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google-api-ruby-client/generated/google-apis-ml_v1/lib/google/apis/ml_v1/classes.rb

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chore: Initial generation of separate libraries (#2139)
2021-01-01 03:01:13 +00:00
# Copyright 2020 Google LLC
#
# 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<Hash<String,Object>>]
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
#
class GoogleCloudMlV1AutomatedStoppingConfigDecayCurveAutomatedStoppingConfig
include Google::Apis::Core::Hashable
# If true, measurement.elapsed_time is used as the x-axis of each Trials Decay
# Curve. Otherwise, Measurement.steps will be used as the x-axis.
# Corresponds to the JSON property `useElapsedTime`
# @return [Boolean]
attr_accessor :use_elapsed_time
alias_method :use_elapsed_time?, :use_elapsed_time
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@use_elapsed_time = args[:use_elapsed_time] if args.key?(:use_elapsed_time)
end
end
# The median automated stopping rule stops a pending trial if the trial's best
# objective_value is strictly below the median 'performance' of all completed
# trials reported up to the trial's last measurement. Currently, 'performance'
# refers to the running average of the objective values reported by the trial in
# each measurement.
class GoogleCloudMlV1AutomatedStoppingConfigMedianAutomatedStoppingConfig
include Google::Apis::Core::Hashable
# If true, the median automated stopping rule applies to measurement.
# use_elapsed_time, which means the elapsed_time field of the current trial's
# latest measurement is used to compute the median objective value for each
# completed trial.
# Corresponds to the JSON property `useElapsedTime`
# @return [Boolean]
attr_accessor :use_elapsed_time
alias_method :use_elapsed_time?, :use_elapsed_time
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@use_elapsed_time = args[:use_elapsed_time] if args.key?(:use_elapsed_time)
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
# A message representing a metric in the measurement.
class GoogleCloudMlV1MeasurementMetric
include Google::Apis::Core::Hashable
# Required. Metric name.
# Corresponds to the JSON property `metric`
# @return [String]
attr_accessor :metric
# Required. The value for this metric.
# Corresponds to the JSON property `value`
# @return [Float]
attr_accessor :value
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@metric = args[:metric] if args.key?(:metric)
@value = args[:value] if args.key?(:value)
end
end
#
class GoogleCloudMlV1StudyConfigParameterSpecCategoricalValueSpec
include Google::Apis::Core::Hashable
# Must be specified if type is `CATEGORICAL`. The list of possible categories.
# Corresponds to the JSON property `values`
# @return [Array<String>]
attr_accessor :values
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@values = args[:values] if args.key?(:values)
end
end
#
class GoogleCloudMlV1StudyConfigParameterSpecDiscreteValueSpec
include Google::Apis::Core::Hashable
# Must be specified 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 `values`
# @return [Array<Float>]
attr_accessor :values
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@values = args[:values] if args.key?(:values)
end
end
#
class GoogleCloudMlV1StudyConfigParameterSpecDoubleValueSpec
include Google::Apis::Core::Hashable
# Must be specified if type is `DOUBLE`. Maximum value of the parameter.
# Corresponds to the JSON property `maxValue`
# @return [Float]
attr_accessor :max_value
# Must be specified if type is `DOUBLE`. Minimum value of the parameter.
# Corresponds to the JSON property `minValue`
# @return [Float]
attr_accessor :min_value
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@max_value = args[:max_value] if args.key?(:max_value)
@min_value = args[:min_value] if args.key?(:min_value)
end
end
#
class GoogleCloudMlV1StudyConfigParameterSpecIntegerValueSpec
include Google::Apis::Core::Hashable
# Must be specified if type is `INTEGER`. Maximum value of the parameter.
# Corresponds to the JSON property `maxValue`
# @return [Fixnum]
attr_accessor :max_value
# Must be specified if type is `INTEGER`. Minimum value of the parameter.
# Corresponds to the JSON property `minValue`
# @return [Fixnum]
attr_accessor :min_value
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@max_value = args[:max_value] if args.key?(:max_value)
@min_value = args[:min_value] if args.key?(:min_value)
end
end
# Represents the spec to match categorical values from parent parameter.
class GoogleCloudMlV1StudyConfigParameterSpecMatchingParentCategoricalValueSpec
include Google::Apis::Core::Hashable
# Matches values of the parent parameter with type 'CATEGORICAL'. All values
# must exist in `categorical_value_spec` of parent parameter.
# Corresponds to the JSON property `values`
# @return [Array<String>]
attr_accessor :values
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@values = args[:values] if args.key?(:values)
end
end
# Represents the spec to match discrete values from parent parameter.
class GoogleCloudMlV1StudyConfigParameterSpecMatchingParentDiscreteValueSpec
include Google::Apis::Core::Hashable
# Matches values of the parent parameter with type 'DISCRETE'. All values must
# exist in `discrete_value_spec` of parent parameter.
# Corresponds to the JSON property `values`
# @return [Array<Float>]
attr_accessor :values
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@values = args[:values] if args.key?(:values)
end
end
# Represents the spec to match integer values from parent parameter.
class GoogleCloudMlV1StudyConfigParameterSpecMatchingParentIntValueSpec
include Google::Apis::Core::Hashable
# Matches values of the parent parameter with type 'INTEGER'. All values must
# lie in `integer_value_spec` of parent parameter.
# Corresponds to the JSON property `values`
# @return [Array<Fixnum>]
attr_accessor :values
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@values = args[:values] if args.key?(:values)
end
end
# Represents a metric to optimize.
class GoogleCloudMlV1StudyConfigMetricSpec
include Google::Apis::Core::Hashable
# Required. The optimization goal of the metric.
# Corresponds to the JSON property `goal`
# @return [String]
attr_accessor :goal
# Required. The name of the metric.
# Corresponds to the JSON property `metric`
# @return [String]
attr_accessor :metric
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@goal = args[:goal] if args.key?(:goal)
@metric = args[:metric] if args.key?(:metric)
