# Copyright 2015 Google Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. require 'date' require 'google/apis/core/base_service' require 'google/apis/core/json_representation' require 'google/apis/core/hashable' require 'google/apis/errors' module Google module Apis module MlV1 # 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. class GoogleApiHttpBody include Google::Apis::Core::Hashable # The HTTP Content-Type header value specifying the content type of the body. # Corresponds to the JSON property `contentType` # @return [String] attr_accessor :content_type # The HTTP request/response body as raw binary. # Corresponds to the JSON property `data` # NOTE: Values are automatically base64 encoded/decoded in the client library. # @return [String] attr_accessor :data # Application specific response metadata. Must be set in the first response # for streaming APIs. # Corresponds to the JSON property `extensions` # @return [Array>] attr_accessor :extensions def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @content_type = args[:content_type] if args.key?(:content_type) @data = args[:data] if args.key?(:data) @extensions = args[:extensions] if args.key?(:extensions) end end # An observed value of a metric. class GoogleCloudMlV1HyperparameterOutputHyperparameterMetric include Google::Apis::Core::Hashable # The objective value at this training step. # Corresponds to the JSON property `objectiveValue` # @return [Float] attr_accessor :objective_value # The global training step for this metric. # Corresponds to the JSON property `trainingStep` # @return [Fixnum] attr_accessor :training_step def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @objective_value = args[:objective_value] if args.key?(:objective_value) @training_step = args[:training_step] if args.key?(:training_step) end end # Represents a hardware accelerator request config. # Note that the AcceleratorConfig can be used in both Jobs and Versions. # Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and # [accelerators for online # prediction](/ml-engine/docs/machine-types-online-prediction#gpus). class GoogleCloudMlV1AcceleratorConfig include Google::Apis::Core::Hashable # The number of accelerators to attach to each machine running the job. # Corresponds to the JSON property `count` # @return [Fixnum] attr_accessor :count # The type of accelerator to use. # Corresponds to the JSON property `type` # @return [String] attr_accessor :type def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @count = args[:count] if args.key?(:count) @type = args[:type] if args.key?(:type) end end # Options for automatically scaling a model. class GoogleCloudMlV1AutoScaling include Google::Apis::Core::Hashable # 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](/ml-engine/docs/pricing), # 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](/ml-engine/docs/machine-types-online-prediction), # `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](/ml-engine/docs/machine-types-online-prediction), # `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](#Version.FIELDS.accelerator_config). 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
        #
# Corresponds to the JSON property `minNodes` # @return [Fixnum] attr_accessor :min_nodes def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @min_nodes = args[:min_nodes] if args.key?(:min_nodes) end end # Represents output related to a built-in algorithm Job. class GoogleCloudMlV1BuiltInAlgorithmOutput include Google::Apis::Core::Hashable # Framework on which the built-in algorithm was trained. # Corresponds to the JSON property `framework` # @return [String] attr_accessor :framework # 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. # Corresponds to the JSON property `modelPath` # @return [String] attr_accessor :model_path # Python version on which the built-in algorithm was trained. # Corresponds to the JSON property `pythonVersion` # @return [String] attr_accessor :python_version # AI Platform runtime version on which the built-in algorithm was # trained. # Corresponds to the JSON property `runtimeVersion` # @return [String] attr_accessor :runtime_version def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @framework = args[:framework] if args.key?(:framework) @model_path = args[:model_path] if args.key?(:model_path) @python_version = args[:python_version] if args.key?(:python_version) @runtime_version = args[:runtime_version] if args.key?(:runtime_version) end end # Request message for the CancelJob method. class GoogleCloudMlV1CancelJobRequest include Google::Apis::Core::Hashable def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) end end # class GoogleCloudMlV1Capability include Google::Apis::Core::Hashable # Available accelerators for the capability. # Corresponds to the JSON property `availableAccelerators` # @return [Array] attr_accessor :available_accelerators # # Corresponds to the JSON property `type` # @return [String] attr_accessor :type def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @available_accelerators = args[:available_accelerators] if args.key?(:available_accelerators) @type = args[:type] if args.key?(:type) end end # class GoogleCloudMlV1Config include Google::Apis::Core::Hashable # The service account Cloud ML uses to run on TPU node. # Corresponds to the JSON property `tpuServiceAccount` # @return [String] attr_accessor :tpu_service_account def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @tpu_service_account = args[:tpu_service_account] if args.key?(:tpu_service_account) end end # Returns service account information associated with a project. class GoogleCloudMlV1GetConfigResponse include Google::Apis::Core::Hashable # # Corresponds to the JSON property `config` # @return [Google::Apis::MlV1::GoogleCloudMlV1Config] attr_accessor :config # The service account Cloud ML uses to access resources in the project. # Corresponds to the JSON property `serviceAccount` # @return [String] attr_accessor :service_account # The project number for `service_account`. # Corresponds to the JSON property `serviceAccountProject` # @return [Fixnum] attr_accessor :service_account_project def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @config = args[:config] if args.key?(:config) @service_account = args[:service_account] if args.key?(:service_account) @service_account_project = args[:service_account_project] if args.key?(:service_account_project) end end # 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. class GoogleCloudMlV1HyperparameterOutput include Google::Apis::Core::Hashable # All recorded object metrics for this trial. This field is not currently # populated. # Corresponds to the JSON property `allMetrics` # @return [Array] attr_accessor :all_metrics # Represents output related to a built-in algorithm Job. # Corresponds to the JSON property `builtInAlgorithmOutput` # @return [Google::Apis::MlV1::GoogleCloudMlV1BuiltInAlgorithmOutput] attr_accessor :built_in_algorithm_output # Output only. End time for the trial. # Corresponds to the JSON property `endTime` # @return [String] attr_accessor :end_time # An observed value of a metric. # Corresponds to the JSON property `finalMetric` # @return [Google::Apis::MlV1::GoogleCloudMlV1HyperparameterOutputHyperparameterMetric] attr_accessor :final_metric # The hyperparameters given to this trial. # Corresponds to the JSON property `hyperparameters` # @return [Hash] attr_accessor :hyperparameters # True if the trial is stopped early. # Corresponds to the JSON property `isTrialStoppedEarly` # @return [Boolean] attr_accessor :is_trial_stopped_early alias_method :is_trial_stopped_early?, :is_trial_stopped_early # Output only. Start time for the trial. # Corresponds to the JSON property `startTime` # @return [String] attr_accessor :start_time # Output only. The detailed state of the trial. # Corresponds to the JSON property `state` # @return [String] attr_accessor :state # The trial id for these results. # Corresponds to the JSON property `trialId` # @return [String] attr_accessor :trial_id def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @all_metrics = args[:all_metrics] if args.key?(:all_metrics) @built_in_algorithm_output = args[:built_in_algorithm_output] if args.key?(:built_in_algorithm_output) @end_time = args[:end_time] if args.key?(:end_time) @final_metric = args[:final_metric] if args.key?(:final_metric) @hyperparameters = args[:hyperparameters] if args.key?(:hyperparameters) @is_trial_stopped_early = args[:is_trial_stopped_early] if args.key?(:is_trial_stopped_early) @start_time = args[:start_time] if args.key?(:start_time) @state = args[:state] if args.key?(:state) @trial_id = args[:trial_id] if args.key?