# 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 string representing the content type of the body. # Corresponds to the JSON property `contentType` # @return [String] attr_accessor :content_type # HTTP body binary data. # 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. 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 available types of 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) @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 not specified, `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. # 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 # 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 # 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 # 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) @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) @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 CloudML Engine 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 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_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. Next field: 19 # 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, enables StackDriver Logging for online prediction. # 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 ML Engine 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_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. Next field: 19 class GoogleCloudMlV1PredictionInput include Google::Apis::Core::Hashable # Represents a hardware accelerator request config. # Corresponds to the JSON property `accelerator` # @return [Google::Apis::MlV1::GoogleCloudMlV1AcceleratorConfig] attr_accessor :accelerator # 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 Google 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 ML Engine services. # Corresponds to the JSON property `region` # @return [String] attr_accessor :region # Optional. The Google Cloud ML runtime version to use for this batch # prediction. If not set, Google Cloud ML 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) @accelerator = args[:accelerator] if args.key?(:accelerator) @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 # 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 # Optional. Specifies the type of virtual machine to use for your training # job's master worker. # The following types are supported: #
#
standard
#
# A basic machine configuration suitable for training simple models with # small to moderate datasets. #
#
large_model
#
# A machine with a lot of memory, specially suited for parameter servers # when your model is large (having many hidden layers or layers with very # large numbers of nodes). #
#
complex_model_s
#
# A machine suitable for the master and workers of the cluster when your # model requires more computation than the standard machine can handle # satisfactorily. #
#
complex_model_m
#
# A machine with roughly twice the number of cores and roughly double the # memory of complex_model_s. #
#
complex_model_l
#
# A machine with roughly twice the number of cores and roughly double the # memory of complex_model_m. #
#
standard_gpu
#
# A machine equivalent to standard that # also includes a single NVIDIA Tesla K80 GPU. See more about # using GPUs to # train your model. #
#
complex_model_m_gpu
#
# A machine equivalent to complex_model_m that also includes # four NVIDIA Tesla K80 GPUs. #
#
complex_model_l_gpu
#
# A machine equivalent to complex_model_l that also includes # eight NVIDIA Tesla K80 GPUs. #
#
standard_p100
#
# A machine equivalent to standard that # also includes a single NVIDIA Tesla P100 GPU. #
#
complex_model_m_p100
#
# A machine equivalent to complex_model_m that also includes # four NVIDIA Tesla P100 GPUs. #
#
standard_v100
#
# A machine equivalent to standard that # also includes a single NVIDIA Tesla V100 GPU. The availability of these # GPUs is in the Beta launch stage. #
#
large_model_v100
#
# A machine equivalent to large_model that # also includes a single NVIDIA Tesla V100 GPU. The availability of these # GPUs is in the Beta launch stage. #
#
complex_model_m_v100
#
# A machine equivalent to complex_model_m that # also includes four NVIDIA Tesla V100 GPUs. The availability of these # GPUs is in the Beta launch stage. #
#
complex_model_l_v100
#
# A machine equivalent to complex_model_l that # also includes eight NVIDIA Tesla V100 GPUs. The availability of these # GPUs is in the Beta launch stage. #
#
cloud_tpu
#
# A TPU VM including one Cloud TPU. See more about # using TPUs to train # your model. #
#
# You must set this value when `scaleTier` is set to `CUSTOM`. # 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 # 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`. # 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 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 ML Engine services. # Corresponds to the JSON property `region` # @return [String] attr_accessor :region # Optional. The Google Cloud ML runtime version to use for training. If not # set, Google Cloud ML will choose a stable version, which is defined in the # documentation of runtime version list. # 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. 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`. # 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 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_type = args[:master_type] if args.key?(:master_type) @package_uris = args[:package_uris] if args.key?(:package_uris) @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) @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 # 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 # 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) @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) @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 # 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 Google 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 Cloud ML Engine uses to train # this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, # `XGBOOST`. If you do not specify a framework, Cloud ML Engine # 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. # 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. # The following are currently supported and will be deprecated in # Beta release. # mls1-highmem-1 1 core 2 Gb RAM # mls1-highcpu-4 4 core 2 Gb RAM # The following are available in Beta: # mls1-c1-m2 1 core 2 Gb RAM Default # mls1-c4-m2 4 core 2 Gb RAM # 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. 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 # Optional. The Google Cloud ML runtime version to use for this deployment. # If not set, Google Cloud ML will choose a version. # Corresponds to the JSON property `runtimeVersion` # @return [String] attr_accessor :runtime_version # 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) @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) @python_version = args[:python_version] if args.key?(:python_version) @runtime_version = args[:runtime_version] if args.key?(:runtime_version) @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:foo@gmail.com" # ] # `, # ` # "log_type": "DATA_WRITE", # `, # ` # "log_type": "ADMIN_READ", # ` # ] # `, # ` # "service": "fooservice.googleapis.com" # "audit_log_configs": [ # ` # "log_type": "DATA_READ", # `, # ` # "log_type": "DATA_WRITE", # "exempted_members": [ # "user:bar@gmail.com" # ] # ` # ] # ` # ] # ` # For fooservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ # logging. It also exempts foo@gmail.com from DATA_READ logging, and # bar@gmail.com from DATA_WRITE logging. 