end
end
# Represents a single parameter to optimize.
class GoogleCloudMlV1StudyConfigParameterSpec
include Google::Apis::Core::Hashable
# The value spec for a 'CATEGORICAL' parameter.
# Corresponds to the JSON property `categoricalValueSpec`
# @return [Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpecCategoricalValueSpec]
attr_accessor :categorical_value_spec
# A child node is active if the parameter's value matches the child node's
# matching_parent_values. If two items in child_parameter_specs have the same
# name, they must have disjoint matching_parent_values.
# Corresponds to the JSON property `childParameterSpecs`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpec>]
attr_accessor :child_parameter_specs
# The value spec for a 'DISCRETE' parameter.
# Corresponds to the JSON property `discreteValueSpec`
# @return [Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpecDiscreteValueSpec]
attr_accessor :discrete_value_spec
# The value spec for a 'DOUBLE' parameter.
# Corresponds to the JSON property `doubleValueSpec`
# @return [Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpecDoubleValueSpec]
attr_accessor :double_value_spec
# The value spec for an 'INTEGER' parameter.
# Corresponds to the JSON property `integerValueSpec`
# @return [Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpecIntegerValueSpec]
attr_accessor :integer_value_spec
# Required. The parameter name must be unique amongst all ParameterSpecs.
# Corresponds to the JSON property `parameter`
# @return [String]
attr_accessor :parameter
# Represents the spec to match categorical values from parent parameter.
# Corresponds to the JSON property `parentCategoricalValues`
# @return [Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpecMatchingParentCategoricalValueSpec]
attr_accessor :parent_categorical_values
# Represents the spec to match discrete values from parent parameter.
# Corresponds to the JSON property `parentDiscreteValues`
# @return [Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpecMatchingParentDiscreteValueSpec]
attr_accessor :parent_discrete_values
# Represents the spec to match integer values from parent parameter.
# Corresponds to the JSON property `parentIntValues`
# @return [Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpecMatchingParentIntValueSpec]
attr_accessor :parent_int_values
# How the parameter should be scaled. Leave unset for categorical parameters.
# 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_value_spec = args[:categorical_value_spec] if args.key?(:categorical_value_spec)
@child_parameter_specs = args[:child_parameter_specs] if args.key?(:child_parameter_specs)
@discrete_value_spec = args[:discrete_value_spec] if args.key?(:discrete_value_spec)
@double_value_spec = args[:double_value_spec] if args.key?(:double_value_spec)
@integer_value_spec = args[:integer_value_spec] if args.key?(:integer_value_spec)
@parameter = args[:parameter] if args.key?(:parameter)
@parent_categorical_values = args[:parent_categorical_values] if args.key?(:parent_categorical_values)
@parent_discrete_values = args[:parent_discrete_values] if args.key?(:parent_discrete_values)
@parent_int_values = args[:parent_int_values] if args.key?(:parent_int_values)
@scale_type = args[:scale_type] if args.key?(:scale_type)
@type = args[:type] if args.key?(:type)
end
end
# A message representing a parameter to be tuned. Contains the name of the
# parameter and the suggested value to use for this trial.
class GoogleCloudMlV1TrialParameter
include Google::Apis::Core::Hashable
# Must be set if ParameterType is DOUBLE or DISCRETE.
# Corresponds to the JSON property `floatValue`
# @return [Float]
attr_accessor :float_value
# Must be set if ParameterType is INTEGER
# Corresponds to the JSON property `intValue`
# @return [Fixnum]
attr_accessor :int_value
# The name of the parameter.
# Corresponds to the JSON property `parameter`
# @return [String]
attr_accessor :parameter
# Must be set if ParameterTypeis CATEGORICAL
# Corresponds to the JSON property `stringValue`
# @return [String]
attr_accessor :string_value
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@float_value = args[:float_value] if args.key?(:float_value)
@int_value = args[:int_value] if args.key?(:int_value)
@parameter = args[:parameter] if args.key?(:parameter)
@string_value = args[:string_value] if args.key?(:string_value)
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
# The request message for the AddTrialMeasurement service method.
class GoogleCloudMlV1AddTrialMeasurementRequest
include Google::Apis::Core::Hashable
# A message representing a measurement.
# Corresponds to the JSON property `measurement`
# @return [Google::Apis::MlV1::GoogleCloudMlV1Measurement]
attr_accessor :measurement
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@measurement = args[:measurement] if args.key?(:measurement)
end
end
# Options for automatically scaling a model.
class GoogleCloudMlV1AutoScaling
include Google::Apis::Core::Hashable
# The maximum number of nodes to scale this model under load. The actual value
# will depend on resource quota and availability.
# Corresponds to the JSON property `maxNodes`
# @return [Fixnum]
attr_accessor :max_nodes
# MetricSpec contains the specifications to use to calculate the desired nodes
# count.
# Corresponds to the JSON property `metrics`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1MetricSpec>]
attr_accessor :metrics
# 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`
feat: Automated regeneration of ml v1 client (#2255)
2021-01-08 16:44:10 +00:00
# must be at least 1 for use with a Compute Engine machine type. You can set `
chore: Initial generation of separate libraries (#2139)
2021-01-01 03:01:13 +00:00
# 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)
@max_nodes = args[:max_nodes] if args.key?(:max_nodes)
@metrics = args[:metrics] if args.key?(:metrics)
@min_nodes = args[:min_nodes] if args.key?(:min_nodes)
end
end
# Configuration for Automated Early Stopping of Trials. If no
# implementation_config is set, automated early stopping will not be run.
class GoogleCloudMlV1AutomatedStoppingConfig
include Google::Apis::Core::Hashable
#
# Corresponds to the JSON property `decayCurveStoppingConfig`
# @return [Google::Apis::MlV1::GoogleCloudMlV1AutomatedStoppingConfigDecayCurveAutomatedStoppingConfig]
attr_accessor :decay_curve_stopping_config
# The median automated stopping rule stops a pending trial if the trial's best
# objective_value is strictly below the median 'performance' of all completed
# trials reported up to the trial's last measurement. Currently, 'performance'
# refers to the running average of the objective values reported by the trial in
# each measurement.
# Corresponds to the JSON property `medianAutomatedStoppingConfig`
# @return [Google::Apis::MlV1::GoogleCloudMlV1AutomatedStoppingConfigMedianAutomatedStoppingConfig]
attr_accessor :median_automated_stopping_config
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@decay_curve_stopping_config = args[:decay_curve_stopping_config] if args.key?(:decay_curve_stopping_config)
@median_automated_stopping_config = args[:median_automated_stopping_config] if args.key?(:median_automated_stopping_config)
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<String>]
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
# This message will be placed in the metadata field of a google.longrunning.
# Operation associated with a CheckTrialEarlyStoppingState request.
class GoogleCloudMlV1CheckTrialEarlyStoppingStateMetatdata
include Google::Apis::Core::Hashable
# The time at which the operation was submitted.
# Corresponds to the JSON property `createTime`
# @return [String]
attr_accessor :create_time
# The name of the study that the trial belongs to.
# Corresponds to the JSON property `study`
# @return [String]
attr_accessor :study
# The trial name.
# Corresponds to the JSON property `trial`
# @return [String]
attr_accessor :trial
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@create_time = args[:create_time] if args.key?(:create_time)
@study = args[:study] if args.key?(:study)
@trial = args[:trial] if args.key?(:trial)
end
end
# The request message for the CheckTrialEarlyStoppingState service method.
class GoogleCloudMlV1CheckTrialEarlyStoppingStateRequest
include Google::Apis::Core::Hashable
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
end
end
# The message will be placed in the response field of a completed google.
# longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
class GoogleCloudMlV1CheckTrialEarlyStoppingStateResponse
include Google::Apis::Core::Hashable
# The time at which operation processing completed.
# Corresponds to the JSON property `endTime`
# @return [String]
attr_accessor :end_time
# True if the Trial should stop.
# Corresponds to the JSON property `shouldStop`
# @return [Boolean]
attr_accessor :should_stop
alias_method :should_stop?, :should_stop
# The time at which the operation was started.
# Corresponds to the JSON property `startTime`
# @return [String]
attr_accessor :start_time
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@end_time = args[:end_time] if args.key?(:end_time)
@should_stop = args[:should_stop] if args.key?(:should_stop)
@start_time = args[:start_time] if args.key?(:start_time)
