def EndpointSpec(framework, storage_uri, service_account):
if framework == "tensorflow":
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
tensorflow=V1alpha2TensorflowSpec(storage_uri=storage_uri),
service_account_name=service_account,
))
elif framework == "pytorch":
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
pytorch=V1alpha2PyTorchSpec(storage_uri=storage_uri),
service_account_name=service_account,
))
elif framework == "sklearn":
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
sklearn=V1alpha2SKLearnSpec(storage_uri=storage_uri),
service_account_name=service_account,
))
elif framework == "xgboost":
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
xgboost=V1alpha2XGBoostSpec(storage_uri=storage_uri),
service_account_name=service_account,
))
elif framework == "onnx":
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
onnx=V1alpha2ONNXSpec(storage_uri=storage_uri),
service_account_name=service_account,
))
elif framework == "tensorrt":
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
tensorrt=V1alpha2TensorRTSpec(storage_uri=storage_uri),
service_account_name=service_account,
))
else:
raise ("Error: No matching framework: " + framework)
def EndpointSpec(framework,
storage_uri,
service_account_name="k8s-sa",
transformer_custom_image=""):
if framework == 'tensorflow':
return V1alpha2EndpointSpec(
predictor=V1alpha2PredictorSpec(
service_account_name=service_account_name,
tensorflow=V1alpha2TensorflowSpec(storage_uri=storage_uri)),
transformer=V1alpha2TransformerSpec(
min_replicas=1,
custom=V1alpha2CustomSpec(container=client.V1Container(
image=transformer_custom_image,
name="kfserving-container"))))
elif framework == 'pytorch':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
pytorch=V1alpha2PyTorchSpec(storage_uri=storage_uri)))
elif framework == 'sklearn':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
sklearn=V1alpha2SKLearnSpec(storage_uri=storage_uri)))
elif framework == 'xgboost':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
xgboost=V1alpha2XGBoostSpec(storage_uri=storage_uri)))
elif framework == 'onnx':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
onnx=V1alpha2ONNXSpec(storage_uri=storage_uri)))
elif framework == 'tensorrt':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
tensorrt=V1alpha2TensorRTSpec(storage_uri=storage_uri)))
else:
raise ("Error: No matching framework: " + framework)
def EndpointSpec(framework, storage_uri):
if framework == 'tensorflow':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
tensorflow=V1alpha2TensorflowSpec(storage_uri=storage_uri)))
elif framework == 'pytorch':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
pytorch=V1alpha2PyTorchSpec(storage_uri=storage_uri)))
elif framework == 'sklearn':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
sklearn=V1alpha2SKLearnSpec(storage_uri=storage_uri)))
elif framework == 'xgboost':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
xgboost=V1alpha2XGBoostSpec(storage_uri=storage_uri)))
elif framework == 'onnx':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
onnx=V1alpha2ONNXSpec(storage_uri=storage_uri)))
elif framework == 'tensorrt':
return V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
tensorrt=V1alpha2TensorRTSpec(storage_uri=storage_uri)))
else:
raise ("Error: No matching framework: " + framework)
def EndpointSpec(framework, storage_uri, service_account, min_replicas,
max_replicas):
endpointSpec = V1alpha2EndpointSpec(predictor=V1alpha2PredictorSpec(
service_account_name=service_account,
min_replicas=(min_replicas if min_replicas >= 0 else None),
max_replicas=(max_replicas if max_replicas > 0
and max_replicas >= min_replicas else None)))
if framework == "tensorflow":
endpointSpec.predictor.tensorflow = V1alpha2TensorflowSpec(
storage_uri=storage_uri)
return endpointSpec
elif framework == "pytorch":
endpointSpec.predictor.pytorch = V1alpha2PyTorchSpec(
storage_uri=storage_uri)
return endpointSpec
elif framework == "sklearn":
endpointSpec.predictor.sklearn = V1alpha2SKLearnSpec(
storage_uri=storage_uri)
return endpointSpec
elif framework == "xgboost":
endpointSpec.predictor.xgboost = V1alpha2XGBoostSpec(
storage_uri=storage_uri)
return endpointSpec
elif framework == "onnx":
endpointSpec.predictor.onnx = V1alpha2ONNXSpec(storage_uri=storage_uri)
return endpointSpec
elif framework == "tensorrt":
endpointSpec.predictor.tensorrt = V1alpha2TensorRTSpec(
storage_uri=storage_uri)
return endpointSpec
else:
raise ("Error: No matching framework: " + framework)