code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
values |
|---|---|---|---|---|---|---|---|
async def models(self) -> ListModelsResponse:
"""Get a list of models in the model registry.
Returns:
ListModelsResponse: List of models object.
"""
models = list(self.dataplane.model_registry.get_models().keys())
return ListModelsResponse.model_validate({"models": m... | Get a list of models in the model registry.
Returns:
ListModelsResponse: List of models object.
| models | python | kserve/kserve | python/kserve/kserve/protocol/rest/v2_endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/v2_endpoints.py | Apache-2.0 |
async def model_metadata(
self, model_name: str, model_version: Optional[str] = None
) -> ModelMetadataResponse:
"""Model metadata handler. It provides information about a model.
Args:
model_name (str): Model name.
model_version (Optional[str]): Model version (option... | Model metadata handler. It provides information about a model.
Args:
model_name (str): Model name.
model_version (Optional[str]): Model version (optional).
Returns:
ModelMetadataResponse: Model metadata object.
| model_metadata | python | kserve/kserve | python/kserve/kserve/protocol/rest/v2_endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/v2_endpoints.py | Apache-2.0 |
async def model_ready(
self, model_name: str, model_version: Optional[str] = None
) -> ModelReadyResponse:
"""Check if a given model is ready.
Args:
model_name (str): Model name.
model_version (str): Model version.
Returns:
ModelReadyResponse: Mo... | Check if a given model is ready.
Args:
model_name (str): Model name.
model_version (str): Model version.
Returns:
ModelReadyResponse: Model ready object
| model_ready | python | kserve/kserve | python/kserve/kserve/protocol/rest/v2_endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/v2_endpoints.py | Apache-2.0 |
async def infer(
self,
raw_request: Request,
raw_response: Response,
model_name: str,
request_body: Union[InferenceRequest, bytes],
model_version: Optional[str] = None,
) -> Union[InferenceResponse, Response]:
"""Infer handler.
Args:
raw_r... | Infer handler.
Args:
raw_request (Request): fastapi request object,
raw_response (Response): fastapi response object,
model_name (str): Model name.
request_body (InferenceRequest): Inference request body.
model_version (Optional[str]): Model version (... | infer | python | kserve/kserve | python/kserve/kserve/protocol/rest/v2_endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/v2_endpoints.py | Apache-2.0 |
async def load(self, model_name: str) -> Dict:
"""Model load handler.
Args:
model_name (str): Model name.
Returns:
Dict: {"name": model_name, "load": True}
"""
await self.model_repository_extension.load(model_name)
return {"name": model_name, "lo... | Model load handler.
Args:
model_name (str): Model name.
Returns:
Dict: {"name": model_name, "load": True}
| load | python | kserve/kserve | python/kserve/kserve/protocol/rest/v2_endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/v2_endpoints.py | Apache-2.0 |
async def unload(self, model_name: str) -> Dict:
"""Model unload handler.
Args:
model_name (str): Model name.
Returns:
Dict: {"name": model_name, "unload": True}
"""
await self.model_repository_extension.unload(model_name)
return {"name": model_n... | Model unload handler.
Args:
model_name (str): Model name.
Returns:
Dict: {"name": model_name, "unload": True}
| unload | python | kserve/kserve | python/kserve/kserve/protocol/rest/v2_endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/v2_endpoints.py | Apache-2.0 |
def register_v2_endpoints(
app: FastAPI,
dataplane: DataPlane,
model_repository_extension: Optional[ModelRepositoryExtension],
):
"""Register V2 endpoints.
Args:
app (FastAPI): FastAPI app.
dataplane (DataPlane): DataPlane object.
model_repository_extension (Optional[ModelRe... | Register V2 endpoints.
