Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1IndexDatapoint

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1/classes.rb,
lib/google/apis/aiplatform_v1/representations.rb,
lib/google/apis/aiplatform_v1/representations.rb

Overview

A datapoint of Index.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1IndexDatapoint

Returns a new instance of GoogleCloudAiplatformV1IndexDatapoint.



7610
7611
7612
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 7610

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#crowding_tag ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1IndexDatapointCrowdingTag

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. Corresponds to the JSON property crowdingTag

Returns:



7589
7590
7591
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 7589

def crowding_tag
  @crowding_tag
end

#datapoint_id ⇒ String

Required. Unique identifier of the datapoint. Corresponds to the JSON property datapointId

Returns:

  • (String) 


7594
7595
7596
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 7594

def datapoint_id
  @datapoint_id
end

#feature_vector ⇒ Array<Float>

Required. Feature embedding vector. An array of numbers with the length of [ NearestNeighborSearchConfig.dimensions]. Corresponds to the JSON property featureVector

Returns:

  • (Array<Float>) 


7600
7601
7602
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 7600

def feature_vector
  @feature_vector
end

#restricts ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1IndexDatapointRestriction>

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 Corresponds to the JSON property restricts

Returns:



7608
7609
7610
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 7608

def restricts
  @restricts
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



7615
7616
7617
7618
7619
7620
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 7615

def update!(**args)
  @crowding_tag = args[:crowding_tag] if args.key?(:crowding_tag)
  @datapoint_id = args[:datapoint_id] if args.key?(:datapoint_id)
  @feature_vector = args[:feature_vector] if args.key?(:feature_vector)
  @restricts = args[:restricts] if args.key?(:restricts)
end