(:trial_id) end end # Represents a set of hyperparameters to optimize. class GoogleCloudMlV1HyperparameterSpec include Google::Apis::Core::Hashable # Optional. The search algorithm specified for the hyperparameter # tuning job. # Uses the default AI Platform hyperparameter tuning # algorithm if unspecified. # Corresponds to the JSON property `algorithm` # @return [String] attr_accessor :algorithm # Optional. Indicates if the hyperparameter tuning job enables auto trial # early stopping. # Corresponds to the JSON property `enableTrialEarlyStopping` # @return [Boolean] attr_accessor :enable_trial_early_stopping alias_method :enable_trial_early_stopping?, :enable_trial_early_stopping # Required. The type of goal to use for tuning. Available types are # `MAXIMIZE` and `MINIMIZE`. # Defaults to `MAXIMIZE`. # Corresponds to the JSON property `goal` # @return [String] attr_accessor :goal # Optional. The TensorFlow summary tag name to use for optimizing trials. For # current versions of TensorFlow, this tag name should exactly match what is # shown in TensorBoard, including all scopes. For versions of TensorFlow # prior to 0.12, this should be only the tag passed to tf.Summary. # By default, "training/hptuning/metric" will be used. # Corresponds to the JSON property `hyperparameterMetricTag` # @return [String] attr_accessor :hyperparameter_metric_tag # Optional. The number of failed trials that need to be seen before failing # the hyperparameter tuning job. You can specify this field to override the # default failing criteria for AI Platform hyperparameter tuning jobs. # Defaults to zero, which means the service decides when a hyperparameter # job should fail. # Corresponds to the JSON property `maxFailedTrials` # @return [Fixnum] attr_accessor :max_failed_trials # Optional. The number of training trials to run concurrently. # You can reduce the time it takes to perform hyperparameter tuning by adding # trials in parallel. However, each trail only benefits from the information # gained in completed trials. That means that a trial does not get access to # the results of trials running at the same time, which could reduce the # quality of the overall optimization. # Each trial will use the same scale tier and machine types. # Defaults to one. # Corresponds to the JSON property `maxParallelTrials` # @return [Fixnum] attr_accessor :max_parallel_trials # Optional. How many training trials should be attempted to optimize # the specified hyperparameters. # Defaults to one. # Corresponds to the JSON property `maxTrials` # @return [Fixnum] attr_accessor :max_trials # Required. The set of parameters to tune. # Corresponds to the JSON property `params` # @return [Array] attr_accessor :params # Optional. The prior hyperparameter tuning job id that users hope to # continue with. The job id will be used to find the corresponding vizier # study guid and resume the study. # Corresponds to the JSON property `resumePreviousJobId` # @return [String] attr_accessor :resume_previous_job_id def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @algorithm = args[:algorithm] if args.key?(:algorithm) @enable_trial_early_stopping = args[:enable_trial_early_stopping] if args.key?(:enable_trial_early_stopping) @goal = args[:goal] if args.key?(:goal) @hyperparameter_metric_tag = args[:hyperparameter_metric_tag] if args.key?(:hyperparameter_metric_tag) @max_failed_trials = args[:max_failed_trials] if args.key?(:max_failed_trials) @max_parallel_trials = args[:max_parallel_trials] if args.key?(:max_parallel_trials) @max_trials = args[:max_trials] if args.key?(:max_trials) @params = args[:params] if args.key?(:params) @resume_previous_job_id = args[:resume_previous_job_id] if args.key?(:resume_previous_job_id) end end # Represents a training or prediction job. class GoogleCloudMlV1Job include Google::Apis::Core::Hashable # Output only. When the job was created. # Corresponds to the JSON property `createTime` # @return [String] attr_accessor :create_time # Output only. When the job processing was completed. # Corresponds to the JSON property `endTime` # @return [String] attr_accessor :end_time # Output only. The details of a failure or a cancellation. # Corresponds to the JSON property `errorMessage` # @return [String] attr_accessor :error_message # `etag` is used for optimistic concurrency control as a way to help # prevent simultaneous updates of a job from overwriting each other. # It is strongly suggested that systems make use of the `etag` in the # read-modify-write cycle to perform job updates in order to avoid race # conditions: An `etag` is returned in the response to `GetJob`, and # systems are expected to put that etag in the request to `UpdateJob` to # ensure that their change will be applied to the same version of the job. # Corresponds to the JSON property `etag` # NOTE: Values are automatically base64 encoded/decoded in the client library. # @return [String] attr_accessor :etag # Required. The user-specified id of the job. # Corresponds to the JSON property `jobId` # @return [String] attr_accessor :job_id # Optional. One or more labels that you can add, to organize your jobs. # 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] attr_accessor :labels # Represents input parameters for a prediction job. # Corresponds to the JSON property `predictionInput` # @return [Google::Apis::MlV1::GoogleCloudMlV1PredictionInput] attr_accessor :prediction_input # Represents results of a prediction job. # Corresponds to the JSON property `predictionOutput` # @return [Google::Apis::MlV1::GoogleCloudMlV1PredictionOutput] attr_accessor :prediction_output # Output only. When the job processing was started. # Corresponds to the JSON property `startTime` # @return [String] attr_accessor :start_time # Output only. The detailed state of a job. # Corresponds to the JSON property `state` # @return [String] attr_accessor :state # 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 # submitting a training # job. # Corresponds to the JSON property `trainingInput` # @return [Google::Apis::MlV1::GoogleCloudMlV1TrainingInput] attr_accessor :training_input # Represents results of a training job. Output only. # Corresponds to the JSON property `trainingOutput` # @return [Google::Apis::MlV1::GoogleCloudMlV1TrainingOutput] attr_accessor :training_output def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @create_time = args[:create_time] if args.key?(:create_time) @end_time = args[:end_time] if args.key?(:end_time) @error_message = args[:error_message] if args.key?(:error_message) @etag = args[:etag] if args.key?(:etag) @job_id = args[:job_id] if args.key?(:job_id) @labels = args[:labels] if args.key?(:labels) @prediction_input = args[:prediction_input] if args.key?(:prediction_input) @prediction_output = args[:prediction_output] if args.key?(:prediction_output) @start_time = args[:start_time] if args.key?(:start_time) @state = args[:state] if args.key?(:state) @training_input = args[:training_input] if args.key?(:training_input) @training_output = args[:training_output] if args.key?(:training_output) end end # Response message for the ListJobs method. class GoogleCloudMlV1ListJobsResponse include Google::Apis::Core::Hashable # The list of jobs. # Corresponds to the JSON property `jobs` # @return [Array] attr_accessor :jobs # Optional. Pass this token as the `page_token` field of the request for a # subsequent call. # Corresponds to the JSON property `nextPageToken` # @return [String] attr_accessor :next_page_token def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @jobs = args[:jobs] if args.key?(:jobs) @next_page_token = args[:next_page_token] if args.key?(:next_page_token) end end # class GoogleCloudMlV1ListLocationsResponse include Google::Apis::Core::Hashable # Locations where at least one type of CMLE capability is available. # Corresponds to the JSON property `locations` # @return [Array] attr_accessor :locations # Optional. Pass this token as the `page_token` field of the request for a # subsequent call. # Corresponds to the JSON property `nextPageToken` # @return [String] attr_accessor :next_page_token def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @locations = args[:locations] if args.key?(:locations) @next_page_token = args[:next_page_token] if args.key?(:next_page_token) end end # Response message for the ListModels method. class GoogleCloudMlV1ListModelsResponse include Google::Apis::Core::Hashable # The list of models. # Corresponds to the JSON property `models` # @return [Array] attr_accessor :models # Optional. Pass this token as the `page_token` field of the request for a # subsequent call. # Corresponds to the JSON property `nextPageToken` # @return [String] attr_accessor :next_page_token def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @models = args[:models] if args.key?