aws.sdk.kotlin.services.transcribe.model.CreateLanguageModelResponse.kt Maven / Gradle / Ivy

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Amazon Transcribe Service
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// Code generated by smithy-kotlin-codegen. DO NOT EDIT!

package aws.sdk.kotlin.services.transcribe.model



class CreateLanguageModelResponse private constructor(builder: Builder) {
    /**
     * The Amazon Transcribe standard language model, or base model, you used when creating your
     * custom language model.
     * If your audio has a sample rate of 16,000 Hz or greater, this value should be
     * WideBand. If your audio has a sample rate of less than
     * 16,000 Hz, this value should be NarrowBand.
     */
    val baseModelName: aws.sdk.kotlin.services.transcribe.model.BaseModelName? = builder.baseModelName
    /**
     * Lists your data access role ARN (Amazon Resource Name) and the Amazon S3
     * locations your provided for your training (S3Uri) and tuning
     * (TuningDataS3Uri) data.
     */
    val inputDataConfig: aws.sdk.kotlin.services.transcribe.model.InputDataConfig? = builder.inputDataConfig
    /**
     * The language code you selected for your custom language model.
     */
    val languageCode: aws.sdk.kotlin.services.transcribe.model.ClmLanguageCode? = builder.languageCode
    /**
     * The unique name you chose for your custom language model.
     */
    val modelName: kotlin.String? = builder.modelName
    /**
     * The status of your custom language model. When the status shows as
     * COMPLETED, your model is ready to use.
     */
    val modelStatus: aws.sdk.kotlin.services.transcribe.model.ModelStatus? = builder.modelStatus

    companion object {
        operator fun invoke(block: Builder.() -> kotlin.Unit): aws.sdk.kotlin.services.transcribe.model.CreateLanguageModelResponse = Builder().apply(block).build()
    }

    override fun toString(): kotlin.String = buildString {
        append("CreateLanguageModelResponse(")
        append("baseModelName=$baseModelName,")
        append("inputDataConfig=$inputDataConfig,")
        append("languageCode=$languageCode,")
        append("modelName=$modelName,")
        append("modelStatus=$modelStatus)")
    }

    override fun hashCode(): kotlin.Int {
        var result = baseModelName?.hashCode() ?: 0
        result = 31 * result + (inputDataConfig?.hashCode() ?: 0)
        result = 31 * result + (languageCode?.hashCode() ?: 0)
        result = 31 * result + (modelName?.hashCode() ?: 0)
        result = 31 * result + (modelStatus?.hashCode() ?: 0)
        return result
    }

    override fun equals(other: kotlin.Any?): kotlin.Boolean {
        if (this === other) return true
        if (other == null || this::class != other::class) return false

        other as CreateLanguageModelResponse

        if (baseModelName != other.baseModelName) return false
        if (inputDataConfig != other.inputDataConfig) return false
        if (languageCode != other.languageCode) return false
        if (modelName != other.modelName) return false
        if (modelStatus != other.modelStatus) return false

        return true
    }

    inline fun copy(block: Builder.() -> kotlin.Unit = {}): aws.sdk.kotlin.services.transcribe.model.CreateLanguageModelResponse = Builder(this).apply(block).build()

    class Builder {
        /**
         * The Amazon Transcribe standard language model, or base model, you used when creating your
         * custom language model.
         * If your audio has a sample rate of 16,000 Hz or greater, this value should be
         * WideBand. If your audio has a sample rate of less than
         * 16,000 Hz, this value should be NarrowBand.
         */
        var baseModelName: aws.sdk.kotlin.services.transcribe.model.BaseModelName? = null
        /**
         * Lists your data access role ARN (Amazon Resource Name) and the Amazon S3
         * locations your provided for your training (S3Uri) and tuning
         * (TuningDataS3Uri) data.
         */
        var inputDataConfig: aws.sdk.kotlin.services.transcribe.model.InputDataConfig? = null
        /**
         * The language code you selected for your custom language model.
         */
        var languageCode: aws.sdk.kotlin.services.transcribe.model.ClmLanguageCode? = null
        /**
         * The unique name you chose for your custom language model.
         */
        var modelName: kotlin.String? = null
        /**
         * The status of your custom language model. When the status shows as
         * COMPLETED, your model is ready to use.
         */
        var modelStatus: aws.sdk.kotlin.services.transcribe.model.ModelStatus? = null

        internal constructor()
        @PublishedApi
        internal constructor(x: aws.sdk.kotlin.services.transcribe.model.CreateLanguageModelResponse) : this() {
            this.baseModelName = x.baseModelName
            this.inputDataConfig = x.inputDataConfig
            this.languageCode = x.languageCode
            this.modelName = x.modelName
            this.modelStatus = x.modelStatus
        }

        @PublishedApi
        internal fun build(): aws.sdk.kotlin.services.transcribe.model.CreateLanguageModelResponse = CreateLanguageModelResponse(this)

        /**
         * construct an [aws.sdk.kotlin.services.transcribe.model.InputDataConfig] inside the given [block]
         */
        fun inputDataConfig(block: aws.sdk.kotlin.services.transcribe.model.InputDataConfig.Builder.() -> kotlin.Unit) {
            this.inputDataConfig = aws.sdk.kotlin.services.transcribe.model.InputDataConfig.invoke(block)
        }
    }
}