Args:
app (FastAPI): FastAPI app.
dataplane (DataPlane): DataPlane object.
model_repository_extension (Optional[ModelRepositoryExtension]): Model repository extension.
| register_v2_endpoints | python | kserve/kserve | python/kserve/kserve/protocol/rest/v2_endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/v2_endpoints.py | Apache-2.0 |
async def wait_for_termination(self, grace_period: Optional[int] = None):
"""Wait for the process to terminate. When a timeout occurs,
it cancels the task and raises TimeoutError."""
async def _wait_for_process():
while self._process.exitcode is None:
await asyncio.s... | Wait for the process to terminate. When a timeout occurs,
it cancels the task and raises TimeoutError. | wait_for_termination | python | kserve/kserve | python/kserve/kserve/protocol/rest/multiprocess/server.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/multiprocess/server.py | Apache-2.0 |
async def terminate_all(self) -> None:
"""Propagate signal to all child processes and wait for termination."""
for p in self._processes:
p.terminate()
async def force_terminate(process) -> None:
try:
await process.wait_for_termination(
... | Propagate signal to all child processes and wait for termination. | terminate_all | python | kserve/kserve | python/kserve/kserve/protocol/rest/multiprocess/server.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/multiprocess/server.py | Apache-2.0 |
def get_open_ai_models(repository: ModelRepository) -> dict[str, Model]:
"""Retrieve all models in the repository that implement the OpenAI interface"""
from .openai_model import OpenAIModel
return {
name: model
for name, model in repository.get_models().items()
if isinstance(model,... | Retrieve all models in the repository that implement the OpenAI interface | get_open_ai_models | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/config.py | Apache-2.0 |
async def create_completion(
self,
model_name: str,
request: CompletionRequest,
raw_request: Request,
headers: Headers,
response: Response,
) -> Union[AsyncGenerator[str, None], Completion, ErrorResponse]:
"""Generate the text with the provided text prompt.
... | Generate the text with the provided text prompt.
Args:
model_name (str): Model name.
request (CompletionRequest): Params to create a completion.
raw_request (Request): fastapi request object.
headers: (Headers): Request headers.
response: (Response): ... | create_completion | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/dataplane.py | Apache-2.0 |
async def create_chat_completion(
self,
model_name: str,
request: ChatCompletionRequest,
raw_request: Request,
headers: Headers,
response: Response,
) -> Union[AsyncGenerator[str, None], ChatCompletion, ErrorResponse]:
"""Generate the text with the provided te... | Generate the text with the provided text prompt.
Args:
model_name (str): Model name.
request (CreateChatCompletionRequest): Params to create a chat completion.
headers: (Optional[Dict[str, str]]): Request headers.
Returns:
response: A non-streaming or st... | create_chat_completion | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/dataplane.py | Apache-2.0 |
async def create_embedding(
self,
model_name: str,
request: EmbeddingRequest,
raw_request: Request,
headers: Headers,
response: Response,
) -> Union[AsyncGenerator[str, None], Embedding, ErrorResponse]:
"""Generate the text with the provided text prompt.
... | Generate the text with the provided text prompt.
Args:
model_name (str): Model name.
request (EmbeddingRequest): Params to create a embedding.
raw_request (Request): fastapi request object.
headers: (Headers): Request headers.
response: (Response): Fa... | create_embedding | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/dataplane.py | Apache-2.0 |
async def create_rerank(
self,
model_name: str,
request: RerankRequest,
raw_request: Request,
headers: Headers,
response: Response,
) -> Union[AsyncGenerator[str, None], Rerank, ErrorResponse]:
"""Generate the text with the provided text prompt.
Args:
... | Generate the text with the provided text prompt.
Args:
model_name (str): Model name.
request (RerankRequest): Params to create rerank response.
raw_request (Request): fastapi request object.
headers: (Headers): Request headers.
response: (Response): Fa... | create_rerank | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/dataplane.py | Apache-2.0 |
async def models(self) -> List[OpenAIModel]:
"""Retrieve a list of models
Returns:
response: A list of OpenAIModel instances
"""
return [
model
for model in self.model_registry.get_models().values()
if isinstance(model, OpenAIModel)
... | Retrieve a list of models
Returns:
response: A list of OpenAIModel instances
| models | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/dataplane.py | Apache-2.0 |
async def create_completion(
self,
request_body: CompletionRequest,
raw_request: Request,
response: Response,
) -> Response:
"""Create completion handler.
Args:
request_body (CompletionCreateParams): Completion params body.
raw_request (Reques... | Create completion handler.
Args:
request_body (CompletionCreateParams): Completion params body.
raw_request (Request): fastapi request object,
response (Response): fastapi response object
Returns:
InferenceResponse: Inference response object.
| create_completion | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/endpoints.py | Apache-2.0 |
async def create_chat_completion(
self,
request_body: ChatCompletionRequest,
raw_request: Request,
response: Response,
) -> Response:
"""Create chat completion handler.
