com.pulumi.gcp.vertex.kotlin.outputs.GetAiIndexMetadataConfig.kt Maven / Gradle / Ivy
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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.
@file:Suppress("NAME_SHADOWING", "DEPRECATION")
package com.pulumi.gcp.vertex.kotlin.outputs
import kotlin.Int
import kotlin.String
import kotlin.Suppress
import kotlin.collections.List
/**
*
* @property algorithmConfigs The configuration with regard to the algorithms used for efficient search.
* @property approximateNeighborsCount The default number of neighbors to find via approximate search before exact reordering is
* performed. Exact reordering is a procedure where results returned by an
* approximate search algorithm are reordered via a more expensive distance computation.
* Required if tree-AH algorithm is used.
* @property dimensions The number of dimensions of the input vectors.
* @property distanceMeasureType The distance measure used in nearest neighbor search. The value must be one of the followings:
* * SQUARED_L2_DISTANCE: Euclidean (L_2) Distance
* * L1_DISTANCE: Manhattan (L_1) Distance
* * COSINE_DISTANCE: Cosine Distance. Defined as 1 - cosine similarity.
* * DOT_PRODUCT_DISTANCE: Dot Product Distance. Defined as a negative of the dot product
* @property featureNormType Type of normalization to be carried out on each vector. The value must be one of the followings:
* * UNIT_L2_NORM: Unit L2 normalization type
* * NONE: No normalization type is specified.
* @property shardSize Index data is split into equal parts to be processed. These are called "shards".
* The shard size must be specified when creating an index. The value must be one of the followings:
* * SHARD_SIZE_SMALL: Small (2GB)
* * SHARD_SIZE_MEDIUM: Medium (20GB)
* * SHARD_SIZE_LARGE: Large (50GB)
*/
public data class GetAiIndexMetadataConfig(
public val algorithmConfigs: List,
public val approximateNeighborsCount: Int,
public val dimensions: Int,
public val distanceMeasureType: String,
public val featureNormType: String,
public val shardSize: String,
) {
public companion object {
public fun toKotlin(javaType: com.pulumi.gcp.vertex.outputs.GetAiIndexMetadataConfig): GetAiIndexMetadataConfig = GetAiIndexMetadataConfig(
algorithmConfigs = javaType.algorithmConfigs().map({ args0 ->
args0.let({ args0 ->
com.pulumi.gcp.vertex.kotlin.outputs.GetAiIndexMetadataConfigAlgorithmConfig.Companion.toKotlin(args0)
})
}),
approximateNeighborsCount = javaType.approximateNeighborsCount(),
dimensions = javaType.dimensions(),
distanceMeasureType = javaType.distanceMeasureType(),
featureNormType = javaType.featureNormType(),
shardSize = javaType.shardSize(),
)
}
}
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