class Qdrant::Api::QuantizationSearchParams

Overview

Additional parameters of the search

Included Modules

Defined in:

qdrant-api/models/quantization_search_params.cr

Constructors

Instance Method Summary

Macros inherited from module Qdrant::Api::Validation

validates(name, klass, nilable, **rules) validates

Instance methods inherited from module Qdrant::Api::Serializable

eql?(other) eql?, to_body : Hash(String, JSON::Any) to_body, to_h : Hash(String, JSON::Any) to_h, to_s(io : IO) : Nil to_s

Constructor Detail

def self.new(ctx : YAML::ParseContext, node : YAML::Nodes::Node) #

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def self.new(pull : JSON::PullParser) #

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def self.new(ignore : Bool | Nil = false, rescore : Bool | Nil = nil, oversampling : Float64 | Nil = nil) #

Initializes the object @param [Hash] attributes Model attributes in the form of hash


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def self.new(*, __pull_for_json_serializable pull : JSON::PullParser) #

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def self.new(*, __context_for_yaml_serializable ctx : YAML::ParseContext, __node_for_yaml_serializable node : YAML::Nodes::Node) #

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Instance Method Detail

def ==(other : self) #
Description copied from class Reference

Returns true if this reference is the same as other. Invokes same?.


def hash(hasher) #
Description copied from class Reference

See Object#hash(hasher)


def ignore : Bool | Nil #

Optional properties If true, quantized vectors are ignored. Default is false.


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def ignore=(ignore : Bool | Nil) #

Optional properties If true, quantized vectors are ignored. Default is false.


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def list_invalid_properties #

Show invalid properties with the reasons. Usually used together with valid? @return Array for valid properties with the reasons


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def oversampling : Float64 | Nil #

Oversampling factor for quantization. Default is 1.0. Defines how many extra vectors should be preselected using quantized index, and then re-scored using original vectors. For example, if #oversampling is 2.4 and limit is 100, then 240 vectors will be preselected using quantized index, and then top-100 will be returned after re-scoring.


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def oversampling=(value : Float64 | Nil) #

Oversampling factor for quantization. Default is 1.0. Defines how many extra vectors should be preselected using quantized index, and then re-scored using original vectors. For example, if #oversampling is 2.4 and limit is 100, then 240 vectors will be preselected using quantized index, and then top-100 will be returned after re-scoring.


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def oversampling_validation_error(value) : String | Nil #

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def rescore : Bool | Nil #

If true, use original vectors to re-score top-k results. Might require more time in case if original vectors are stored on disk. If not set, qdrant decides automatically apply rescoring or not.


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def rescore=(rescore : Bool | Nil) #

If true, use original vectors to re-score top-k results. Might require more time in case if original vectors are stored on disk. If not set, qdrant decides automatically apply rescoring or not.


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def valid? #

Check to see if the all the properties in the model are valid @return true if the model is valid


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