import {z} from 'zod'

export type GoogleCloudAiplatformV1GenieSource = {baseModelUri?: string | undefined};

export type GoogleCloudAiplatformV1ModelGardenSource = {publicModelName?: string | undefined, skipHfModelCache?: boolean | undefined, versionId?: string | undefined};

export type GoogleCloudAiplatformV1ModelBaseModelSource = {genieSource?: GoogleCloudAiplatformV1GenieSource | undefined, modelGardenSource?: GoogleCloudAiplatformV1ModelGardenSource | undefined};

export type GoogleCloudAiplatformV1Checkpoint = {checkpointId?: string | undefined, epoch?: unknown | undefined, step?: unknown | undefined};

export type GoogleCloudAiplatformV1EnvVar = {name?: string | undefined, value?: string | undefined};

export type GoogleCloudAiplatformV1Port = {containerPort?: number | undefined};

export type GoogleCloudAiplatformV1ProbeExecAction = {command?: Array<string> | undefined};

export type GoogleCloudAiplatformV1ProbeGrpcAction = {port?: number | undefined, service?: string | undefined};

export type GoogleCloudAiplatformV1ProbeHttpHeader = {name?: string | undefined, value?: string | undefined};

export type GoogleCloudAiplatformV1ProbeHttpGetAction = {host?: string | undefined, httpHeaders?: Array<GoogleCloudAiplatformV1ProbeHttpHeader> | undefined, path?: string | undefined, port?: number | undefined, scheme?: string | undefined};

export type GoogleCloudAiplatformV1ProbeTcpSocketAction = {host?: string | undefined, port?: number | undefined};

export type GoogleCloudAiplatformV1Probe = {exec?: GoogleCloudAiplatformV1ProbeExecAction | undefined, failureThreshold?: number | undefined, grpc?: GoogleCloudAiplatformV1ProbeGrpcAction | undefined, httpGet?: GoogleCloudAiplatformV1ProbeHttpGetAction | undefined, initialDelaySeconds?: number | undefined, periodSeconds?: number | undefined, successThreshold?: number | undefined, tcpSocket?: GoogleCloudAiplatformV1ProbeTcpSocketAction | undefined, timeoutSeconds?: number | undefined};

export type GoogleCloudAiplatformV1ModelContainerSpec = {args?: Array<string> | undefined, command?: Array<string> | undefined, deploymentTimeout?: unknown | undefined, env?: Array<GoogleCloudAiplatformV1EnvVar> | undefined, grpcPorts?: Array<GoogleCloudAiplatformV1Port> | undefined, healthProbe?: GoogleCloudAiplatformV1Probe | undefined, healthRoute?: string | undefined, imageUri?: string | undefined, invokeRoutePrefix?: string | undefined, livenessProbe?: GoogleCloudAiplatformV1Probe | undefined, ports?: Array<GoogleCloudAiplatformV1Port> | undefined, predictRoute?: string | undefined, sharedMemorySizeMb?: unknown | undefined, startupProbe?: GoogleCloudAiplatformV1Probe | undefined};

export type GoogleCloudAiplatformV1ModelDataStats = {testAnnotationsCount?: unknown | undefined, testDataItemsCount?: unknown | undefined, trainingAnnotationsCount?: unknown | undefined, trainingDataItemsCount?: unknown | undefined, validationAnnotationsCount?: unknown | undefined, validationDataItemsCount?: unknown | undefined};

export type GoogleCloudAiplatformV1DeployedModelRef = {checkpointId?: string | undefined, deployedModelId?: string | undefined, endpoint?: string | undefined};