Args:
request_body (ChatCompletionRequestAdapter): Chat completion params body.
... | Create chat completion handler.
Args:
request_body (ChatCompletionRequestAdapter): Chat completion params body.
raw_request (Request): fastapi request object,
response (Response): fastapi response object
Returns:
InferenceResponse: Inference response obj... | create_chat_completion | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/endpoints.py | Apache-2.0 |
async def create_embedding(
self,
request_body: EmbeddingRequest,
raw_request: Request,
response: Response,
) -> Response:
"""Create embedding handler.
Args:
request_body (EmbeddingRequestAdapter): Embedding params body.
raw_request (Request): ... | Create embedding handler.
Args:
request_body (EmbeddingRequestAdapter): Embedding params body.
raw_request (Request): fastapi request object,
model_name (str): Model name.
Returns:
InferenceResponse: Inference response object.
| create_embedding | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/endpoints.py | Apache-2.0 |
async def create_rerank(
self,
raw_request: Request,
request_body: RerankRequest,
response: Response,
) -> Response:
"""Create rerank handler.
Args:
raw_request (Request): fastapi request object,
model_name (str): Model name.
reques... | Create rerank handler.
Args:
raw_request (Request): fastapi request object,
model_name (str): Model name.
request_body (RerankRequestAdapter): Rerank params body.
Returns:
InferenceResponse: Inference response object.
| create_rerank | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/endpoints.py | Apache-2.0 |
async def models(
self,
) -> ModelList:
"""Create chat completion handler.
Args:
raw_request (Request): fastapi request object,
Returns:
ModelList: Model response object.
"""
models = await self.dataplane.models()
return ModelList(
... | Create chat completion handler.
Args:
raw_request (Request): fastapi request object,
Returns:
ModelList: Model response object.
| models | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/endpoints.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/endpoints.py | Apache-2.0 |
def postprocess_completion(
self,
completion: Completion,
request: CompletionRequest,
raw_request: Optional[Request] = None,
):
"""Postprocess a completion. Only called when response is not being streamed (i.e. stream=false)"""
pass | Postprocess a completion. Only called when response is not being streamed (i.e. stream=false) | postprocess_completion | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/openai_proxy_model.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/openai_proxy_model.py | Apache-2.0 |
def postprocess_completion_chunk(
self,
completion: Completion,
request: CompletionRequest,
raw_request: Optional[Request] = None,
):
"""Postprocess a completion chunk. Only called when response is being streamed (i.e. stream=true)
This method will be called once for ... | Postprocess a completion chunk. Only called when response is being streamed (i.e. stream=true)
This method will be called once for each chunk that is streamed back to the user.
| postprocess_completion_chunk | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/openai_proxy_model.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/openai_proxy_model.py | Apache-2.0 |
def postprocess_chat_completion(
self,
chat_completion: ChatCompletion,
request: ChatCompletionRequest,
raw_request: Optional[Request] = None,
):
"""Postprocess a chat completion. Only called when response is not being streamed (i.e. stream=false)"""
pass | Postprocess a chat completion. Only called when response is not being streamed (i.e. stream=false) | postprocess_chat_completion | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/openai_proxy_model.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/openai_proxy_model.py | Apache-2.0 |
def postprocess_chat_completion_chunk(
self,
chat_completion_chunk: ChatCompletionChunk,
request: ChatCompletionRequest,
raw_request: Optional[Request] = None,
):
"""Postprocess a chat completion chunk. Only called when response is being streamed (i.e. stream=true)
Th... | Postprocess a chat completion chunk. Only called when response is being streamed (i.e. stream=true)
This method will be called once for each chunk that is streamed back to the user.
| postprocess_chat_completion_chunk | python | kserve/kserve | python/kserve/kserve/protocol/rest/openai/openai_proxy_model.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/rest/openai/openai_proxy_model.py | Apache-2.0 |
def is_structured_cloudevent(body: Dict) -> bool:
"""Returns True if the JSON request body resembles a structured CloudEvent"""
return (
"time" in body
and "type" in body
and "source" in body
and "id" in body
and "specversion" in body
and "data" in body
) | Returns True if the JSON request body resembles a structured CloudEvent | is_structured_cloudevent | python | kserve/kserve | python/kserve/kserve/utils/utils.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/utils/utils.py | Apache-2.0 |
def strtobool(val: str) -> bool:
"""Convert a string representation of truth to True or False.
