6.0.0 • Published 5 years ago

@datafire/google_ml v6.0.0

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1
License
MIT
Repository
github
Last release
5 years ago

@datafire/google_ml

Client library for AI Platform Training & Prediction API

Installation and Usage

npm install --save @datafire/google_ml
let google_ml = require('@datafire/google_ml').create({
  access_token: "",
  refresh_token: "",
  client_id: "",
  client_secret: "",
  redirect_uri: ""
});

.then(data => {
  console.log(data);
});

Description

An API to enable creating and using machine learning models.

Actions

oauthCallback

Exchange the code passed to your redirect URI for an access_token

google_ml.oauthCallback({
  "code": ""
}, context)

Input

  • input object
    • code required string

Output

  • output object
    • access_token string
    • refresh_token string
    • token_type string
    • scope string
    • expiration string

oauthRefresh

Exchange a refresh_token for an access_token

google_ml.oauthRefresh(null, context)

Input

This action has no parameters

Output

  • output object
    • access_token string
    • refresh_token string
    • token_type string
    • scope string
    • expiration string

ml.projects.models.versions.delete

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.

google_ml.ml.projects.models.versions.delete({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The name of the version. You can get the names of all the versions of a model by calling projects.models.versions.list.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.operations.get

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.

google_ml.ml.projects.operations.get({
  "name": ""
}, context)

Input

  • input object
    • name required string: The name of the operation resource.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.versions.patch

Updates the specified Version resource. Currently the only update-able fields are description, requestLoggingConfig, autoScaling.minNodes, and manualScaling.nodes.

google_ml.ml.projects.models.versions.patch({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The name of the model.
    • updateMask 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, requestLoggingConfig, autoScaling.minNodes, and manualScaling.nodes. However, you can only update manualScaling.nodes if the version uses a Compute Engine (N1) machine type.
    • body GoogleCloudMlV1__Version
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.operations.list

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/*/operations. To override the binding, API services can add a binding such as "/v1/{name=users/*}/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.

google_ml.ml.projects.operations.list({
  "name": ""
}, context)

Input

  • input object
    • name required string: The name of the operation's parent resource.
    • filter string: The standard list filter.
    • pageSize integer: The standard list page size.
    • pageToken string: The standard list page token.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.trials.addMeasurement

Adds a measurement of the objective metrics to a trial. This measurement is assumed to have been taken before the trial is complete.

google_ml.ml.projects.locations.studies.trials.addMeasurement({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The trial name.
    • body GoogleCloudMlV1__AddTrialMeasurementRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.operations.cancel

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.

google_ml.ml.projects.operations.cancel({
  "name": ""
}, context)

Input

  • input object
    • name required string: The name of the operation resource to be cancelled.
    • body GoogleCloudMlV1__CancelJobRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.trials.checkEarlyStoppingState

Checks whether a trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.

google_ml.ml.projects.locations.studies.trials.checkEarlyStoppingState({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The trial name.
    • body GoogleCloudMlV1__CheckTrialEarlyStoppingStateRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.trials.complete

Marks a trial as complete.

google_ml.ml.projects.locations.studies.trials.complete({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The trial name.metat
    • body GoogleCloudMlV1__CompleteTrialRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.explain

Performs explanation on the data in the request. {% dynamic include "/ai-platform/includes/___explain-request" %} 

google_ml.ml.projects.explain({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The resource name of a model or a version. Authorization: requires the predict permission on the specified resource.
    • body GoogleCloudMlV1__ExplainRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.getConfig

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.

google_ml.ml.projects.getConfig({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The project name.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.predict

Performs online prediction on the data in the request. {% dynamic include "/ai-platform/includes/___predict-request" %} 

google_ml.ml.projects.predict({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The resource name of a model or a version. Authorization: requires the predict permission on the specified resource.
    • body GoogleCloudMlV1__PredictRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.versions.setDefault

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.

google_ml.ml.projects.models.versions.setDefault({
  "name": ""
}, context)

Input

  • input object
    • name required string: 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.
    • body GoogleCloudMlV1__SetDefaultVersionRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.trials.stop

Stops a trial.

google_ml.ml.projects.locations.studies.trials.stop({
  "name": ""
}, context)

Input

  • input object
    • name required string: Required. The trial name.
    • body GoogleCloudMlV1__StopTrialRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.jobs.list