end
end
# The request message for the CompleteTrial service method.
class GoogleCloudMlV1CompleteTrialRequest
include Google::Apis::Core::Hashable
# A message representing a measurement.
# Corresponds to the JSON property `finalMeasurement`
# @return [Google::Apis::MlV1::GoogleCloudMlV1Measurement]
attr_accessor :final_measurement
# Optional. A human readable reason why the trial was infeasible. This should
# only be provided if `trial_infeasible` is true.
# Corresponds to the JSON property `infeasibleReason`
# @return [String]
attr_accessor :infeasible_reason
# Optional. True if the trial cannot be run with the given Parameter, and
# final_measurement will be ignored.
# Corresponds to the JSON property `trialInfeasible`
# @return [Boolean]
attr_accessor :trial_infeasible
alias_method :trial_infeasible?, :trial_infeasible
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@final_measurement = args[:final_measurement] if args.key?(:final_measurement)
@infeasible_reason = args[:infeasible_reason] if args.key?(:infeasible_reason)
@trial_infeasible = args[:trial_infeasible] if args.key?(:trial_infeasible)
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
# Represents a network port in a single container. This message is a subset of
# the [Kubernetes ContainerPort v1 core specification](https://kubernetes.io/
# docs/reference/generated/kubernetes-api/v1.18/#containerport-v1-core).
class GoogleCloudMlV1ContainerPort
include Google::Apis::Core::Hashable
# Number of the port to expose on the container. This must be a valid port
# number: 0 < PORT_NUMBER < 65536.
# Corresponds to the JSON property `containerPort`
# @return [Fixnum]
attr_accessor :container_port
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@container_port = args[:container_port] if args.key?(:container_port)
end
end
# Specification of a custom container for serving predictions. This message is a
# subset of the [Kubernetes Container v1 core specification](https://kubernetes.
# io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
class GoogleCloudMlV1ContainerSpec
include Google::Apis::Core::Hashable
# Immutable. Specifies arguments for the command that runs when the container
# starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/
# reference/builder/#cmd). Specify this field as an array of executable and
# arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't
# specify this field but do specify the command field, then the command from the
# `command` field runs without any additional arguments. See the [Kubernetes
# documentation about how the `command` and `args` fields interact with a
# container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-
# data-application/define-command-argument-container/#notes). If you don't
# specify this field and don't specify the `commmand` field, then the container'
# s [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `
# CMD` determine what runs based on their default behavior. See the [Docker
# documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.
# com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In
# this field, you can reference [environment variables set by AI Platform
# Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-
# variables) and environment variables set in the env field. You cannot
# reference environment variables set in the Docker image. In order for
# environment variables to be expanded, reference them by using the following
# syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion,
# which does not use parentheses. If a variable cannot be resolved, the
# reference in the input string is used unchanged. To avoid variable expansion,
# you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This
# field corresponds to the `args` field of the [Kubernetes Containers v1 core
# API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#
# container-v1-core).
# Corresponds to the JSON property `args`
# @return [Array<String>]
attr_accessor :args
# Immutable. Specifies the command that runs when the container starts. This
# overrides the container's [`ENTRYPOINT`](https://docs.docker.com/engine/
# reference/builder/#entrypoint). Specify this field as an array of executable
# and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell"
# form. If you do not specify this field, then the container's `ENTRYPOINT` runs,
# in conjunction with the args field or the container's [`CMD`](https://docs.
# docker.com/engine/reference/builder/#cmd), if either exists. If this field is
# not specified and the container does not have an `ENTRYPOINT`, then refer to
# the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://
# docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-
# interact). If you specify this field, then you can also specify the `args`
# field to provide additional arguments for this command. However, if you
# specify this field, then the container's `CMD` is ignored. See the [Kubernetes
# documentation about how the `command` and `args` fields interact with a
# container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-
# data-application/define-command-argument-container/#notes). In this field, you
# can reference [environment variables set by AI Platform Prediction](/ai-
# platform/prediction/docs/custom-container-requirements#aip-variables) and
# environment variables set in the env field. You cannot reference environment
# variables set in the Docker image. In order for environment variables to be
# expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note
# that this differs from Bash variable expansion, which does not use parentheses.
# If a variable cannot be resolved, the reference in the input string is used
# unchanged. To avoid variable expansion, you can escape this syntax with `$$`;
# for example: $$(VARIABLE_NAME) This field corresponds to the `command` field
# of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/
# reference/generated/kubernetes-api/v1.18/#container-v1-core).
# Corresponds to the JSON property `command`
# @return [Array<String>]
attr_accessor :command
# Immutable. List of environment variables to set in the container. After the
# container starts running, code running in the container can read these
# environment variables. Additionally, the command and args fields can reference
# these variables. Later entries in this list can also reference earlier entries.
# For example, the following example sets the variable `VAR_2` to have the
# value `foo bar`: ```json [ ` "name": "VAR_1", "value": "foo" `, ` "name": "
# VAR_2", "value": "$(VAR_1) bar" ` ] ``` If you switch the order of the
# variables in the example, then the expansion does not occur. This field
# corresponds to the `env` field of the [Kubernetes Containers v1 core API](
# https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-
# v1-core).
# Corresponds to the JSON property `env`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1EnvVar>]
attr_accessor :env
# URI of the Docker image to be used as the custom container for serving
# predictions. This URI must identify [an image in Artifact Registry](/artifact-
# registry/docs/overview) and begin with the hostname ``REGION`-docker.pkg.dev`,
# where ``REGION`` is replaced by the region that matches AI Platform Prediction
# [regional endpoint](/ai-platform/prediction/docs/regional-endpoints) that you
# are using. For example, if you are using the `us-central1-ml.googleapis.com`
# endpoint, then this URI must begin with `us-central1-docker.pkg.dev`. To use a
# custom container, the [AI Platform Google-managed service account](/ai-
# platform/prediction/docs/custom-service-account#default) must have permission
# to pull (read) the Docker image at this URI. The AI Platform Google-managed
# service account has the following format: `service-`PROJECT_NUMBER`@cloud-ml.
# google.com.iam.gserviceaccount.com` `PROJECT_NUMBER` is replaced by your
# Google Cloud project number. By default, this service account has necessary
# permissions to pull an Artifact Registry image in the same Google Cloud
# project where you are using AI Platform Prediction. In this case, no
# configuration is necessary. If you want to use an image from a different
# Google Cloud project, learn how to [grant the Artifact Registry Reader (roles/
# artifactregistry.reader) role for a repository](/artifact-registry/docs/access-
# control#grant-repo) to your projet's AI Platform Google-managed service
# account. To learn about the requirements for the Docker image itself, read [
# Custom container requirements](/ai-platform/prediction/docs/custom-container-
# requirements).
# Corresponds to the JSON property `image`
# @return [String]
attr_accessor :image
# Immutable. List of ports to expose from the container. AI Platform Prediction
# sends any prediction requests that it receives to the first port on this list.
# AI Platform Prediction also sends [liveness and health checks](/ai-platform/
# prediction/docs/custom-container-requirements#health) to this port. If you do
# not specify this field, it defaults to following value: ```json [ ` "
# containerPort": 8080 ` ] ``` AI Platform Prediction does not use ports other
# than the first one listed. This field corresponds to the `ports` field of the [
# Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/
# generated/kubernetes-api/v1.18/#container-v1-core).
# Corresponds to the JSON property `ports`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1ContainerPort>]
attr_accessor :ports
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@args = args[:args] if args.key?(:args)
@command = args[:command] if args.key?(:command)
@env = args[:env] if args.key?(:env)
@image = args[:image] if args.key?(:image)
@ports = args[:ports] if args.key?(:ports)