True values are 'y', 'yes', 't', 'true', 'on', and '1'; false values
are 'n', 'no', 'f', 'false', 'off', and '0'. Raises ValueError if
'val' is anything else.
Adapted from deprecated `distutils`
htt... | Convert a string representation of truth to True or False.
True values are 'y', 'yes', 't', 'true', 'on', and '1'; false values
are 'n', 'no', 'f', 'false', 'off', and '0'. Raises ValueError if
'val' is anything else.
Adapted from deprecated `distutils`
https://github.com/python/cpython/blob/3.11... | strtobool | python | kserve/kserve | python/kserve/kserve/utils/utils.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/utils/utils.py | Apache-2.0 |
def test_inferenceservice_client_creat():
"""Unit test for kserve create api"""
with patch(
"kserve.api.kserve_client.KServeClient.create", return_value=mocked_unit_result
):
isvc = generate_inferenceservice()
assert mocked_unit_result == kserve_client.create(isvc, namespace="kubeflo... | Unit test for kserve create api | test_inferenceservice_client_creat | python | kserve/kserve | python/kserve/test/skip_test_inference_service_client.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/skip_test_inference_service_client.py | Apache-2.0 |
def test_inferenceservice_client_get():
"""Unit test for kserve get api"""
with patch(
"kserve.api.kserve_client.KServeClient.get", return_value=mocked_unit_result
):
assert mocked_unit_result == kserve_client.get(
"flower-sample", namespace="kubeflow"
) | Unit test for kserve get api | test_inferenceservice_client_get | python | kserve/kserve | python/kserve/test/skip_test_inference_service_client.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/skip_test_inference_service_client.py | Apache-2.0 |
def test_inferenceservice_client_patch():
"""Unit test for kserve patch api"""
with patch(
"kserve.api.kserve_client.KServeClient.patch", return_value=mocked_unit_result
):
isvc = generate_inferenceservice()
assert mocked_unit_result == kserve_client.patch(
"flower-sample... | Unit test for kserve patch api | test_inferenceservice_client_patch | python | kserve/kserve | python/kserve/test/skip_test_inference_service_client.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/skip_test_inference_service_client.py | Apache-2.0 |
def test_inferenceservice_client_rollout_canary():
"""Unit test for kserve promote api"""
with patch(
"kserve.api.kserve_client.KServeClient.rollout_canary",
return_value=mocked_unit_result,
):
assert mocked_unit_result == kserve_client.rollout_canary(
"flower-sample", na... | Unit test for kserve promote api | test_inferenceservice_client_rollout_canary | python | kserve/kserve | python/kserve/test/skip_test_inference_service_client.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/skip_test_inference_service_client.py | Apache-2.0 |
def test_inferenceservice_client_replace():
"""Unit test for kserve replace api"""
with patch(
"kserve.api.kserve_client.KServeClient.replace", return_value=mocked_unit_result
):
isvc = generate_inferenceservice()
assert mocked_unit_result == kserve_client.replace(
"flowe... | Unit test for kserve replace api | test_inferenceservice_client_replace | python | kserve/kserve | python/kserve/test/skip_test_inference_service_client.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/skip_test_inference_service_client.py | Apache-2.0 |
def test_inferenceservice_client_delete():
"""Unit test for kserve delete api"""
with patch(
"kserve.api.kserve_client.KServeClient.delete", return_value=mocked_unit_result
):
assert mocked_unit_result == kserve_client.delete(
"flower-sample", namespace="kubeflow"
) | Unit test for kserve delete api | test_inferenceservice_client_delete | python | kserve/kserve | python/kserve/test/skip_test_inference_service_client.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/skip_test_inference_service_client.py | Apache-2.0 |
async def test_grpc_raw_inputs(mock_to_headers, server):
"""
If we receive raw inputs then, the response also should be in raw output format.