(:models) @next_page_token = args[:next_page_token] if args.key?(:next_page_token) end end # Response message for the ListVersions method. class GoogleCloudMlV1ListVersionsResponse include Google::Apis::Core::Hashable # Optional. Pass this token as the `page_token` field of the request for a # subsequent call. # Corresponds to the JSON property `nextPageToken` # @return [String] attr_accessor :next_page_token # The list of versions. # Corresponds to the JSON property `versions` # @return [Array] attr_accessor :versions def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @next_page_token = args[:next_page_token] if args.key?(:next_page_token) @versions = args[:versions] if args.key?(:versions) end end # class GoogleCloudMlV1Location include Google::Apis::Core::Hashable # Capabilities available in the location. # Corresponds to the JSON property `capabilities` # @return [Array] attr_accessor :capabilities # # Corresponds to the JSON property `name` # @return [String] attr_accessor :name def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @capabilities = args[:capabilities] if args.key?(:capabilities) @name = args[:name] if args.key?(:name) end end # Options for manually scaling a model. class GoogleCloudMlV1ManualScaling include Google::Apis::Core::Hashable # The number of nodes to allocate for this model. These nodes are always up, # starting from the time the model is deployed, so the cost of operating # this model will be proportional to `nodes` * number of hours since # last billing cycle plus the cost for each prediction performed. # Corresponds to the JSON property `nodes` # @return [Fixnum] attr_accessor :nodes def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @nodes = args[:nodes] if args.key?(:nodes) end end # 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. class GoogleCloudMlV1Model include Google::Apis::Core::Hashable # 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](/ml-engine/reference/rest/v1/projects.models. # versions/list). # Corresponds to the JSON property `defaultVersion` # @return [Google::Apis::MlV1::GoogleCloudMlV1Version] attr_accessor :default_version # Optional. The description specified for the model when it was created. # Corresponds to the JSON property `description` # @return [String] attr_accessor :description # `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] attr_accessor :etag # 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] attr_accessor :labels # 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] attr_accessor :name # Optional. If true, online prediction nodes send `stderr` and `stdout` # streams to Stackdriver 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 # [Stackdriver 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] attr_accessor :online_prediction_console_logging alias_method :online_prediction_console_logging?, :online_prediction_console_logging # Optional. If true, online prediction access logs are sent to StackDriver # Logging. These logs are like standard server access logs, containing # information like timestamp and latency for each request. Note that # [Stackdriver 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] attr_accessor :online_prediction_logging alias_method :online_prediction_logging?, :online_prediction_logging # Optional. The list of regions where the model is going to be deployed. # Currently 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] attr_accessor :regions def initialize(**args) update!(**args) end # Update properties of this object 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 end # Represents the metadata of the long-running operation. class GoogleCloudMlV1OperationMetadata include Google::Apis::Core::Hashable # The time the operation was submitted. # Corresponds to the JSON property `createTime` # @return [String] attr_accessor :create_time # The time operation processing completed. # Corresponds to the JSON property `endTime` # @return [String] attr_accessor :end_time # Indicates whether a request to cancel this operation has been made. # Corresponds to the JSON property `isCancellationRequested` # @return [Boolean] attr_accessor :is_cancellation_requested alias_method :is_cancellation_requested?, :is_cancellation_requested # The user labels, inherited from the model or the model version being # operated on. # Corresponds to the JSON property `labels` # @return [Hash] attr_accessor :labels # Contains the name of the model associated with the operation. # Corresponds to the JSON property `modelName` # @return [String] attr_accessor :model_name # The operation type. # Corresponds to the JSON property `operationType` # @return [String] attr_accessor :operation_type # Contains the project number associated with the operation. # Corresponds to the JSON property `projectNumber` # @return [Fixnum] attr_accessor :project_number # The time operation processing started. # Corresponds to the JSON property `startTime` # @return [String] attr_accessor :start_time # 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](/ml-engine/reference/rest/v1/projects.models. # versions/list). # Corresponds to the JSON property `version` # @return [Google::Apis::MlV1::GoogleCloudMlV1Version] attr_accessor :version def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @create_time = args[:create_time] if args.key?(:create_time) @end_time = args[:end_time] if args.key?(:end_time) @is_cancellation_requested = args[:is_cancellation_requested] if args.key?(:is_cancellation_requested) @labels = args[:labels] if args.key?(:labels) @model_name = args[:model_name] if args.key?(:model_name) @operation_type = args[:operation_type] if args.key?(:operation_type) @project_number = args[:project_number] if args.key?(:project_number) @start_time = args[:start_time] if args.key?(:start_time) @version = args[:version] if args.key?(:version) end end # Represents a single hyperparameter to optimize. class GoogleCloudMlV1ParameterSpec include Google::Apis::Core::Hashable # Required if type is `CATEGORICAL`. The list of possible categories. # Corresponds to the JSON property `categoricalValues` # @return [Array] attr_accessor :categorical_values # Required 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. # Corresponds to the JSON property `discreteValues` # @return [Array] attr_accessor :discrete_values # Required if type is `DOUBLE` or `INTEGER`. This field # should be unset if type is `CATEGORICAL`. This value should be integers if # type is `INTEGER`. # Corresponds to the JSON property `maxValue` # @return [Float] attr_accessor :max_value # Required if type is `DOUBLE` or `INTEGER`. This field # should be unset if type is `CATEGORICAL`. This value should be integers if # type is INTEGER. # Corresponds to the JSON property `minValue` # @return [Float] attr_accessor :min_value # Required. The parameter name must be unique amongst all ParameterConfigs in # a HyperparameterSpec message. E.g., "learning_rate". # Corresponds to the JSON property `parameterName` # @return [String] attr_accessor :parameter_name # Optional. How the parameter should be scaled to the hypercube. # Leave unset for categorical parameters. # Some kind of scaling is strongly recommended for real or integral # parameters (e.g., `UNIT_LINEAR_SCALE`). # Corresponds to the JSON property `scaleType` # @return [String] attr_accessor :scale_type # Required. The type of the parameter. # Corresponds to the JSON property `type` # @return [String] attr_accessor :type def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @categorical_values = args[:categorical_values] if args.key?(:categorical_values) @discrete_values = args[:discrete_values] if args.key?(:discrete_values) @max_value = args[:max_value] if args.key?(:max_value) @min_value = args[:min_value] if args.key?(:min_value) @parameter_name = args[:parameter_name] if args.key?(:parameter_name) @scale_type = args[:scale_type] if args.key?(:scale_type) @type = args[:type] if args.key?(:type) end end # Request for predictions to be issued against a trained model. class GoogleCloudMlV1PredictRequest include Google::Apis::Core::Hashable # 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. # Corresponds to the JSON property `httpBody` # @return [Google::Apis::MlV1::GoogleApiHttpBody] attr_accessor :http_body def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @http_body = args[:http_body] if args.key?