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Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class IndexDatapoint.
A datapoint of Index.
Generated from protobuf message google.cloud.aiplatform.v1.IndexDatapoint
Namespace
Google \ Cloud \ AIPlatform \ V1Methods
__construct
Constructor.
data
array
Optional. Data for populating the Message object.
↳ datapoint_id
string
Required. Unique identifier of the datapoint.
↳ feature_vector
array
Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].
↳ sparse_embedding
↳ restricts
array< 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
↳ numeric_restricts
array< IndexDatapoint\NumericRestriction
>
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 numeric comparisons.
↳ crowding_tag
IndexDatapoint\CrowdingTag
Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.
getDatapointId
Required. Unique identifier of the datapoint.
string
setDatapointId
Required. Unique identifier of the datapoint.
var
string
$this
getFeatureVector
Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].
setFeatureVector
Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].
var
float[]
$this
getSparseEmbedding
Optional. Feature embedding vector for sparse index.
hasSparseEmbedding
clearSparseEmbedding
setSparseEmbedding
Optional. Feature embedding vector for sparse index.
$this
getRestricts
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
setRestricts
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
$this
getNumericRestricts
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 numeric comparisons.
setNumericRestricts
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 numeric comparisons.
$this
getCrowdingTag
Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.
hasCrowdingTag
clearCrowdingTag
setCrowdingTag
Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.
$this
