update hpi config (#14187)

ppocr/utils/export_model.py

@@ -39,42 +39,42 @@ def setup_orderdict():
 def dump_infer_config(config, path, logger):
     setup_orderdict()
     infer_cfg = OrderedDict()
-    if config["Global"].get("hpi_config_path", None):
-        hpi_config = yaml.safe_load(open(config["Global"]["hpi_config_path"], "r"))
-        rec_resize_img_dict = next(
-            (
-                item
-                for item in config["Eval"]["dataset"]["transforms"]
-                if "RecResizeImg" in item
-            ),
-            None,
-        )
-        if rec_resize_img_dict:
-            dynamic_shapes = [1] + rec_resize_img_dict["RecResizeImg"]["image_shape"]
-            if hpi_config["Hpi"]["backend_config"].get("paddle_tensorrt", None):
-                hpi_config["Hpi"]["backend_config"]["paddle_tensorrt"][
-                    "dynamic_shapes"
-                ]["x"] = [dynamic_shapes for i in range(3)]
-                hpi_config["Hpi"]["backend_config"]["paddle_tensorrt"][
-                    "max_batch_size"
-                ] = 1
-            if hpi_config["Hpi"]["backend_config"].get("tensorrt", None):
-                hpi_config["Hpi"]["backend_config"]["tensorrt"]["dynamic_shapes"][
-                    "x"
-                ] = [dynamic_shapes for i in range(3)]
-                hpi_config["Hpi"]["backend_config"]["tensorrt"]["max_batch_size"] = 1
-        else:
-            if hpi_config["Hpi"]["backend_config"].get("paddle_tensorrt", None):
-                hpi_config["Hpi"]["supported_backends"]["gpu"].remove("paddle_tensorrt")
-                del hpi_config["Hpi"]["backend_config"]["paddle_tensorrt"]
-            if hpi_config["Hpi"]["backend_config"].get("tensorrt", None):
-                hpi_config["Hpi"]["supported_backends"]["gpu"].remove("tensorrt")
-                del hpi_config["Hpi"]["backend_config"]["tensorrt"]
-            hpi_config["Hpi"]["selected_backends"]["gpu"] = "paddle_infer"
-        infer_cfg["Hpi"] = hpi_config["Hpi"]
     if config["Global"].get("pdx_model_name", None):
-        infer_cfg["Global"] = {}
-        infer_cfg["Global"]["model_name"] = config["Global"]["pdx_model_name"]
+        infer_cfg["Global"] = {"model_name": config["Global"]["pdx_model_name"]}
+    if config["Global"].get("uniform_output_enabled", None):
+        arch_config = config["Architecture"]
+        if arch_config["algorithm"] in ["SVTR_LCNet", "SVTR_HGNet"]:
+            common_dynamic_shapes = {
+                "x": [[1, 3, 48, 320], [1, 3, 48, 320], [8, 3, 48, 320]]
+            }
+        elif arch_config["model_type"] == "det":
+            common_dynamic_shapes = {
+                "x": [[1, 3, 160, 160], [1, 3, 160, 160], [1, 3, 1280, 1280]]
+            }
+        elif arch_config["algorithm"] == "SLANet":
+            common_dynamic_shapes = {
+                "x": [[1, 3, 32, 32], [1, 3, 64, 448], [8, 3, 192, 672]]
+            }
+        elif arch_config["algorithm"] == "LaTeXOCR":
+            common_dynamic_shapes = {
+                "x": [[1, 3, 224, 224], [1, 3, 448, 448], [8, 3, 1280, 1280]]
+            }
+        else:
+            common_dynamic_shapes = None
+
+        backend_keys = ["paddle_infer", "tensorrt"]
+        hpi_config = {
+            "backend_configs": {
+                key: {
+                    (
+                        "dynamic_shapes" if key == "tensorrt" else "trt_dynamic_shapes"
+                    ): common_dynamic_shapes
+                }
+                for key in backend_keys
+            }
+        }
+        if common_dynamic_shapes:
+            infer_cfg["Hpi"] = hpi_config
 
     infer_cfg["PreProcess"] = {"transform_ops": config["Eval"]["dataset"]["transforms"]}
     postprocess = OrderedDict()
@@ -96,10 +96,8 @@ def dump_infer_config(config, path, logger):
 
     infer_cfg["PostProcess"] = postprocess
 
-    with open(path, "w") as f:
-        yaml.dump(
-            infer_cfg, f, default_flow_style=False, encoding="utf-8", allow_unicode=True
-        )
+    with open(path, "w", encoding="utf-8") as f:
+        yaml.dump(infer_cfg, f, default_flow_style=False, allow_unicode=True)
     logger.info("Export inference config file to {}".format(os.path.join(path)))