Lists the jobs in the project. If there are no jobs that match the request parameters, the list request returns an empty response body: {}.

google_ml.ml.projects.jobs.list({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the project for which to list jobs.
    • filter string: 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 ai-platform jobs list --filter='jobId:census' List all failed jobs with names that start with 'rnn': gcloud ai-platform jobs list --filter='jobId:rnn AND state:FAILED' For more examples, see the guide to monitoring jobs.
    • pageSize integer: 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.
    • pageToken string: 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.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.jobs.create

Creates a training or a batch prediction job.

google_ml.ml.projects.jobs.create({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The project name.
    • body GoogleCloudMlV1__Job
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.list

List all locations that provides at least one type of CMLE capability.

google_ml.ml.projects.locations.list({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the project for which available locations are to be listed (since some locations might be whitelisted for specific projects).
    • pageSize integer: 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.
    • pageToken string: 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.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.list

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: {}.

google_ml.ml.projects.models.list({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the project whose models are to be listed.
    • filter string: Optional. Specifies the subset of models to retrieve.
    • pageSize integer: 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.
    • pageToken string: 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.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.create

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.

google_ml.ml.projects.models.create({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The project name.
    • body GoogleCloudMlV1__Model
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.list

Lists all the studies in a region for an associated project.

google_ml.ml.projects.locations.studies.list({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The project and location that the study belongs to. Format: projects/{project}/locations/{location}
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.create

Creates a study.

google_ml.ml.projects.locations.studies.create({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The project and location that the study belongs to. Format: projects/{project}/locations/{location}
    • studyId string: Required. The ID to use for the study, which will become the final component of the study's resource name.
    • body GoogleCloudMlV1__Study
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.trials.list

Lists the trials associated with a study.

google_ml.ml.projects.locations.studies.trials.list({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the study that the trial belongs to.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.trials.create

Adds a user provided trial to a study.

google_ml.ml.projects.locations.studies.trials.create({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the study that the trial belongs to.
    • body GoogleCloudMlV1__Trial
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.trials.listOptimalTrials

Lists the pareto-optimal trials for multi-objective study or the optimal trials for single-objective study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency

google_ml.ml.projects.locations.studies.trials.listOptimalTrials({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the study that the pareto-optimal trial belongs to.
    • body GoogleCloudMlV1__ListOptimalTrialsRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.locations.studies.trials.suggest

Adds one or more trials to a study, with parameter values suggested by AI Platform Vizier. Returns a long-running operation associated with the generation of trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.

google_ml.ml.projects.locations.studies.trials.suggest({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the study that the trial belongs to.
    • body GoogleCloudMlV1__SuggestTrialsRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.versions.list

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: {}.

google_ml.ml.projects.models.versions.list({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the model for which to list the version.
    • filter string: Optional. Specifies the subset of versions to retrieve.
    • pageSize integer: 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.
    • pageToken string: 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.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.versions.create

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.

google_ml.ml.projects.models.versions.create({
  "parent": ""
}, context)

Input

  • input object
    • parent required string: Required. The name of the model.
    • body GoogleCloudMlV1__Version
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.getIamPolicy

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

google_ml.ml.projects.models.getIamPolicy({
  "resource": ""
}, context)

Input

  • input object
    • resource required string: REQUIRED: The resource for which the policy is being requested. See the operation documentation for the appropriate value for this field.
    • options.requestedPolicyVersion integer: Optional. The policy format version to be returned. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional bindings must specify version 3. Policies without any conditional bindings may specify any valid value or leave the field unset. To learn which resources support conditions in their IAM policies, see the IAM documentation.
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.setIamPolicy

Sets the access control policy on the specified resource. Replaces any existing policy. Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIED errors.

google_ml.ml.projects.models.setIamPolicy({
  "resource": ""
}, context)

Input

  • input object
    • resource required string: REQUIRED: The resource for which the policy is being specified. See the operation documentation for the appropriate value for this field.
    • body GoogleIamV1__SetIamPolicyRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

ml.projects.models.testIamPermissions

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.

google_ml.ml.projects.models.testIamPermissions({
  "resource": ""
}, context)