"""
fp32_data = np.array([6.8, 2.8, 4.8, 1.4, 6.0, 3.4, 4.5, 1.6], dtype=np.float32)
int32_data = np.array([6, 2, 4, 1, 6, 3, 4, 1], dtype=np.int32)
str_d... |
If we receive raw inputs then, the response also should be in raw output format.
| test_grpc_raw_inputs | python | kserve/kserve | python/kserve/test/test_grpc_server.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_grpc_server.py | Apache-2.0 |
async def test_grpc_fp16_output(mock_to_headers, server):
"""
If the output contains FP16 datatype, then the outputs should be returned as raw outputs.
"""
fp32_data = [6.8, 2.8, 4.8, 1.4, 6.0, 3.4, 4.5, 1.6]
request = grpc_predict_v2_pb2.ModelInferRequest(
model_name="FP16OutputModel",
... |
If the output contains FP16 datatype, then the outputs should be returned as raw outputs.
| test_grpc_fp16_output | python | kserve/kserve | python/kserve/test/test_grpc_server.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_grpc_server.py | Apache-2.0 |
async def test_grpc_raw_inputs_with_missing_input_data(mock_to_headers, server):
"""
Server should raise InvalidInput if raw_input_contents missing some input data.
"""
raw_input_contents = [
np.array([6.8, 2.8, 4.8, 1.4, 6.0, 3.4, 4.5, 1.6], dtype=np.float32).tobytes(),
np.array([6, 2, ... |
Server should raise InvalidInput if raw_input_contents missing some input data.
| test_grpc_raw_inputs_with_missing_input_data | python | kserve/kserve | python/kserve/test/test_grpc_server.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_grpc_server.py | Apache-2.0 |
async def test_grpc_raw_inputs_with_contents_specified(mock_to_headers, server):
"""
Server should raise InvalidInput if both contents and raw_input_contents specified.
"""
raw_input_contents = [
np.array([6.8, 2.8, 4.8, 1.4, 6.0, 3.4, 4.5, 1.6], dtype=np.float32).tobytes(),
np.array([6,... |
Server should raise InvalidInput if both contents and raw_input_contents specified.
| test_grpc_raw_inputs_with_contents_specified | python | kserve/kserve | python/kserve/test/test_grpc_server.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_grpc_server.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1BuiltInAdapter
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_built_in_adapter.V1alpha1BuiltInAdapte... | Test V1alpha1BuiltInAdapter
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_built_in_adapter.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_built_in_adapter.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ClusterServingRuntime
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_cluster_serving_runtime.V1alpha... | Test V1alpha1ClusterServingRuntime
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_cluster_serving_runtime.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_cluster_serving_runtime.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ClusterServingRuntimeList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_cluster_serving_runtime_lis... | Test V1alpha1ClusterServingRuntimeList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_cluster_serving_runtime_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_cluster_serving_runtime_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ClusterStorageContainer
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_cluster_storage_container.V1a... | Test V1alpha1ClusterStorageContainer
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_cluster_storage_container.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_cluster_storage_container.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ClusterStorageContainerList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_cluster_storage_container... | Test V1alpha1ClusterStorageContainerList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_cluster_storage_container_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_cluster_storage_container_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1Container
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_container.V1alpha1Container() # noqa: E501... | Test V1alpha1Container
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_container.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_container.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1InferenceGraph
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_inference_graph.V1alpha1InferenceGraph... | Test V1alpha1InferenceGraph
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_inference_graph.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_inference_graph.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1InferenceGraphList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_inference_graph_list.V1alpha1Infer... | Test V1alpha1InferenceGraphList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_inference_graph_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_inference_graph_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1InferenceGraphSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_inference_graph_spec.V1alpha1Infer... | Test V1alpha1InferenceGraphSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_inference_graph_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_inference_graph_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1InferenceGraphStatus
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_inference_graph_status.V1alpha1I... | Test V1alpha1InferenceGraphStatus
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_inference_graph_status.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_inference_graph_status.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1InferenceRouter
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_inference_router.V1alpha1InferenceRou... | Test V1alpha1InferenceRouter
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_inference_router.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_inference_router.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1InferenceStep
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_inference_step.V1alpha1InferenceStep() ... | Test V1alpha1InferenceStep
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_inference_step.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_inference_step.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1InferenceTarget
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_inference_target.V1alpha1InferenceTar... | Test V1alpha1InferenceTarget
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_inference_target.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_inference_target.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelCache
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_cache.V1alpha1LocalModelC... | Test V1alpha1LocalModelCache
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_cache.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_cache.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelCacheList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_cache_list.V1alpha1Lo... | Test V1alpha1LocalModelCacheList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_cache_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_cache_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelCacheSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_cache_spec.V1alpha1Lo... | Test V1alpha1LocalModelCacheSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_cache_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_cache_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelNode
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_node.V1alpha1LocalModelNod... | Test V1alpha1LocalModelNode
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_node.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_node.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelNodeGroup
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_node_group.V1alpha1Lo... | Test V1alpha1LocalModelNodeGroup
