
                         f"when using tensorrt, dynamic shape is a suggested option, you can use '--shape_info_filename=shape.txt' for offline dygnamic shape tuning"