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:foo@gmail.com" # ] # `, # ` # "log_type": "DATA_WRITE", # ` # ] # ` # This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting # foo@gmail.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@gmail.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``: A Google Apps domain name 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` consists of a list of `bindings`. A `binding` binds a list of # `members` to a `role`, where the members can be user accounts, Google groups, # Google domains, and service accounts. A `role` is a named list of permissions # defined by IAM. # **JSON Example** # ` # "bindings": [ # ` # "role": "roles/owner", # "members": [ # "user:mike@example.com", # "group:admins@example.com", # "domain:google.com", # "serviceAccount:my-other-app@appspot.gserviceaccount.com" # ] # `, # ` # "role": "roles/viewer", # "members": ["user:sean@example.com"] # ` # ] # ` # **YAML Example** # bindings: # - members: # - user:mike@example.com # - group:admins@example.com # - domain:google.com # - serviceAccount:my-other-app@appspot.gserviceaccount.com # role: roles/owner # - members: # - user:sean@example.com # role: roles/viewer # For a description of IAM and its features, see the # [IAM developer's guide](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`. # `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 blindly. # Corresponds to the JSON property `etag` # NOTE: Values are automatically base64 encoded/decoded in the client library. # @return [String] attr_accessor :etag # Deprecated. # 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` consists of a list of `bindings`. A `binding` binds a list of # `members` to a `role`, where the members can be user accounts, Google groups, # Google domains, and service accounts. A `role` is a named list of permissions # defined by IAM. # **JSON Example** # ` # "bindings": [ # ` # "role": "roles/owner", # "members": [ # "user:mike@example.com", # "group:admins@example.com", # "domain:google.com", # "serviceAccount:my-other-app@appspot.gserviceaccount.com" # ] # `, # ` # "role": "roles/viewer", # "members": ["user:sean@example.com"] # ` # ] # ` # **YAML Example** # bindings: # - members: # - user:mike@example.com # - group:admins@example.com # - domain:google.com # - serviceAccount:my-other-app@appspot.gserviceaccount.com # role: roles/owner # - members: # - user:sean@example.com # role: roles/viewer # For a description of IAM and its features, see the # [IAM developer's guide](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). The error model is designed to be: # - Simple to use and understand for most users # - Flexible enough to meet unexpected needs # # Overview # The `Status` message contains three pieces of data: error code, error message, # and error details. The error code should be an enum value of # google.rpc.Code, but it may accept additional error codes if needed. The # error message should be a developer-facing English message that helps # developers *understand* and *resolve* the error. If a localized user-facing # error message is needed, put the localized message in the error details or # localize it in the client. The optional error details may contain arbitrary # information about the error. There is a predefined set of error detail types # in the package `google.rpc` that can be used for common error conditions. # # Language mapping # The `Status` message is the logical representation of the error model, but it # is not necessarily the actual wire format. When the `Status` message is # exposed in different client libraries and different wire protocols, it can be # mapped differently. For example, it will likely be mapped to some exceptions # in Java, but more likely mapped to some error codes in C. # # Other uses # The error model and the `Status` message can be used in a variety of # environments, either with or without APIs, to provide a # consistent developer experience across different environments. # Example uses of this error model include: # - Partial errors. If a service needs to return partial errors to the client, # it may embed the `Status` in the normal response to indicate the partial # errors. # - Workflow errors. A typical workflow has multiple steps. Each step may # have a `Status` message for error reporting. # - Batch operations. If a client uses batch request and batch response, the # `Status` message should be used directly inside batch response, one for # each error sub-response. # - Asynchronous operations. If an API call embeds asynchronous operation # results in its response, the status of those operations should be # represented directly using the `Status` message. # - Logging. If some API errors are stored in logs, the message `Status` could # be used directly after any stripping needed for security/privacy reasons. # 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 have the format of `operations/some/unique/name`. # 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). The error model is designed to be: # - Simple to use and understand for most users # - Flexible enough to meet unexpected needs # # Overview # The `Status` message contains three pieces of data: error code, error message, # and error details. The error code should be an enum value of # google.rpc.Code, but it may accept additional error codes if needed. The # error message should be a developer-facing English message that helps # developers *understand* and *resolve* the error. If a localized user-facing # error message is needed, put the localized message in the error details or # localize it in the client. The optional error details may contain arbitrary # information about the error. There is a predefined set of error detail types # in the package `google.rpc` that can be used for common error conditions. # # Language mapping # The `Status` message is the logical representation of the error model, but it # is not necessarily the actual wire format. When the `Status` message is # exposed in different client libraries and different wire protocols, it can be # mapped differently. For example, it will likely be mapped to some exceptions # in Java, but more likely mapped to some error codes in C. # # Other uses # The error model and the `Status` message can be used in a variety of # environments, either with or without APIs, to provide a # consistent developer experience across different environments. # Example uses of this error model include: # - Partial errors. If a service needs to return partial errors to the client, # it may embed the `Status` in the normal response to indicate the partial # errors. # - Workflow errors. A typical workflow has multiple steps. Each step may # have a `Status` message for error reporting. # - Batch operations. If a client uses batch request and batch response, the # `Status` message should be used directly inside batch response, one for # each error sub-response. # - Asynchronous operations. If an API call embeds asynchronous operation # results in its response, the status of those operations should be # represented directly using the `Status` message. # - Logging. If some API errors are stored in logs, the message `Status` could # be used directly after any stripping needed for security/privacy reasons. 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