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_node_group.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_node_group.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelNodeGroupList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_node_group_list.V... | Test V1alpha1LocalModelNodeGroupList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_node_group_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_node_group_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelNodeGroupSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_node_group_spec.V... | Test V1alpha1LocalModelNodeGroupSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_node_group_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_node_group_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelNodeList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_node_list.V1alpha1Loca... | Test V1alpha1LocalModelNodeList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_node_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_node_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1LocalModelNodeSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_local_model_node_spec.V1alpha1Loca... | Test V1alpha1LocalModelNodeSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_local_model_node_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_local_model_node_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ModelSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_model_spec.V1alpha1ModelSpec() # noqa: E50... | Test V1alpha1ModelSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_model_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_model_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ServingRuntime
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_serving_runtime.V1alpha1ServingRuntime... | Test V1alpha1ServingRuntime
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_serving_runtime.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_serving_runtime.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ServingRuntimeList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_serving_runtime_list.V1alpha1Servi... | Test V1alpha1ServingRuntimeList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_serving_runtime_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_serving_runtime_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ServingRuntimePodSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_serving_runtime_pod_spec.V1alph... | Test V1alpha1ServingRuntimePodSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_serving_runtime_pod_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_serving_runtime_pod_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1ServingRuntimeSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_serving_runtime_spec.V1alpha1Servi... | Test V1alpha1ServingRuntimeSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_serving_runtime_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_serving_runtime_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1StorageContainerSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_storage_container_spec.V1alpha1S... | Test V1alpha1StorageContainerSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_storage_container_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_storage_container_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1StorageHelper
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_storage_helper.V1alpha1StorageHelper() ... | Test V1alpha1StorageHelper
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_storage_helper.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_storage_helper.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1SupportedModelFormat
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_supported_model_format.V1alpha1S... | Test V1alpha1SupportedModelFormat
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_supported_model_format.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_supported_model_format.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1SupportedUriFormat
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_supported_uri_format.V1alpha1Suppo... | Test V1alpha1SupportedUriFormat
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_supported_uri_format.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_supported_uri_format.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1TrainedModel
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_trained_model.V1alpha1TrainedModel() # ... | Test V1alpha1TrainedModel
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_trained_model.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_trained_model.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1TrainedModelList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_trained_model_list.V1alpha1TrainedMo... | Test V1alpha1TrainedModelList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_trained_model_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_trained_model_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1alpha1TrainedModelSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included"""
# model = kserve.models.v1alpha1_trained_model_spec.V1alpha1TrainedMo... | Test V1alpha1TrainedModelSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1alpha1_trained_model_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1alpha1_trained_model_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ARTExplainerSpec
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_art_explainer_spec.V1beta1ARTExplainer... | Test V1beta1ARTExplainerSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_art_explainer_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_art_explainer_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1AutoScalingSpec
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_auto_scaling_spec.V1beta1AutoScalingSpe... | Test V1beta1AutoScalingSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_auto_scaling_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_auto_scaling_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1Batcher
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_batcher.V1beta1Batcher() # noqa: E501
... | Test V1beta1Batcher
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_batcher.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_batcher.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ComponentExtensionSpec
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_component_extension_spec.V1beta1... | Test V1beta1ComponentExtensionSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_component_extension_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_component_extension_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ComponentStatusSpec
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_component_status_spec.V1beta1Compon... | Test V1beta1ComponentStatusSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_component_status_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_component_status_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1CustomExplainer
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_custom_explainer.V1beta1CustomExplainer... | Test V1beta1CustomExplainer
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_custom_explainer.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_custom_explainer.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1CustomPredictor
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_custom_predictor.V1beta1CustomPredictor... | Test V1beta1CustomPredictor
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_custom_predictor.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_custom_predictor.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1CustomTransformer