(:http_body) end end # Represents input parameters for a prediction job. class GoogleCloudMlV1PredictionInput include Google::Apis::Core::Hashable # Optional. Number of records per batch, defaults to 64. # The service will buffer batch_size number of records in memory before # invoking one Tensorflow prediction call internally. So take the record # size and memory available into consideration when setting this parameter. # Corresponds to the JSON property `batchSize` # @return [Fixnum] attr_accessor :batch_size # Required. The format of the input data files. # Corresponds to the JSON property `dataFormat` # @return [String] attr_accessor :data_format # Required. The Cloud Storage location of the input data files. May contain # wildcards. # Corresponds to the JSON property `inputPaths` # @return [Array] attr_accessor :input_paths # Optional. The maximum number of workers to be used for parallel processing. # Defaults to 10 if not specified. # Corresponds to the JSON property `maxWorkerCount` # @return [Fixnum] attr_accessor :max_worker_count # Use this field if you want to use the default version for the specified # model. The string must use the following format: # `"projects/YOUR_PROJECT/models/YOUR_MODEL"` # Corresponds to the JSON property `modelName` # @return [String] attr_accessor :model_name # Optional. Format of the output data files, defaults to JSON. # Corresponds to the JSON property `outputDataFormat` # @return [String] attr_accessor :output_data_format # Required. The output Google Cloud Storage location. # Corresponds to the JSON property `outputPath` # @return [String] attr_accessor :output_path # Required. The Google Compute Engine region to run the prediction job in. # See the available regions # for AI Platform services. # Corresponds to the JSON property `region` # @return [String] attr_accessor :region # Optional. The AI Platform runtime version to use for this batch # prediction. If not set, AI Platform will pick the runtime version used # during the CreateVersion request for this model version, or choose the # latest stable version when model version information is not available # such as when the model is specified by uri. # Corresponds to the JSON property `runtimeVersion` # @return [String] attr_accessor :runtime_version # Optional. The name of the signature defined in the SavedModel to use for # this job. Please refer to # [SavedModel](https://tensorflow.github.io/serving/serving_basic.html) # for information about how to use signatures. # Defaults to # [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/ # tf/saved_model/signature_constants) # , which is "serving_default". # Corresponds to the JSON property `signatureName` # @return [String] attr_accessor :signature_name # Use this field if you want to specify a Google Cloud Storage path for # the model to use. # Corresponds to the JSON property `uri` # @return [String] attr_accessor :uri # Use this field if you want to specify a version of the model to use. The # string is formatted the same way as `model_version`, with the addition # of the version information: # `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"` # Corresponds to the JSON property `versionName` # @return [String] attr_accessor :version_name def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @batch_size = args[:batch_size] if args.key?(:batch_size) @data_format = args[:data_format] if args.key?(:data_format) @input_paths = args[:input_paths] if args.key?(:input_paths) @max_worker_count = args[:max_worker_count] if args.key?(:max_worker_count) @model_name = args[:model_name] if args.key?(:model_name) @output_data_format = args[:output_data_format] if args.key?(:output_data_format) @output_path = args[:output_path] if args.key?(:output_path) @region = args[:region] if args.key?(:region) @runtime_version = args[:runtime_version] if args.key?(:runtime_version) @signature_name = args[:signature_name] if args.key?(:signature_name) @uri = args[:uri] if args.key?(:uri) @version_name = args[:version_name] if args.key?(:version_name) end end # Represents results of a prediction job. class GoogleCloudMlV1PredictionOutput include Google::Apis::Core::Hashable # The number of data instances which resulted in errors. # Corresponds to the JSON property `errorCount` # @return [Fixnum] attr_accessor :error_count # Node hours used by the batch prediction job. # Corresponds to the JSON property `nodeHours` # @return [Float] attr_accessor :node_hours # The output Google Cloud Storage location provided at the job creation time. # Corresponds to the JSON property `outputPath` # @return [String] attr_accessor :output_path # The number of generated predictions. # Corresponds to the JSON property `predictionCount` # @return [Fixnum] attr_accessor :prediction_count def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @error_count = args[:error_count] if args.key?(:error_count) @node_hours = args[:node_hours] if args.key?(:node_hours) @output_path = args[:output_path] if args.key?(:output_path) @prediction_count = args[:prediction_count] if args.key?(:prediction_count) end end # Represents the configuration for a replica in a cluster. class GoogleCloudMlV1ReplicaConfig include Google::Apis::Core::Hashable # Represents a hardware accelerator request config. # Note that the AcceleratorConfig can be used in both Jobs and Versions. # Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and # [accelerators for online # prediction](/ml-engine/docs/machine-types-online-prediction#gpus). # Corresponds to the JSON property `acceleratorConfig` # @return [Google::Apis::MlV1::GoogleCloudMlV1AcceleratorConfig] attr_accessor :accelerator_config # The Docker image to run on the replica. This image must be in Container # Registry. Learn more about [configuring custom # containers](/ml-engine/docs/distributed-training-containers). # Corresponds to the JSON property `imageUri` # @return [String] attr_accessor :image_uri # The AI Platform runtime version that includes a TensorFlow version matching # the one used in the custom container. This field is required if the replica # is a TPU worker that uses a custom container. Otherwise, do not specify # this field. This must be a [runtime version that currently supports # training with # TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support). # Note that the version of TensorFlow included in a runtime version may # differ from the numbering of the runtime version itself, because it may # have a different [patch # version](https://www.tensorflow.org/guide/version_compat# # semantic_versioning_20). # In this field, you must specify the runtime version (TensorFlow minor # version). For example, if your custom container runs TensorFlow `1.x.y`, # specify `1.x`. # Corresponds to the JSON property `tpuTfVersion` # @return [String] attr_accessor :tpu_tf_version def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @accelerator_config = args[:accelerator_config] if args.key?(:accelerator_config) @image_uri = args[:image_uri] if args.key?(:image_uri) @tpu_tf_version = args[:tpu_tf_version] if args.key?(:tpu_tf_version) end end # Configuration for logging request-response pairs to a BigQuery table. # Online prediction requests to a model version and the responses to these # requests are converted to raw strings and saved to the specified BigQuery # table. Logging is constrained by [BigQuery quotas and # limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits, # AI Platform Prediction does not log request-response pairs, but it continues # to serve predictions. # If you are using [continuous # evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to # specify this configuration manually. Setting up continuous evaluation # automatically enables logging of request-response pairs. class GoogleCloudMlV1RequestLoggingConfig include Google::Apis::Core::Hashable # Required. Fully qualified BigQuery table name in the following format: # "project_id.dataset_name.table_name" # The specifcied table must already exist, and the "Cloud ML Service Agent" # for your project must have permission to write to it. The table must have # the following [schema](/bigquery/docs/schemas): # # # # # # # # # #
Field nameTypeMode
modelSTRINGREQUIRED
model_versionSTRINGREQUIRED
timeTIMESTAMPREQUIRED
raw_dataSTRINGREQUIRED
raw_predictionSTRINGNULLABLE
groundtruthSTRINGNULLABLE
