/** * Copyright 2019 Google LLC * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ import { GaxiosPromise } from 'gaxios'; import { Compute, JWT, OAuth2Client, UserRefreshClient } from 'google-auth-library'; import { BodyResponseCallback, GlobalOptions, GoogleConfigurable, MethodOptions } from 'googleapis-common'; export declare namespace ml_v1 { interface Options extends GlobalOptions { version: 'v1'; } interface StandardParameters { /** * V1 error format. */ '$.xgafv'?: string; /** * OAuth access token. */ access_token?: string; /** * Data format for response. */ alt?: string; /** * JSONP */ callback?: string; /** * Selector specifying which fields to include in a partial response. */ fields?: string; /** * API key. Your API key identifies your project and provides you with API * access, quota, and reports. Required unless you provide an OAuth 2.0 * token. */ key?: string; /** * OAuth 2.0 token for the current user. */ oauth_token?: string; /** * Returns response with indentations and line breaks. */ prettyPrint?: boolean; /** * Available to use for quota purposes for server-side applications. Can be * any arbitrary string assigned to a user, but should not exceed 40 * characters. */ quotaUser?: string; /** * Legacy upload protocol for media (e.g. "media", "multipart"). */ uploadType?: string; /** * Upload protocol for media (e.g. "raw", "multipart"). */ upload_protocol?: string; } /** * Cloud Machine Learning Engine * * An API to enable creating and using machine learning models. * * @example * const {google} = require('googleapis'); * const ml = google.ml('v1'); * * @namespace ml * @type {Function} * @version v1 * @variation v1 * @param {object=} options Options for Ml */ class Ml { operations: Resource$Operations; projects: Resource$Projects; constructor(options: GlobalOptions, google?: GoogleConfigurable); } /** * Message that represents an arbitrary HTTP body. It should only be used for * payload formats that can't be represented as JSON, such as raw binary * or an HTML page. This message can be used both in streaming and * non-streaming API methods in the request as well as the response. It can * be used as a top-level request field, which is convenient if one wants to * extract parameters from either the URL or HTTP template into the request * fields and also want access to the raw HTTP body. Example: message * GetResourceRequest { // A unique request id. string request_id * = 1; // The raw HTTP body is bound to this field. * google.api.HttpBody http_body = 2; } service ResourceService { rpc * GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc * UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } * Example with streaming methods: service CaldavService { rpc * GetCalendar(stream google.api.HttpBody) returns (stream * google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) * returns (stream google.api.HttpBody); } Use of this type only changes * how the request and response bodies are handled, all other features will * continue to work unchanged. */ interface Schema$GoogleApi__HttpBody { /** * The HTTP Content-Type header value specifying the content type of the * body. */ contentType?: string; /** * The HTTP request/response body as raw binary. */ data?: string; /** * Application specific response metadata. Must be set in the first response * for streaming APIs. */ extensions?: Array<{ [key: string]: any; }>; } /** * An observed value of a metric. */ interface Schema$GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric { /** * The objective value at this training step. */ objectiveValue?: number; /** * The global training step for this metric. */ trainingStep?: string; } /** * Represents a hardware accelerator request config. */ interface Schema$GoogleCloudMlV1__AcceleratorConfig { /** * The number of accelerators to attach to each machine running the job. */ count?: string; /** * The available types of accelerators. */ type?: string; } /** * Options for automatically scaling a model. */ interface Schema$GoogleCloudMlV1__AutoScaling { /** * Optional. The minimum number of nodes to allocate for this model. These * nodes are always up, starting from the time the model is deployed. * Therefore, the cost of operating this model will be at least `rate` * * `min_nodes` * number of hours since last billing cycle, where `rate` is * the cost per node-hour as documented in the [pricing * guide](/ml-engine/docs/pricing), even if no predictions are performed. * There is additional cost for each prediction performed. Unlike manual * scaling, if the load gets too heavy for the nodes that are up, the * service will automatically add nodes to handle the increased load as well * as scale back as traffic drops, always maintaining at least `min_nodes`. * You will be charged for the time in which additional nodes are used. If * not specified, `min_nodes` defaults to 0, in which case, when traffic to * a model stops (and after a cool-down period), nodes will be shut down and * no charges will be incurred until traffic to the model resumes. You can * set `min_nodes` when creating the model version, and you can also update * `min_nodes` for an existing version: <pre> update_body.json: { * 'autoScaling': { 'minNodes': 5 } } </pre> * HTTP request: <pre> PATCH * https://ml.googleapis.com/v1/{name=projects/x/models/x/versions/*}?update_mask=autoScaling.minNodes * -d @./update_body.json </pre> */ minNodes?: number; } /** * Request message for the CancelJob method. */ interface Schema$GoogleCloudMlV1__CancelJobRequest { } interface Schema$GoogleCloudMlV1__Capability { /** * Available accelerators for the capability. */ availableAccelerators?: string[]; type?: string; } interface Schema$GoogleCloudMlV1__Config { /** * The service account Cloud ML uses to run on TPU node. */ tpuServiceAccount?: string; } /** * Returns service account information associated with a project. */ interface Schema$GoogleCloudMlV1__GetConfigResponse { config?: Schema$GoogleCloudMlV1__Config; /** * The service account Cloud ML uses to access resources in the project. */ serviceAccount?: string; /** * The project number for `service_account`. */ serviceAccountProject?: string; } /** * Represents the result of a single hyperparameter tuning trial from a * training job. The TrainingOutput object that is returned on successful * completion of a training job with hyperparameter tuning includes a list of * HyperparameterOutput objects, one for each successful trial. */ interface Schema$GoogleCloudMlV1__HyperparameterOutput { /** * All recorded object metrics for this trial. This field is not currently * populated. */ allMetrics?: Schema$GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric[]; /** * The final objective metric seen for this trial. */ finalMetric?: Schema$GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric; /** * The hyperparameters given to this trial. */ hyperparameters?: { [key: string]: string; }; /** * True if the trial is stopped early. */ isTrialStoppedEarly?: boolean; /** * The trial id for these results. */ trialId?: string; } /** * Represents a set of hyperparameters to optimize. */ interface Schema$GoogleCloudMlV1__HyperparameterSpec { /** * Optional. The search algorithm specified for the hyperparameter tuning * job. Uses the default CloudML Engine hyperparameter tuning algorithm if * unspecified. */ algorithm?: string; /** * Optional. Indicates if the hyperparameter tuning job enables auto trial * early stopping. */ enableTrialEarlyStopping?: boolean; /** * Required. The type of goal to use for tuning. Available types are * `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`. */ goal?: string; /** * Optional. The Tensorflow summary tag name to use for optimizing trials. * For current versions of Tensorflow, this tag name should exactly match * what is shown in Tensorboard, including all scopes. For versions of * Tensorflow prior to 0.12, this should be only the tag passed to * tf.Summary. By default, "training/hptuning/metric" will be * used. */ hyperparameterMetricTag?: string; /** * Optional. The number of training trials to run concurrently. You can * reduce the time it takes to perform hyperparameter tuning by adding * trials in parallel. However, each trail only benefits from the * information gained in completed trials. That means that a trial does not * get access to the results of trials running at the same time, which could * reduce the quality of the overall optimization. Each trial will use the * same scale tier and machine types. Defaults to one. */ maxParallelTrials?: number; /** * Optional. How many training trials should be attempted to optimize the * specified hyperparameters. Defaults to one. */ maxTrials?: number; /** * Required. The set of parameters to tune. */ params?: Schema$GoogleCloudMlV1__ParameterSpec[]; /** * Optional. The prior hyperparameter tuning job id that users hope to * continue with. The job id will be used to find the corresponding vizier * study guid and resume the study. */ resumePreviousJobId?: string; } /** * Represents a training or prediction job. */ interface Schema$GoogleCloudMlV1__Job { /** * Output only. When the job was created. */ createTime?: string; /** * Output only. When the job processing was completed. */ endTime?: string; /** * Output only. The details of a failure or a cancellation. */ errorMessage?: string; /** * `etag` is used for optimistic concurrency control as a way to help * prevent simultaneous updates of a job from overwriting each other. It is * strongly suggested that systems make use of the `etag` in the * read-modify-write cycle to perform job updates in order to avoid race * conditions: An `etag` is returned in the response to `GetJob`, and * systems are expected to put that etag in the request to `UpdateJob` to * ensure that their change will be applied to the same version of the job. */ etag?: string; /** * Required. The user-specified id of the job. */ jobId?: string; /** * Optional. One or more labels that you can add, to organize your jobs. * Each label is a key-value pair, where both the key and the value are * arbitrary strings that you supply. For more information, see the * documentation on <a * href="/ml-engine/docs/tensorflow/resource-labels">using * labels</a>. */ labels?: { [key: string]: string; }; /** * Input parameters to create a prediction job. */ predictionInput?: Schema$GoogleCloudMlV1__PredictionInput; /** * The current prediction job result. */ predictionOutput?: Schema$GoogleCloudMlV1__PredictionOutput; /** * Output only. When the job processing was started. */ startTime?: string; /** * Output only. The detailed state of a job. */ state?: string; /** * Input parameters to create a training job. */ trainingInput?: Schema$GoogleCloudMlV1__TrainingInput; /** * The current training job result. */ trainingOutput?: Schema$GoogleCloudMlV1__TrainingOutput; } /** * Response message for the ListJobs method. */ interface Schema$GoogleCloudMlV1__ListJobsResponse { /** * The list of jobs. */ jobs?: Schema$GoogleCloudMlV1__Job[]; /** * Optional. Pass this token as the `page_token` field