end
end
# Represents the config of disk options.
class GoogleCloudMlV1DiskConfig
include Google::Apis::Core::Hashable
# Size in GB of the boot disk (default is 100GB).
# Corresponds to the JSON property `bootDiskSizeGb`
# @return [Fixnum]
attr_accessor :boot_disk_size_gb
# Type of the boot disk (default is "pd-standard"). Valid values: "pd-ssd" (
# Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk
# Drive).
# Corresponds to the JSON property `bootDiskType`
# @return [String]
attr_accessor :boot_disk_type
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@boot_disk_size_gb = args[:boot_disk_size_gb] if args.key?(:boot_disk_size_gb)
@boot_disk_type = args[:boot_disk_type] if args.key?(:boot_disk_type)
end
end
# Represents a custom encryption key configuration that can be applied to a
# resource.
class GoogleCloudMlV1EncryptionConfig
include Google::Apis::Core::Hashable
# The Cloud KMS resource identifier of the customer-managed encryption key used
# to protect a resource, such as a training job. It has the following format: `
# projects/`PROJECT_ID`/locations/`REGION`/keyRings/`KEY_RING_NAME`/cryptoKeys/`
# KEY_NAME``
# Corresponds to the JSON property `kmsKeyName`
# @return [String]
attr_accessor :kms_key_name
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@kms_key_name = args[:kms_key_name] if args.key?(:kms_key_name)
end
end
# Represents an environment variable to be made available in a container. This
# message is a subset of the [Kubernetes EnvVar v1 core specification](https://
# kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#envvar-v1-core).
class GoogleCloudMlV1EnvVar
include Google::Apis::Core::Hashable
# Name of the environment variable. Must be a [valid C identifier](https://
# github.com/kubernetes/kubernetes/blob/v1.18.8/staging/src/k8s.io/apimachinery/
# pkg/util/validation/validation.go#L258) and must not begin with the prefix `
# AIP_`.
# Corresponds to the JSON property `name`
# @return [String]
attr_accessor :name
# Value of the environment variable. Defaults to an empty string. In this field,
# you can reference [environment variables set by AI Platform Prediction](/ai-
# platform/prediction/docs/custom-container-requirements#aip-variables) and
# environment variables set earlier in the same env field as where this message
# occurs. You cannot reference environment variables set in the Docker image. In
# order for environment variables to be expanded, reference them by using the
# following syntax: $(VARIABLE_NAME) Note that this differs from Bash variable
# expansion, which does not use parentheses. If a variable cannot be resolved,
# the reference in the input string is used unchanged. To avoid variable
# expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME)
# Corresponds to the JSON property `value`
# @return [String]
attr_accessor :value
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@name = args[:name] if args.key?(:name)
@value = args[:value] if args.key?(:value)
end
end
# Request for explanations to be issued against a trained model.
class GoogleCloudMlV1ExplainRequest
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
# Message holding configuration options for explaining model predictions. There
# are three feature attribution methods supported for TensorFlow models:
# integrated gradients, sampled Shapley, and XRAI. [Learn more about feature
# attributions.](/ai-platform/prediction/docs/ai-explanations/overview)
class GoogleCloudMlV1ExplanationConfig
include Google::Apis::Core::Hashable
# Attributes credit by computing the Aumann-Shapley value taking advantage of
# the model's fully differentiable structure. Refer to this paper for more
# details: https://arxiv.org/abs/1703.01365
# Corresponds to the JSON property `integratedGradientsAttribution`
# @return [Google::Apis::MlV1::GoogleCloudMlV1IntegratedGradientsAttribution]
attr_accessor :integrated_gradients_attribution
# An attribution method that approximates Shapley values for features that
# contribute to the label being predicted. A sampling strategy is used to
# approximate the value rather than considering all subsets of features.
# Corresponds to the JSON property `sampledShapleyAttribution`
# @return [Google::Apis::MlV1::GoogleCloudMlV1SampledShapleyAttribution]
attr_accessor :sampled_shapley_attribution
# Attributes credit by computing the XRAI taking advantage of the model's fully
# differentiable structure. Refer to this paper for more details: https://arxiv.
# org/abs/1906.02825 Currently only implemented for models with natural image
# inputs.
# Corresponds to the JSON property `xraiAttribution`
# @return [Google::Apis::MlV1::GoogleCloudMlV1XraiAttribution]
attr_accessor :xrai_attribution
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@integrated_gradients_attribution = args[:integrated_gradients_attribution] if args.key?(:integrated_gradients_attribution)
@sampled_shapley_attribution = args[:sampled_shapley_attribution] if args.key?(:sampled_shapley_attribution)
@xrai_attribution = args[:xrai_attribution] if args.key?(:xrai_attribution)
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<Google::Apis::MlV1::GoogleCloudMlV1HyperparameterOutputHyperparameterMetric>]
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<String,String>]
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<Google::Apis::MlV1::GoogleCloudMlV1ParameterSpec>]
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
# Attributes credit by computing the Aumann-Shapley value taking advantage of
# the model's fully differentiable structure. Refer to this paper for more
# details: https://arxiv.org/abs/1703.01365
class GoogleCloudMlV1IntegratedGradientsAttribution
include Google::Apis::Core::Hashable
# Number of steps for approximating the path integral. A good value to start is
# 50 and gradually increase until the sum to diff property is met within the
# desired error range.
# Corresponds to the JSON property `numIntegralSteps`
# @return [Fixnum]
attr_accessor :num_integral_steps
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@num_integral_steps = args[:num_integral_steps] if args.key?(:num_integral_steps)
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<String,String>]
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](/ai-platform/training/docs/training-jobs).
# 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<Google::Apis::MlV1::GoogleCloudMlV1Job>]
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<Google::Apis::MlV1::GoogleCloudMlV1Location>]
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<Google::Apis::MlV1::GoogleCloudMlV1Model>]
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
# The request message for the ListTrials service method.
class GoogleCloudMlV1ListOptimalTrialsRequest
include Google::Apis::Core::Hashable
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
end
end
# The response message for the ListOptimalTrials method.
class GoogleCloudMlV1ListOptimalTrialsResponse
include Google::Apis::Core::Hashable
# The pareto-optimal trials for multiple objective study or the optimal trial
# for single objective study. The definition of pareto-optimal can be checked in
# wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency
# Corresponds to the JSON property `trials`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1Trial>]
attr_accessor :trials
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@trials = args[:trials] if args.key?(:trials)
end
end
#
class GoogleCloudMlV1ListStudiesResponse
include Google::Apis::Core::Hashable
# The studies associated with the project.
# Corresponds to the JSON property `studies`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1Study>]
attr_accessor :studies
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@studies = args[:studies] if args.key?(:studies)
end
end
# The response message for the ListTrials method.
class GoogleCloudMlV1ListTrialsResponse
include Google::Apis::Core::Hashable
# The trials associated with the study.
# Corresponds to the JSON property `trials`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1Trial>]
attr_accessor :trials
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@trials = args[:trials] if args.key?(:trials)
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<Google::Apis::MlV1::GoogleCloudMlV1Version>]
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<Google::Apis::MlV1::GoogleCloudMlV1Capability>]
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
# A message representing a measurement.
class GoogleCloudMlV1Measurement
include Google::Apis::Core::Hashable
# Output only. Time that the trial has been running at the point of this
# measurement.
# Corresponds to the JSON property `elapsedTime`
# @return [String]
attr_accessor :elapsed_time
# Provides a list of metrics that act as inputs into the objective function.
# Corresponds to the JSON property `metrics`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1MeasurementMetric>]
attr_accessor :metrics
# The number of steps a machine learning model has been trained for. Must be non-
# negative.
# Corresponds to the JSON property `stepCount`
# @return [Fixnum]
attr_accessor :step_count
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@elapsed_time = args[:elapsed_time] if args.key?(:elapsed_time)
@metrics = args[:metrics] if args.key?(:metrics)
@step_count = args[:step_count] if args.key?(:step_count)
end
end
# MetricSpec contains the specifications to use to calculate the desired nodes
# count when autoscaling is enabled.
class GoogleCloudMlV1MetricSpec
include Google::Apis::Core::Hashable
# metric name.
# Corresponds to the JSON property `name`
# @return [String]
attr_accessor :name
# Target specifies the target value for the given metric; once real metric
# deviates from the threshold by a certain percentage, the node count changes.
# Corresponds to the JSON property `target`
# @return [Fixnum]
attr_accessor :target
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@name = args[:name] if args.key?(:name)
@target = args[:target] if args.key?(:target)
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.
