Style and some more changes

src/deepsparse/evaluation/results.py

@@ -98,7 +98,7 @@ def _save_to_json(result: Result, save_path: str):
 
 
 def _save_to_yaml(result: Result, save_path: str):
-    _save(yaml.dump(result.dict()), save_path, expected_ext=".yaml")
+    _save(yaml.dump(result.model_dump()), save_path, expected_ext=".yaml")
 
 
 def _save(data: str, save_path: str, expected_ext: str):

src/deepsparse/loggers/config.py

@@ -82,8 +82,6 @@ class LoggingConfig(BaseModel):
         description="Metric level config",
     )
 
-    # TODO[pydantic]: We couldn't refactor the `validator`, please replace it by `field_validator` manually.
-    # Check https://docs.pydantic.dev/dev-v2/migration/#changes-to-validators for more information.
     @validator("loggers", always=True)
     def always_include_python_logger(cls, value):
         if "default" not in value:

src/deepsparse/loggers/logger_manager.py

@@ -65,7 +65,7 @@ class LoggerManager(AsyncExecutor, LoggerFactory):
     """
 
     def __init__(self, config: str = ""):
-        self.config = LoggingConfig.from_config(config).dict()
+        self.config = LoggingConfig.from_config(config).model_dump()
         super().__init__(config=self.config)
 
     def log(

src/deepsparse/loggers/root_logger.py

@@ -38,7 +38,7 @@ class RootLogger(FrequencyFilter):
     its own FrequencyFilter
 
     :param config: config with respect to
-     the log_type (LoggerConfig().dict().get(log_type))
+     the log_type (LoggerConfig().model_dump().get(log_type))
     :param leaf_logger: leaf logger singleton shared among other RootLogger
 
     """

src/deepsparse/pipelines/numpy_schemas.py

@@ -15,7 +15,7 @@
 from typing import Generic, Type, TypeVar
 
 import numpy
-from pydantic.fields import ModelField
+from pydantic.v1.fields import ModelField
 
 
 Dtype = TypeVar("Dtype")
@@ -39,8 +39,6 @@ class Model(BaseModel):
     """
 
     @classmethod
-    # TODO[pydantic]: We couldn't refactor `__get_validators__`, please create the `__get_pydantic_core_schema__` manually.
-    # Check https://docs.pydantic.dev/latest/migration/#defining-custom-types for more information.
     def __get_validators__(cls):
         yield cls.validate
 
@@ -78,8 +76,6 @@ class _NumpyDtypeValidator:
     expected: Type[numpy.dtype]
 
     @classmethod
-    # TODO[pydantic]: We couldn't refactor `__get_validators__`, please create the `__get_pydantic_core_schema__` manually.
-    # Check https://docs.pydantic.dev/latest/migration/#defining-custom-types for more information.
     def __get_validators__(cls):
         yield cls.validate
 

src/deepsparse/server/cli.py

@@ -249,7 +249,7 @@ def main(
         with TemporaryDirectory() as tmp_dir:
             config_path = os.path.join(tmp_dir, "server-config.yaml")
             with open(config_path, "w") as fp:
-                yaml.dump(cfg.dict(), fp)
+                yaml.dump(cfg.model_dump(), fp)
 
             server = _fetch_server(integration=integration, config=config_path)
             server.start_server(

src/deepsparse/server/config_hot_reloading.py

@@ -114,7 +114,7 @@ def _diff_generator(
         timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
         with open(old_path, "w") as fp:
             fp.write(f"# Version {version} saved at {timestamp} by deepsparse.server\n")
-            yaml.safe_dump(old_config.dict(), fp)
+            yaml.safe_dump(old_config.model_dump(), fp)
         _LOGGER.info(f"Saved old version of config to {old_path}")
         version += 1
 
@@ -147,10 +147,10 @@ def _update_endpoints(
 
     for endpoint in removed:
         _LOGGER.info(f"Requesting removal of endpoint '{endpoint.route}'")
-        requests.delete(url, json=endpoint.dict()).raise_for_status()
+        requests.delete(url, json=endpoint.model_dump()).raise_for_status()
 
     for endpoint in added:
         _LOGGER.info(f"Requesting addition of endpoint '{endpoint.route}'")
-        requests.post(url, json=endpoint.dict()).raise_for_status()
+        requests.post(url, json=endpoint.model_dump()).raise_for_status()
 
     return added, removed

src/deepsparse/server/helpers.py

@@ -35,7 +35,7 @@
 
 def create_error_response(status_code: HTTPStatus, message: str) -> JSONResponse:
     return JSONResponse(
-        ErrorResponse(message=message, type="invalid_request_error").dict(),
+        ErrorResponse(message=message, type="invalid_request_error").model_dump(),
         status_code=status_code.value,
     )
 

src/deepsparse/server/server.py

@@ -279,7 +279,7 @@ async def benchmark(
         json_params = await raw_request.json()
         benchmark_config = PipelineBenchmarkConfig(**json_params)
         results = benchmark_from_pipeline(
-            pipeline=proxy_pipeline.pipeline, **benchmark_config.dict()
+            pipeline=proxy_pipeline.pipeline, **benchmark_config.model_dump()
         )
 
         return results

src/deepsparse/transformers/haystack/helpers.py

@@ -34,8 +34,9 @@ def print_pipeline_documents(
     if isinstance(haystack_pipeline_output.query, list):
         for i in range(len(haystack_pipeline_output.query)):
             results_dict = {
-                key: value[i] for key, value in haystack_pipeline_output.dict().items()
+                key: value[i]
+                for key, value in haystack_pipeline_output.model_dump().items()
             }
             print_documents(results_dict)
     else:
-        print_documents(haystack_pipeline_output.dict())
+        print_documents(haystack_pipeline_output.model_dump())

src/deepsparse/transformers/pipelines/chat/chat.py

@@ -55,8 +55,6 @@ class ChatInput(TextGenerationInput):
         "will be set to a random uuid.",
     )
 
-    # TODO[pydantic]: We couldn't refactor the `validator`, please replace it by `field_validator` manually.
-    # Check https://docs.pydantic.dev/dev-v2/migration/#changes-to-validators for more information.
     @validator("session_ids")
     def validate_session_ids(cls, value, values) -> Union[None, List[str]]:
         # make sure that the that format session_ids confirms with the

src/deepsparse/transformers/pipelines_cli.py

@@ -233,7 +233,7 @@ def response_to_json(response: Any):
     elif isinstance(response, dict):
         return {key: response_to_json(val) for key, val in response.items()}
     elif isinstance(response, BaseModel):
-        return response.dict()
+        return response.model_dump()
     return json.dumps(response)
 
 

src/deepsparse/yolo/schemas.py

@@ -18,7 +18,7 @@
 """
 
 from collections import namedtuple
-from typing import Any, Iterable, List, Optional, TextIO
+from typing import Any, Iterable, List, Optional, TextIO, Union
 
 import numpy
 from PIL import Image
@@ -106,7 +106,7 @@ class YOLOOutput(BaseModel):
     scores: List[List[float]] = Field(
         description="List of scores, one for each prediction"
     )
-    labels: List[List[str]] = Field(
+    labels: List[Union[List[str], List[float]]] = Field(
         description="List of labels, one for each prediction"
     )
     intermediate_outputs: Optional[Any] = Field(

tests/deepsparse/loggers/test_config.py

@@ -47,7 +47,7 @@ def test_config_generates_default_json():
 
     """
     expected_dict = yaml.safe_load(expected_config)
-    default_dict = LoggingConfig().dict()
+    default_dict = LoggingConfig().model_dump()
     assert expected_dict == default_dict
 
 

tests/deepsparse/utils/test_data.py

@@ -85,7 +85,7 @@ def test_prep_for_serialization(unserialized_output, target_serialized_output):
     def check_dict_equality(dict_1, dict_2):
         for key, value in dict_1.items():
             if isinstance(value, BaseModel):
-                value = value.dict()
+                value = value.model_dump()
                 check_dict_equality(value, dict_2[key].dict())
             elif isinstance(value, dict):
                 check_dict_equality(value, dict_2[key])
@@ -97,6 +97,6 @@ def check_dict_equality(dict_1, dict_2):
                 assert value == dict_2[key]
 
     serialized_output = prep_for_serialization(unserialized_output)
-    serialized_output = serialized_output.dict()
-    target_serialized_output = target_serialized_output.dict()
+    serialized_output = serialized_output.model_dump()
+    target_serialized_output = target_serialized_output.model_dump()
     check_dict_equality(target_serialized_output, serialized_output)