of the request for a * subsequent call. */ nextPageToken?: string; } interface Schema$GoogleCloudMlV1__ListLocationsResponse { /** * Locations where at least one type of CMLE capability is available. */ locations?: Schema$GoogleCloudMlV1__Location[]; /** * Optional. Pass this token as the `page_token` field of the request for a * subsequent call. */ nextPageToken?: string; } /** * Response message for the ListModels method. */ interface Schema$GoogleCloudMlV1__ListModelsResponse { /** * The list of models. */ models?: Schema$GoogleCloudMlV1__Model[]; /** * Optional. Pass this token as the `page_token` field of the request for a * subsequent call. */ nextPageToken?: string; } /** * Response message for the ListVersions method. */ interface Schema$GoogleCloudMlV1__ListVersionsResponse { /** * Optional. Pass this token as the `page_token` field of the request for a * subsequent call. */ nextPageToken?: string; /** * The list of versions. */ versions?: Schema$GoogleCloudMlV1__Version[]; } interface Schema$GoogleCloudMlV1__Location { /** * Capabilities available in the location. */ capabilities?: Schema$GoogleCloudMlV1__Capability[]; name?: string; } /** * Options for manually scaling a model. */ interface Schema$GoogleCloudMlV1__ManualScaling { /** * The number of nodes to allocate for this model. These nodes are always * up, starting from the time the model is deployed, so the cost of * operating this model will be proportional to `nodes` * number of hours * since last billing cycle plus the cost for each prediction performed. */ nodes?: number; } /** * Represents a machine learning solution. A model can have multiple * versions, each of which is a deployed, trained model ready to receive * prediction requests. The model itself is just a container. */ interface Schema$GoogleCloudMlV1__Model { /** * Output only. The default version of the model. This version will be used * to handle prediction requests that do not specify a version. You can * change the default version by calling * [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault). */ defaultVersion?: Schema$GoogleCloudMlV1__Version; /** * Optional. The description specified for the model when it was created. */ description?: string; /** * `etag` is used for optimistic concurrency control as a way to help * prevent simultaneous updates of a model from overwriting each other. It * is strongly suggested that systems make use of the `etag` in the * read-modify-write cycle to perform model updates in order to avoid race * conditions: An `etag` is returned in the response to `GetModel`, and * systems are expected to put that etag in the request to `UpdateModel` to * ensure that their change will be applied to the model as intended. */ etag?: string; /** * Optional. One or more labels that you can add, to organize your models. * Each label is a key-value pair, where both the key and the value are * arbitrary strings that you supply. For more information, see the * documentation on <a * href="/ml-engine/docs/tensorflow/resource-labels">using * labels</a>. */ labels?: { [key: string]: string; }; /** * Required. The name specified for the model when it was created. The * model name must be unique within the project it is created in. */ name?: string; /** * Optional. If true, enables StackDriver Logging for online prediction. * Default is false. */ onlinePredictionLogging?: boolean; /** * Optional. The list of regions where the model is going to be deployed. * Currently only one region per model is supported. Defaults to * 'us-central1' if nothing is set. See the <a * href="/ml-engine/docs/tensorflow/regions">available * regions</a> for ML Engine services. Note: * No matter where a * model is deployed, it can always be accessed by users from anywhere, * both for online and batch prediction. * The region for a batch * prediction job is set by the region field when submitting the batch * prediction job and does not take its value from this field. */ regions?: string[]; } /** * Represents the metadata of the long-running operation. */ interface Schema$GoogleCloudMlV1__OperationMetadata { /** * The time the operation was submitted. */ createTime?: string; /** * The time operation processing completed. */ endTime?: string; /** * Indicates whether a request to cancel this operation has been made. */ isCancellationRequested?: boolean; /** * The user labels, inherited from the model or the model version being * operated on. */ labels?: { [key: string]: string; }; /** * Contains the name of the model associated with the operation. */ modelName?: string; /** * The operation type. */ operationType?: string; /** * Contains the project number associated with the operation. */ projectNumber?: string; /** * The time operation processing started. */ startTime?: string; /** * Contains the version associated with the operation. */ version?: Schema$GoogleCloudMlV1__Version; } /** * Represents a single hyperparameter to optimize. */ interface Schema$GoogleCloudMlV1__ParameterSpec { /** * Required if type is `CATEGORICAL`. The list of possible categories. */ categoricalValues?: string[]; /** * Required if type is `DISCRETE`. A list of feasible points. The list * should be in strictly increasing order. For instance, this parameter * might have possible settings of 1.5, 2.5, and 4.0. This list should not * contain more than 1,000 values. */ discreteValues?: number[]; /** * Required if type is `DOUBLE` or `INTEGER`. This field should be unset if * type is `CATEGORICAL`. This value should be integers if type is * `INTEGER`. */ maxValue?: number; /** * Required if type is `DOUBLE` or `INTEGER`. This field should be unset if * type is `CATEGORICAL`. This value should be integers if type is INTEGER. */ minValue?: number; /** * Required. The parameter name must be unique amongst all ParameterConfigs * in a HyperparameterSpec message. E.g., "learning_rate". */ parameterName?: string; /** * Optional. How the parameter should be scaled to the hypercube. Leave * unset for categorical parameters. Some kind of scaling is strongly * recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`). */ scaleType?: string; /** * Required. The type of the parameter. */ type?: string; } /** * Represents input parameters for a prediction job. */ interface Schema$GoogleCloudMlV1__PredictionInput { /** * Optional. The type and number of accelerators to be attached to each * machine running the job. */ accelerator?: Schema$GoogleCloudMlV1__AcceleratorConfig; /** * Optional. Number of records per batch, defaults to 64. The service will * buffer batch_size number of records in memory before invoking one * Tensorflow prediction call internally. So take the record size and memory * available into consideration when setting this parameter. */ batchSize?: string; /** * Required. The format of the input data files. */ dataFormat?: string; /** * Required. The Google Cloud Storage location of the input data files. May * contain wildcards. */ inputPaths?: string[]; /** * Optional. The maximum number of workers to be used for parallel * processing. Defaults to 10 if not specified. */ maxWorkerCount?: string; /** * Use this field if you want to use the default version for the specified * model. The string must use the following format: * `"projects/YOUR_PROJECT/models/YOUR_MODEL"` */ modelName?: string; /** * Optional. Format of the output data files, defaults to JSON. */ outputDataFormat?: string; /** * Required. The output Google Cloud Storage location. */ outputPath?: string; /** * Required. The Google Compute Engine region to run the prediction job in. * See the <a * href="/ml-engine/docs/tensorflow/regions">available * regions</a> for ML Engine services. */ region?: string; /** * Optional. The Cloud ML Engine runtime version to use for this batch * prediction. If not set, Cloud ML Engine will pick the runtime version * used during the CreateVersion request for this model version, or choose * the latest stable version when model version information is not available * such as when the model is specified by uri. */ runtimeVersion?: string; /** * Optional. The name of the signature defined in the SavedModel to use for * this job. Please refer to * [SavedModel](https://tensorflow.github.io/serving/serving_basic.html) for * information about how to use signatures. Defaults to * [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants) * , which is "serving_default". */ signatureName?: string; /** * Use this field if you want to specify a Google Cloud Storage path for the * model to use. */ uri?: string; /** * Use this field if you want to specify a version of the model to use. The * string is formatted the same way as `model_version`, with the addition of * the version information: * `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"` */ versionName?: string; } /** * Represents results of a prediction job. */ interface Schema$GoogleCloudMlV1__PredictionOutput { /** * The number of data instances which resulted in errors. */ errorCount?: string; /** * Node hours used by the batch prediction job. */ nodeHours?: number; /** * The output Google Cloud Storage location provided at the job creation * time. */ outputPath?: string; /** * The number of generated predictions. */ predictionCount?: string; } /** * Request for predictions to be issued against a trained model. */ interface Schema$GoogleCloudMlV1__PredictRequest { /** * Required. The prediction request body. */ httpBody?: Schema$GoogleApi__HttpBody; } /** * Represents the configration for a replica in a cluster. */ interface Schema$GoogleCloudMlV1__ReplicaConfig { acceleratorConfig?: Schema$GoogleCloudMlV1__AcceleratorConfig; /** * The docker image to run on worker. This image must be in Google Container * Registry. */ imageUri?: string; } /** * Request message for the SetDefaultVersion request. */ interface Schema$GoogleCloudMlV1__SetDefaultVersionRequest { } /** * Represents input parameters for a training job. When using the gcloud * command to submit your training job, you can specify the input parameters * as command-line arguments and/or in a YAML configuration file referenced * from the --config command-line argument. For details, see the guide to * <a * href="/ml-engine/docs/tensorflow/training-jobs">submitting a * training job</a>. */ interface Schema$GoogleCloudMlV1__TrainingInput { /** * Optional. Command line arguments to pass to the program. */ args?: string[]; /** * Optional. The set of Hyperparameters to tune. */ hyperparameters?: Schema$GoogleCloudMlV1__HyperparameterSpec; /** * Optional. A Google Cloud Storage path in which to store training outputs * and other data needed for training. This path is passed to your * TensorFlow program as the '--job-dir' command-line argument. The * benefit of specifying this field is that Cloud ML validates the path for * use in training. */ jobDir?: string; /** * Optional. The configuration for master. Only one of * `masterConfig.imageUri` and `runtimeVersion` should be set. */ masterConfig?: Schema$GoogleCloudMlV1__ReplicaConfig; /** * Optional. Specifies the type of virtual machine