export type GoogleCloudAiplatformV1EncryptionSpec = {kmsKeyName?: string | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain = {maxValue?: number | undefined, minValue?: number | undefined, originalMean?: number | undefined, originalStddev?: number | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization = {clipPercentLowerbound?: number | undefined, clipPercentUpperbound?: number | undefined, colorMap?: ('COLOR_MAP_UNSPECIFIED' | 'PINK_GREEN' | 'VIRIDIS' | 'RED' | 'GREEN' | 'RED_GREEN' | 'PINK_WHITE_GREEN') | undefined, overlayType?: ('OVERLAY_TYPE_UNSPECIFIED' | 'NONE' | 'ORIGINAL' | 'GRAYSCALE' | 'MASK_BLACK') | undefined, polarity?: ('POLARITY_UNSPECIFIED' | 'POSITIVE' | 'NEGATIVE' | 'BOTH') | undefined, type?: ('TYPE_UNSPECIFIED' | 'PIXELS' | 'OUTLINES') | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadataInputMetadata = {denseShapeTensorName?: string | undefined, encodedBaselines?: Array<unknown> | undefined, encodedTensorName?: string | undefined, encoding?: ('ENCODING_UNSPECIFIED' | 'IDENTITY' | 'BAG_OF_FEATURES' | 'BAG_OF_FEATURES_SPARSE' | 'INDICATOR' | 'COMBINED_EMBEDDING' | 'CONCAT_EMBEDDING') | undefined, featureValueDomain?: GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain | undefined, groupName?: string | undefined, indexFeatureMapping?: Array<string> | undefined, indicesTensorName?: string | undefined, inputBaselines?: Array<unknown> | undefined, inputTensorName?: string | undefined, modality?: string | undefined, visualization?: GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata = {displayNameMappingKey?: string | undefined, indexDisplayNameMapping: unknown, outputTensorName?: string | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadata = {featureAttributionsSchemaUri?: string | undefined, inputs?: {[key: string]: GoogleCloudAiplatformV1ExplanationMetadataInputMetadata} | undefined, latentSpaceSource?: string | undefined, outputs?: {[key: string]: GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata} | undefined};

export type GoogleCloudAiplatformV1GcsSource = {uris?: Array<string> | undefined};

export type GoogleCloudAiplatformV1ExamplesExampleGcsSource = {dataFormat?: ('DATA_FORMAT_UNSPECIFIED' | 'JSONL') | undefined, gcsSource?: GoogleCloudAiplatformV1GcsSource | undefined};

export type GoogleCloudAiplatformV1Presets = {modality?: ('MODALITY_UNSPECIFIED' | 'IMAGE' | 'TEXT' | 'TABULAR') | undefined, query?: ('PRECISE' | 'FAST') | undefined};

export type GoogleCloudAiplatformV1Examples = {exampleGcsSource?: GoogleCloudAiplatformV1ExamplesExampleGcsSource | undefined, nearestNeighborSearchConfig: unknown, neighborCount?: number | undefined, presets?: GoogleCloudAiplatformV1Presets | undefined};

export type GoogleCloudAiplatformV1BlurBaselineConfig = {maxBlurSigma?: number | undefined};

export type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature = {name?: string | undefined, sigma?: number | undefined};

export type GoogleCloudAiplatformV1FeatureNoiseSigma = {noiseSigma?: Array<GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature> | undefined};

export type GoogleCloudAiplatformV1SmoothGradConfig = {featureNoiseSigma?: GoogleCloudAiplatformV1FeatureNoiseSigma | undefined, noiseSigma?: number | undefined, noisySampleCount?: number | undefined};

export type GoogleCloudAiplatformV1IntegratedGradientsAttribution = {blurBaselineConfig?: GoogleCloudAiplatformV1BlurBaselineConfig | undefined, smoothGradConfig?: GoogleCloudAiplatformV1SmoothGradConfig | undefined, stepCount?: number | undefined};

export type GoogleCloudAiplatformV1SampledShapleyAttribution = {pathCount?: number | undefined};

export type GoogleCloudAiplatformV1XraiAttribution = {blurBaselineConfig?: GoogleCloudAiplatformV1BlurBaselineConfig | undefined, smoothGradConfig?: GoogleCloudAiplatformV1SmoothGradConfig | undefined, stepCount?: number | undefined};

export type GoogleCloudAiplatformV1ExplanationParameters = {examples?: GoogleCloudAiplatformV1Examples | undefined, integratedGradientsAttribution?: GoogleCloudAiplatformV1IntegratedGradientsAttribution | undefined, outputIndices?: Array<unknown> | undefined, sampledShapleyAttribution?: GoogleCloudAiplatformV1SampledShapleyAttribution | undefined, topK?: number | undefined, xraiAttribution?: GoogleCloudAiplatformV1XraiAttribution | undefined};

export type GoogleCloudAiplatformV1ExplanationSpec = {metadata?: GoogleCloudAiplatformV1ExplanationMetadata | undefined, parameters?: GoogleCloudAiplatformV1ExplanationParameters | undefined};

export type GoogleCloudAiplatformV1ModelSourceInfo = {copy?: boolean | undefined, sourceType?: ('MODEL_SOURCE_TYPE_UNSPECIFIED' | 'AUTOML' | 'CUSTOM' | 'BQML' | 'MODEL_GARDEN' | 'GENIE' | 'CUSTOM_TEXT_EMBEDDING' | 'MARKETPLACE') | undefined};

