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ScalarQuantizationCompression Class

Contains configuration options specific to the scalar quantization compression method used during indexing and querying.

Constructor

ScalarQuantizationCompression(*args: Any, **kwargs: Any)

Variables

Name	Description
compression_name	str The name to associate with this particular configuration. Required.
rescoring_options	RescoringOptions Contains the options for rescoring.
truncation_dimension	int The number of dimensions to truncate the vectors to. Truncating the vectors reduces the size of the vectors and the amount of data that needs to be transferred during search. This can save storage cost and improve search performance at the expense of recall. It should be only used for embeddings trained with Matryoshka Representation Learning (MRL) such as OpenAI text-embedding-3-large (small). The default value is null, which means no truncation.
parameters	ScalarQuantizationParameters Contains the parameters specific to Scalar Quantization.
kind	str or <xref:azure.search.documents.indexes.models.SCALAR_QUANTIZATION> The name of the kind of compression method being configured for use with vector search. Required. Scalar Quantization, a type of compression method. In scalar quantization, the original vectors values are compressed to a narrower type by discretizing and representing each component of a vector using a reduced set of quantized values, thereby reducing the overall data size.

Methods

as_dict	Return a dict that can be turned into json using json.dump.
clear	Remove all items from D.
copy
get	Get the value for key if key is in the dictionary, else default. :param str key: The key to look up. :param any default: The value to return if key is not in the dictionary. Defaults to None :returns: D[k] if k in D, else d. :rtype: any
items
keys
pop	Removes specified key and return the corresponding value. :param str key: The key to pop. :param any default: The value to return if key is not in the dictionary :returns: The value corresponding to the key. :rtype: any :raises KeyError: If key is not found and default is not given.
popitem	Removes and returns some (key, value) pair :returns: The (key, value) pair. :rtype: tuple :raises KeyError: if D is empty.
setdefault	Same as calling D.get(k, d), and setting D[k]=d if k not found :param str key: The key to look up. :param any default: The value to set if key is not in the dictionary :returns: D[k] if k in D, else d. :rtype: any
update	Updates D from mapping/iterable E and F. :param any args: Either a mapping object or an iterable of key-value pairs.
values

as_dict

Return a dict that can be turned into json using json.dump.

as_dict(*, exclude_readonly: bool = False) -> dict[str, Any]

Keyword-Only Parameters

Name	Description
exclude_readonly	bool Whether to remove the readonly properties. Default value: False

Returns

Type	Description
dict	A dict JSON compatible object

clear

Remove all items from D.

clear() -> None

copy

copy() -> Model

get

Get the value for key if key is in the dictionary, else default. :param str key: The key to look up. :param any default: The value to return if key is not in the dictionary. Defaults to None :returns: D[k] if k in D, else d. :rtype: any

get(key: str, default: Any = None) -> Any

Parameters

Name	Description
key Required
default	Default value: None

items

items() -> ItemsView[str, Any]

Returns

Type	Description
ItemsView	set-like object providing a view on D's items

keys

keys() -> KeysView[str]

Returns

Type	Description
KeysView	a set-like object providing a view on D's keys

pop

Removes specified key and return the corresponding value. :param str key: The key to pop. :param any default: The value to return if key is not in the dictionary :returns: The value corresponding to the key. :rtype: any :raises KeyError: If key is not found and default is not given.

pop(key: str, default: ~typing.Any = <object object>) -> Any

Parameters

Name	Description
key Required
default

popitem

Removes and returns some (key, value) pair :returns: The (key, value) pair. :rtype: tuple :raises KeyError: if D is empty.

popitem() -> tuple[str, Any]

setdefault

Same as calling D.get(k, d), and setting D[k]=d if k not found :param str key: The key to look up. :param any default: The value to set if key is not in the dictionary :returns: D[k] if k in D, else d. :rtype: any

setdefault(key: str, default: ~typing.Any = <object object>) -> Any

Parameters

Name	Description
key Required
default

update

Updates D from mapping/iterable E and F. :param any args: Either a mapping object or an iterable of key-value pairs.

update(*args: Any, **kwargs: Any) -> None

values

values() -> ValuesView[Any]

Returns

Type	Description
ValuesView	an object providing a view on D's values

Attributes

compression_name

The name to associate with this particular configuration. Required.

compression_name: str

kind

The name of the kind of compression method being configured for use with vector search. Required. Scalar Quantization, a type of compression method. In scalar quantization, the original vectors values are compressed to a narrower type by discretizing and representing each component of a vector using a reduced set of quantized values, thereby reducing the overall data size.

kind: SCALAR_QUANTIZATION: 'scalarQuantization'>]

parameters

Contains the parameters specific to Scalar Quantization.

parameters: _models.ScalarQuantizationParameters | None

rescoring_options

Contains the options for rescoring.

rescoring_options: '_models.RescoringOptions' | None

truncation_dimension

The number of dimensions to truncate the vectors to. Truncating the vectors reduces the size of the vectors and the amount of data that needs to be transferred during search. This can save storage cost and improve search performance at the expense of recall. It should be only used for embeddings trained with Matryoshka Representation Learning (MRL) such as OpenAI text-embedding-3-large (small). The default value is null, which means no truncation.

truncation_dimension: int | None

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