# 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<String,String>]
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 Cloud Logging. These can be more verbose than the standard access logs (see
# `onlinePredictionLogging`) and can incur higher cost. However, they are
# helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing),
# especially if your project receives prediction requests at a high QPS.
# Estimate your costs before enabling this option. Default is false.
# Corresponds to the JSON property `onlinePredictionConsoleLogging`
# @return [Boolean]
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 Cloud Logging.
# These logs are like standard server access logs, containing information like
# timestamp and latency for each request. Note that [logs may incur a cost](/
# stackdriver/pricing), especially if your project receives prediction requests
# at a high queries per second rate (QPS). Estimate your costs before enabling
# this option. Default is false.
# Corresponds to the JSON property `onlinePredictionLogging`
# @return [Boolean]
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. Only
# one region per model is supported. Defaults to 'us-central1' if nothing is set.
# See the available regions for AI Platform services. Note: * No matter where a
# model is deployed, it can always be accessed by users from anywhere, both for
# online and batch prediction. * The region for a batch prediction job is set by
# the region field when submitting the batch prediction job and does not take
# its value from this field.
# Corresponds to the JSON property `regions`
# @return [Array<String>]
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<String,String>]
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.
# 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<String>]
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<Float>]
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<String>]
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
# Arguments to the entrypoint command. The following rules apply for
# container_command and container_args: - If you do not supply command or args:
# The defaults defined in the Docker image are used. - If you supply a command
# but no args: The default EntryPoint and the default Cmd defined in the Docker
# image are ignored. Your command is run without any arguments. - If you supply
# only args: The default Entrypoint defined in the Docker image is run with the
# args that you supplied. - If you supply a command and args: The default
# Entrypoint and the default Cmd defined in the Docker image are ignored. Your
# command is run with your args. It cannot be set if custom container image is
# not provided. Note that this field and [TrainingInput.args] are mutually
# exclusive, i.e., both cannot be set at the same time.
# Corresponds to the JSON property `containerArgs`
# @return [Array<String>]
attr_accessor :container_args
# The command with which the replica's custom container is run. If provided, it
# will override default ENTRYPOINT of the docker image. If not provided, the
# docker image's ENTRYPOINT is used. It cannot be set if custom container image
# is not provided. Note that this field and [TrainingInput.args] are mutually
# exclusive, i.e., both cannot be set at the same time.
# Corresponds to the JSON property `containerCommand`
# @return [Array<String>]
attr_accessor :container_command
# Represents the config of disk options.
# Corresponds to the JSON property `diskConfig`
# @return [Google::Apis::MlV1::GoogleCloudMlV1DiskConfig]
attr_accessor :disk_config
# The Docker image to run on the replica. This image must be in Container
# Registry. Learn more about [configuring custom containers](/ai-platform/
# training/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)
@container_args = args[:container_args] if args.key?(:container_args)
@container_command = args[:container_command] if args.key?(:container_command)
@disk_config = args[:disk_config] if args.key?(:disk_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 specified 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 nameType Mode model STRING REQUIRED model_version STRING REQUIRED time
# TIMESTAMP REQUIRED raw_data STRING REQUIRED raw_prediction STRING NULLABLE
# groundtruth STRING NULLABLE
# 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
# Specifies HTTP paths served by a custom container. AI Platform Prediction
# sends requests to these paths on the container; the custom container must run
# an HTTP server that responds to these requests with appropriate responses.
# Read [Custom container requirements](/ai-platform/prediction/docs/custom-
# container-requirements) for details on how to create your container image to
# meet these requirements.
class GoogleCloudMlV1RouteMap
include Google::Apis::Core::Hashable
# HTTP path on the container to send health checkss to. AI Platform Prediction
# intermittently sends GET requests to this path on the container's IP address
# and port to check that the container is healthy. Read more about [health
# checks](/ai-platform/prediction/docs/custom-container-requirements#checks).
# For example, if you set this field to `/bar`, then AI Platform Prediction
# intermittently sends a GET request to the `/bar` path on the port of your
# container specified by the first value of Version.container.ports. If you don'
# t specify this field, it defaults to the following value: /v1/models/ MODEL/
# versions/VERSION The placeholders in this value are replaced as follows: *
# MODEL: The name of the parent Model. This does not include the "projects/
# PROJECT_ID/models/" prefix that the API returns in output; it is the bare
# model name, as provided to projects.models.create. * VERSION: The name of the
# model version. This does not include the "projects/PROJECT_ID /models/MODEL/
# versions/" prefix that the API returns in output; it is the bare version name,
# as provided to projects.models.versions.create.
# Corresponds to the JSON property `health`
# @return [String]
attr_accessor :health
# HTTP path on the container to send prediction requests to. AI Platform
# Prediction forwards requests sent using projects.predict to this path on the
# container's IP address and port. AI Platform Prediction then returns the
# container's response in the API response. For example, if you set this field
# to `/foo`, then when AI Platform Prediction receives a prediction request, it
# forwards the request body in a POST request to the `/foo` path on the port of
# your container specified by the first value of Version.container.ports. If you
# don't specify this field, it defaults to the following value: /v1/models/MODEL/
# versions/VERSION:predict The placeholders in this value are replaced as
# follows: * MODEL: The name of the parent Model. This does not include the "
# projects/PROJECT_ID/models/" prefix that the API returns in output; it is the
# bare model name, as provided to projects.models.create. * VERSION: The name of
# the model version. This does not include the "projects/PROJECT_ID/models/MODEL/
# versions/" prefix that the API returns in output; it is the bare version name,
# as provided to projects.models.versions.create.
# Corresponds to the JSON property `predict`
# @return [String]
attr_accessor :predict
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@health = args[:health] if args.key?(:health)
@predict = args[:predict] if args.key?(:predict)
