Crate google_ml1_beta1

Expand description

This documentation was generated from Cloud Machine Learning Engine crate version 1.0.6+20170515, where 20170515 is the exact revision of the ml:v1beta1 schema built by the mako code generator v1.0.6.

Everything else about the Cloud Machine Learning Engine v1_beta1 API can be found at the official documentation site. The original source code is on github.

§Features

Handle the following Resources with ease from the central hub …

projects
get config, jobs cancel, jobs create, jobs get, jobs list, models create, models delete, models get, models list, models versions create, models versions delete, models versions get, models versions list, models versions set default, operations cancel, operations delete, operations get, operations list and predict

Not what you are looking for ? Find all other Google APIs in their Rust documentation index.

§Structure of this Library

The API is structured into the following primary items:

Hub
- a central object to maintain state and allow accessing all Activities
- creates Method Builders which in turn allow access to individual Call Builders
Resources
- primary types that you can apply Activities to
- a collection of properties and Parts
- Parts
  - a collection of properties
  - never directly used in Activities
Activities
- operations to apply to Resources

All structures are marked with applicable traits to further categorize them and ease browsing.

Generally speaking, you can invoke Activities like this:

let r = hub.resource().activity(...).doit()

Or specifically …

let r = hub.projects().models_versions_delete(...).doit()
let r = hub.projects().models_delete(...).doit()
let r = hub.projects().models_versions_create(...).doit()
let r = hub.projects().operations_get(...).doit()

The resource() and activity(...) calls create builders. The second one dealing with Activities supports various methods to configure the impending operation (not shown here). It is made such that all required arguments have to be specified right away (i.e. (...)), whereas all optional ones can be build up as desired. The doit() method performs the actual communication with the server and returns the respective result.

§Usage

§Setting up your Project

To use this library, you would put the following lines into your Cargo.toml file:

[dependencies]
google-ml1_beta1 = "*"

§A complete example

extern crate hyper;
extern crate hyper_rustls;
extern crate yup_oauth2 as oauth2;
extern crate google_ml1_beta1 as ml1_beta1;
use ml1_beta1::GoogleCloudMlV1beta1__Version;
use ml1_beta1::{Result, Error};
use std::default::Default;
use oauth2::{Authenticator, DefaultAuthenticatorDelegate, ApplicationSecret, MemoryStorage};
use ml1_beta1::CloudMachineLearningEngine;
 
// Get an ApplicationSecret instance by some means. It contains the `client_id` and 
// `client_secret`, among other things.
let secret: ApplicationSecret = Default::default();
// Instantiate the authenticator. It will choose a suitable authentication flow for you, 
// unless you replace  `None` with the desired Flow.
// Provide your own `AuthenticatorDelegate` to adjust the way it operates and get feedback about 
// what's going on. You probably want to bring in your own `TokenStorage` to persist tokens and
// retrieve them from storage.
let auth = Authenticator::new(&secret, DefaultAuthenticatorDelegate,
                              hyper::Client::with_connector(hyper::net::HttpsConnector::new(hyper_rustls::TlsClient::new())),
                              <MemoryStorage as Default>::default(), None);
let mut hub = CloudMachineLearningEngine::new(hyper::Client::with_connector(hyper::net::HttpsConnector::new(hyper_rustls::TlsClient::new())), auth);
// As the method needs a request, you would usually fill it with the desired information
// into the respective structure. Some of the parts shown here might not be applicable !
// Values shown here are possibly random and not representative !
let mut req = GoogleCloudMlV1beta1__Version::default();
 
// You can configure optional parameters by calling the respective setters at will, and
// execute the final call using `doit()`.
// Values shown here are possibly random and not representative !
let result = hub.projects().models_versions_create(req, "parent")
             .doit();
 
match result {
    Err(e) => match e {
        // The Error enum provides details about what exactly happened.
        // You can also just use its `Debug`, `Display` or `Error` traits
         Error::HttpError(_)
        |Error::MissingAPIKey
        |Error::MissingToken(_)
        |Error::Cancelled
        |Error::UploadSizeLimitExceeded(_, _)
        |Error::Failure(_)
        |Error::BadRequest(_)
        |Error::FieldClash(_)
        |Error::JsonDecodeError(_, _) => println!("{}", e),
    },
    Ok(res) => println!("Success: {:?}", res),
}

§Handling Errors

All errors produced by the system are provided either as Result enumeration as return value of the doit() methods, or handed as possibly intermediate results to either the Hub Delegate, or the Authenticator Delegate.

When delegates handle errors or intermediate values, they may have a chance to instruct the system to retry. This makes the system potentially resilient to all kinds of errors.

§Uploads and Downloads

If a method supports downloads, the response body, which is part of the Result, should be read by you to obtain the media. If such a method also supports a Response Result, it will return that by default. You can see it as meta-data for the actual media. To trigger a media download, you will have to set up the builder by making this call: .param("alt", "media").

Methods supporting uploads can do so using up to 2 different protocols: simple and resumable. The distinctiveness of each is represented by customized doit(...) methods, which are then named upload(...) and upload_resumable(...) respectively.

§Customization and Callbacks

You may alter the way an doit() method is called by providing a delegate to the Method Builder before making the final doit() call. Respective methods will be called to provide progress information, as well as determine whether the system should retry on failure.

The delegate trait is default-implemented, allowing you to customize it with minimal effort.

§Optional Parts in Server-Requests

All structures provided by this library are made to be enocodable and decodable via json. Optionals are used to indicate that partial requests are responses are valid. Most optionals are are considered Parts which are identifiable by name, which will be sent to the server to indicate either the set parts of the request or the desired parts in the response.

