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create_model_bundle metadata param #98

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Merged
merged 2 commits into from
May 15, 2023
Merged

create_model_bundle metadata param #98

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6468425
create_model_bundle metadata param
squeakymouse May 13, 2023
ad6a044
Fix
squeakymouse May 15, 2023
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53 changes: 36 additions & 17 deletions launch/client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -330,11 +330,8 @@ def _upload_model_bundle(
self,
load_model_fn: Callable,
load_predict_fn: Callable,
bundle_metadata: Dict[str, Any],
):
bundle = dict(load_model_fn=load_model_fn, load_predict_fn=load_predict_fn)
bundle_metadata["load_predict_fn"] = inspect.getsource(load_predict_fn) # type: ignore
bundle_metadata["load_model_fn"] = inspect.getsource(load_model_fn) # type: ignore
Comment on lines -336 to -337
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@phil-scale Is this ok to remove? Didn't look like bundle_metadata was being used anywhere

serialized_bundle = cloudpickle.dumps(bundle)
bundle_location = self._upload_data(data=serialized_bundle)
return bundle_location
Expand All @@ -361,6 +358,7 @@ def create_model_bundle_from_callable_v2(
custom_base_image_repository: Optional[str] = None,
custom_base_image_tag: Optional[str] = None,
app_config: Optional[Union[Dict[str, Any], str]] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> CreateModelBundleV2Response:
"""
Uploads and registers a model bundle to Scale Launch.
Expand Down Expand Up @@ -420,14 +418,15 @@ def predict_fn(input):
bundle when it is run. These values can be accessed by the bundle via the
``app_config`` global variable.

metadata: Metadata to record with the bundle.

Returns:
An object containing the following keys:

- ``model_bundle_id``: The ID of the created model bundle.
"""
nonnull_requirements = requirements or []
bundle_metadata: Dict[str, Any] = {}
bundle_location = self._upload_model_bundle(load_model_fn, load_predict_fn, bundle_metadata)
bundle_location = self._upload_model_bundle(load_model_fn, load_predict_fn)
schema_location = self._upload_schemas(request_schema=request_schema, response_schema=response_schema)
framework = _get_model_bundle_framework(
pytorch_image_tag=pytorch_image_tag,
Expand All @@ -447,9 +446,12 @@ def predict_fn(input):
)
)
create_model_bundle_request = CreateModelBundleV2Request(
name=model_bundle_name,
schema_location=schema_location,
flavor=flavor,
**dict_not_none(
name=model_bundle_name,
schema_location=schema_location,
flavor=flavor,
metadata=metadata,
)
)
with ApiClient(self.configuration) as api_client:
api_instance = DefaultApi(api_client)
Expand All @@ -476,6 +478,7 @@ def create_model_bundle_from_dirs_v2(
custom_base_image_repository: Optional[str] = None,
custom_base_image_tag: Optional[str] = None,
app_config: Optional[Dict[str, Any]] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> CreateModelBundleV2Response:
"""
Packages up code from one or more local filesystem folders and uploads them as a bundle
Expand Down Expand Up @@ -556,6 +559,8 @@ def create_model_bundle_from_dirs_v2(
bundle when it is run. These values can be accessed by the bundle via the
``app_config`` global variable.

metadata: Metadata to record with the bundle.

Returns:
An object containing the following keys:

Expand Down Expand Up @@ -585,9 +590,12 @@ def create_model_bundle_from_dirs_v2(
)
)
create_model_bundle_request = CreateModelBundleV2Request(
name=model_bundle_name,
schema_location=schema_location,
flavor=flavor,
**dict_not_none(
name=model_bundle_name,
schema_location=schema_location,
flavor=flavor,
metadata=metadata,
)
)
with ApiClient(self.configuration) as api_client:
api_instance = DefaultApi(api_client)
Expand All @@ -610,6 +618,7 @@ def create_model_bundle_from_runnable_image_v2(
command: List[str],
env: Dict[str, str],
readiness_initial_delay_seconds: int,
metadata: Optional[Dict[str, Any]] = None,
) -> CreateModelBundleV2Response:
"""
Create a model bundle from a runnable image. The specified ``command`` must start a process
Expand All @@ -636,6 +645,7 @@ def create_model_bundle_from_runnable_image_v2(
readiness_initial_delay_seconds: The number of seconds to wait for the HTTP server to become ready and
successfully respond on its healthcheck.

metadata: Metadata to record with the bundle.

Returns:
An object containing the following keys:
Expand All @@ -655,9 +665,12 @@ def create_model_bundle_from_runnable_image_v2(
)
)
create_model_bundle_request = CreateModelBundleV2Request(
name=model_bundle_name,
schema_location=schema_location,
flavor=flavor,
**dict_not_none(
name=model_bundle_name,
schema_location=schema_location,
flavor=flavor,
metadata=metadata,
)
)

with ApiClient(self.configuration) as api_client:
Expand Down Expand Up @@ -688,6 +701,7 @@ def create_model_bundle_from_triton_enhanced_runnable_image_v2(
triton_storage: Optional[str],
triton_memory: Optional[str],
triton_readiness_initial_delay_seconds: int,
metadata: Optional[Dict[str, Any]] = None,
) -> CreateModelBundleV2Response:
"""
Create a model bundle from a runnable image and a tritonserver image.
Expand Down Expand Up @@ -732,6 +746,8 @@ def create_model_bundle_from_triton_enhanced_runnable_image_v2(
triton_readiness_initial_delay_seconds: Like readiness_initial_delay_seconds, but for
tritonserver's own healthcheck.

metadata: Metadata to record with the bundle.

Returns:
An object containing the following keys:

Expand All @@ -757,9 +773,12 @@ def create_model_bundle_from_triton_enhanced_runnable_image_v2(
)
)
create_model_bundle_request = CreateModelBundleV2Request(
name=model_bundle_name,
schema_location=schema_location,
flavor=flavor,
**dict_not_none(
name=model_bundle_name,
schema_location=schema_location,
flavor=flavor,
metadata=metadata,
)
)

with ApiClient(self.configuration) as api_client:
Expand Down