Add config overrides for protected namespaces to remove warnings for …

…pydantic classes that have model_* params (#1657)

* Add config overrides for protected namespaces to remove warnings for pydantic classes that have model_* params

* make quality

src/deepsparse/pipeline_config.py

@@ -14,7 +14,7 @@
 
 from typing import Any, Dict, List, Optional
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 from deepsparse.operators.engine_operator import DEEPSPARSE_ENGINE
 
@@ -84,3 +84,6 @@ class PipelineConfig(BaseModel):
             "into the pipeline as kwargs"
         ),
     )
+
+    # override name spaces due to model_ warnings in pydantic 2.X
+    model_config = ConfigDict(protected_namespaces=())

src/deepsparse/server/server.py

@@ -20,7 +20,7 @@
 from typing import AsyncGenerator, List, Optional, Union
 
 import yaml
-from pydantic import BaseModel
+from pydantic import BaseModel, ConfigDict
 
 import uvicorn
 from deepsparse.benchmark.benchmark_pipeline import benchmark_from_pipeline
@@ -52,6 +52,9 @@ class CheckReady(BaseModel):
 class ModelMetaData(BaseModel):
     model_path: str
 
+    # override name spaces due to model_ warnings in pydantic 2.X
+    model_config = ConfigDict(protected_namespaces=())
+
 
 # For deepsparse endpoints, we bind the `predict`` and `predict_from_files` functions to
 # each of the added routes. As we require access to the pipeline to run inference on