export type GoogleCloudAiplatformV1ModelOriginalModelInfo = {model?: string | undefined};

export type GoogleCloudAiplatformV1PredictSchemata = {instanceSchemaUri?: string | undefined, parametersSchemaUri?: string | undefined, predictionSchemaUri?: string | undefined};

export type GoogleCloudAiplatformV1ModelExportFormat = {exportableContents?: (Array<'EXPORTABLE_CONTENT_UNSPECIFIED' | 'ARTIFACT' | 'IMAGE'>) | undefined, id?: string | undefined};

export type GoogleCloudAiplatformV1Model = {artifactUri?: string | undefined, baseModelSource?: GoogleCloudAiplatformV1ModelBaseModelSource | undefined, checkpoints?: Array<GoogleCloudAiplatformV1Checkpoint> | undefined, containerSpec?: GoogleCloudAiplatformV1ModelContainerSpec | undefined, createTime?: unknown | undefined, dataStats?: GoogleCloudAiplatformV1ModelDataStats | undefined, defaultCheckpointId?: string | undefined, deployedModels?: Array<GoogleCloudAiplatformV1DeployedModelRef> | undefined, description?: string | undefined, displayName?: string | undefined, encryptionSpec?: GoogleCloudAiplatformV1EncryptionSpec | undefined, etag?: string | undefined, explanationSpec?: GoogleCloudAiplatformV1ExplanationSpec | undefined, labels?: {[key: string]: string} | undefined, metadata: unknown, metadataArtifact?: string | undefined, metadataSchemaUri?: string | undefined, modelSourceInfo?: GoogleCloudAiplatformV1ModelSourceInfo | undefined, name?: string | undefined, originalModelInfo?: GoogleCloudAiplatformV1ModelOriginalModelInfo | undefined, pipelineJob?: string | undefined, predictSchemata?: GoogleCloudAiplatformV1PredictSchemata | undefined, satisfiesPzi?: boolean | undefined, satisfiesPzs?: boolean | undefined, supportedDeploymentResourcesTypes?: (Array<'DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED' | 'DEDICATED_RESOURCES' | 'AUTOMATIC_RESOURCES' | 'SHARED_RESOURCES'>) | undefined, supportedExportFormats?: Array<GoogleCloudAiplatformV1ModelExportFormat> | undefined, supportedInputStorageFormats?: Array<string> | undefined, supportedOutputStorageFormats?: Array<string> | undefined, trainingPipeline?: string | undefined, updateTime?: unknown | undefined, versionAliases?: Array<string> | undefined, versionCreateTime?: unknown | undefined, versionDescription?: string | undefined, versionId?: string | undefined, versionUpdateTime?: unknown | undefined};

export type PatchApiV1ProjectsProjectsIdLocationsLocationsIdModelsModelsIdArgs = {projectsId: string, locationsId: string, modelsId: string, updateMask?: unknown | undefined, body: GoogleCloudAiplatformV1Model};

export type PatchApiV1ProjectsProjectsIdLocationsLocationsIdModelsModelsIdOptions = {baseUrl?: string | undefined, Oauth2?: string | undefined, Oauth2c?: string | undefined, fetch?: typeof fetch | undefined};

export const googleCloudAiplatformV1GenieSource = z.object({baseModelUri: z.string().optional()});

export const googleCloudAiplatformV1ModelGardenSource = z.object({publicModelName: z.string().optional(), skipHfModelCache: z.boolean().optional(), versionId: z.string().optional()});

export const googleCloudAiplatformV1ModelBaseModelSource = z.object({genieSource: googleCloudAiplatformV1GenieSource.optional(), modelGardenSource: googleCloudAiplatformV1ModelGardenSource.optional()});

export const googleCloudAiplatformV1Checkpoint = z.object({checkpointId: z.string().optional(), epoch: z.string().optional(), step: z.string().optional()});

export const googleCloudAiplatformV1EnvVar = z.object({name: z.string().optional(), value: z.string().optional()});

export const googleCloudAiplatformV1Port = z.object({containerPort: z.number().int().optional()});

export const googleCloudAiplatformV1ProbeExecAction = z.object({command: z.array(z.string()).optional()});

export const googleCloudAiplatformV1ProbeGrpcAction = z.object({port: z.number().int().optional(), service: z.string().optional()});