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_custom_transformer.V1beta1CustomTrans... | Test V1beta1CustomTransformer
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_custom_transformer.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_custom_transformer.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1DeployConfig
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_deploy_config.V1beta1DeployConfig() # noq... | Test V1beta1DeployConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_deploy_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_deploy_config.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ExplainersConfig
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_explainers_config.V1beta1ExplainersCon... | Test V1beta1ExplainersConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_explainers_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_explainers_config.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ExplainerConfig
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_explainer_config.V1beta1ExplainerConfig... | Test V1beta1ExplainerConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_explainer_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_explainer_config.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ExplainerExtensionSpec
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_explainer_extension_spec.V1beta1... | Test V1beta1ExplainerExtensionSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_explainer_extension_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_explainer_extension_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ExplainerSpec
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_explainer_spec.V1beta1ExplainerSpec() # ... | Test V1beta1ExplainerSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_explainer_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_explainer_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ExternalMetrics
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_external_metrics.V1beta1ExternalMetrics... | Test V1beta1ExternalMetrics
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_external_metrics.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_external_metrics.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1ExternalMetricSource
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_external_metric_source.V1beta1Exte... | Test V1beta1ExternalMetricSource
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_external_metric_source.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_external_metric_source.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1FailureInfo
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_failure_info.V1beta1FailureInfo() # noqa: ... | Test V1beta1FailureInfo
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_failure_info.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_failure_info.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1HuggingFaceRuntimeSpec
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_hugging_face_runtime_spec.V1beta... | Test V1beta1HuggingFaceRuntimeSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_hugging_face_runtime_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_hugging_face_runtime_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1InferenceService
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_inference_service.V1beta1InferenceServ... | Test V1beta1InferenceService
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_inference_service.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_inference_service.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1InferenceServicesConfig
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_inference_services_config.V1bet... | Test V1beta1InferenceServicesConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_inference_services_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_inference_services_config.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1InferenceServiceList
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_inference_service_list.V1beta1Infe... | Test V1beta1InferenceServiceList
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_inference_service_list.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_inference_service_list.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1InferenceServiceSpec
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_inference_service_spec.V1beta1Infe... | Test V1beta1InferenceServiceSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_inference_service_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_inference_service_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1InferenceServiceStatus
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_inference_service_status.V1beta1... | Test V1beta1InferenceServiceStatus
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_inference_service_status.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_inference_service_status.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1IngressConfig
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_ingress_config.V1beta1IngressConfig() # ... | Test V1beta1IngressConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_ingress_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_ingress_config.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1KedaScaler
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_keda_scaler.V1beta1KedaScaler() # noqa: E50... | Test V1beta1KedaScaler
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_keda_scaler.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_keda_scaler.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1LightGBMSpec
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_light_gbm_spec.V1beta1LightGBMSpec() # no... | Test V1beta1LightGBMSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_light_gbm_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_light_gbm_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1LocalModelConfig
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_local_model_config.V1beta1LocalModelCo... | Test V1beta1LocalModelConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_local_model_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_local_model_config.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1LoggerSpec
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_logger_spec.V1beta1LoggerSpec() # noqa: E50... | Test V1beta1LoggerSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_logger_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_logger_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1MetricsConfig
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_metrics_config.V1beta1MetricsConfig() # ... | Test V1beta1MetricsConfig
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_metrics_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_metrics_config.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1MetricsSpec
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_metrics_spec.V1beta1MetricsSpec() # noqa: ... | Test V1beta1MetricsSpec
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_metrics_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_metrics_spec.py | Apache-2.0 |
def make_instance(self, include_optional):
"""Test V1beta1MetricSource
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_metric_source.V1beta1MetricSource() # noq... | Test V1beta1MetricSource
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | make_instance | python | kserve/kserve | python/kserve/test/test_v1beta1_metric_source.py | https://github.com/kserve/kserve/blob/master/python/kserve/test/test_v1beta1_metric_source.py | Apache-2.0 |
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