class Google::Apis::MlV1::GoogleCloudMlV1Model

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.

Attributes

default_version[RW]

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. Corresponds to the JSON property `defaultVersion` @return [Google::Apis::MlV1::GoogleCloudMlV1Version]

description[RW]

Optional. The description specified for the model when it was created. Corresponds to the JSON property `description` @return [String]

etag[RW]

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended. Corresponds to the JSON property `etag` NOTE: Values are automatically base64 encoded/decoded in the client library. @return [String]

labels[RW]

Optional. One or more labels that you can add, to organize your models. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels. Corresponds to the JSON property `labels` @return [Hash<String,String>]

name[RW]

Required. The name specified for the model when it was created. The model name must be unique within the project it is created in. Corresponds to the JSON property `name` @return [String]

online_prediction_console_logging[RW]

Optional. If true, online prediction nodes send `stderr` and `stdout` streams to Cloud Logging. These can be more verbose than the standard access logs (see `onlinePredictionLogging`) and can incur higher cost. However, they are helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high QPS. Estimate your costs before enabling this option. Default is false. Corresponds to the JSON property `onlinePredictionConsoleLogging` @return [Boolean]

online_prediction_console_logging?[RW]

Optional. If true, online prediction nodes send `stderr` and `stdout` streams to Cloud Logging. These can be more verbose than the standard access logs (see `onlinePredictionLogging`) and can incur higher cost. However, they are helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high QPS. Estimate your costs before enabling this option. Default is false. Corresponds to the JSON property `onlinePredictionConsoleLogging` @return [Boolean]

online_prediction_logging[RW]

Optional. If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each request. Note that [logs may incur a cost](/ stackdriver/pricing), especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. Default is false. Corresponds to the JSON property `onlinePredictionLogging` @return [Boolean]

online_prediction_logging?[RW]

Optional. If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each request. Note that [logs may incur a cost](/ stackdriver/pricing), especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. Default is false. Corresponds to the JSON property `onlinePredictionLogging` @return [Boolean]

regions[RW]

Optional. The list of regions where the model is going to be deployed. Only one region per model is supported. Defaults to 'us-central1' if nothing is set. See the available regions for AI Platform services. Note: * No matter where a model is deployed, it can always be accessed by users from anywhere, both for online and batch prediction. * The region for a batch prediction job is set by the region field when submitting the batch prediction job and does not take its value from this field. Corresponds to the JSON property `regions` @return [Array<String>]

Public Class Methods

new(**args) click to toggle source
# File lib/google/apis/ml_v1/classes.rb, line 1811
def initialize(**args)
   update!(**args)
end

Public Instance Methods

update!(**args) click to toggle source

Update properties of this object

# File lib/google/apis/ml_v1/classes.rb, line 1816
def update!(**args)
  @default_version = args[:default_version] if args.key?(:default_version)
  @description = args[:description] if args.key?(:description)
  @etag = args[:etag] if args.key?(:etag)
  @labels = args[:labels] if args.key?(:labels)
  @name = args[:name] if args.key?(:name)
  @online_prediction_console_logging = args[:online_prediction_console_logging] if args.key?(:online_prediction_console_logging)
  @online_prediction_logging = args[:online_prediction_logging] if args.key?(:online_prediction_logging)
  @regions = args[:regions] if args.key?(:regions)
end