export const googleCloudAiplatformV1ProbeHttpHeader = z.object({name: z.string().optional(), value: z.string().optional()});

export const googleCloudAiplatformV1ProbeHttpGetAction = z.object({host: z.string().optional(), httpHeaders: z.array(googleCloudAiplatformV1ProbeHttpHeader).optional(), path: z.string().optional(), port: z.number().int().optional(), scheme: z.string().optional()});

export const googleCloudAiplatformV1ProbeTcpSocketAction = z.object({host: z.string().optional(), port: z.number().int().optional()});

export const googleCloudAiplatformV1Probe = z.object({exec: googleCloudAiplatformV1ProbeExecAction.optional(), failureThreshold: z.number().int().optional(), grpc: googleCloudAiplatformV1ProbeGrpcAction.optional(), httpGet: googleCloudAiplatformV1ProbeHttpGetAction.optional(), initialDelaySeconds: z.number().int().optional(), periodSeconds: z.number().int().optional(), successThreshold: z.number().int().optional(), tcpSocket: googleCloudAiplatformV1ProbeTcpSocketAction.optional(), timeoutSeconds: z.number().int().optional()});

export const googleCloudAiplatformV1ModelContainerSpec = z.object({args: z.array(z.string()).optional(), command: z.array(z.string()).optional(), deploymentTimeout: z.string().optional(), env: z.array(googleCloudAiplatformV1EnvVar).optional(), grpcPorts: z.array(googleCloudAiplatformV1Port).optional(), healthProbe: googleCloudAiplatformV1Probe.optional(), healthRoute: z.string().optional(), imageUri: z.string().optional(), invokeRoutePrefix: z.string().optional(), livenessProbe: googleCloudAiplatformV1Probe.optional(), ports: z.array(googleCloudAiplatformV1Port).optional(), predictRoute: z.string().optional(), sharedMemorySizeMb: z.string().optional(), startupProbe: googleCloudAiplatformV1Probe.optional()});

export const googleCloudAiplatformV1ModelDataStats = z.object({testAnnotationsCount: z.string().optional(), testDataItemsCount: z.string().optional(), trainingAnnotationsCount: z.string().optional(), trainingDataItemsCount: z.string().optional(), validationAnnotationsCount: z.string().optional(), validationDataItemsCount: z.string().optional()});

export const googleCloudAiplatformV1DeployedModelRef = z.object({checkpointId: z.string().optional(), deployedModelId: z.string().optional(), endpoint: z.string().optional()});

export const googleCloudAiplatformV1EncryptionSpec = z.object({kmsKeyName: z.string().optional()});

export const googleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain = z.object({maxValue: z.number().optional(), minValue: z.number().optional(), originalMean: z.number().optional(), originalStddev: z.number().optional()});

export const googleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization = z.object({clipPercentLowerbound: z.number().optional(), clipPercentUpperbound: z.number().optional(), colorMap: z.enum(["COLOR_MAP_UNSPECIFIED", "PINK_GREEN", "VIRIDIS", "RED", "GREEN", "RED_GREEN", "PINK_WHITE_GREEN"]).optional(), overlayType: z.enum(["OVERLAY_TYPE_UNSPECIFIED", "NONE", "ORIGINAL", "GRAYSCALE", "MASK_BLACK"]).optional(), polarity: z.enum(["POLARITY_UNSPECIFIED", "POSITIVE", "NEGATIVE", "BOTH"]).optional(), type: z.enum(["TYPE_UNSPECIFIED", "PIXELS", "OUTLINES"]).optional()});

export const googleCloudAiplatformV1ExplanationMetadataInputMetadata = z.object({denseShapeTensorName: z.string().optional(), encodedBaselines: z.array(z.unknown()).optional(), encodedTensorName: z.string().optional(), encoding: z.enum(["ENCODING_UNSPECIFIED", "IDENTITY", "BAG_OF_FEATURES", "BAG_OF_FEATURES_SPARSE", "INDICATOR", "COMBINED_EMBEDDING", "CONCAT_EMBEDDING"]).optional(), featureValueDomain: googleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain.optional(), groupName: z.string().optional(), indexFeatureMapping: z.array(z.string()).optional(), indicesTensorName: z.string().optional(), inputBaselines: z.array(z.unknown()).optional(), inputTensorName: z.string().optional(), modality: z.string().optional(), visualization: googleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization.optional()});

