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Auto-generated API code (#2322)
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elasticsearch/_async/client/ml.py

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@@ -3236,6 +3236,7 @@ async def put_trained_model(
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model_type: t.Optional[
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t.Union["t.Literal['lang_ident', 'pytorch', 'tree_ensemble']", str]
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] = None,
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platform_architecture: t.Optional[str] = None,
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pretty: t.Optional[bool] = None,
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tags: t.Optional[t.Union[t.List[str], t.Tuple[str, ...]]] = None,
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) -> ObjectApiResponse[t.Any]:
@@ -3264,6 +3265,14 @@ async def put_trained_model(
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model in memory. This property is supported only if defer_definition_decompression
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is true or the model definition is not supplied.
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:param model_type: The model type.
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:param platform_architecture: The platform architecture (if applicable) of the
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trained mode. If the model only works on one platform, because it is heavily
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optimized for a particular processor architecture and OS combination, then
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this field specifies which. The format of the string must match the platform
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identifiers used by Elasticsearch, so one of, `linux-x86_64`, `linux-aarch64`,
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`darwin-x86_64`, `darwin-aarch64`, or `windows-x86_64`. For portable models
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(those that work independent of processor architecture or OS features), leave
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this field unset.
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:param tags: An array of tags to organize the model.
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"""
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if model_id in SKIP_IN_PATH:
@@ -3295,6 +3304,8 @@ async def put_trained_model(
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__body["model_size_bytes"] = model_size_bytes
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if model_type is not None:
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__body["model_type"] = model_type
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if platform_architecture is not None:
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__body["platform_architecture"] = platform_architecture
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if pretty is not None:
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__query["pretty"] = pretty
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if tags is not None:

elasticsearch/_sync/client/ml.py

Lines changed: 11 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -3236,6 +3236,7 @@ def put_trained_model(
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model_type: t.Optional[
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t.Union["t.Literal['lang_ident', 'pytorch', 'tree_ensemble']", str]
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] = None,
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platform_architecture: t.Optional[str] = None,
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pretty: t.Optional[bool] = None,
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tags: t.Optional[t.Union[t.List[str], t.Tuple[str, ...]]] = None,
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) -> ObjectApiResponse[t.Any]:
@@ -3264,6 +3265,14 @@ def put_trained_model(
32643265
model in memory. This property is supported only if defer_definition_decompression
32653266
is true or the model definition is not supplied.
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:param model_type: The model type.
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:param platform_architecture: The platform architecture (if applicable) of the
3269+
trained mode. If the model only works on one platform, because it is heavily
3270+
optimized for a particular processor architecture and OS combination, then
3271+
this field specifies which. The format of the string must match the platform
3272+
identifiers used by Elasticsearch, so one of, `linux-x86_64`, `linux-aarch64`,
3273+
`darwin-x86_64`, `darwin-aarch64`, or `windows-x86_64`. For portable models
3274+
(those that work independent of processor architecture or OS features), leave
3275+
this field unset.
32673276
:param tags: An array of tags to organize the model.
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"""
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if model_id in SKIP_IN_PATH:
@@ -3295,6 +3304,8 @@ def put_trained_model(
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__body["model_size_bytes"] = model_size_bytes
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if model_type is not None:
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__body["model_type"] = model_type
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if platform_architecture is not None:
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__body["platform_architecture"] = platform_architecture
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if pretty is not None:
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__query["pretty"] = pretty
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if tags is not None:

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