to use for your training * job's master worker. The following types are supported: <dl> * <dt>standard</dt> <dd> A basic machine * configuration suitable for training simple models with small to * moderate datasets. </dd> <dt>large_model</dt> * <dd> A machine with a lot of memory, specially suited for * parameter servers when your model is large (having many hidden layers * or layers with very large numbers of nodes). </dd> * <dt>complex_model_s</dt> <dd> A machine suitable * for the master and workers of the cluster when your model requires more * computation than the standard machine can handle satisfactorily. * </dd> <dt>complex_model_m</dt> <dd> A * machine with roughly twice the number of cores and roughly double the * memory of <i>complex_model_s</i>. </dd> * <dt>complex_model_l</dt> <dd> A machine with * roughly twice the number of cores and roughly double the memory of * <i>complex_model_m</i>. </dd> * <dt>standard_gpu</dt> <dd> A machine equivalent to * <i>standard</i> that also includes a single NVIDIA Tesla * K80 GPU. See more about <a * href="/ml-engine/docs/tensorflow/using-gpus">using GPUs to * train your model</a>. </dd> * <dt>complex_model_m_gpu</dt> <dd> A machine * equivalent to <i>complex_model_m</i> that also includes four * NVIDIA Tesla K80 GPUs. </dd> * <dt>complex_model_l_gpu</dt> <dd> A machine * equivalent to <i>complex_model_l</i> that also includes eight * NVIDIA Tesla K80 GPUs. </dd> <dt>standard_p100</dt> * <dd> A machine equivalent to <i>standard</i> that * also includes a single NVIDIA Tesla P100 GPU. </dd> * <dt>complex_model_m_p100</dt> <dd> A machine * equivalent to <i>complex_model_m</i> that also includes four * NVIDIA Tesla P100 GPUs. </dd> <dt>standard_v100</dt> * <dd> A machine equivalent to <i>standard</i> that * also includes a single NVIDIA Tesla V100 GPU. </dd> * <dt>large_model_v100</dt> <dd> A machine equivalent * to <i>large_model</i> that also includes a single NVIDIA * Tesla V100 GPU. </dd> <dt>complex_model_m_v100</dt> * <dd> A machine equivalent to <i>complex_model_m</i> * that also includes four NVIDIA Tesla V100 GPUs. </dd> * <dt>complex_model_l_v100</dt> <dd> A machine * equivalent to <i>complex_model_l</i> that also includes * eight NVIDIA Tesla V100 GPUs. </dd> * <dt>cloud_tpu</dt> <dd> A TPU VM including one * Cloud TPU. See more about <a * href="/ml-engine/docs/tensorflow/using-tpus">using TPUs to * train your model</a>. </dd> </dl> You must set * this value when `scaleTier` is set to `CUSTOM`. */ masterType?: string; /** * Required. The Google Cloud Storage location of the packages with the * training program and any additional dependencies. The maximum number of * package URIs is 100. */ packageUris?: string[]; /** * Optional. The config of parameter servers. If * `parameterServerConfig.imageUri` has not been set, the value of * `masterConfig.imageUri` will be used. */ parameterServerConfig?: Schema$GoogleCloudMlV1__ReplicaConfig; /** * Optional. The number of parameter server replicas to use for the training * job. Each replica in the cluster will be of the type specified in * `parameter_server_type`. This value can only be used when `scale_tier` * is set to `CUSTOM`.If you set this value, you must also set * `parameter_server_type`. The default value is zero. */ parameterServerCount?: string; /** * Optional. Specifies the type of virtual machine to use for your training * job's parameter server. The supported values are the same as those * described in the entry for `master_type`. This value must be present * when `scaleTier` is set to `CUSTOM` and `parameter_server_count` is * greater than zero. */ parameterServerType?: string; /** * Required. The Python module name to run after installing the packages. */ pythonModule?: string; /** * Optional. The version of Python used in training. If not set, the default * version is '2.7'. Python '3.5' is available when * `runtime_version` is set to '1.4' and above. Python '2.7' * works with all supported <a * href="/ml-engine/docs/runtime-version-list">runtime * versions</a>. */ pythonVersion?: string; /** * Required. The Google Compute Engine region to run the training job in. * See the <a * href="/ml-engine/docs/tensorflow/regions">available * regions</a> for ML Engine services. */ region?: string; /** * Optional. The Cloud ML Engine runtime version to use for training. If not * set, Cloud ML Engine uses the default stable version, 1.0. For more * information, see the <a * href="/ml-engine/docs/runtime-version-list">runtime version * list</a> and <a * href="/ml-engine/docs/versioning">how to manage runtime * versions</a>. */ runtimeVersion?: string; /** * Required. Specifies the machine types, the number of replicas for workers * and parameter servers. */ scaleTier?: string; /** * Optional. The configrations for workers. If `workerConfig.imageUri` has * not been set, the value of `masterConfig.imageUri` will be used. */ workerConfig?: Schema$GoogleCloudMlV1__ReplicaConfig; /** * Optional. The number of worker replicas to use for the training job. Each * replica in the cluster will be of the type specified in `worker_type`. * This value can only be used when `scale_tier` is set to `CUSTOM`. If you * set this value, you must also set `worker_type`. The default value is * zero. */ workerCount?: string; /** * Optional. Specifies the type of virtual machine to use for your training * job's worker nodes. The supported values are the same as those * described in the entry for `masterType`. This value must be present when * `scaleTier` is set to `CUSTOM` and `workerCount` is greater than zero. */ workerType?: string; } /** * Represents results of a training job. Output only. */ interface Schema$GoogleCloudMlV1__TrainingOutput { /** * The number of hyperparameter tuning trials that completed successfully. * Only set for hyperparameter tuning jobs. */ completedTrialCount?: string; /** * The amount of ML units consumed by the job. */ consumedMLUnits?: number; /** * Whether this job is a hyperparameter tuning job. */ isHyperparameterTuningJob?: boolean; /** * Results for individual Hyperparameter trials. Only set for hyperparameter * tuning jobs. */ trials?: Schema$GoogleCloudMlV1__HyperparameterOutput[]; } /** * Represents a version of the model. Each version is a trained model * deployed in the cloud, ready to handle prediction requests. A model can * have multiple versions. You can get information about all of the versions * of a given model by calling * [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list). */ interface Schema$GoogleCloudMlV1__Version { /** * Automatically scale the number of nodes used to serve the model in * response to increases and decreases in traffic. Care should be taken to * ramp up traffic according to the model's ability to scale or you will * start seeing increases in latency and 429 response codes. */ autoScaling?: Schema$GoogleCloudMlV1__AutoScaling; /** * Output only. The time the version was created. */ createTime?: string; /** * Required. The Google Cloud Storage location of the trained model used to * create the version. See the [guide to model * deployment](/ml-engine/docs/tensorflow/deploying-models) for more * information. When passing Version to * [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create) * the model service uses the specified location as the source of the model. * Once deployed, the model version is hosted by the prediction service, so * this location is useful only as a historical record. The total number of * model files can't exceed 1000. */ deploymentUri?: string; /** * Optional. The description specified for the version when it was created. */ description?: string; /** * Output only. The details of a failure or a cancellation. */ errorMessage?: string; /** * `etag` is used for optimistic concurrency control as a way to help * prevent simultaneous updates of a model from overwriting each other. It * is strongly suggested that systems make use of the `etag` in the * read-modify-write cycle to perform model updates in order to avoid race * conditions: An `etag` is returned in the response to `GetVersion`, and * systems are expected to put that etag in the request to `UpdateVersion` * to ensure that their change will be applied to the model as intended. */ etag?: string; /** * Optional. The machine learning framework Cloud ML Engine uses to train * this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, * `XGBOOST`. If you do not specify a framework, Cloud ML Engine will * analyze files in the deployment_uri to determine a framework. If you * choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version * of the model to 1.4 or greater. */ framework?: string; /** * Output only. If true, this version will be used to handle prediction * requests that do not specify a version. You can change the default * version by calling * [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault). */ isDefault?: boolean; /** * Optional. One or more labels that you can add, to organize your model * versions. Each label is a key-value pair, where both the key and the * value are arbitrary strings that you supply. For more information, see * the documentation on <a * href="/ml-engine/docs/tensorflow/resource-labels">using * labels</a>. */ labels?: { [key: string]: string; }; /** * Output only. The time the version was last used for prediction. */ lastUseTime?: string; /** * Optional. The type of machine on which to serve the model. Currently only * applies to online prediction service. The following are currently * supported and will be deprecated in Beta release. mls1-highmem-1 1 * core 2 Gb RAM mls1-highcpu-4 4 core 2 Gb RAM The following are * available in Beta: mls1-c1-m2 1 core 2 Gb RAM Default * mls1-c4-m2 4 core 2 Gb RAM */ machineType?: string; /** * Manually select the number of nodes to use for serving the model. You * should generally use `auto_scaling` with an appropriate `min_nodes` * instead, but this option is available if you want more predictable * billing. Beware that latency and error rates will increase if the traffic * exceeds that capability of the system to serve it based on the selected * number of nodes. */ manualScaling?: Schema$GoogleCloudMlV1__ManualScaling; /** * Required.The name specified for the version when it was created. The * version name must be unique within the model it is created in. */ name?: string; /** * Optional. The version of Python used in prediction. If not set, the * default version is '2.7'. Python '3.5' is available when * `runtime_version` is set to '1.4' and above. Python '2.7' * works with all supported runtime versions. */ pythonVersion?: string; /** * Optional. The Cloud ML Engine runtime version to use for this deployment. * If not set, Cloud ML Engine uses the default stable version, 1.0. For * more information, see the [runtime version * list](/ml-engine/docs/runtime-version-list) and [how to manage runtime * versions](/ml-engine/docs/versioning). */ runtimeVersion?: string; /** * Output only. The state of a version. */ state?: string; } /** * Specifies the audit