Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::IndexDatapoint (v0.48.0)

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

#crowding_tag=

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

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

#numeric_restricts

def numeric_restricts() -> ::Array<::Google::Cloud::AIPlatform::V1::IndexDatapoint::NumericRestriction>
Returns

#numeric_restricts=

def numeric_restricts=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::IndexDatapoint::NumericRestriction>
Parameter
Returns

#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

#sparse_embedding

def sparse_embedding() -> ::Google::Cloud::AIPlatform::V1::IndexDatapoint::SparseEmbedding
Returns

#sparse_embedding=

def sparse_embedding=(value) -> ::Google::Cloud::AIPlatform::V1::IndexDatapoint::SparseEmbedding
Parameter
Returns