Merge pull request #1390 from jagadeeshi2i/kserve-class-rename

fix: Kserve class rename

Author: HamidShojanazeri

kubernetes/kserve/image_transformer/image_transformer/__main__.py

@@ -15,12 +15,20 @@
 import argparse
 import json
 import kserve
+from importlib.metadata import version
 from .image_transformer import ImageTransformer
 from .transformer_model_repository import TransformerModelRepository
 
+if version('kserve') >= '0.8.0':
+    import kserve.model_server as model_server
+    from kserve.model_server import ModelServer
+else:
+    import kserve.kfserver as model_server
+    from kserve.kfserver import KFServer as ModelServer
+
 DEFAULT_MODEL_NAME = "model"
 
-parser = argparse.ArgumentParser(parents=[kserve.kfserver.parser])
+parser = argparse.ArgumentParser(parents=[model_server.parser])
 parser.add_argument("--predictor_host",
                     help="The URL for the model predict function",
                     required=True)
@@ -67,7 +75,7 @@ def parse_config():
         transformer = ImageTransformer(model_name,
                                        predictor_host=args.predictor_host)
         models.append(transformer)
-    kserve.KFServer(
+    ModelServer(
         registered_models=TransformerModelRepository(args.predictor_host),
         http_port=8080,
     ).start(models=models)

kubernetes/kserve/image_transformer/image_transformer/image_transformer.py

@@ -17,11 +17,17 @@
 import json
 import logging
 from typing import List, Dict
+from importlib.metadata import version
 import tornado
 from PIL import Image
 import torchvision.transforms as transforms
 import kserve
 
+if version('kserve') >= '0.8.0':
+    from kserve.model import Model as Model
+else:
+    from kserve.kfmodel import KFModel as Model
+
 logging.basicConfig(level=kserve.constants.KSERVE_LOGLEVEL)
 
 EXPLAINER_URL_FORMAT = "http://{0}/v1/models/{1}:explain"
@@ -49,12 +55,12 @@ def image_transform(instance):
     return instance
 
 
-class ImageTransformer(kserve.KFModel):
+class ImageTransformer(Model):
     """ A class object for the data handling activities of Image Classification
     Task and returns a KServe compatible response.
 
     Args:
-        kserve (class object): The KFModel class from the KServe
+        kserve (class object): The Model class from the KServe
         modeule is passed here.
     """
 

kubernetes/kserve/image_transformer/image_transformer/transformer_model_repository.py

@@ -1,12 +1,18 @@
 """ A respository of image transformer models """
 import logging
-from kserve.kfmodel_repository import KFModelRepository
+from importlib.metadata import version
 import kserve
 
+if version('kserve') >= '0.8.0':
+    from kserve.model_repository import ModelRepository as ModelRepository
+else:
+    from kserve.kfmodel_repository import KFModelRepository as ModelRepository
+
 logging.basicConfig(level=kserve.constants.KSERVE_LOGLEVEL)
 
+logging.basicConfig(level=kserve.constants.KSERVE_LOGLEVEL)
 
-class TransformerModelRepository(KFModelRepository):
+class TransformerModelRepository(ModelRepository):
     """Stores the Image Transformer Models
 
     Args:

kubernetes/kserve/kserve_wrapper/TSModelRepository.py

@@ -1,12 +1,16 @@
 """ The repository to serve the Torchserve Models in the kserve side"""
 import logging
+from importlib.metadata import version
 import kserve
-from kserve.kfmodel_repository import KFModelRepository
 
-logging.basicConfig(level=kserve.constants.KSERVE_LOGLEVEL)
+if version('kserve') >= '0.8.0':
+    from kserve.model_repository import ModelRepository as ModelRepository
+else:
+    from kserve.kfmodel_repository import KFModelRepository as ModelRepository
 
+logging.basicConfig(level=kserve.constants.KSERVE_LOGLEVEL)
 
-class TSModelRepository(KFModelRepository):
+class TSModelRepository(ModelRepository):
     """A repository of kserve KFModels
     Args:
         KFModelRepository (object): The parameters from the KFModelRepository is passed

kubernetes/kserve/kserve_wrapper/TorchserveModel.py

@@ -3,9 +3,15 @@
 import json
 from typing import Dict
 import logging
+from importlib.metadata import version
 import kserve
 import tornado.web
 
+if version('kserve') >= '0.8.0':
+    from kserve.model import Model as Model
+else:
+    from kserve.kfmodel import KFModel as Model
+
 logging.basicConfig(level=kserve.constants.KSERVE_LOGLEVEL)
 
 REGISTER_URL_FORMAT = "{0}/models?initial_workers=1&url={1}"
@@ -15,7 +21,7 @@
 EXPLAINER_URL_FORMAT = "http://{0}/v1/models/{1}:explain"
 
 
-class TorchserveModel(kserve.KFModel):
+class TorchserveModel(Model):
     """The torchserve side inference and explain end-points requests are handled to
     return a KServe side response
 

kubernetes/kserve/kserve_wrapper/__main__.py

@@ -1,10 +1,17 @@
 """ KServe wrapper to handler inference in the kserve_predictor """
 import json
 import logging
+from importlib.metadata import version
 import kserve
+
 from TorchserveModel import TorchserveModel
 from TSModelRepository import TSModelRepository
 
+if version('kserve') >= '0.8.0':
+    from kserve.model_server import ModelServer
+else:
+    from kserve.kfserver import KFServer as ModelServer
+
 logging.basicConfig(level=kserve.constants.KSERVE_LOGLEVEL)
 
 DEFAULT_MODEL_NAME = "model"
@@ -84,7 +91,7 @@ def parse_config():
         model = TorchserveModel(model_name, inference_address,
                                 management_address, model_dir)
         models.append(model)
-    kserve.KFServer(
+    ModelServer(
         registered_models=TSModelRepository(inference_address,
                                             management_address, model_dir),
         http_port=8080,