§Builder Arguments

Using method builders, you are able to prepare an action call by repeatedly calling it’s methods. These will always take a single argument, for which the following statements are true.

PODs are handed by copy
strings are passed as &str
request values are moved

Arguments will always be copied or cloned into the builder, to make them independent of their original life times.

Structs§

CloudMachineLearningEngine: Central instance to access all CloudMachineLearningEngine related resource activities
DefaultDelegate: A delegate with a conservative default implementation, which is used if no other delegate is set.
ErrorResponse: A utility to represent detailed errors we might see in case there are BadRequests. The latter happen if the sent parameters or request structures are unsound
GoogleApi__HttpBody: 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.
GoogleCloudMlV1beta1_HyperparameterOutput_HyperparameterMetric: An observed value of a metric.
GoogleCloudMlV1beta1__CancelJobRequest: Request message for the CancelJob method.
GoogleCloudMlV1beta1__GetConfigResponse: Returns service account information associated with a project.
GoogleCloudMlV1beta1__HyperparameterOutput: 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.
GoogleCloudMlV1beta1__HyperparameterSpec: Represents a set of hyperparameters to optimize.
GoogleCloudMlV1beta1__Job: Represents a training or prediction job.
GoogleCloudMlV1beta1__ListJobsResponse: Response message for the ListJobs method.
GoogleCloudMlV1beta1__ListModelsResponse: Response message for the ListModels method.
GoogleCloudMlV1beta1__ListVersionsResponse: Response message for the ListVersions method.
GoogleCloudMlV1beta1__ManualScaling: Options for manually scaling a model.
GoogleCloudMlV1beta1__Model: Represents a machine learning solution.
GoogleCloudMlV1beta1__ParameterSpec: Represents a single hyperparameter to optimize.
GoogleCloudMlV1beta1__PredictRequest: Request for predictions to be issued against a trained model.
GoogleCloudMlV1beta1__PredictionInput: Represents input parameters for a prediction job.
GoogleCloudMlV1beta1__PredictionOutput: Represents results of a prediction job.
GoogleCloudMlV1beta1__SetDefaultVersionRequest: Request message for the SetDefaultVersion request.
GoogleCloudMlV1beta1__TrainingInput: Represents input parameters for a training job.
GoogleCloudMlV1beta1__TrainingOutput: Represents results of a training job. Output only.
GoogleCloudMlV1beta1__Version: Represents a version of the model.
GoogleLongrunning__ListOperationsResponse: The response message for Operations.ListOperations.
GoogleLongrunning__Operation: This resource represents a long-running operation that is the result of a network API call.
GoogleProtobuf__Empty: 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:
GoogleRpc__Status: 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. The error model is designed to be:
MethodInfo: Contains information about an API request.
MultiPartReader: Provides a Read interface that converts multiple parts into the protocol identified by RFC2387. Note: This implementation is just as rich as it needs to be to perform uploads to google APIs, and might not be a fully-featured implementation.
ProjectGetConfigCall: Get the service account information associated with your project. You need this information in order to grant the service account persmissions for the Google Cloud Storage location where you put your model training code for training the model with Google Cloud Machine Learning.
ProjectJobCancelCall: Cancels a running job.
ProjectJobCreateCall: Creates a training or a batch prediction job.
ProjectJobGetCall: Describes a job.
ProjectJobListCall: Lists the jobs in the project.
ProjectMethods: A builder providing access to all methods supported on project resources. It is not used directly, but through the CloudMachineLearningEngine hub.
ProjectModelCreateCall: Creates a model which will later contain one or more versions.
ProjectModelDeleteCall: Deletes a model.
ProjectModelGetCall: 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).
ProjectModelListCall: Lists the models in a project.
ProjectModelVersionCreateCall: Creates a new version of a model from a trained TensorFlow model.
ProjectModelVersionDeleteCall: Deletes a model version.
ProjectModelVersionGetCall: Gets information about a model version.
ProjectModelVersionListCall: Gets basic information about all the versions of a model.
ProjectModelVersionSetDefaultCall: Designates a version to be the default for the model.
ProjectOperationCancelCall: 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.
ProjectOperationDeleteCall: 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.
ProjectOperationGetCall: 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.
ProjectOperationListCall: Lists operations that match the specified filter in the request. If the server doesn’t support this method, it returns UNIMPLEMENTED.
ProjectPredictCall: Performs prediction on the data in the request.

Enums§

Error
Scope: Identifies the an OAuth2 authorization scope. A scope is needed when requesting an authorization token.

Traits§

CallBuilder: Identifies types which represent builders for a particular resource method
Delegate: A trait specifying functionality to help controlling any request performed by the API. The trait has a conservative default implementation.
Hub: Identifies the Hub. There is only one per library, this trait is supposed to make intended use more explicit. The hub allows to access all resource methods more easily.
MethodsBuilder: Identifies types for building methods of a particular resource type
NestedType: Identifies types which are only used by other types internally. They have no special meaning, this trait just marks them for completeness.
Part: Identifies types which are only used as part of other types, which usually are carrying the Resource trait.
ReadSeek: A utility to specify reader types which provide seeking capabilities too
RequestValue: Identifies types which are used in API requests.
Resource: Identifies types which can be inserted and deleted. Types with this trait are most commonly used by clients of this API.
ResponseResult: Identifies types which are used in API responses.
ToParts: A trait for all types that can convert themselves into a parts string

Functions§

remove_json_null_values

Type Aliases§

Result: A universal result type used as return for all calls.