Input

  • input object
    • resource required string: REQUIRED: The resource for which the policy detail is being requested. See the operation documentation for the appropriate value for this field.
    • body GoogleIamV1__TestIamPermissionsRequest
    • $.xgafv string (values: 1, 2): V1 error format.
    • access_token string: OAuth access token.
    • alt string (values: json, media, proto): Data format for response.
    • callback string: JSONP
    • fields string: Selector specifying which fields to include in a partial response.
    • key 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.
    • oauth_token string: OAuth 2.0 token for the current user.
    • prettyPrint boolean: Returns response with indentations and line breaks.
    • quotaUser string: 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.
    • upload_protocol string: Upload protocol for media (e.g. "raw", "multipart").
    • uploadType string: Legacy upload protocol for media (e.g. "media", "multipart").

Output

Definitions

GoogleApi__HttpBody

  • GoogleApi__HttpBody object: 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.
    • contentType string: The HTTP Content-Type header value specifying the content type of the body.
    • data string: The HTTP request/response body as raw binary.
    • extensions array: Application specific response metadata. Must be set in the first response for streaming APIs.
      • items object

GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfig

  • GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfig object
    • useElapsedTime boolean: If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.

GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfig

  • GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfig object: The median automated stopping rule stops a pending trial if the trial's best objective_value is strictly below the median 'performance' of all completed trials reported up to the trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the trial in each measurement.
    • useElapsedTime boolean: If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.

GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric

  • GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric object: An observed value of a metric.
    • objectiveValue number: The objective value at this training step.
    • trainingStep string: The global training step for this metric.

GoogleCloudMlV1_Measurement_Metric

  • GoogleCloudMlV1_Measurement_Metric object: A message representing a metric in the measurement.
    • metric string: Required. Metric name.
    • value number: Required. The value for this metric.

GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec

  • GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec object
    • values array: Must be specified if type is CATEGORICAL. The list of possible categories.
      • items string

GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec

  • GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec object
    • values array: Must be specified 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.
      • items number

GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec

  • GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec object
    • maxValue number: Must be specified if type is DOUBLE. Maximum value of the parameter.
    • minValue number: Must be specified if type is DOUBLE. Minimum value of the parameter.

GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec

  • GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec object
    • maxValue string: Must be specified if type is INTEGER. Maximum value of the parameter.
    • minValue string: Must be specified if type is INTEGER. Minimum value of the parameter.

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec

  • GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec object: Represents the spec to match categorical values from parent parameter.
    • values array: Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
      • items string

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec

  • GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec object: Represents the spec to match discrete values from parent parameter.
    • values array: Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
      • items number

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec

  • GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec object: Represents the spec to match integer values from parent parameter.
    • values array: Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
      • items string

GoogleCloudMlV1_StudyConfig_MetricSpec

  • GoogleCloudMlV1_StudyConfig_MetricSpec object: Represents a metric to optimize.
    • goal string (values: GOAL_TYPE_UNSPECIFIED, MAXIMIZE, MINIMIZE): Required. The optimization goal of the metric.
    • metric string: Required. The name of the metric.

GoogleCloudMlV1_StudyConfig_ParameterSpec

GoogleCloudMlV1_Trial_Parameter

  • GoogleCloudMlV1_Trial_Parameter object: A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
    • floatValue number: Must be set if ParameterType is DOUBLE or DISCRETE.
    • intValue string: Must be set if ParameterType is INTEGER
    • parameter string: The name of the parameter.
    • stringValue string: Must be set if ParameterTypeis CATEGORICAL

GoogleCloudMlV1__AcceleratorConfig

  • GoogleCloudMlV1__AcceleratorConfig object: Represents a hardware accelerator request config. Note that the AcceleratorConfig can be used in both Jobs and Versions. Learn more about accelerators for training and accelerators for online prediction.
    • count string: The number of accelerators to attach to each machine running the job.
    • type string (values: ACCELERATOR_TYPE_UNSPECIFIED, NVIDIA_TESLA_K80, NVIDIA_TESLA_P100, NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, NVIDIA_TESLA_A100, TPU_V2, TPU_V3): The type of accelerator to use.

GoogleCloudMlV1__AddTrialMeasurementRequest

  • GoogleCloudMlV1__AddTrialMeasurementRequest object: The request message for the AddTrialMeasurement service method.

GoogleCloudMlV1__AutoScaling

  • GoogleCloudMlV1__AutoScaling object: Options for automatically scaling a model.
    • maxNodes integer: The maximum number of nodes to scale this model under load. The actual value will depend on resource quota and availability.
    • metrics array: MetricSpec contains the specifications to use to calculate the desired nodes count.
    • minNodes integer: 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, 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 min_nodes is not specified and AutoScaling is used with a legacy (MLS1) machine type, 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. If min_nodes is not specified and AutoScaling is used with a Compute Engine (N1) machine type, min_nodes defaults to 1. min_nodes must be at least 1 for use with a Compute Engine machine type. Note that you cannot use AutoScaling if your version uses GPUs. Instead, you must use ManualScaling. You can set min_nodes when creating the model version, and you can also update min_nodes for an existing version: update_body.json: { 'autoScaling': { 'minNodes': 5 } } HTTP request: PATCH https://ml.googleapis.com/v1/{name=projects//models//versions/*}?update_mask=autoScaling.minNodes -d @./update_body.json

GoogleCloudMlV1__AutomatedStoppingConfig

GoogleCloudMlV1__BuiltInAlgorithmOutput

  • GoogleCloudMlV1__BuiltInAlgorithmOutput object: Represents output related to a built-in algorithm Job.
    • framework string: Framework on which the built-in algorithm was trained.
    • modelPath string: The Cloud Storage path to the model/ directory where the training job saves the trained model. Only set for successful jobs that don't use hyperparameter tuning.
    • pythonVersion string: Python version on which the built-in algorithm was trained.
    • runtimeVersion string: AI Platform runtime version on which the built-in algorithm was trained.

GoogleCloudMlV1__CancelJobRequest

  • GoogleCloudMlV1__CancelJobRequest object: Request message for the CancelJob method.

GoogleCloudMlV1__Capability

  • GoogleCloudMlV1__Capability object
    • availableAccelerators array: Available accelerators for the capability.
      • items string (values: ACCELERATOR_TYPE_UNSPECIFIED, NVIDIA_TESLA_K80, NVIDIA_TESLA_P100, NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, NVIDIA_TESLA_A100, TPU_V2, TPU_V3)
    • type string (values: TYPE_UNSPECIFIED, TRAINING, BATCH_PREDICTION, ONLINE_PREDICTION)

GoogleCloudMlV1__CheckTrialEarlyStoppingStateMetatdata

  • GoogleCloudMlV1__CheckTrialEarlyStoppingStateMetatdata object: This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
    • createTime string: The time at which the operation was submitted.
    • study string: The name of the study that the trial belongs to.
    • trial string: The trial name.

GoogleCloudMlV1__CheckTrialEarlyStoppingStateRequest

  • GoogleCloudMlV1__CheckTrialEarlyStoppingStateRequest object: The request message for the CheckTrialEarlyStoppingState service method.

GoogleCloudMlV1__CheckTrialEarlyStoppingStateResponse

  • GoogleCloudMlV1__CheckTrialEarlyStoppingStateResponse object: The message will be placed in the response field of a completed google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
    • endTime string: The time at which operation processing completed.
    • shouldStop boolean: True if the Trial should stop.
    • startTime string: The time at which the operation was started.

GoogleCloudMlV1__CompleteTrialRequest

  • GoogleCloudMlV1__CompleteTrialRequest object: The request message for the CompleteTrial service method.
    • finalMeasurement GoogleCloudMlV1__Measurement
    • infeasibleReason string: Optional. A human readable reason why the trial was infeasible. This should only be provided if trial_infeasible is true.
    • trialInfeasible boolean: Optional. True if the trial cannot be run with the given Parameter, and final_measurement will be ignored.

GoogleCloudMlV1__Config

  • GoogleCloudMlV1__Config object
    • tpuServiceAccount string: The service account Cloud ML uses to run on TPU node.

GoogleCloudMlV1__ContainerPort

  • GoogleCloudMlV1__ContainerPort object: Represents a network port in a single container. This message is a subset of the Kubernetes ContainerPort v1 core specification.
    • containerPort integer: Number of the port to expose on the container. This must be a valid port number: 0 < PORT_NUMBER < 65536.

GoogleCloudMlV1__ContainerSpec

datafire
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