google_api_machine_learning v0.7.1 API Reference

Modules

API calls for all endpoints tagged Operations.

API calls for all endpoints tagged Projects.

Handle Tesla connections for GoogleApi.MachineLearning.V1.

Helper functions for deserializing responses into models.

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.

Represents a hardware accelerator request config.

Options for automatically scaling a model.

Represents output related to a built-in algorithm Job.

Request message for the CancelJob method.

Attributes

  • availableAccelerators ([String.t]): Available accelerators for the capability. Defaults to: null.

Attributes

  • tpuServiceAccount (String.t): The service account Cloud ML uses to run on TPU node. Defaults to: null.

Returns service account information associated with a project.

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.

Represents a set of hyperparameters to optimize.

Represents a training or prediction job.

Response message for the ListJobs method.

Attributes

  • locations ([GoogleCloudMlV1Location]): Locations where at least one type of CMLE capability is available. Defaults to: null.
  • nextPageToken (String.t): Optional. Pass this token as the `page_token` field of the request for a subsequent call. Defaults to: null.

Response message for the ListModels method.

Response message for the ListVersions method.

Attributes

  • capabilities ([GoogleCloudMlV1Capability]): Capabilities available in the location. Defaults to: null.
  • name (String.t): Defaults to: null.

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.

Represents the metadata of the long-running operation.

Represents a single hyperparameter to optimize.

Request for predictions to be issued against a trained model.

Represents input parameters for a prediction job.

Represents the configuration for a replica in a cluster.

Request message for the SetDefaultVersion request.

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>.

Represents results of a training job. Output only.

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.

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.

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.

Associates `members` with a `role`.

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.

Request message for `SetIamPolicy` method.

Request message for `TestIamPermissions` method.

Response message for `TestIamPermissions` method.

Increment a streamz counter with the specified metric and field names. Metric names should start with a '/', generally be lowercase-only, and end in "_count". Field names should not contain an initial slash. The actual exported metric names will have "/iam/policy" prepended. Field names correspond to IAM request parameters and field values are their respective values. At present the only supported field names are - "iam_principal", corresponding to IAMContext.principal; - "" (empty string), resulting in one aggretated counter with no field. Examples: counter { metric: "/debug_access_count" field: "iam_principal" } ==> increment counter /iam/policy/backend_debug_access_count {iam_principal=[value of IAMContext.principal]} At this time we do not support: multiple field names (though this may be supported in the future) decrementing the counter * incrementing it by anything other than 1

The response message for Operations.ListOperations.

This resource represents a long-running operation that is the result of a network API call.

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 `{}`.

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: - 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.

Represents an expression text. Example: title: "User account presence" description: "Determines whether the request has a user account" expression: "size(request.user) > 0"

Helper functions for building Tesla requests.