Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::IndexDatapoint (v0.33.0)

Version 0.33.0

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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::IndexDatapoint.

A datapoint of Index.

Inherits

• Object

Extended By

• Google::Protobuf::MessageExts::ClassMethods

Includes

• Google::Protobuf::MessageExts

Methods

#crowding_tag

def crowding_tag() -> ::Google::Cloud::AIPlatform::V1::IndexDatapoint::CrowdingTag

Returns

• (::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.

#crowding_tag=

def crowding_tag=(value) -> ::Google::Cloud::AIPlatform::V1::IndexDatapoint::CrowdingTag

Parameter

• value (::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.

Returns

• (::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.

#datapoint_id

def datapoint_id() -> ::String

Returns

• (::String) — Required. Unique identifier of the datapoint.

#datapoint_id=

def datapoint_id=(value) -> ::String

Parameter

• value (::String) — Required. Unique identifier of the datapoint.

Returns

• (::String) — Required. Unique identifier of the datapoint.

#feature_vector

def feature_vector() -> ::Array<::Float>

Returns

• (::Array<::Float>) — Required. Feature embedding vector. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

#feature_vector=

def feature_vector=(value) -> ::Array<::Float>

Parameter

• value (::Array<::Float>) — Required. Feature embedding vector. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

Returns

• (::Array<::Float>) — Required. Feature embedding vector. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].

#restricts

def restricts() -> ::Array<::Google::Cloud::AIPlatform::V1::IndexDatapoint::Restriction>

Returns

• (::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. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

#restricts=

def restricts=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::IndexDatapoint::Restriction>

Parameter

• value (::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. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering

Returns

• (::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. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering