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Merged
merged 2 commits into from
Mar 14, 2024
Merged

Auto-generated code for 8.13 #2472

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97931da
Auto-generated API code
elasticmachine Mar 14, 2024
652c65b
Merge remote-tracking branch 'origin/8.13' into generates_8.13_code
pquentin Mar 14, 2024
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5 changes: 5 additions & 0 deletions elasticsearch/_async/client/ml.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -3627,6 +3627,7 @@ async def put_job(
"model_size_bytes",
"model_type",
"platform_architecture",
"prefix_strings",
"tags",
),
)
Expand All @@ -3649,6 +3650,7 @@ async def put_trained_model(
t.Union["t.Literal['lang_ident', 'pytorch', 'tree_ensemble']", str]
] = None,
platform_architecture: t.Optional[str] = None,
prefix_strings: t.Optional[t.Mapping[str, t.Any]] = None,
pretty: t.Optional[bool] = None,
tags: t.Optional[t.Sequence[str]] = None,
body: t.Optional[t.Dict[str, t.Any]] = None,
Expand Down Expand Up @@ -3686,6 +3688,7 @@ async def put_trained_model(
`darwin-x86_64`, `darwin-aarch64`, or `windows-x86_64`. For portable models
(those that work independent of processor architecture or OS features), leave
this field unset.
:param prefix_strings: Optional prefix strings applied at inference
:param tags: An array of tags to organize the model.
"""
if model_id in SKIP_IN_PATH:
Expand Down Expand Up @@ -3723,6 +3726,8 @@ async def put_trained_model(
__body["model_type"] = model_type
if platform_architecture is not None:
__body["platform_architecture"] = platform_architecture
if prefix_strings is not None:
__body["prefix_strings"] = prefix_strings
if tags is not None:
__body["tags"] = tags
__headers = {"accept": "application/json", "content-type": "application/json"}
Expand Down
5 changes: 5 additions & 0 deletions elasticsearch/_sync/client/ml.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3627,6 +3627,7 @@ def put_job(
"model_size_bytes",
"model_type",
"platform_architecture",
"prefix_strings",
"tags",
),
)
Expand All @@ -3649,6 +3650,7 @@ def put_trained_model(
t.Union["t.Literal['lang_ident', 'pytorch', 'tree_ensemble']", str]
] = None,
platform_architecture: t.Optional[str] = None,
prefix_strings: t.Optional[t.Mapping[str, t.Any]] = None,
pretty: t.Optional[bool] = None,
tags: t.Optional[t.Sequence[str]] = None,
body: t.Optional[t.Dict[str, t.Any]] = None,
Expand Down Expand Up @@ -3686,6 +3688,7 @@ def put_trained_model(
`darwin-x86_64`, `darwin-aarch64`, or `windows-x86_64`. For portable models
(those that work independent of processor architecture or OS features), leave
this field unset.
:param prefix_strings: Optional prefix strings applied at inference
:param tags: An array of tags to organize the model.
"""
if model_id in SKIP_IN_PATH:
Expand Down Expand Up @@ -3723,6 +3726,8 @@ def put_trained_model(
__body["model_type"] = model_type
if platform_architecture is not None:
__body["platform_architecture"] = platform_architecture
if prefix_strings is not None:
__body["prefix_strings"] = prefix_strings
if tags is not None:
__body["tags"] = tags
__headers = {"accept": "application/json", "content-type": "application/json"}
Expand Down