# Corresponds to the JSON property `bigqueryTableName` # @return [String] attr_accessor :bigquery_table_name # Percentage of requests to be logged, expressed as a fraction from 0 to 1. # For example, if you want to log 10% of requests, enter `0.1`. The sampling # window is the lifetime of the model version. Defaults to 0. # Corresponds to the JSON property `samplingPercentage` # @return [Float] attr_accessor :sampling_percentage def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @bigquery_table_name = args[:bigquery_table_name] if args.key?(:bigquery_table_name) @sampling_percentage = args[:sampling_percentage] if args.key?(:sampling_percentage) end end # Request message for the SetDefaultVersion request. class GoogleCloudMlV1SetDefaultVersionRequest include Google::Apis::Core::Hashable def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) end end # 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 # submitting a training # job. class GoogleCloudMlV1TrainingInput include Google::Apis::Core::Hashable # Optional. Command line arguments to pass to the program. # Corresponds to the JSON property `args` # @return [Array] attr_accessor :args # Represents a set of hyperparameters to optimize. # Corresponds to the JSON property `hyperparameters` # @return [Google::Apis::MlV1::GoogleCloudMlV1HyperparameterSpec] attr_accessor :hyperparameters # Optional. A Google Cloud Storage path in which to store training outputs # and other data needed for training. This path is passed to your TensorFlow # program as the '--job-dir' command-line argument. The benefit of specifying # this field is that Cloud ML validates the path for use in training. # Corresponds to the JSON property `jobDir` # @return [String] attr_accessor :job_dir # Represents the configuration for a replica in a cluster. # Corresponds to the JSON property `masterConfig` # @return [Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig] attr_accessor :master_config # Optional. Specifies the type of virtual machine to use for your training # job's master worker. You must specify this field when `scaleTier` is set to # `CUSTOM`. # You can use certain Compute Engine machine types directly in this field. # The following types are supported: # - `n1-standard-4` # - `n1-standard-8` # - `n1-standard-16` # - `n1-standard-32` # - `n1-standard-64` # - `n1-standard-96` # - `n1-highmem-2` # - `n1-highmem-4` # - `n1-highmem-8` # - `n1-highmem-16` # - `n1-highmem-32` # - `n1-highmem-64` # - `n1-highmem-96` # - `n1-highcpu-16` # - `n1-highcpu-32` # - `n1-highcpu-64` # - `n1-highcpu-96` # Learn more about [using Compute Engine machine # types](/ml-engine/docs/machine-types#compute-engine-machine-types). # Alternatively, you can use the following legacy machine types: # - `standard` # - `large_model` # - `complex_model_s` # - `complex_model_m` # - `complex_model_l` # - `standard_gpu` # - `complex_model_m_gpu` # - `complex_model_l_gpu` # - `standard_p100` # - `complex_model_m_p100` # - `standard_v100` # - `large_model_v100` # - `complex_model_m_v100` # - `complex_model_l_v100` # Learn more about [using legacy machine # types](/ml-engine/docs/machine-types#legacy-machine-types). # Finally, if you want to use a TPU for training, specify `cloud_tpu` in this # field. Learn more about the [special configuration options for training # with # TPUs](/ml-engine/docs/tensorflow/using-tpus#configuring_a_custom_tpu_machine). # Corresponds to the JSON property `masterType` # @return [String] attr_accessor :master_type # Required. The Google Cloud Storage location of the packages with # the training program and any additional dependencies. # The maximum number of package URIs is 100. # Corresponds to the JSON property `packageUris` # @return [Array] attr_accessor :package_uris # Represents the configuration for a replica in a cluster. # Corresponds to the JSON property `parameterServerConfig` # @return [Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig] attr_accessor :parameter_server_config # Optional. The number of parameter server replicas to use for the training # job. Each replica in the cluster will be of the type specified in # `parameter_server_type`. # This value can only be used when `scale_tier` is set to `CUSTOM`.If you # set this value, you must also set `parameter_server_type`. # The default value is zero. # Corresponds to the JSON property `parameterServerCount` # @return [Fixnum] attr_accessor :parameter_server_count # Optional. Specifies the type of virtual machine to use for your training # job's parameter server. # The supported values are the same as those described in the entry for # `master_type`. # This value must be consistent with the category of machine type that # `masterType` uses. In other words, both must be Compute Engine machine # types or both must be legacy machine types. # This value must be present when `scaleTier` is set to `CUSTOM` and # `parameter_server_count` is greater than zero. # Corresponds to the JSON property `parameterServerType` # @return [String] attr_accessor :parameter_server_type # Required. The Python module name to run after installing the packages. # Corresponds to the JSON property `pythonModule` # @return [String] attr_accessor :python_module # Optional. The version of Python used in training. If not set, the default # version is '2.7'. Python '3.5' is available when `runtime_version` is set # to '1.4' and above. Python '2.7' works with all supported # runtime versions. # Corresponds to the JSON property `pythonVersion` # @return [String] attr_accessor :python_version # Required. The Google Compute Engine region to run the training job in. # See the available regions # for AI Platform services. # Corresponds to the JSON property `region` # @return [String] attr_accessor :region # Optional. The AI Platform runtime version to use for training. If not # set, AI Platform uses the default stable version, 1.0. For more # information, see the # runtime version list # and # how to manage runtime versions. # Corresponds to the JSON property `runtimeVersion` # @return [String] attr_accessor :runtime_version # Required. Specifies the machine types, the number of replicas for workers # and parameter servers. # Corresponds to the JSON property `scaleTier` # @return [String] attr_accessor :scale_tier # Optional. Use 'chief' instead of 'master' in TF_CONFIG when Custom # Container is used and evaluator is not specified. # Defaults to false. # Corresponds to the JSON property `useChiefInTfConfig` # @return [Boolean] attr_accessor :use_chief_in_tf_config alias_method :use_chief_in_tf_config?, :use_chief_in_tf_config # Represents the configuration for a replica in a cluster. # Corresponds to the JSON property `workerConfig` # @return [Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig] attr_accessor :worker_config # Optional. The number of worker replicas to use for the training job. Each # replica in the cluster will be of the type specified in `worker_type`. # This value can only be used when `scale_tier` is set to `CUSTOM`. If you # set this value, you must also set `worker_type`. # The default value is zero. # Corresponds to the JSON property `workerCount` # @return [Fixnum] attr_accessor :worker_count # Optional. Specifies the type of virtual machine to use for your training # job's worker nodes. # The supported values are the same as those described in the entry for # `masterType`. # This value must be consistent with the category of machine type that # `masterType` uses. In other words, both must be Compute Engine machine # types or both must be legacy machine types. # If you use `cloud_tpu` for this value, see special instructions for # [configuring a custom TPU # machine](/ml-engine/docs/tensorflow/using-tpus# # configuring_a_custom_tpu_machine). # This value must be present when `scaleTier` is set to `CUSTOM` and # `workerCount` is greater than zero. # Corresponds to the JSON property `workerType` # @return [String] attr_accessor :worker_type def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @args = args[:args] if args.key?(:args) @hyperparameters = args[:hyperparameters] if args.key?(:hyperparameters) @job_dir = args[:job_dir] if args.key?(:job_dir) @master_config = args[:master_config] if args.key?(:master_config) @master_type = args[:master_type] if args.key?(:master_type) @package_uris = args[:package_uris] if args.key?(:package_uris) @parameter_server_config = args[:parameter_server_config] if args.key?(:parameter_server_config) @parameter_server_count = args[:parameter_server_count] if args.key?(:parameter_server_count) @parameter_server_type = args[:parameter_server_type] if args.key?(:parameter_server_type) @python_module = args[:python_module] if args.key?(:python_module) @python_version = args[:python_version] if args.key?(:python_version) @region = args[:region] if args.key?(:region) @runtime_version = args[:runtime_version] if args.key?(:runtime_version) @scale_tier = args[:scale_tier] if args.key?(:scale_tier) @use_chief_in_tf_config = args[:use_chief_in_tf_config] if args.key?(:use_chief_in_tf_config) @worker_config = args[:worker_config] if args.key?(:worker_config) @worker_count = args[:worker_count] if args.key?(:worker_count) @worker_type = args[:worker_type] if args.key?