- 1.59.0 (latest)
- 1.58.0
- 1.57.0
- 1.56.0
- 1.55.0
- 1.54.1
- 1.53.0
- 1.52.0
- 1.51.0
- 1.50.0
- 1.49.0
- 1.48.0
- 1.47.0
- 1.46.0
- 1.45.0
- 1.44.0
- 1.43.0
- 1.39.0
- 1.38.1
- 1.37.0
- 1.36.4
- 1.35.0
- 1.34.0
- 1.33.1
- 1.32.0
- 1.31.1
- 1.30.1
- 1.29.0
- 1.28.1
- 1.27.1
- 1.26.1
- 1.25.0
- 1.24.1
- 1.23.0
- 1.22.1
- 1.21.0
- 1.20.0
- 1.19.1
- 1.18.3
- 1.17.1
- 1.16.1
- 1.15.1
- 1.14.0
- 1.13.1
- 1.12.1
- 1.11.0
- 1.10.0
- 1.9.0
- 1.8.1
- 1.7.1
- 1.6.2
- 1.5.0
- 1.4.3
- 1.3.0
- 1.2.0
- 1.1.1
- 1.0.1
- 0.9.0
- 0.8.0
- 0.7.1
- 0.6.0
- 0.5.1
- 0.4.0
- 0.3.1
IndexDatapoint(mapping=None, *, ignore_unknown_fields=False, **kwargs)
A datapoint of Index.
Attributes |
|
---|---|
Name | Description |
datapoint_id |
str
Required. Unique identifier of the datapoint. |
feature_vector |
MutableSequence[float]
Required. Feature embedding vector. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions]. |
restricts |
MutableSequence[google.cloud.aiplatform_v1beta1.types.IndexDatapoint.Restriction]
Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering |
crowding_tag |
google.cloud.aiplatform_v1beta1.types.IndexDatapoint.CrowdingTag
Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query. |
Classes
CrowdingTag
CrowdingTag(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute.
Restriction
Restriction(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces).