ml
import { ml } from "https://googleapis.deno.dev/v1/ml:v1.ts";
An API to enable creating and using machine learning models.
§Methods
Performs explanation on the data in the request. {% dynamic include "/ai-platform/includes/___explain-request" %}
Required. The resource name of a model or a version. Authorization: requires the predict
permission on the specified resource.
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.
Required. The project name.
Cancels a running job.
Required. The name of the job to cancel.
Describes a job.
Required. The name of the job to get the description of.
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
REQUIRED: The resource for which the policy is being requested. See Resource names for the appropriate value for this field.
Lists the jobs in the project. If there are no jobs that match the request parameters, the list request returns an empty response body: {}.
Required. The name of the project for which to list jobs.
Updates a specific job resource. Currently the only supported fields to
update are labels
.
Required. The job name.
Sets the access control policy on the specified resource. Replaces any
existing policy. Can return NOT_FOUND
, INVALID_ARGUMENT
, and
PERMISSION_DENIED
errors.
REQUIRED: The resource for which the policy is being specified. See Resource names for the appropriate value for this field.
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.
REQUIRED: The resource for which the policy detail is being requested. See Resource names for the appropriate value for this field.
Get the complete list of CMLE capabilities in a location, along with their location-specific properties.
Required. The name of the location.
List all locations that provides at least one type of CMLE capability.
Required. The name of the project for which available locations are to be listed (since some locations might be whitelisted for specific projects).
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
.
The name of the operation resource to be cancelled.
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.
The name of the operation resource.
Creates a study.
Required. The project and location that the study belongs to. Format: projects/{project}/locations/{location}
Deletes a study.
Required. The study name.
Gets a study.
Required. The study name.
Lists all the studies in a region for an associated project.
Required. The project and location that the study belongs to. Format: projects/{project}/locations/{location}
Adds a measurement of the objective metrics to a trial. This measurement is assumed to have been taken before the trial is complete.
Required. The trial name.
Checks whether a trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.
Required. The trial name.
Marks a trial as complete.
Required. The trial name.metat
Adds a user provided trial to a study.
Required. The name of the study that the trial belongs to.
Deletes a trial.
Required. The trial name.
Gets a trial.
Required. The trial name.
Lists the trials associated with a study.
Required. The name of the study that the trial belongs to.
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
Required. The name of the study that the pareto-optimal trial belongs to.
Stops a trial.
Required. The trial name.
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.
Required. The name of the study that the trial belongs to.
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.
Required. The project name.
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.
Required. The name of the model.
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).
Required. The name of the model.
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
REQUIRED: The resource for which the policy is being requested. See Resource names for the appropriate value for this field.
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: {}.
Required. The name of the project whose models are to be listed.
Updates a specific model resource. Currently the only supported fields to
update are description
and default_version.name
.
Required. The project name.
Sets the access control policy on the specified resource. Replaces any
existing policy. Can return NOT_FOUND
, INVALID_ARGUMENT
, and
PERMISSION_DENIED
errors.
REQUIRED: The resource for which the policy is being specified. See Resource names for the appropriate value for this field.
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.
REQUIRED: The resource for which the policy detail is being requested. See Resource names for the appropriate value for this field.
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.
Required. The name of the model.
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.
Required. The name of the version. You can get the names of all the versions of a model by calling projects.models.versions.list.
Gets information about a model version. Models can have multiple versions. You can call projects.models.versions.list to get the same information that this method returns for all of the versions of a model.
Required. The name of the version.
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: {}.
Required. The name of the model for which to list the version.
Updates the specified Version resource. Currently the only update-able
fields are description
, requestLoggingConfig
, autoScaling.minNodes
,
and manualScaling.nodes
.
Required. The name of the model.
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.
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.
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
.
The name of the operation resource to be cancelled.
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.
The name of the operation resource.
Lists operations that match the specified filter in the request. If the
server doesn't support this method, it returns UNIMPLEMENTED
.
The name of the operation's parent resource.