end
end
# An attribution method that approximates Shapley values for features that
# contribute to the label being predicted. A sampling strategy is used to
# approximate the value rather than considering all subsets of features.
class GoogleCloudMlV1SampledShapleyAttribution
include Google::Apis::Core::Hashable
# The number of feature permutations to consider when approximating the Shapley
# values.
# Corresponds to the JSON property `numPaths`
# @return [Fixnum]
attr_accessor :num_paths
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@num_paths = args[:num_paths] if args.key?(:num_paths)
end
end
# All parameters related to scheduling of training jobs.
class GoogleCloudMlV1Scheduling
include Google::Apis::Core::Hashable
# Optional. The maximum job running time, expressed in seconds. The field can
# contain up to nine fractional digits, terminated by `s`. If not specified,
# this field defaults to `604800s` (seven days). If the training job is still
# running after this duration, AI Platform Training cancels it. The duration is
# measured from when the job enters the `RUNNING` state; therefore it does not
# overlap with the duration limited by Scheduling.max_wait_time. For example, if
# you want to ensure your job runs for no more than 2 hours, set this field to `
# 7200s` (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your
# training job using the `gcloud` tool, you can [specify this field in a `config.
# yaml` file](/ai-platform/training/docs/training-jobs#
# formatting_your_configuration_parameters). For example: ```yaml trainingInput:
# scheduling: maxRunningTime: 7200s ```
# Corresponds to the JSON property `maxRunningTime`
# @return [String]
attr_accessor :max_running_time
# Optional. The maximum job wait time, expressed in seconds. The field can
# contain up to nine fractional digits, terminated by `s`. If not specified,
# there is no limit to the wait time. The minimum for this field is `1800s` (30
# minutes). If the training job has not entered the `RUNNING` state after this
# duration, AI Platform Training cancels it. After the job begins running, it
# can no longer be cancelled due to the maximum wait time. Therefore the
# duration limited by this field does not overlap with the duration limited by
# Scheduling.max_running_time. For example, if the job temporarily stops running
# and retries due to a [VM restart](/ai-platform/training/docs/overview#restarts)
# , this cannot lead to a maximum wait time cancellation. However, independently
# of this constraint, AI Platform Training might stop a job if there are too
# many retries due to exhausted resources in a region. The following example
# describes how you might use this field: To cancel your job if it doesn't start
# running within 1 hour, set this field to `3600s` (1 hour * 60 minutes / hour *
# 60 seconds / minute). If the job is still in the `QUEUED` or `PREPARING` state
# after an hour of waiting, AI Platform Training cancels the job. If you submit
# your training job using the `gcloud` tool, you can [specify this field in a `
# config.yaml` file](/ai-platform/training/docs/training-jobs#
# formatting_your_configuration_parameters). For example: ```yaml trainingInput:
# scheduling: maxWaitTime: 3600s ```
# Corresponds to the JSON property `maxWaitTime`
# @return [String]
attr_accessor :max_wait_time
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@max_running_time = args[:max_running_time] if args.key?(:max_running_time)
@max_wait_time = args[:max_wait_time] if args.key?(:max_wait_time)
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
#
class GoogleCloudMlV1StopTrialRequest
include Google::Apis::Core::Hashable
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
end
end
# A message representing a Study.
class GoogleCloudMlV1Study
include Google::Apis::Core::Hashable
# Output only. Time at which the study was created.
# Corresponds to the JSON property `createTime`
# @return [String]
attr_accessor :create_time
# Output only. A human readable reason why the Study is inactive. This should be
# empty if a study is ACTIVE or COMPLETED.
# Corresponds to the JSON property `inactiveReason`
# @return [String]
attr_accessor :inactive_reason
# Output only. The name of a study.
# Corresponds to the JSON property `name`
# @return [String]
attr_accessor :name
# Output only. The detailed state of a study.
# Corresponds to the JSON property `state`
# @return [String]
attr_accessor :state
# Represents configuration of a study.
# Corresponds to the JSON property `studyConfig`
# @return [Google::Apis::MlV1::GoogleCloudMlV1StudyConfig]
attr_accessor :study_config
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@create_time = args[:create_time] if args.key?(:create_time)
@inactive_reason = args[:inactive_reason] if args.key?(:inactive_reason)
@name = args[:name] if args.key?(:name)
@state = args[:state] if args.key?(:state)
@study_config = args[:study_config] if args.key?(:study_config)
end
end
# Represents configuration of a study.
class GoogleCloudMlV1StudyConfig
include Google::Apis::Core::Hashable
# The search algorithm specified for the study.
# Corresponds to the JSON property `algorithm`
# @return [String]
attr_accessor :algorithm
# Configuration for Automated Early Stopping of Trials. If no
# implementation_config is set, automated early stopping will not be run.
# Corresponds to the JSON property `automatedStoppingConfig`
# @return [Google::Apis::MlV1::GoogleCloudMlV1AutomatedStoppingConfig]
attr_accessor :automated_stopping_config
# Metric specs for the study.
# Corresponds to the JSON property `metrics`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1StudyConfigMetricSpec>]
attr_accessor :metrics
# Required. The set of parameters to tune.
# Corresponds to the JSON property `parameters`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1StudyConfigParameterSpec>]
attr_accessor :parameters
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@algorithm = args[:algorithm] if args.key?(:algorithm)
@automated_stopping_config = args[:automated_stopping_config] if args.key?(:automated_stopping_config)
@metrics = args[:metrics] if args.key?(:metrics)
@parameters = args[:parameters] if args.key?(:parameters)
end
end
# Metadata field of a google.longrunning.Operation associated with a
# SuggestTrialsRequest.
class GoogleCloudMlV1SuggestTrialsMetadata
include Google::Apis::Core::Hashable
# The identifier of the client that is requesting the suggestion.
# Corresponds to the JSON property `clientId`
# @return [String]
attr_accessor :client_id
# The time operation was submitted.
# Corresponds to the JSON property `createTime`
# @return [String]
attr_accessor :create_time
# The name of the study that the trial belongs to.
# Corresponds to the JSON property `study`
# @return [String]
attr_accessor :study
# The number of suggestions requested.
# Corresponds to the JSON property `suggestionCount`
# @return [Fixnum]
attr_accessor :suggestion_count
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@client_id = args[:client_id] if args.key?(:client_id)
@create_time = args[:create_time] if args.key?(:create_time)
@study = args[:study] if args.key?(:study)
@suggestion_count = args[:suggestion_count] if args.key?(:suggestion_count)
end
end
# The request message for the SuggestTrial service method.
class GoogleCloudMlV1SuggestTrialsRequest
include Google::Apis::Core::Hashable
# Required. The identifier of the client that is requesting the suggestion. If
# multiple SuggestTrialsRequests have the same `client_id`, the service will
# return the identical suggested trial if the trial is pending, and provide a
# new trial if the last suggested trial was completed.
# Corresponds to the JSON property `clientId`
# @return [String]
attr_accessor :client_id
# Required. The number of suggestions requested.
# Corresponds to the JSON property `suggestionCount`
# @return [Fixnum]
attr_accessor :suggestion_count
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@client_id = args[:client_id] if args.key?(:client_id)
@suggestion_count = args[:suggestion_count] if args.key?(:suggestion_count)
end
end
# This message will be placed in the response field of a completed google.
# longrunning.Operation associated with a SuggestTrials request.
class GoogleCloudMlV1SuggestTrialsResponse
include Google::Apis::Core::Hashable
# The time at which operation processing completed.
# Corresponds to the JSON property `endTime`
# @return [String]
attr_accessor :end_time
# The time at which the operation was started.
# Corresponds to the JSON property `startTime`
# @return [String]
attr_accessor :start_time
# The state of the study.
# Corresponds to the JSON property `studyState`
# @return [String]
attr_accessor :study_state
# A list of trials.
# Corresponds to the JSON property `trials`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1Trial>]
attr_accessor :trials
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@end_time = args[:end_time] if args.key?(:end_time)
@start_time = args[:start_time] if args.key?(:start_time)
@study_state = args[:study_state] if args.key?(:study_state)
@trials = args[:trials] if args.key?(:trials)
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](/ai-platform/training/docs/training-jobs).