configuration for a service. The configuration * determines which permission types are logged, and what identities, if any, * are exempted from logging. An AuditConfig must have one or more * AuditLogConfigs. If there are AuditConfigs for both `allServices` and a * specific service, the union of the two AuditConfigs is used for that * service: the log_types specified in each AuditConfig are enabled, and the * exempted_members in each AuditLogConfig are exempted. Example Policy with * multiple AuditConfigs: { "audit_configs": [ { * "service": "allServices" "audit_log_configs": * [ { "log_type": "DATA_READ", * "exempted_members": [ "user:foo@gmail.com" ] }, { * "log_type": "DATA_WRITE", }, { * "log_type": "ADMIN_READ", } ] }, * { "service": "fooservice.googleapis.com" * "audit_log_configs": [ { "log_type": * "DATA_READ", }, { "log_type": * "DATA_WRITE", "exempted_members": [ * "user:bar@gmail.com" ] } ] } * ] } For fooservice, this policy enables DATA_READ, DATA_WRITE and * ADMIN_READ logging. It also exempts foo@gmail.com from DATA_READ logging, * and bar@gmail.com from DATA_WRITE logging. */ interface Schema$GoogleIamV1__AuditConfig { /** * The configuration for logging of each type of permission. */ auditLogConfigs?: Schema$GoogleIamV1__AuditLogConfig[]; /** * Specifies a service that will be enabled for audit logging. For example, * `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a * special value that covers all services. */ service?: string; } /** * Provides the configuration for logging a type of permissions. Example: { * "audit_log_configs": [ { "log_type": * "DATA_READ", "exempted_members": [ * "user:foo@gmail.com" ] }, { * "log_type": "DATA_WRITE", } ] } This * enables 'DATA_READ' and 'DATA_WRITE' logging, while * exempting foo@gmail.com from DATA_READ logging. */ interface Schema$GoogleIamV1__AuditLogConfig { /** * Specifies the identities that do not cause logging for this type of * permission. Follows the same format of Binding.members. */ exemptedMembers?: string[]; /** * The log type that this config enables. */ logType?: string; } /** * Associates `members` with a `role`. */ interface Schema$GoogleIamV1__Binding { /** * Unimplemented. The condition that is associated with this binding. NOTE: * an unsatisfied condition will not allow user access via current binding. * Different bindings, including their conditions, are examined * independently. */ condition?: Schema$GoogleType__Expr; /** * Specifies the identities requesting access for a Cloud Platform resource. * `members` can have the following values: * `allUsers`: A special * identifier that represents anyone who is on the internet; with or * without a Google account. * `allAuthenticatedUsers`: A special * identifier that represents anyone who is authenticated with a Google * account or a service account. * `user:{emailid}`: An email address that * represents a specific Google account. For example, `alice@gmail.com` . * * `serviceAccount:{emailid}`: An email address that represents a service * account. For example, `my-other-app@appspot.gserviceaccount.com`. * * `group:{emailid}`: An email address that represents a Google group. For * example, `admins@example.com`. * `domain:{domain}`: A Google Apps * domain name that represents all the users of that domain. For example, * `google.com` or `example.com`. */ members?: string[]; /** * Role that is assigned to `members`. For example, `roles/viewer`, * `roles/editor`, or `roles/owner`. */ role?: string; } /** * Defines an Identity and Access Management (IAM) policy. It is used to * specify access control policies for Cloud Platform resources. A `Policy` * consists of a list of `bindings`. A `binding` binds a list of `members` to * a `role`, where the members can be user accounts, Google groups, Google * domains, and service accounts. A `role` is a named list of permissions * defined by IAM. **JSON Example** { "bindings": [ { * "role": "roles/owner", "members": [ * "user:mike@example.com", "group:admins@example.com", * "domain:google.com", * "serviceAccount:my-other-app@appspot.gserviceaccount.com" ] }, { * "role": "roles/viewer", "members": * ["user:sean@example.com"] } ] } **YAML * Example** bindings: - members: - user:mike@example.com - * group:admins@example.com - domain:google.com - * serviceAccount:my-other-app@appspot.gserviceaccount.com role: * roles/owner - members: - user:sean@example.com role: * roles/viewer For a description of IAM and its features, see the [IAM * developer's guide](https://cloud.google.com/iam/docs). */ interface Schema$GoogleIamV1__Policy { /** * Specifies cloud audit logging configuration for this policy. */ auditConfigs?: Schema$GoogleIamV1__AuditConfig[]; /** * Associates a list of `members` to a `role`. `bindings` with no members * will result in an error. */ bindings?: Schema$GoogleIamV1__Binding[]; /** * `etag` is used for optimistic concurrency control as a way to help * prevent simultaneous updates of a policy from overwriting each other. It * is strongly suggested that systems make use of the `etag` in the * read-modify-write cycle to perform policy updates in order to avoid race * conditions: An `etag` is returned in the response to `getIamPolicy`, and * systems are expected to put that etag in the request to `setIamPolicy` to * ensure that their change will be applied to the same version of the * policy. If no `etag` is provided in the call to `setIamPolicy`, then the * existing policy is overwritten blindly. */ etag?: string; /** * Deprecated. */ version?: number; } /** * Request message for `SetIamPolicy` method. */ interface Schema$GoogleIamV1__SetIamPolicyRequest { /** * REQUIRED: The complete policy to be applied to the `resource`. The size * of the policy is limited to a few 10s of KB. An empty policy is a valid * policy but certain Cloud Platform services (such as Projects) might * reject them. */ policy?: Schema$GoogleIamV1__Policy; /** * OPTIONAL: A FieldMask specifying which fields of the policy to modify. * Only the fields in the mask will be modified. If no mask is provided, the * following default mask is used: paths: "bindings, etag" This * field is only used by Cloud IAM. */ updateMask?: string; } /** * Request message for `TestIamPermissions` method. */ interface Schema$GoogleIamV1__TestIamPermissionsRequest { /** * The set of permissions to check for the `resource`. Permissions with * wildcards (such as '*' or 'storage.*') are not allowed. * For more information see [IAM * Overview](https://cloud.google.com/iam/docs/overview#permissions). */ permissions?: string[]; } /** * Response message for `TestIamPermissions` method. */ interface Schema$GoogleIamV1__TestIamPermissionsResponse { /** * A subset of `TestPermissionsRequest.permissions` that the caller is * allowed. */ permissions?: string[]; } /** * The response message for Operations.ListOperations. */ interface Schema$GoogleLongrunning__ListOperationsResponse { /** * The standard List next-page token. */ nextPageToken?: string; /** * A list of operations that matches the specified filter in the request. */ operations?: Schema$GoogleLongrunning__Operation[]; } /** * This resource represents a long-running operation that is the result of a * network API call. */ interface Schema$GoogleLongrunning__Operation { /** * If the value is `false`, it means the operation is still in progress. If * `true`, the operation is completed, and either `error` or `response` is * available. */ done?: boolean; /** * The error result of the operation in case of failure or cancellation. */ error?: Schema$GoogleRpc__Status; /** * Service-specific metadata associated with the operation. It typically * contains progress information and common metadata such as create time. * Some services might not provide such metadata. Any method that returns a * long-running operation should document the metadata type, if any. */ metadata?: { [key: string]: any; }; /** * The server-assigned name, which is only unique within the same service * that originally returns it. If you use the default HTTP mapping, the * `name` should have the format of `operations/some/unique/name`. */ name?: string; /** * The normal response of the operation in case of success. If the original * method returns no data on success, such as `Delete`, the response is * `google.protobuf.Empty`. If the original method is standard * `Get`/`Create`/`Update`, the response should be the resource. For other * methods, the response should have the type `XxxResponse`, where `Xxx` is * the original method name. For example, if the original method name is * `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`. */ response?: { [key: string]: any; }; } /** * A generic empty message that you can re-use to avoid defining duplicated * empty messages in your APIs. A typical example is to use it as the request * or the response type of an API method. For instance: service Foo { rpc * Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON * representation for `Empty` is empty JSON object `{}`. */ interface Schema$GoogleProtobuf__Empty { } /** * The `Status` type defines a logical error model that is suitable for * different programming environments, including REST APIs and RPC APIs. It is * used by [gRPC](https://github.com/grpc). The error model is designed to be: * - Simple to use and understand for most users - Flexible enough to meet * unexpected needs # Overview The `Status` message contains three pieces of * data: error code, error message, and error details. The error code should * be an enum value of google.rpc.Code, but it may accept additional error * codes if needed. The error message should be a developer-facing English * message that helps developers *understand* and *resolve* the error. If a * localized user-facing error message is needed, put the localized message in * the error details or localize it in the client. The optional error details * may contain arbitrary information about the error. There is a predefined * set of error detail types in the package `google.rpc` that can be used for * common error conditions. # Language mapping The `Status` message is the * logical representation of the error model, but it is not necessarily the * actual wire format. When the `Status` message is exposed in different * client libraries and different wire protocols, it can be mapped * differently. For example, it will likely be mapped to some exceptions in * Java, but more likely mapped to some error codes in C. # Other uses The * error model and the `Status` message can be used in a variety of * environments, either with or without APIs, to provide a consistent * developer experience across different environments. Example uses of this * error model include: - Partial errors. If a service needs to return * partial errors to the client, it may embed the `Status` in the normal * response to indicate the partial errors. - Workflow errors. A typical * workflow has multiple steps. Each step may have a `Status` message for * error reporting. - Batch operations. If a client uses batch request and * batch response, the `Status` message