(:worker_type) end end # Represents results of a training job. Output only. class GoogleCloudMlV1TrainingOutput include Google::Apis::Core::Hashable # Represents output related to a built-in algorithm Job. # Corresponds to the JSON property `builtInAlgorithmOutput` # @return [Google::Apis::MlV1::GoogleCloudMlV1BuiltInAlgorithmOutput] attr_accessor :built_in_algorithm_output # The number of hyperparameter tuning trials that completed successfully. # Only set for hyperparameter tuning jobs. # Corresponds to the JSON property `completedTrialCount` # @return [Fixnum] attr_accessor :completed_trial_count # The amount of ML units consumed by the job. # Corresponds to the JSON property `consumedMLUnits` # @return [Float] attr_accessor :consumed_ml_units # The TensorFlow summary tag name used for optimizing hyperparameter tuning # trials. See # [`HyperparameterSpec.hyperparameterMetricTag`](#HyperparameterSpec.FIELDS. # hyperparameter_metric_tag) # for more information. Only set for hyperparameter tuning jobs. # Corresponds to the JSON property `hyperparameterMetricTag` # @return [String] attr_accessor :hyperparameter_metric_tag # Whether this job is a built-in Algorithm job. # Corresponds to the JSON property `isBuiltInAlgorithmJob` # @return [Boolean] attr_accessor :is_built_in_algorithm_job alias_method :is_built_in_algorithm_job?, :is_built_in_algorithm_job # Whether this job is a hyperparameter tuning job. # Corresponds to the JSON property `isHyperparameterTuningJob` # @return [Boolean] attr_accessor :is_hyperparameter_tuning_job alias_method :is_hyperparameter_tuning_job?, :is_hyperparameter_tuning_job # Results for individual Hyperparameter trials. # Only set for hyperparameter tuning jobs. # Corresponds to the JSON property `trials` # @return [Array] attr_accessor :trials def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @built_in_algorithm_output = args[:built_in_algorithm_output] if args.key?(:built_in_algorithm_output) @completed_trial_count = args[:completed_trial_count] if args.key?(:completed_trial_count) @consumed_ml_units = args[:consumed_ml_units] if args.key?(:consumed_ml_units) @hyperparameter_metric_tag = args[:hyperparameter_metric_tag] if args.key?(:hyperparameter_metric_tag) @is_built_in_algorithm_job = args[:is_built_in_algorithm_job] if args.key?(:is_built_in_algorithm_job) @is_hyperparameter_tuning_job = args[:is_hyperparameter_tuning_job] if args.key?(:is_hyperparameter_tuning_job) @trials = args[:trials] if args.key?(:trials) end end # 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](/ml-engine/reference/rest/v1/projects.models. # versions/list). class GoogleCloudMlV1Version include Google::Apis::Core::Hashable # Represents a hardware accelerator request config. # Note that the AcceleratorConfig can be used in both Jobs and Versions. # Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and # [accelerators for online # prediction](/ml-engine/docs/machine-types-online-prediction#gpus). # Corresponds to the JSON property `acceleratorConfig` # @return [Google::Apis::MlV1::GoogleCloudMlV1AcceleratorConfig] attr_accessor :accelerator_config # Options for automatically scaling a model. # Corresponds to the JSON property `autoScaling` # @return [Google::Apis::MlV1::GoogleCloudMlV1AutoScaling] attr_accessor :auto_scaling # Output only. The time the version was created. # Corresponds to the JSON property `createTime` # @return [String] attr_accessor :create_time # Required. The Cloud Storage location of the trained model used to # create the version. See the # [guide to model # deployment](/ml-engine/docs/tensorflow/deploying-models) for more # information. # When passing Version to # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models. # versions/create) # the model service uses the specified location as the source of the model. # Once deployed, the model version is hosted by the prediction service, so # this location is useful only as a historical record. # The total number of model files can't exceed 1000. # Corresponds to the JSON property `deploymentUri` # @return [String] attr_accessor :deployment_uri # Optional. The description specified for the version when it was created. # Corresponds to the JSON property `description` # @return [String] attr_accessor :description # Output only. The details of a failure or a cancellation. # Corresponds to the JSON property `errorMessage` # @return [String] attr_accessor :error_message # `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 `GetVersion`, and # systems are expected to put that etag in the request to `UpdateVersion` 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] attr_accessor :etag # Optional. The machine learning framework AI Platform uses to train # this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, # `XGBOOST`. If you do not specify a framework, AI Platform # will analyze files in the deployment_uri to determine a framework. If you # choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version # of the model to 1.4 or greater. # Do **not** specify a framework if you're deploying a [custom # prediction routine](/ml-engine/docs/tensorflow/custom-prediction-routines). # If you specify a [Compute Engine (N1) machine # type](/ml-engine/docs/machine-types-online-prediction) in the # `machineType` field, you must specify `TENSORFLOW` # for the framework. # Corresponds to the JSON property `framework` # @return [String] attr_accessor :framework # Output only. If true, this version will be used to handle prediction # requests that do not specify a version. # You can change the default version by calling # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects. # models.versions/setDefault). # Corresponds to the JSON property `isDefault` # @return [Boolean] attr_accessor :is_default alias_method :is_default?, :is_default # Optional. One or more labels that you can add, to organize your model # versions. 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] attr_accessor :labels # Output only. The time the version was last used for prediction. # Corresponds to the JSON property `lastUseTime` # @return [String] attr_accessor :last_use_time # Optional. The type of machine on which to serve the model. Currently only # applies to online prediction service. If this field is not specified, it # defaults to `mls1-c1-m2`. # Online prediction supports the following machine types: # * `mls1-c1-m2` # * `mls1-c4-m2` # * `n1-standard-2` # * `n1-standard-4` # * `n1-standard-8` # * `n1-standard-16` # * `n1-standard-32` # * `n1-highmem-2` # * `n1-highmem-4` # * `n1-highmem-8` # * `n1-highmem-16` # * `n1-highmem-32` # * `n1-highcpu-2` # * `n1-highcpu-4` # * `n1-highcpu-8` # * `n1-highcpu-16` # * `n1-highcpu-32` # `mls1-c1-m2` is generally available. All other machine types are available # in beta. Learn more about the [differences between machine # types](/ml-engine/docs/machine-types-online-prediction). # Corresponds to the JSON property `machineType` # @return [String] attr_accessor :machine_type # Options for manually scaling a model. # Corresponds to the JSON property `manualScaling` # @return [Google::Apis::MlV1::GoogleCloudMlV1ManualScaling] attr_accessor :manual_scaling # Required. The name specified for the version when it was created. # The version name must be unique within the model it is created in. # Corresponds to the JSON property `name` # @return [String] attr_accessor :name # Optional. Cloud Storage paths (`gs://…`) of packages for [custom # prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines) # or [scikit-learn pipelines with custom # code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code). # For a custom prediction routine, one of these packages must contain your # Predictor class (see # [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally, # include any dependencies used by your Predictor or scikit-learn pipeline # uses that are not already included in your selected [runtime # version](/ml-engine/docs/tensorflow/runtime-version-list). # If you specify this field, you must also set # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater. # Corresponds to the JSON property `packageUris` # @return [Array] attr_accessor :package_uris # Optional. The fully qualified name # (module_name.class_name) of a class that implements # the Predictor interface described in this reference field. The module # containing this class should be included in a package provided to the # [`packageUris` field](#Version.FIELDS.package_uris). # Specify this field if and only if you are deploying a [custom prediction # routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines). # If you specify this field, you must set # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater and # you must set `machineType` to a [legacy (MLS1) # machine type](/ml-engine/docs/machine-types-online-prediction). # The following code sample provides the Predictor interface: # 