export const googleCloudAiplatformV1ExplanationMetadataOutputMetadata = z.object({displayNameMappingKey: z.string().optional(), indexDisplayNameMapping: z.unknown(), outputTensorName: z.string().optional()});

export const googleCloudAiplatformV1ExplanationMetadata = z.object({featureAttributionsSchemaUri: z.string().optional(), inputs: z.record(z.string(), googleCloudAiplatformV1ExplanationMetadataInputMetadata).optional(), latentSpaceSource: z.string().optional(), outputs: z.record(z.string(), googleCloudAiplatformV1ExplanationMetadataOutputMetadata).optional()});

export const googleCloudAiplatformV1GcsSource = z.object({uris: z.array(z.string()).optional()});

export const googleCloudAiplatformV1ExamplesExampleGcsSource = z.object({dataFormat: z.enum(["DATA_FORMAT_UNSPECIFIED", "JSONL"]).optional(), gcsSource: googleCloudAiplatformV1GcsSource.optional()});

export const googleCloudAiplatformV1Presets = z.object({modality: z.enum(["MODALITY_UNSPECIFIED", "IMAGE", "TEXT", "TABULAR"]).optional(), query: z.enum(["PRECISE", "FAST"]).optional()});

export const googleCloudAiplatformV1Examples = z.object({exampleGcsSource: googleCloudAiplatformV1ExamplesExampleGcsSource.optional(), nearestNeighborSearchConfig: z.unknown(), neighborCount: z.number().int().optional(), presets: googleCloudAiplatformV1Presets.optional()});

export const googleCloudAiplatformV1BlurBaselineConfig = z.object({maxBlurSigma: z.number().optional()});

export const googleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature = z.object({name: z.string().optional(), sigma: z.number().optional()});

export const googleCloudAiplatformV1FeatureNoiseSigma = z.object({noiseSigma: z.array(googleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature).optional()});

export const googleCloudAiplatformV1SmoothGradConfig = z.object({featureNoiseSigma: googleCloudAiplatformV1FeatureNoiseSigma.optional(), noiseSigma: z.number().optional(), noisySampleCount: z.number().int().optional()});

export const googleCloudAiplatformV1IntegratedGradientsAttribution = z.object({blurBaselineConfig: googleCloudAiplatformV1BlurBaselineConfig.optional(), smoothGradConfig: googleCloudAiplatformV1SmoothGradConfig.optional(), stepCount: z.number().int().optional()});

export const googleCloudAiplatformV1SampledShapleyAttribution = z.object({pathCount: z.number().int().optional()});

export const googleCloudAiplatformV1XraiAttribution = z.object({blurBaselineConfig: googleCloudAiplatformV1BlurBaselineConfig.optional(), smoothGradConfig: googleCloudAiplatformV1SmoothGradConfig.optional(), stepCount: z.number().int().optional()});

export const googleCloudAiplatformV1ExplanationParameters = z.object({examples: googleCloudAiplatformV1Examples.optional(), integratedGradientsAttribution: googleCloudAiplatformV1IntegratedGradientsAttribution.optional(), outputIndices: z.array(z.unknown()).optional(), sampledShapleyAttribution: googleCloudAiplatformV1SampledShapleyAttribution.optional(), topK: z.number().int().optional(), xraiAttribution: googleCloudAiplatformV1XraiAttribution.optional()});

export const googleCloudAiplatformV1ExplanationSpec = z.object({metadata: googleCloudAiplatformV1ExplanationMetadata.optional(), parameters: googleCloudAiplatformV1ExplanationParameters.optional()});

export const googleCloudAiplatformV1ModelSourceInfo = z.object({copy: z.boolean().optional(), sourceType: z.enum(["MODEL_SOURCE_TYPE_UNSPECIFIED", "AUTOML", "CUSTOM", "BQML", "MODEL_GARDEN", "GENIE", "CUSTOM_TEXT_EMBEDDING", "MARKETPLACE"]).optional()});

export const googleCloudAiplatformV1ModelOriginalModelInfo = z.object({model: z.string().optional()});

export const googleCloudAiplatformV1PredictSchemata = z.object({instanceSchemaUri: z.string().optional(), parametersSchemaUri: z.string().optional(), predictionSchemaUri: z.string().optional()});

export const googleCloudAiplatformV1ModelExportFormat = z.object({exportableContents: z.array(z.enum(["EXPORTABLE_CONTENT_UNSPECIFIED", "ARTIFACT", "IMAGE"])).optional(), id: z.string().optional()});