class GoogleCloudMlV1TrainingInput
include Google::Apis::Core::Hashable
# Optional. Command-line arguments passed to the training application when it
# starts. If your job uses a custom container, then the arguments are passed to
# the container's `ENTRYPOINT` command.
# Corresponds to the JSON property `args`
# @return [Array<String>]
attr_accessor :args
# Represents a custom encryption key configuration that can be applied to a
# resource.
# Corresponds to the JSON property `encryptionConfig`
# @return [Google::Apis::MlV1::GoogleCloudMlV1EncryptionConfig]
attr_accessor :encryption_config
# Represents the configuration for a replica in a cluster.
# Corresponds to the JSON property `evaluatorConfig`
# @return [Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig]
attr_accessor :evaluator_config
# Optional. The number of evaluator replicas to use for the training job. Each
# replica in the cluster will be of the type specified in `evaluator_type`. This
# value can only be used when `scale_tier` is set to `CUSTOM`. If you set this
# value, you must also set `evaluator_type`. The default value is zero.
# Corresponds to the JSON property `evaluatorCount`
# @return [Fixnum]
attr_accessor :evaluator_count
# Optional. Specifies the type of virtual machine to use for your training job's
# evaluator 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. This value must be
# present when `scaleTier` is set to `CUSTOM` and `evaluatorCount` is greater
# than zero.
# Corresponds to the JSON property `evaluatorType`
# @return [String]
attr_accessor :evaluator_type
# 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
# Optional. The full name of the [Compute Engine network](/vpc/docs/vpc) to
# which the Job is peered. For example, `projects/12345/global/networks/myVPC`.
# The format of this field is `projects/`project`/global/networks/`network``,
# where `project` is a project number (like `12345`) and `network` is network
# name. Private services access must already be configured for the network. If
# left unspecified, the Job is not peered with any network. [Learn about using
# VPC Network Peering.](/ai-platform/training/docs/vpc-peering).
# Corresponds to the JSON property `network`
# @return [String]
attr_accessor :network
# 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<String>]
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. You must either specify this
# field or specify `masterConfig.imageUri`. The following Python versions are
# available: * Python '3.7' is available when `runtime_version` is set to '1.15'
# or later. * Python '3.5' is available when `runtime_version` is set to a
# version from '1.4' to '1.14'. * Python '2.7' is available when `
# runtime_version` is set to '1.15' or earlier. Read more about the Python
# versions available for [each runtime version](/ml-engine/docs/runtime-version-
# list).
# Corresponds to the JSON property `pythonVersion`
# @return [String]
attr_accessor :python_version
# Required. The region to run the training job in. See the [available regions](/
# ai-platform/training/docs/regions) for AI Platform Training.
# Corresponds to the JSON property `region`
# @return [String]
attr_accessor :region
# Optional. The AI Platform runtime version to use for training. You must either
# specify this field or specify `masterConfig.imageUri`. For more information,
# see the [runtime version list](/ai-platform/training/docs/runtime-version-list)
# and learn [how to manage runtime versions](/ai-platform/training/docs/
# versioning).
# 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
# All parameters related to scheduling of training jobs.
# Corresponds to the JSON property `scheduling`
# @return [Google::Apis::MlV1::GoogleCloudMlV1Scheduling]
attr_accessor :scheduling
# Optional. The email address of a service account to use when running the
# training appplication. You must have the `iam.serviceAccounts.actAs`
# permission for the specified service account. In addition, the AI Platform
# Training Google-managed service account must have the `roles/iam.
# serviceAccountAdmin` role for the specified service account. [Learn more about
# configuring a service account.](/ai-platform/training/docs/custom-service-
# account) If not specified, the AI Platform Training Google-managed service
# account is used by default.
# Corresponds to the JSON property `serviceAccount`
# @return [String]
attr_accessor :service_account
# Optional. Use `chief` instead of `master` in the `TF_CONFIG` environment
# variable when training with a custom container. Defaults to `false`. [Learn
# more about this field.](/ai-platform/training/docs/distributed-training-
# details#chief-versus-master) This field has no effect for training jobs that
# don't use a custom container.
# 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)
@encryption_config = args[:encryption_config] if args.key?(:encryption_config)
@evaluator_config = args[:evaluator_config] if args.key?(:evaluator_config)
@evaluator_count = args[:evaluator_count] if args.key?(:evaluator_count)
@evaluator_type = args[:evaluator_type] if args.key?(:evaluator_type)
@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)
@network = args[:network] if args.key?(:network)
@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)
@scheduling = args[:scheduling] if args.key?(:scheduling)
@service_account = args[:service_account] if args.key?(:service_account)
@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<Google::Apis::MlV1::GoogleCloudMlV1HyperparameterOutput>]
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
# A message representing a trial.
class GoogleCloudMlV1Trial
include Google::Apis::Core::Hashable
# Output only. The identifier of the client that originally requested this trial.
# Corresponds to the JSON property `clientId`
# @return [String]
attr_accessor :client_id
# Output only. Time at which the trial's status changed to COMPLETED.
# Corresponds to the JSON property `endTime`
# @return [String]
attr_accessor :end_time
# A message representing a measurement.
# Corresponds to the JSON property `finalMeasurement`
# @return [Google::Apis::MlV1::GoogleCloudMlV1Measurement]
attr_accessor :final_measurement
# Output only. A human readable string describing why the trial is infeasible.
# This should only be set if trial_infeasible is true.
# Corresponds to the JSON property `infeasibleReason`
# @return [String]
attr_accessor :infeasible_reason
# A list of measurements that are strictly lexicographically ordered by their
# induced tuples (steps, elapsed_time). These are used for early stopping
# computations.
# Corresponds to the JSON property `measurements`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1Measurement>]
attr_accessor :measurements
# Output only. Name of the trial assigned by the service.
# Corresponds to the JSON property `name`
# @return [String]
attr_accessor :name
# The parameters of the trial.
# Corresponds to the JSON property `parameters`
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1TrialParameter>]
attr_accessor :parameters
# Output only. Time at which the trial was started.
# Corresponds to the JSON property `startTime`
# @return [String]
attr_accessor :start_time
# The detailed state of a trial.
# Corresponds to the JSON property `state`
# @return [String]
attr_accessor :state
# Output only. If true, the parameters in this trial are not attempted again.
# Corresponds to the JSON property `trialInfeasible`
# @return [Boolean]
attr_accessor :trial_infeasible
alias_method :trial_infeasible?, :trial_infeasible
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@client_id = args[:client_id] if args.key?(:client_id)
@end_time = args[:end_time] if args.key?(:end_time)
@final_measurement = args[:final_measurement] if args.key?(:final_measurement)
@infeasible_reason = args[:infeasible_reason] if args.key?(:infeasible_reason)
@measurements = args[:measurements] if args.key?(:measurements)
@name = args[:name] if args.key?(:name)
@parameters = args[:parameters] if args.key?(:parameters)
@start_time = args[:start_time] if args.key?(:start_time)
@state = args[:state] if args.key?(:state)
@trial_infeasible = args[:trial_infeasible] if args.key?(:trial_infeasible)
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.