        # class Predictor(object):
        # """Interface for constructing custom predictors."""
        # def predict(self, instances, **kwargs):
        # """Performs custom prediction.
        # Instances are the decoded values from the request. They have already
        # been deserialized from JSON.
        # Args:
        # instances: A list of prediction input instances.
        # **kwargs: A dictionary of keyword args provided as additional
        # fields on the predict request body.
        # Returns:
        # A list of outputs containing the prediction results. This list must
        # be JSON serializable.
        # """
        # raise NotImplementedError()
        # @classmethod
        # def from_path(cls, model_dir):
        # """Creates an instance of Predictor using the given path.
        # Loading of the predictor should be done in this method.
        # Args:
        # model_dir: The local directory that contains the exported model
        # file along with any additional files uploaded when creating the
        # version resource.
        # Returns:
        # An instance implementing this Predictor class.
        # """
        # raise NotImplementedError()
        #
# Learn more about [the Predictor interface and custom prediction # routines](/ml-engine/docs/tensorflow/custom-prediction-routines). # Corresponds to the JSON property `predictionClass` # @return [String] attr_accessor :prediction_class # Optional. The version of Python used in prediction. If not set, the default # version is '2.7'. Python '3.5' is available when `runtime_version` is set # to '1.4' and above. Python '2.7' works with all supported runtime versions. # Corresponds to the JSON property `pythonVersion` # @return [String] attr_accessor :python_version # Configuration for logging request-response pairs to a BigQuery table. # Online prediction requests to a model version and the responses to these # requests are converted to raw strings and saved to the specified BigQuery # table. Logging is constrained by [BigQuery quotas and # limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits, # AI Platform Prediction does not log request-response pairs, but it continues # to serve predictions. # If you are using [continuous # evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to # specify this configuration manually. Setting up continuous evaluation # automatically enables logging of request-response pairs. # Corresponds to the JSON property `requestLoggingConfig` # @return [Google::Apis::MlV1::GoogleCloudMlV1RequestLoggingConfig] attr_accessor :request_logging_config # Optional. The AI Platform runtime version to use for this deployment. # If not set, AI Platform uses the default stable version, 1.0. For more # information, see the # [runtime version list](/ml-engine/docs/runtime-version-list) and # [how to manage runtime versions](/ml-engine/docs/versioning). # Corresponds to the JSON property `runtimeVersion` # @return [String] attr_accessor :runtime_version # Optional. Specifies the service account for resource access control. # Corresponds to the JSON property `serviceAccount` # @return [String] attr_accessor :service_account # Output only. The state of a version. # Corresponds to the JSON property `state` # @return [String] attr_accessor :state def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @accelerator_config = args[:accelerator_config] if args.key?(:accelerator_config) @auto_scaling = args[:auto_scaling] if args.key?(:auto_scaling) @create_time = args[:create_time] if args.key?(:create_time) @deployment_uri = args[:deployment_uri] if args.key?(:deployment_uri) @description = args[:description] if args.key?(:description) @error_message = args[:error_message] if args.key?(:error_message) @etag = args[:etag] if args.key?(:etag) @framework = args[:framework] if args.key?(:framework) @is_default = args[:is_default] if args.key?(:is_default) @labels = args[:labels] if args.key?(:labels) @last_use_time = args[:last_use_time] if args.key?(:last_use_time) @machine_type = args[:machine_type] if args.key?(:machine_type) @manual_scaling = args[:manual_scaling] if args.key?(:manual_scaling) @name = args[:name] if args.key?(:name) @package_uris = args[:package_uris] if args.key?(:package_uris) @prediction_class = args[:prediction_class] if args.key?(:prediction_class) @python_version = args[:python_version] if args.key?(:python_version) @request_logging_config = args[:request_logging_config] if args.key?(:request_logging_config) @runtime_version = args[:runtime_version] if args.key?(:runtime_version) @service_account = args[:service_account] if args.key?(:service_account) @state = args[:state] if args.key?(:state) end end # 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:jose@example.com" # ] # `, # ` # "log_type": "DATA_WRITE", # `, # ` # "log_type": "ADMIN_READ", # ` # ] # `, # ` # "service": "sampleservice.googleapis.com" # "audit_log_configs": [ # ` # "log_type": "DATA_READ", # `, # ` # "log_type": "DATA_WRITE", # "exempted_members": [ # "user:aliya@example.com" # ] # ` # ] # ` # ] # ` # For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ # logging. It also exempts jose@example.com from DATA_READ logging, and # aliya@example.com from DATA_WRITE logging. class GoogleIamV1AuditConfig include Google::Apis::Core::Hashable # The configuration for logging of each type of permission. # Corresponds to the JSON property `auditLogConfigs` # @return [Array] attr_accessor :audit_log_configs # Specifies a service that will be enabled for audit logging. # For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. # `allServices` is a special value that covers all services. # Corresponds to the JSON property `service` # @return [String] attr_accessor :service def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @audit_log_configs = args[:audit_log_configs] if args.key?(:audit_log_configs) @service = args[:service] if args.key?(:service) end end # Provides the configuration for logging a type of permissions. # Example: # ` # "audit_log_configs": [ # ` # "log_type": "DATA_READ", # "exempted_members": [ # "user:jose@example.com" # ] # `, # ` # "log_type": "DATA_WRITE", # ` # ] # ` # This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting # jose@example.com from DATA_READ logging. class GoogleIamV1AuditLogConfig include Google::Apis::Core::Hashable # Specifies the identities that do not cause logging for this type of # permission. # Follows the same format of Binding.members. # Corresponds to the JSON property `exemptedMembers` # @return [Array] attr_accessor :exempted_members # The log type that this config enables. # Corresponds to the JSON property `logType` # @return [String] attr_accessor :log_type def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @exempted_members = args[:exempted_members] if args.key?(:exempted_members) @log_type = args[:log_type] if args.key?(:log_type) end end # Associates `members` with a `role`. class GoogleIamV1Binding include Google::Apis::Core::Hashable # Represents an expression text. Example: # title: "User account presence" # description: "Determines whether the request has a user account" # expression: "size(request.user) > 0" # Corresponds to the JSON property `condition` # @return [Google::Apis::MlV1::GoogleTypeExpr] attr_accessor :condition # Specifies the identities requesting access for a Cloud Platform resource. # `members` can have the following values: # * `allUsers`: A special identifier that represents anyone who is # on the internet; with or without a Google account. # * `allAuthenticatedUsers`: A special identifier that represents anyone # who is authenticated with a Google account or a service account. # * `user:`emailid``: An email address that represents a specific Google # account. For example, `alice@example.com` . # * `serviceAccount:`emailid``: An email address that represents a service # account. For example, `my-other-app@appspot.gserviceaccount.com`. # * `group:`emailid``: An email address that represents a Google group. # For example, `admins@example.com`. # * `domain:`domain``: The G Suite domain (primary) that represents all the # users of that domain. For example, `google.com` or `example.com`. # Corresponds to the JSON property `members` # @return [Array] attr_accessor :members # Role that is assigned to `members`. # For example, `roles/viewer`, `roles/editor`, or `roles/owner`. # Corresponds to the JSON property `role` # @return [String] attr_accessor :role def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @condition = args[:condition] if args.key?(:condition) @members = args[:members] if args.key?(:members) @role = args[:role] if args.key?(:role) end end # Defines an Identity and Access Management (IAM) policy. It is used to # specify access control policies for Cloud Platform resources. # A `Policy` is a collection of `bindings`. A `binding` binds one or more # `members` to a single `role`. Members can be user accounts, service accounts, # Google groups, and domains (such as G Suite). A `role` is a named list of # permissions (defined by IAM or configured by users). A `binding` can # optionally specify a `condition`, which is a logic expression that further # constrains the role binding based on attributes about the request and/or # target resource. # **JSON Example** # ` # "bindings": [ # ` # "role": "roles/resourcemanager.organizationAdmin", # "members": [ # "user:mike@example.com", # "group:admins@example.com", # "domain:google.com", # "serviceAccount:my-project-id@appspot.gserviceaccount.com" # ] # `, # ` # "role": "roles/resourcemanager.organizationViewer", # "members": ["user:eve@example.com"], # "condition": ` # "title": "expirable access", # "description": "Does not grant access after Sep 2020", # "expression": "request.time < # timestamp('2020-10-01T00:00:00.000Z')", # ` # ` # ] # ` # **YAML Example** # bindings: # - members: # - user:mike@example.com # - group:admins@example.com # - domain:google.com # - serviceAccount:my-project-id@appspot.gserviceaccount.com # role: roles/resourcemanager.organizationAdmin # - members: # - user:eve@example.com # role: roles/resourcemanager.organizationViewer # condition: # title: expirable access # description: Does not grant access after Sep 2020 # expression: request.time < timestamp('2020-10-01T00:00:00.000Z') # For a description of IAM and its features, see the # [IAM developer's guide](https://cloud.google.com/iam/docs). class GoogleIamV1Policy include Google::Apis::Core::Hashable # Specifies cloud audit logging configuration for this policy. # Corresponds to the JSON property `auditConfigs` # @return [Array] attr_accessor :audit_configs # Associates a list of `members` to a `role`. Optionally may specify a # `condition` that determines when binding is in effect. # `bindings` with no members will result in an error. # Corresponds to the JSON property `bindings` # @return [Array] attr_accessor :bindings # `etag` is used for optimistic concurrency control as a way to help # prevent simultaneous updates of a policy from overwriting each other. # It is strongly suggested that systems make use of the `etag` in the # read-modify-write cycle to perform policy updates in order to avoid race # conditions: An `etag` is returned in the response to `getIamPolicy`, and # systems are expected to put that etag in the request to `setIamPolicy` to # ensure that their change will be applied to the same version of the policy. # If no `etag` is provided in the call to `setIamPolicy`, then the existing # policy is overwritten. Due to blind-set semantics of an etag-less policy, # 'setIamPolicy' will not fail even if either of incoming or stored policy # does not meet the version requirements. # Corresponds to the JSON property `etag` # NOTE: Values are automatically base64 encoded/decoded in the client library. # @return [String] attr_accessor :etag # Specifies the format of the policy. # Valid values are 0, 1, and 3. Requests specifying an invalid value will be # rejected. # Operations affecting conditional bindings must specify version 3. This can # be either setting a conditional policy, modifying a conditional binding, # or removing a conditional binding from the stored conditional policy. # Operations on non-conditional policies may specify any valid value or # leave the field unset. # If no etag is provided in the call to `setIamPolicy`, any version # compliance checks on the incoming and/or stored policy is skipped. # Corresponds to the JSON property `version` # @return [Fixnum] attr_accessor :version def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @audit_configs = args[:audit_configs] if args.key?