Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1IndexDatapoint

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb

Overview

A datapoint of Index.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1IndexDatapoint

Returns a new instance of GoogleCloudAiplatformV1beta1IndexDatapoint.



8772
8773
8774
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 8772

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

Instance Attribute Details

#crowding_tag ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag

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:



8751
8752
8753
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 8751

def crowding_tag
  @crowding_tag
end

#datapoint_id ⇒ String

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

Returns:

  • (String) 


8756
8757
8758
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 8756

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>) 


8762
8763
8764
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 8762

def feature_vector
  @feature_vector
end

#restricts ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1IndexDatapointRestriction>

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:



8770
8771
8772
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 8770

def restricts
  @restricts
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



8777
8778
8779
8780
8781
8782
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 8777

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