should be used directly inside * batch response, one for each error sub-response. - Asynchronous * operations. If an API call embeds asynchronous operation results in its * response, the status of those operations should be represented directly * using the `Status` message. - Logging. If some API errors are stored in * logs, the message `Status` could be used directly after any stripping * needed for security/privacy reasons. */ interface Schema$GoogleRpc__Status { /** * The status code, which should be an enum value of google.rpc.Code. */ code?: number; /** * A list of messages that carry the error details. There is a common set * of message types for APIs to use. */ details?: Array<{ [key: string]: any; }>; /** * A developer-facing error message, which should be in English. Any * user-facing error message should be localized and sent in the * google.rpc.Status.details field, or localized by the client. */ message?: string; } /** * Represents an expression text. Example: title: "User account * presence" description: "Determines whether the request has a * user account" expression: "size(request.user) > 0" */ interface Schema$GoogleType__Expr { /** * An optional description of the expression. This is a longer text which * describes the expression, e.g. when hovered over it in a UI. */ description?: string; /** * Textual representation of an expression in Common Expression Language * syntax. The application context of the containing message determines * which well-known feature set of CEL is supported. */ expression?: string; /** * An optional string indicating the location of the expression for error * reporting, e.g. a file name and a position in the file. */ location?: string; /** * An optional title for the expression, i.e. a short string describing its * purpose. This can be used e.g. in UIs which allow to enter the * expression. */ title?: string; } class Resource$Operations { constructor(); /** * ml.operations.delete * @desc Deletes a long-running operation. This method indicates that the * client is no longer interested in the operation result. It does not * cancel the operation. If the server doesn't support this method, it * returns `google.rpc.Code.UNIMPLEMENTED`. * @alias ml.operations.delete * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name The name of the operation resource to be deleted. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ delete(params?: Params$Resource$Operations$Delete, options?: MethodOptions): GaxiosPromise; delete(params: Params$Resource$Operations$Delete, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; delete(params: Params$Resource$Operations$Delete, callback: BodyResponseCallback): void; delete(callback: BodyResponseCallback): void; } interface Params$Resource$Operations$Delete extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * The name of the operation resource to be deleted. */ name?: string; } class Resource$Projects { jobs: Resource$Projects$Jobs; locations: Resource$Projects$Locations; models: Resource$Projects$Models; operations: Resource$Projects$Operations; constructor(); /** * ml.projects.getConfig * @desc Get the service account information associated with your project. * You need this information in order to grant the service account * permissions for the Google Cloud Storage location where you put your * model training code for training the model with Google Cloud Machine * Learning. * @alias ml.projects.getConfig * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The project name. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ getConfig(params?: Params$Resource$Projects$Getconfig, options?: MethodOptions): GaxiosPromise; getConfig(params: Params$Resource$Projects$Getconfig, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; getConfig(params: Params$Resource$Projects$Getconfig, callback: BodyResponseCallback): void; getConfig(callback: BodyResponseCallback): void; /** * ml.projects.predict * @desc Performs prediction on the data in the request. Cloud ML Engine * implements a custom `predict` verb on top of an HTTP POST method.

For * details of the request and response format, see the **guide to the * [predict request format](/ml-engine/docs/v1/predict-request)**. * @alias ml.projects.predict * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The resource name of a model or a version. Authorization: requires the `predict` permission on the specified resource. * @param {().GoogleCloudMlV1__PredictRequest} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ predict(params?: Params$Resource$Projects$Predict, options?: MethodOptions): GaxiosPromise; predict(params: Params$Resource$Projects$Predict, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; predict(params: Params$Resource$Projects$Predict, callback: BodyResponseCallback): void; predict(callback: BodyResponseCallback): void; } interface Params$Resource$Projects$Getconfig extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The project name. */ name?: string; } interface Params$Resource$Projects$Predict extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The resource name of a model or a version. Authorization: * requires the `predict` permission on the specified resource. */ name?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__PredictRequest; } class Resource$Projects$Jobs { constructor(); /** * ml.projects.jobs.cancel * @desc Cancels a running job. * @alias ml.projects.jobs.cancel * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the job to cancel. * @param {().GoogleCloudMlV1__CancelJobRequest} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ cancel(params?: Params$Resource$Projects$Jobs$Cancel, options?: MethodOptions): GaxiosPromise; cancel(params: Params$Resource$Projects$Jobs$Cancel, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; cancel(params: Params$Resource$Projects$Jobs$Cancel, callback: BodyResponseCallback): void; cancel(callback: BodyResponseCallback): void; /** * ml.projects.jobs.create * @desc Creates a training or a batch prediction job. * @alias ml.projects.jobs.create * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.parent Required. The project name. * @param {().GoogleCloudMlV1__Job} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ create(params?: Params$Resource$Projects$Jobs$Create, options?: MethodOptions): GaxiosPromise; create(params: Params$Resource$Projects$Jobs$Create, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; create(params: Params$Resource$Projects$Jobs$Create, callback: BodyResponseCallback): void; create(callback: BodyResponseCallback): void; /** * ml.projects.jobs.get * @desc Describes a job. * @alias ml.projects.jobs.get * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the job to get the description of. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ get(params?: Params$Resource$Projects$Jobs$Get, options?: MethodOptions): GaxiosPromise; get(params: Params$Resource$Projects$Jobs$Get, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; get(params: Params$Resource$Projects$Jobs$Get, callback: BodyResponseCallback): void; get(callback: BodyResponseCallback): void; /** * ml.projects.jobs.getIamPolicy * @desc Gets the access control policy for a resource. Returns an empty * policy if the resource exists and does not have a policy set. * @alias ml.projects.jobs.getIamPolicy * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.resource_ REQUIRED: The resource for which the policy is being requested. See the operation documentation for the appropriate value for this field. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ getIamPolicy(params?: Params$Resource$Projects$Jobs$Getiampolicy, options?: MethodOptions): GaxiosPromise; getIamPolicy(params: Params$Resource$Projects$Jobs$Getiampolicy, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; getIamPolicy(params: Params$Resource$Projects$Jobs$Getiampolicy, callback: BodyResponseCallback): void; getIamPolicy(callback: BodyResponseCallback): void; /** * ml.projects.jobs.list * @desc Lists the jobs in the project. If there are no jobs that match the * request parameters, the list request returns an empty response body: {}. * @alias ml.projects.jobs.list * @memberOf! () * * @param {object} params Parameters for request * @param {string=} params.filter Optional. Specifies the subset of jobs to retrieve. You can filter on the value of one or more attributes of the job object. For example, retrieve jobs with a job identifier that starts with 'census':

gcloud ml-engine jobs list --filter='jobId:census*'

List all failed jobs with names that start with 'rnn':

gcloud ml-engine jobs list --filter='jobId:rnn* AND state:FAILED'

For more examples, see the guide to monitoring jobs. * @param {integer=} params.pageSize Optional. The number of jobs to retrieve per "page" of results. If there are more remaining results than this number, the response message will contain a valid value in the `next_page_token` field. The default value is 20, and the maximum page size is 100. * @param {string=} params.pageToken Optional. A page token to request the next page of results. You get the token from the `next_page_token` field of the response from the previous call. * @param {string} params.parent Required. The name of the project for which to list jobs. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ list(params?: Params$Resource$Projects$Jobs$List, options?: MethodOptions): GaxiosPromise; list(params: Params$Resource$Projects$Jobs$List, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; list(params: Params$Resource$Projects$Jobs$List, callback: BodyResponseCallback): void; list(callback: BodyResponseCallback): void; /** * ml.projects.jobs.patch * @desc Updates a specific job resource. Currently the only supported * fields to update are `labels`. * @alias ml.projects.jobs.patch * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The job name. * @param {string=} params.updateMask Required. Specifies the path, relative to `Job`, of the field to update. To adopt etag mechanism, include `etag` field in the mask, and include the `etag` value in your job resource. For example, to change the labels of a job, the `update_mask` parameter would be specified as `labels`, `etag`, and the `PATCH` request body would specify the new value, as follows: { "labels": { "owner": "Google", "color": "Blue" } "etag": "33a64df551425fcc55e4d42a148795d9f25f89d4" } If `etag` matches the one on the server, the labels of the job will be replaced with the given ones, and the server end `etag` will be recalculated. Currently the only supported update masks are `labels` and `etag`. * @param {().GoogleCloudMlV1__Job} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ patch(params?: Params$Resource$Projects$Jobs$Patch, options?: MethodOptions): GaxiosPromise; patch(params: Params$Resource$Projects$Jobs$Patch, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; patch(params: Params$Resource$Projects$Jobs$Patch, callback: BodyResponseCallback): void; patch(callback: BodyResponseCallback): void; /** * ml.projects.jobs.setIamPolicy * @desc