(:audit_configs) @bindings = args[:bindings] if args.key?(:bindings) @etag = args[:etag] if args.key?(:etag) @version = args[:version] if args.key?(:version) end end # Request message for `SetIamPolicy` method. class GoogleIamV1SetIamPolicyRequest include Google::Apis::Core::Hashable # Defines an Identity and Access Management (IAM) policy. It is used to # specify access control policies for Cloud Platform resources. # A `Policy` is a collection of `bindings`. A `binding` binds one or more # `members` to a single `role`. Members can be user accounts, service accounts, # Google groups, and domains (such as G Suite). A `role` is a named list of # permissions (defined by IAM or configured by users). A `binding` can # optionally specify a `condition`, which is a logic expression that further # constrains the role binding based on attributes about the request and/or # target resource. # **JSON Example** # ` # "bindings": [ # ` # "role": "roles/resourcemanager.organizationAdmin", # "members": [ # "user:mike@example.com", # "group:admins@example.com", # "domain:google.com", # "serviceAccount:my-project-id@appspot.gserviceaccount.com" # ] # `, # ` # "role": "roles/resourcemanager.organizationViewer", # "members": ["user:eve@example.com"], # "condition": ` # "title": "expirable access", # "description": "Does not grant access after Sep 2020", # "expression": "request.time < # timestamp('2020-10-01T00:00:00.000Z')", # ` # ` # ] # ` # **YAML Example** # bindings: # - members: # - user:mike@example.com # - group:admins@example.com # - domain:google.com # - serviceAccount:my-project-id@appspot.gserviceaccount.com # role: roles/resourcemanager.organizationAdmin # - members: # - user:eve@example.com # role: roles/resourcemanager.organizationViewer # condition: # title: expirable access # description: Does not grant access after Sep 2020 # expression: request.time < timestamp('2020-10-01T00:00:00.000Z') # For a description of IAM and its features, see the # [IAM developer's guide](https://cloud.google.com/iam/docs). # Corresponds to the JSON property `policy` # @return [Google::Apis::MlV1::GoogleIamV1Policy] attr_accessor :policy # OPTIONAL: A FieldMask specifying which fields of the policy to modify. Only # the fields in the mask will be modified. If no mask is provided, the # following default mask is used: # paths: "bindings, etag" # This field is only used by Cloud IAM. # Corresponds to the JSON property `updateMask` # @return [String] attr_accessor :update_mask def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @policy = args[:policy] if args.key?(:policy) @update_mask = args[:update_mask] if args.key?(:update_mask) end end # Request message for `TestIamPermissions` method. class GoogleIamV1TestIamPermissionsRequest include Google::Apis::Core::Hashable # The set of permissions to check for the `resource`. Permissions with # wildcards (such as '*' or 'storage.*') are not allowed. For more # information see # [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). # Corresponds to the JSON property `permissions` # @return [Array] attr_accessor :permissions def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @permissions = args[:permissions] if args.key?(:permissions) end end # Response message for `TestIamPermissions` method. class GoogleIamV1TestIamPermissionsResponse include Google::Apis::Core::Hashable # A subset of `TestPermissionsRequest.permissions` that the caller is # allowed. # Corresponds to the JSON property `permissions` # @return [Array] attr_accessor :permissions def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @permissions = args[:permissions] if args.key?(:permissions) end end # The response message for Operations.ListOperations. class GoogleLongrunningListOperationsResponse include Google::Apis::Core::Hashable # The standard List next-page token. # Corresponds to the JSON property `nextPageToken` # @return [String] attr_accessor :next_page_token # A list of operations that matches the specified filter in the request. # Corresponds to the JSON property `operations` # @return [Array] attr_accessor :operations def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @next_page_token = args[:next_page_token] if args.key?(:next_page_token) @operations = args[:operations] if args.key?(:operations) end end # This resource represents a long-running operation that is the result of a # network API call. class GoogleLongrunningOperation include Google::Apis::Core::Hashable # If the value is `false`, it means the operation is still in progress. # If `true`, the operation is completed, and either `error` or `response` is # available. # Corresponds to the JSON property `done` # @return [Boolean] attr_accessor :done alias_method :done?, :done # 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](https://github.com/grpc). Each `Status` message contains # three pieces of data: error code, error message, and error details. # You can find out more about this error model and how to work with it in the # [API Design Guide](https://cloud.google.com/apis/design/errors). # Corresponds to the JSON property `error` # @return [Google::Apis::MlV1::GoogleRpcStatus] attr_accessor :error # Service-specific metadata associated with the operation. It typically # contains progress information and common metadata such as create time. # Some services might not provide such metadata. Any method that returns a # long-running operation should document the metadata type, if any. # Corresponds to the JSON property `metadata` # @return [Hash] attr_accessor :metadata # The server-assigned name, which is only unique within the same service that # originally returns it. If you use the default HTTP mapping, the # `name` should be a resource name ending with `operations/`unique_id``. # Corresponds to the JSON property `name` # @return [String] attr_accessor :name # The normal response of the operation in case of success. If the original # method returns no data on success, such as `Delete`, the response is # `google.protobuf.Empty`. If the original method is standard # `Get`/`Create`/`Update`, the response should be the resource. For other # methods, the response should have the type `XxxResponse`, where `Xxx` # is the original method name. For example, if the original method name # is `TakeSnapshot()`, the inferred response type is # `TakeSnapshotResponse`. # Corresponds to the JSON property `response` # @return [Hash] attr_accessor :response def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @done = args[:done] if args.key?(:done) @error = args[:error] if args.key?(:error) @metadata = args[:metadata] if args.key?(:metadata) @name = args[:name] if args.key?(:name) @response = args[:response] if args.key?(:response) end end # 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 ````. class GoogleProtobufEmpty include Google::Apis::Core::Hashable def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) end end # 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](https://github.com/grpc). Each `Status` message contains # three pieces of data: error code, error message, and error details. # You can find out more about this error model and how to work with it in the # [API Design Guide](https://cloud.google.com/apis/design/errors). class GoogleRpcStatus include Google::Apis::Core::Hashable # The status code, which should be an enum value of google.rpc.Code. # Corresponds to the JSON property `code` # @return [Fixnum] attr_accessor :code # A list of messages that carry the error details. There is a common set of # message types for APIs to use. # Corresponds to the JSON property `details` # @return [Array>] attr_accessor :details # A developer-facing error message, which should be in English. Any # user-facing error message should be localized and sent in the # google.rpc.Status.details field, or localized by the client. # Corresponds to the JSON property `message` # @return [String] attr_accessor :message def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @code = args[:code] if args.key?(:code) @details = args[:details] if args.key?(:details) @message = args[:message] if args.key?(:message) end end # Represents an expression text. Example: # title: "User account presence" # description: "Determines whether the request has a user account" # expression: "size(request.user) > 0" class GoogleTypeExpr include Google::Apis::Core::Hashable # An optional description of the expression. This is a longer text which # describes the expression, e.g. when hovered over it in a UI. # Corresponds to the JSON property `description` # @return [String] attr_accessor :description # Textual representation of an expression in # Common Expression Language syntax. # The application context of the containing message determines which # well-known feature set of CEL is supported. # Corresponds to the JSON property `expression` # @return [String] attr_accessor :expression # An optional string indicating the location of the expression for error # reporting, e.g. a file name and a position in the file. # Corresponds to the JSON property `location` # @return [String] attr_accessor :location # An optional title for the expression, i.e. a short string describing # its purpose. This can be used e.g. in UIs which allow to enter the # expression. # Corresponds to the JSON property `title` # @return [String] attr_accessor :title def initialize(**args) update!(**args) end # Update properties of this object def update!(**args) @description = args[:description] if args.key?(:description) @expression = args[:expression] if args.key?(:expression) @location = args[:location] if args.key?(:location) @title = args[:title] if args.key?(:title) end end end end end