python/kserve/test/test_v1beta1_predictors_config.py
def make_instance(self, include_optional):
        """Test V1beta1PredictorsConfig
            include_option is a boolean, when False only required
            params are included, when True both required and
            optional params are included """
        # model = kserve.models.v1beta1_predictors_config.V1beta1PredictorsConfig()  # noqa: E501
        if include_optional :
            return V1beta1PredictorsConfig(
                onnx = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0', 
                    supported_frameworks=['0'] ), 
                pytorch = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ), 
                sklearn = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ), 
                tensorflow = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ), 
                triton = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ),
                xgboost = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ),
            )
        else :
            return V1beta1PredictorsConfig(
        )
Test V1beta1PredictorsConfig
            include_option is a boolean, when False only required
            params are included, when True both required and
            optional params are included 
Test V1beta1PredictorsConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included
Test V1beta1PredictorsConfig include_option is a boolean when False only required params are included when True both required and optional params are included
def make_instance(self, include_optional):
        if include_optional :
            return V1beta1PredictorsConfig(
                onnx = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0', 
                    supported_frameworks=['0'] ), 
                pytorch = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ), 
                sklearn = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ), 
                tensorflow = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ), 
                triton = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ),
                xgboost = kserve.models.v1beta1_predictor_config.V1beta1PredictorConfig(
                    default_gpu_image_version = '0', 
                    default_image_version = '0', 
                    image = '0',
                    supported_frameworks=['0'] ),
            )
        else :
            return V1beta1PredictorsConfig(
        )
def make_instance ( self , include_optional ) : if include_optional : return V1beta1PredictorsConfig ( onnx = kserve . models . v1beta1_predictor_config . V1beta1PredictorConfig ( default_gpu_image_version = '0' , default_image_version = '0' , image = '0' , supported_frameworks = [ '0' ] ) , pytorch = kserve . models . v1beta1_predictor_config . V1beta1PredictorConfig ( default_gpu_image_version = '0' , default_image_version = '0' , image = '0' , supported_frameworks = [ '0' ] ) , sklearn = kserve . models . v1beta1_predictor_config . V1beta1PredictorConfig ( default_gpu_image_version = '0' , default_image_version = '0' , image = '0' , supported_frameworks = [ '0' ] ) , tensorflow = kserve . models . v1beta1_predictor_config . V1beta1PredictorConfig ( default_gpu_image_version = '0' , default_image_version = '0' , image = '0' , supported_frameworks = [ '0' ] ) , triton = kserve . models . v1beta1_predictor_config . V1beta1PredictorConfig ( default_gpu_image_version = '0' , default_image_version = '0' , image = '0' , supported_frameworks = [ '0' ] ) , xgboost = kserve . models . v1beta1_predictor_config . V1beta1PredictorConfig ( default_gpu_image_version = '0' , default_image_version = '0' , image = '0' , supported_frameworks = [ '0' ] ) , ) else : return V1beta1PredictorsConfig ( )
Test V1beta1PredictorsConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included
Test V1beta1PredictorsConfig include_option is a boolean when False only required params are included when True both required and optional params are included
"""Test V1beta1PredictorsConfig
            include_option is a boolean, when False only required
            params are included, when True both required and
            optional params are included """ # model = kserve.models.v1beta1_predictors_config.V1beta1PredictorsConfig()  # noqa: E501
self
include_optional