Google Cloud Ai Platform V1 Client - Class IndexDatapoint (0.10.0)

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

Methods

__construct

Constructor.

Parameters
NameDescription
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. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

↳ restricts array<Google\Cloud\AIPlatform\V1\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. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

↳ crowding_tag Google\Cloud\AIPlatform\V1\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.

Generated from protobuf field string datapoint_id = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
string

setDatapointId

Required. Unique identifier of the datapoint.

Generated from protobuf field string datapoint_id = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
var string
Returns
TypeDescription
$this

getFeatureVector

Required. Feature embedding vector. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

Generated from protobuf field repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
Google\Protobuf\Internal\RepeatedField

setFeatureVector

Required. Feature embedding vector. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

Generated from protobuf field repeated float feature_vector = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
var float[]
Returns
TypeDescription
$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.

See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

Generated from protobuf field repeated .google.cloud.aiplatform.v1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Returns
TypeDescription
Google\Protobuf\Internal\RepeatedField

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.

See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

Generated from protobuf field repeated .google.cloud.aiplatform.v1.IndexDatapoint.Restriction restricts = 4 [(.google.api.field_behavior) = OPTIONAL];

Parameter
NameDescription
var array<Google\Cloud\AIPlatform\V1\IndexDatapoint\Restriction>
Returns
TypeDescription
$this

getCrowdingTag

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

Generated from protobuf field .google.cloud.aiplatform.v1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Returns
TypeDescription
Google\Cloud\AIPlatform\V1\IndexDatapoint\CrowdingTag|null

hasCrowdingTag

clearCrowdingTag

setCrowdingTag

Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query.

Generated from protobuf field .google.cloud.aiplatform.v1.IndexDatapoint.CrowdingTag crowding_tag = 5 [(.google.api.field_behavior) = OPTIONAL];

Parameter
NameDescription
var Google\Cloud\AIPlatform\V1\IndexDatapoint\CrowdingTag
Returns
TypeDescription
$this