Sets the access control policy on the specified resource. Replaces * any existing policy. * @alias ml.projects.jobs.setIamPolicy * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.resource_ REQUIRED: The resource for which the policy is being specified. See the operation documentation for the appropriate value for this field. * @param {().GoogleIamV1__SetIamPolicyRequest} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ setIamPolicy(params?: Params$Resource$Projects$Jobs$Setiampolicy, options?: MethodOptions): GaxiosPromise; setIamPolicy(params: Params$Resource$Projects$Jobs$Setiampolicy, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; setIamPolicy(params: Params$Resource$Projects$Jobs$Setiampolicy, callback: BodyResponseCallback): void; setIamPolicy(callback: BodyResponseCallback): void; /** * ml.projects.jobs.testIamPermissions * @desc Returns permissions that a caller has on the specified resource. If * the resource does not exist, this will return an empty set of * permissions, not a NOT_FOUND error. Note: This operation is designed to * be used for building permission-aware UIs and command-line tools, not for * authorization checking. This operation may "fail open" without warning. * @alias ml.projects.jobs.testIamPermissions * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.resource_ REQUIRED: The resource for which the policy detail is being requested. See the operation documentation for the appropriate value for this field. * @param {().GoogleIamV1__TestIamPermissionsRequest} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ testIamPermissions(params?: Params$Resource$Projects$Jobs$Testiampermissions, options?: MethodOptions): GaxiosPromise; testIamPermissions(params: Params$Resource$Projects$Jobs$Testiampermissions, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; testIamPermissions(params: Params$Resource$Projects$Jobs$Testiampermissions, callback: BodyResponseCallback): void; testIamPermissions(callback: BodyResponseCallback): void; } interface Params$Resource$Projects$Jobs$Cancel extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the job to cancel. */ name?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__CancelJobRequest; } interface Params$Resource$Projects$Jobs$Create extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The project name. */ parent?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__Job; } interface Params$Resource$Projects$Jobs$Get extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the job to get the description of. */ name?: string; } interface Params$Resource$Projects$Jobs$Getiampolicy extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * REQUIRED: The resource for which the policy is being requested. See the * operation documentation for the appropriate value for this field. */ resource?: string; } interface Params$Resource$Projects$Jobs$List extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Optional. Specifies the subset of jobs to retrieve. You can filter on the * value of one or more attributes of the job object. For example, retrieve * jobs with a job identifier that starts with 'census':

gcloud * ml-engine jobs list --filter='jobId:census*'

List all failed * jobs with names that start with 'rnn':

gcloud ml-engine jobs * list --filter='jobId:rnn* AND state:FAILED'

For more examples, * see the guide to monitoring jobs. */ filter?: string; /** * Optional. The number of jobs to retrieve per "page" of results. If there * are more remaining results than this number, the response message will * contain a valid value in the `next_page_token` field. The default value * is 20, and the maximum page size is 100. */ pageSize?: number; /** * Optional. A page token to request the next page of results. You get the * token from the `next_page_token` field of the response from the previous * call. */ pageToken?: string; /** * Required. The name of the project for which to list jobs. */ parent?: string; } interface Params$Resource$Projects$Jobs$Patch extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The job name. */ name?: string; /** * Required. Specifies the path, relative to `Job`, of the field to update. * To adopt etag mechanism, include `etag` field in the mask, and include * the `etag` value in your job resource. For example, to change the labels * of a job, the `update_mask` parameter would be specified as `labels`, * `etag`, and the `PATCH` request body would specify the new value, as * follows: { "labels": { "owner": "Google", "color": * "Blue" } "etag": "33a64df551425fcc55e4d42a148795d9f25f89d4" * } If `etag` matches the one on the server, the labels of the job will be * replaced with the given ones, and the server end `etag` will be * recalculated. Currently the only supported update masks are `labels` and * `etag`. */ updateMask?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__Job; } interface Params$Resource$Projects$Jobs$Setiampolicy extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * REQUIRED: The resource for which the policy is being specified. See the * operation documentation for the appropriate value for this field. */ resource?: string; /** * Request body metadata */ requestBody?: Schema$GoogleIamV1__SetIamPolicyRequest; } interface Params$Resource$Projects$Jobs$Testiampermissions extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * REQUIRED: The resource for which the policy detail is being requested. * See the operation documentation for the appropriate value for this field. */ resource?: string; /** * Request body metadata */ requestBody?: Schema$GoogleIamV1__TestIamPermissionsRequest; } class Resource$Projects$Locations { constructor(); /** * ml.projects.locations.get * @desc Get the complete list of CMLE capabilities in a location, along * with their location-specific properties. * @alias ml.projects.locations.get * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the location. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ get(params?: Params$Resource$Projects$Locations$Get, options?: MethodOptions): GaxiosPromise; get(params: Params$Resource$Projects$Locations$Get, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; get(params: Params$Resource$Projects$Locations$Get, callback: BodyResponseCallback): void; get(callback: BodyResponseCallback): void; /** * ml.projects.locations.list * @desc List all locations that provides at least one type of CMLE * capability. * @alias ml.projects.locations.list * @memberOf! () * * @param {object} params Parameters for request * @param {integer=} params.pageSize Optional. The number of locations to retrieve per "page" of results. If there are more remaining results than this number, the response message will contain a valid value in the `next_page_token` field. The default value is 20, and the maximum page size is 100. * @param {string=} params.pageToken Optional. A page token to request the next page of results. You get the token from the `next_page_token` field of the response from the previous call. * @param {string} params.parent Required. The name of the project for which available locations are to be listed (since some locations might be whitelisted for specific projects). * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ list(params?: Params$Resource$Projects$Locations$List, options?: MethodOptions): GaxiosPromise; list(params: Params$Resource$Projects$Locations$List, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; list(params: Params$Resource$Projects$Locations$List, callback: BodyResponseCallback): void; list(callback: BodyResponseCallback): void; } interface Params$Resource$Projects$Locations$Get extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the location. */ name?: string; } interface Params$Resource$Projects$Locations$List extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Optional. The number of locations to retrieve per "page" of results. If * there are more remaining results than this number, the response message * will contain a valid value in the `next_page_token` field. The default * value is 20, and the maximum page size is 100. */ pageSize?: number; /** * Optional. A page token to request the next page of results. You get the * token from the `next_page_token` field of the response from the previous * call. */ pageToken?: string; /** * Required. The name of the project for which available locations are to be * listed (since some locations might be whitelisted for specific projects). */ parent?: string; } class Resource$Projects$Models { versions: Resource$Projects$Models$Versions; constructor(); /** * ml.projects.models.create * @desc Creates a model which will later contain one or more versions. You * must add at least one version before you can request predictions from the * model. Add versions by calling * [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create). * @alias ml.projects.models.create * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.parent Required. The project name. * @param {().GoogleCloudMlV1__Model} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ create(params?: Params$Resource$Projects$Models$Create, options?: MethodOptions): GaxiosPromise; create(params: Params$Resource$Projects$Models$Create, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; create(params: Params$Resource$Projects$Models$Create, callback: BodyResponseCallback): void; create(callback: BodyResponseCallback): void; /** * ml.projects.models.delete * @desc Deletes a model. You can only delete a model if there are no * versions in it. You can delete versions by calling * [projects.models.versions.delete](/ml-engine/reference/rest/v1/projects.models.versions/delete). * @alias ml.projects.models.delete * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the model. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ delete(params?: Params$Resource$Projects$Models$Delete, options?: MethodOptions): GaxiosPromise; delete(params: Params$Resource$Projects$Models$Delete, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; delete(params: Params$Resource$Projects$Models$Delete, callback: BodyResponseCallback): void; delete(callback: BodyResponseCallback): void; /** * ml.projects.models.get * @desc Gets information about a model, including its name, the description * (if set), and the default version (if at least one version of the model * has been deployed). * @alias ml.projects.models.get * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the model. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ get(params?: Params$Resource$Projects$Models$Get, options?: MethodOptions): GaxiosPromise; get(params: Params$Resource$Projects$Models$Get, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; get(params: Params$Resource$Projects$Models$Get, callback: BodyResponseCallback): void; get(callback: BodyResponseCallback): void; /** * ml.projects.models.getIamPolicy * @desc Gets the access control policy for a resource. Returns an empty * policy if the resource exists and does not have a policy set. * @alias ml.projects.models.getIamPolicy * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.resource_ REQUIRED: The resource for which the policy is being requested. See the operation documentation for the appropriate value for this field. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ getIamPolicy(params?: Params$Resource$Projects$Models$Getiampolicy, options?: MethodOptions): GaxiosPromise; getIamPolicy(params: Params$Resource$Projects$Models$Getiampolicy, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; getIamPolicy(params: Params$Resource$Projects$Models$Getiampolicy, callback: BodyResponseCallback): void; getIamPolicy(callback: BodyResponseCallback): void; /** * ml.projects.models.list * @desc Lists the models in a project. Each project can contain multiple * models, and each model can have multiple versions. If there are no * models that match the request parameters, the list request returns an * empty response body: {}. * @alias ml.projects.models.list * @memberOf! () * * @param {object} params Parameters for request * @param {string=} params.filter Optional. Specifies the subset of models to retrieve. * @param {integer=} params.pageSize Optional. The number of models to retrieve per "page" of results. If there are more remaining results than this number, the response message will contain a valid value in the `next_page_token` field. The default value is 20, and the maximum page size is 100. * @param {string=} params.pageToken Optional. A page token to request the next page of results. You get the token from the `next_page_token` field of the response from the previous call. * @param {string} params.parent Required. The name of the project whose models are to be listed. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ list(params?: Params$Resource$Projects$Models$List, options?: MethodOptions): GaxiosPromise; list(params: Params$Resource$Projects$Models$List, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; list(params: Params$Resource$Projects$Models$List, callback: BodyResponseCallback): void; list(callback: BodyResponseCallback): void; /** * ml.projects.models.patch * @desc Updates a specific model resource. Currently the only supported * fields to update are `description` and `default_version.name`. * @alias ml.projects.models.patch * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The project name. * @param {string=} params.updateMask Required. Specifies the path, relative to `Model`, of the field to update. For example, to change the description of a model to "foo" and set its default version to "version_1", the `update_mask` parameter would be specified as `description`, `default_version.name`, and the `PATCH` request body would specify the new value, as follows: { "description": "foo", "defaultVersion": { "name":"version_1" } } Currently the supported update masks are `description` and `default_version.name`. * @param {().GoogleCloudMlV1__Model} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ patch(params?: Params$Resource$Projects$Models$Patch, options?: MethodOptions): GaxiosPromise; patch(params: Params$Resource$Projects$Models$Patch, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; patch(params: Params$Resource$Projects$Models$Patch, callback: BodyResponseCallback): void; patch(callback: BodyResponseCallback): void; /** * ml.projects.models.setIamPolicy * @desc Sets the access control policy on the specified resource. Replaces * any existing policy. * @alias ml.projects.models.setIamPolicy * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.resource_ REQUIRED: The resource for which the policy is being specified. See the operation documentation for the appropriate value for this field. * @param {().GoogleIamV1__SetIamPolicyRequest} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ setIamPolicy(params?: Params$Resource$Projects$Models$Setiampolicy, options?: MethodOptions): GaxiosPromise; setIamPolicy(params: Params$Resource$Projects$Models$Setiampolicy, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; setIamPolicy(params: Params$Resource$Projects$Models$Setiampolicy, callback: BodyResponseCallback): void; setIamPolicy(callback: BodyResponseCallback): void; /** * ml.projects.models.testIamPermissions * @desc Returns permissions that a caller has on the specified resource. If * the resource does not exist, this will return an empty set of * permissions, not a NOT_FOUND error. Note: This operation is designed to * be used for building permission-aware UIs and command-line tools, not for * authorization checking. This operation may "fail open" without warning. * @alias ml.projects.models.testIamPermissions * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.resource_ REQUIRED: The resource for which the policy detail is being requested. See the operation documentation for the appropriate value for this field. * @param {().GoogleIamV1__TestIamPermissionsRequest} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ testIamPermissions(params?: Params$Resource$Projects$Models$Testiampermissions, options?: MethodOptions): GaxiosPromise; testIamPermissions(params: Params$Resource$Projects$Models$Testiampermissions, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; testIamPermissions(params: Params$Resource$Projects$Models$Testiampermissions, callback: BodyResponseCallback): void; testIamPermissions(callback: BodyResponseCallback): void; } interface Params$Resource$Projects$Models$Create extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The project name. */ parent?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__Model; } interface Params$Resource$Projects$Models$Delete extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the model. */ name?: string; } interface Params$Resource$Projects$Models$Get extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the model. */ name?: string; } interface Params$Resource$Projects$Models$Getiampolicy extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * REQUIRED: The resource for which the policy is being requested. See the * operation documentation for the appropriate value for this field. */ resource?: string; } interface Params$Resource$Projects$Models$List extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Optional. Specifies the subset of models to retrieve. */ filter?: string; /** * Optional. The number of models to retrieve per "page" of results. If * there are more remaining results than this number, the response message * will contain a valid value in the `next_page_token` field. The default * value is 20, and the maximum page size is 100. */ pageSize?: number; /** * Optional. A page token to request the next page of results. You get the * token from the `next_page_token` field of the response from the previous * call. */ pageToken?: string; /** * Required. The name of the project whose models are to be listed. */ parent?: string; } interface Params$Resource$Projects$Models$Patch extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The project name. */ name?: string; /** * Required. Specifies the path, relative to `Model`, of the field to * update. For example, to change the description of a model to "foo" and * set its default version to "version_1", the `update_mask` parameter would * be specified as `description`, `default_version.name`, and the `PATCH` * request body would specify the new value, as follows: { * "description": "foo", "defaultVersion": { "name":"version_1" } } * Currently the supported update masks are `description` and * `default_version.name`. */ updateMask?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__Model; } interface Params$Resource$Projects$Models$Setiampolicy extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * REQUIRED: The resource for which the policy is being specified. See the * operation documentation for the appropriate value for this field. */ resource?: string; /** * Request body metadata */ requestBody?: Schema$GoogleIamV1__SetIamPolicyRequest; } interface Params$Resource$Projects$Models$Testiampermissions extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * REQUIRED: The resource for which the policy detail is being requested. * See the operation documentation for the appropriate value for this field. */ resource?: string; /** * Request body metadata */ requestBody?: Schema$GoogleIamV1__TestIamPermissionsRequest; } class Resource$Projects$Models$Versions { constructor(); /** * ml.projects.models.versions.create * @desc Creates a new version of a model from a trained TensorFlow model. * If the version created in the cloud by this call is the first deployed * version of the specified model, it will be made the default version of * the model. When you add a version to a model that already has one or more * versions, the default version does not automatically change. If you want * a new version to be the default, you must call * [projects.models.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault). * @alias ml.projects.models.versions.create * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.parent Required. The name of the model. * @param {().GoogleCloudMlV1__Version} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ create(params?: Params$Resource$Projects$Models$Versions$Create, options?: MethodOptions): GaxiosPromise; create(params: Params$Resource$Projects$Models$Versions$Create, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; create(params: Params$Resource$Projects$Models$Versions$Create, callback: BodyResponseCallback): void; create(callback: BodyResponseCallback): void; /** * ml.projects.models.versions.delete * @desc Deletes a model version. Each model can have multiple versions * deployed and in use at any given time. Use this method to remove a single * version. Note: You cannot delete the version that is set as the default * version of the model unless it is the only remaining version. * @alias ml.projects.models.versions.delete * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the version. You can get the names of all the versions of a model by calling [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list). * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ delete(params?: Params$Resource$Projects$Models$Versions$Delete, options?: MethodOptions): GaxiosPromise; delete(params: Params$Resource$Projects$Models$Versions$Delete, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; delete(params: Params$Resource$Projects$Models$Versions$Delete, callback: BodyResponseCallback): void; delete(callback: BodyResponseCallback): void; /** * ml.projects.models.versions.get * @desc Gets information about a model version. Models can have multiple * versions. You can call * [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list) * to get the same information that this method returns for all of the * versions of a model. * @alias ml.projects.models.versions.get * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the version. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ get(params?: Params$Resource$Projects$Models$Versions$Get, options?: MethodOptions): GaxiosPromise; get(params: Params$Resource$Projects$Models$Versions$Get, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; get(params: Params$Resource$Projects$Models$Versions$Get, callback: BodyResponseCallback): void; get(callback: BodyResponseCallback): void; /** * ml.projects.models.versions.list * @desc Gets basic information about all the versions of a model. If you * expect that a model has many versions, or if you need to handle only a * limited number of results at a time, you can request that the list be * retrieved in batches (called pages). If there are no versions that match * the request parameters, the list request returns an empty response body: * {}. * @alias ml.projects.models.versions.list * @memberOf! () * * @param {object} params Parameters for request * @param {string=} params.filter Optional. Specifies the subset of versions to retrieve. * @param {integer=} params.pageSize Optional. The number of versions to retrieve per "page" of results. If there are more remaining results than this number, the response message will contain a valid value in the `next_page_token` field. The default value is 20, and the maximum page size is 100. * @param {string=} params.pageToken Optional. A page token to request the next page of results. You get the token from the `next_page_token` field of the response from the previous call. * @param {string} params.parent Required. The name of the model for which to list the version. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ list(params?: Params$Resource$Projects$Models$Versions$List, options?: MethodOptions): GaxiosPromise; list(params: Params$Resource$Projects$Models$Versions$List, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; list(params: Params$Resource$Projects$Models$Versions$List, callback: BodyResponseCallback): void; list(callback: BodyResponseCallback): void; /** * ml.projects.models.versions.patch * @desc Updates the specified Version resource. Currently the only * update-able fields are `description` and `autoScaling.minNodes`. * @alias ml.projects.models.versions.patch * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the model. * @param {string=} params.updateMask Required. Specifies the path, relative to `Version`, of the field to update. Must be present and non-empty. For example, to change the description of a version to "foo", the `update_mask` parameter would be specified as `description`, and the `PATCH` request body would specify the new value, as follows: { "description": "foo" } Currently the only supported update mask fields are `description` and `autoScaling.minNodes`. * @param {().GoogleCloudMlV1__Version} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ patch(params?: Params$Resource$Projects$Models$Versions$Patch, options?: MethodOptions): GaxiosPromise; patch(params: Params$Resource$Projects$Models$Versions$Patch, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; patch(params: Params$Resource$Projects$Models$Versions$Patch, callback: BodyResponseCallback): void; patch(callback: BodyResponseCallback): void; /** * ml.projects.models.versions.setDefault * @desc Designates a version to be the default for the model. The default * version is used for prediction requests made against the model that don't * specify a version. The first version to be created for a model is * automatically set as the default. You must make any subsequent changes to * the default version setting manually using this method. * @alias ml.projects.models.versions.setDefault * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name Required. The name of the version to make the default for the model. You can get the names of all the versions of a model by calling [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list). * @param {().GoogleCloudMlV1__SetDefaultVersionRequest} params.resource Request body data * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ setDefault(params?: Params$Resource$Projects$Models$Versions$Setdefault, options?: MethodOptions): GaxiosPromise; setDefault(params: Params$Resource$Projects$Models$Versions$Setdefault, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; setDefault(params: Params$Resource$Projects$Models$Versions$Setdefault, callback: BodyResponseCallback): void; setDefault(callback: BodyResponseCallback): void; } interface Params$Resource$Projects$Models$Versions$Create extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the model. */ parent?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__Version; } interface Params$Resource$Projects$Models$Versions$Delete extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the version. You can get the names of all the * versions of a model by calling * [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list). */ name?: string; } interface Params$Resource$Projects$Models$Versions$Get extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the version. */ name?: string; } interface Params$Resource$Projects$Models$Versions$List extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Optional. Specifies the subset of versions to retrieve. */ filter?: string; /** * Optional. The number of versions to retrieve per "page" of results. If * there are more remaining results than this number, the response message * will contain a valid value in the `next_page_token` field. The default * value is 20, and the maximum page size is 100. */ pageSize?: number; /** * Optional. A page token to request the next page of results. You get the * token from the `next_page_token` field of the response from the previous * call. */ pageToken?: string; /** * Required. The name of the model for which to list the version. */ parent?: string; } interface Params$Resource$Projects$Models$Versions$Patch extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the model. */ name?: string; /** * Required. Specifies the path, relative to `Version`, of the field to * update. Must be present and non-empty. For example, to change the * description of a version to "foo", the `update_mask` parameter would be * specified as `description`, and the `PATCH` request body would specify * the new value, as follows: { "description": "foo" } * Currently the only supported update mask fields are `description` and * `autoScaling.minNodes`. */ updateMask?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__Version; } interface Params$Resource$Projects$Models$Versions$Setdefault extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * Required. The name of the version to make the default for the model. You * can get the names of all the versions of a model by calling * [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list). */ name?: string; /** * Request body metadata */ requestBody?: Schema$GoogleCloudMlV1__SetDefaultVersionRequest; } class Resource$Projects$Operations { constructor(); /** * ml.projects.operations.cancel * @desc Starts asynchronous cancellation on a long-running operation. The * server makes a best effort to cancel the operation, but success is not * guaranteed. If the server doesn't support this method, it returns * `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation * or other methods to check whether the cancellation succeeded or whether * the operation completed despite cancellation. On successful cancellation, * the operation is not deleted; instead, it becomes an operation with an * Operation.error value with a google.rpc.Status.code of 1, corresponding * to `Code.CANCELLED`. * @alias ml.projects.operations.cancel * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name The name of the operation resource to be cancelled. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ cancel(params?: Params$Resource$Projects$Operations$Cancel, options?: MethodOptions): GaxiosPromise; cancel(params: Params$Resource$Projects$Operations$Cancel, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; cancel(params: Params$Resource$Projects$Operations$Cancel, callback: BodyResponseCallback): void; cancel(callback: BodyResponseCallback): void; /** * ml.projects.operations.get * @desc Gets the latest state of a long-running operation. Clients can use * this method to poll the operation result at intervals as recommended by * the API service. * @alias ml.projects.operations.get * @memberOf! () * * @param {object} params Parameters for request * @param {string} params.name The name of the operation resource. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ get(params?: Params$Resource$Projects$Operations$Get, options?: MethodOptions): GaxiosPromise; get(params: Params$Resource$Projects$Operations$Get, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; get(params: Params$Resource$Projects$Operations$Get, callback: BodyResponseCallback): void; get(callback: BodyResponseCallback): void; /** * ml.projects.operations.list * @desc Lists operations that match the specified filter in the request. If * the server doesn't support this method, it returns `UNIMPLEMENTED`. NOTE: * the `name` binding allows API services to override the binding to use * different resource name schemes, such as `users/x/operations`. To * override the binding, API services can add a binding such as * `"/v1/{name=users/x}/operations"` to their service configuration. For * backwards compatibility, the default name includes the operations * collection id, however overriding users must ensure the name binding is * the parent resource, without the operations collection id. * @alias ml.projects.operations.list * @memberOf! () * * @param {object} params Parameters for request * @param {string=} params.filter The standard list filter. * @param {string} params.name The name of the operation's parent resource. * @param {integer=} params.pageSize The standard list page size. * @param {string=} params.pageToken The standard list page token. * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`. * @param {callback} callback The callback that handles the response. * @return {object} Request object */ list(params?: Params$Resource$Projects$Operations$List, options?: MethodOptions): GaxiosPromise; list(params: Params$Resource$Projects$Operations$List, options: MethodOptions | BodyResponseCallback, callback: BodyResponseCallback): void; list(params: Params$Resource$Projects$Operations$List, callback: BodyResponseCallback): void; list(callback: BodyResponseCallback): void; } interface Params$Resource$Projects$Operations$Cancel extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * The name of the operation resource to be cancelled. */ name?: string; } interface Params$Resource$Projects$Operations$Get extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * The name of the operation resource. */ name?: string; } interface Params$Resource$Projects$Operations$List extends StandardParameters { /** * Auth client or API Key for the request */ auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient; /** * The standard list filter. */ filter?: string; /** * The name of the operation's parent resource. */ name?: string; /** * The standard list page size. */ pageSize?: number; /** * The standard list page token. */ pageToken?: string; } }