export const googleCloudAiplatformV1Model = z.object({artifactUri: z.string().optional(), baseModelSource: googleCloudAiplatformV1ModelBaseModelSource.optional(), checkpoints: z.array(googleCloudAiplatformV1Checkpoint).optional(), containerSpec: googleCloudAiplatformV1ModelContainerSpec.optional(), createTime: z.string().optional(), dataStats: googleCloudAiplatformV1ModelDataStats.optional(), defaultCheckpointId: z.string().optional(), deployedModels: z.array(googleCloudAiplatformV1DeployedModelRef).optional(), description: z.string().optional(), displayName: z.string().optional(), encryptionSpec: googleCloudAiplatformV1EncryptionSpec.optional(), etag: z.string().optional(), explanationSpec: googleCloudAiplatformV1ExplanationSpec.optional(), labels: z.record(z.string(), z.string()).optional(), metadata: z.unknown(), metadataArtifact: z.string().optional(), metadataSchemaUri: z.string().optional(), modelSourceInfo: googleCloudAiplatformV1ModelSourceInfo.optional(), name: z.string().optional(), originalModelInfo: googleCloudAiplatformV1ModelOriginalModelInfo.optional(), pipelineJob: z.string().optional(), predictSchemata: googleCloudAiplatformV1PredictSchemata.optional(), satisfiesPzi: z.boolean().optional(), satisfiesPzs: z.boolean().optional(), supportedDeploymentResourcesTypes: z.array(z.enum(["DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED", "DEDICATED_RESOURCES", "AUTOMATIC_RESOURCES", "SHARED_RESOURCES"])).optional(), supportedExportFormats: z.array(googleCloudAiplatformV1ModelExportFormat).optional(), supportedInputStorageFormats: z.array(z.string()).optional(), supportedOutputStorageFormats: z.array(z.string()).optional(), trainingPipeline: z.string().optional(), updateTime: z.string().optional(), versionAliases: z.array(z.string()).optional(), versionCreateTime: z.string().optional(), versionDescription: z.string().optional(), versionId: z.string().optional(), versionUpdateTime: z.string().optional()});

export const validateResponse = async <Output>(
  schema: {
    readonly '~standard': {
      readonly validate: (value: unknown) => ({ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }) | Promise<{ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }>
    }
  },
  value: unknown
): Promise<Output> => {
  const result = await schema['~standard'].validate(value)

  if (result.issues !== undefined) {
    const detail = result.issues
      .map(({ message, path }) =>
        path?.length
          ? `${path.map((segment) => String(typeof segment === 'object' ? segment.key : segment)).join('.')}: ${message}`
          : message
      )
      .join('; ')

    throw new Error(`Response does not match the schema: ${detail}`, { cause: { issues: result.issues } })
  }

  return result.value
};

/**
 * Updates a Model.
 * 
 * PATCH /v1/projects/{projectsId}/locations/{locationsId}/models/{modelsId}
 * 
 * Also accepts auth: Oauth2 + Oauth2c
 */
export const patchApiV1ProjectsProjectsIdLocationsLocationsIdModelsModelsId = async (args: PatchApiV1ProjectsProjectsIdLocationsLocationsIdModelsModelsIdArgs, options?: PatchApiV1ProjectsProjectsIdLocationsLocationsIdModelsModelsIdOptions) => {
const {baseUrl = "https://aiplatform.googleapis.com", fetch: fetchFn = fetch, Oauth2, Oauth2c} = options ?? {}

const query = new URLSearchParams()
const headers = new Headers()
headers.set('content-type', "application/json")
headers.set('accept', "application/json")

if (args.updateMask != null) query.append("updateMask", String(args.updateMask))
if (Oauth2 !== undefined) headers.set('authorization', `Bearer ${Oauth2}`)
if (Oauth2c !== undefined) headers.set('authorization', `Bearer ${Oauth2c}`)

const url = `${baseUrl.replace(/\/+$/, '')}/v1/projects/${encodeURIComponent(String(args.projectsId))}/locations/${encodeURIComponent(String(args.locationsId))}/models/${encodeURIComponent(String(args.modelsId))}${query.size > 0 ? `?${query}` : ''}`

const res = await fetchFn(url, {method: "PATCH", headers, body: JSON.stringify(args.body)})

if (!res.ok) throw new Error(`Request failed with status ${res.status}`, {cause: {status: res.status, body: await res.text()}})

return validateResponse(googleCloudAiplatformV1Model, await res.json())
};