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
# Specification of a custom container for serving predictions. This message is a
# subset of the [Kubernetes Container v1 core specification](https://kubernetes.
# io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
# Corresponds to the JSON property `container`
# @return [Google::Apis::MlV1::GoogleCloudMlV1ContainerSpec]
attr_accessor :container
# Output only. The time the version was created.
# Corresponds to the JSON property `createTime`
# @return [String]
attr_accessor :create_time
# The Cloud Storage URI of a directory containing trained model artifacts to be
# used to create the model version. See the [guide to deploying models](/ai-
# platform/prediction/docs/deploying-models) for more information. The total
# number of files under this directory must not exceed 1000. During projects.
# models.versions.create, AI Platform Prediction copies all files from the
# specified directory to a location managed by the service. From then on, AI
# Platform Prediction uses these copies of the model artifacts to serve
# predictions, not the original files in Cloud Storage, so this location is
# useful only as a historical record. If you specify container, then this field
# is optional. Otherwise, it is required. Learn [how to use this field with a
# custom container](/ai-platform/prediction/docs/custom-container-requirements#
# artifacts).
# 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
# Message holding configuration options for explaining model predictions. There
# are three feature attribution methods supported for TensorFlow models:
# integrated gradients, sampled Shapley, and XRAI. [Learn more about feature
# attributions.](/ai-platform/prediction/docs/ai-explanations/overview)
# Corresponds to the JSON property `explanationConfig`
# @return [Google::Apis::MlV1::GoogleCloudMlV1ExplanationConfig]
attr_accessor :explanation_config
# 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](/ai-platform/prediction/docs/custom-prediction-routines) or if you're
# using a [custom container](/ai-platform/prediction/docs/use-custom-container).
# 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.
# 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<String,String>]
attr_accessor :labels
feat: Automated regeneration of ml v1 client (#2380) This PR was generated using Autosynth. :rainbow: <details><summary>Log from Synthtool</summary> ``` 2021-01-13 03:02:07,628 synthtool [DEBUG] > Executing /home/kbuilder/.cache/synthtool/google-api-ruby-client/synth.py. On branch autosynth-ml-v1 nothing to commit, working tree clean 2021-01-13 03:02:07,699 synthtool [DEBUG] > Running: docker run --rm -v/home/kbuilder/.cache/synthtool/google-api-ruby-client:/workspace -v/var/run/docker.sock:/var/run/docker.sock -w /workspace --entrypoint script/synth.rb gcr.io/cloud-devrel-kokoro-resources/yoshi-ruby/autosynth ml v1 DEBUG:synthtool:Running: docker run --rm -v/home/kbuilder/.cache/synthtool/google-api-ruby-client:/workspace -v/var/run/docker.sock:/var/run/docker.sock -w /workspace --entrypoint script/synth.rb gcr.io/cloud-devrel-kokoro-resources/yoshi-ruby/autosynth ml v1 git clean -df bundle install Don't run Bundler as root. Bundler can ask for sudo if it is needed, and installing your bundle as root will break this application for all non-root users on this machine. The dependency jruby-openssl (>= 0) will be unused by any of the platforms Bundler is installing for. Bundler is installing for ruby but the dependency is only for java. To add those platforms to the bundle, run `bundle lock --add-platform java`. Fetching gem metadata from https://rubygems.org/......... Fetching gem metadata from https://rubygems.org/. Resolving dependencies... Fetching rake 11.3.0 Installing rake 11.3.0 Fetching concurrent-ruby 1.1.7 Installing concurrent-ruby 1.1.7 Fetching i18n 1.8.7 Installing i18n 1.8.7 Fetching minitest 5.14.3 Installing minitest 5.14.3 Fetching tzinfo 2.0.4 Installing tzinfo 2.0.4 Fetching zeitwerk 2.4.2 Installing zeitwerk 2.4.2 Fetching activesupport 6.1.1 Installing activesupport 6.1.1 Fetching public_suffix 4.0.6 Installing public_suffix 4.0.6 Fetching addressable 2.7.0 Installing addressable 2.7.0 Fetching ast 2.4.1 Installing ast 2.4.1 Using bundler 2.1.4 Fetching byebug 11.1.3 Installing byebug 11.1.3 with native extensions Fetching coderay 1.1.3 Installing coderay 1.1.3 Fetching json 2.5.1 Installing json 2.5.1 with native extensions Fetching docile 1.3.4 Installing docile 1.3.4 Fetching simplecov-html 0.10.2 Installing simplecov-html 0.10.2 Fetching simplecov 0.16.1 Installing simplecov 0.16.1 Using sync 0.5.0 Fetching tins 1.28.0 Installing tins 1.28.0 Fetching term-ansicolor 1.7.1 Installing term-ansicolor 1.7.1 Fetching thor 0.20.3 Installing thor 0.20.3 Fetching coveralls 0.8.23 Installing coveralls 0.8.23 Fetching rexml 3.2.4 Installing rexml 3.2.4 Fetching crack 0.4.5 Installing crack 0.4.5 Fetching declarative 0.0.20 Installing declarative 0.0.20 Fetching declarative-option 0.1.0 Installing declarative-option 0.1.0 Fetching diff-lcs 1.4.4 Installing diff-lcs 1.4.4 Fetching dotenv 2.7.6 Installing dotenv 2.7.6 Fetching fakefs 0.20.1 Installing fakefs 0.20.1 Fetching faraday-net_http 1.0.1 Installing faraday-net_http 1.0.1 Fetching multipart-post 2.1.1 Installing multipart-post 2.1.1 Fetching ruby2_keywords 0.0.2 Installing ruby2_keywords 0.0.2 Fetching faraday 1.3.0 Installing faraday 1.3.0 Fetching gems 1.2.0 Installing gems 1.2.0 Fetching github-markup 1.7.0 Installing github-markup 1.7.0 Fetching jwt 2.2.2 Installing jwt 2.2.2 Fetching memoist 0.16.2 Installing memoist 0.16.2 Fetching multi_json 1.15.0 Installing multi_json 1.15.0 Fetching os 0.9.6 Installing os 0.9.6 Fetching signet 0.14.0 Installing signet 0.14.0 Fetching googleauth 0.14.0 Installing googleauth 0.14.0 Fetching httpclient 2.8.3 Installing httpclient 2.8.3 Fetching mini_mime 1.0.2 Installing mini_mime 1.0.2 Fetching uber 0.1.0 Installing uber 0.1.0 Fetching representable 3.0.4 Installing representable 3.0.4 Fetching retriable 3.1.2 Installing retriable 3.1.2 Fetching google-apis-core 0.2.0 Installing google-apis-core 0.2.0 Fetching google-apis-discovery_v1 0.1.0 Installing google-apis-discovery_v1 0.1.0 Using google-apis-generator 0.1.1 from source at `.` Fetching google-id-token 1.4.2 Installing google-id-token 1.4.2 Fetching hashdiff 1.0.1 Installing hashdiff 1.0.1 Fetching mime-types-data 3.2020.1104 Installing mime-types-data 3.2020.1104 Fetching mime-types 3.3.1 Installing mime-types 3.3.1 Fetching multi_xml 0.6.0 Installing multi_xml 0.6.0 Fetching httparty 0.18.1 Installing httparty 0.18.1 Fetching rspec-support 3.10.1 Installing rspec-support 3.10.1 Fetching rspec-core 3.10.1 Installing rspec-core 3.10.1 Fetching rspec-expectations 3.10.1 Installing rspec-expectations 3.10.1 Fetching rspec-mocks 3.10.1 Installing rspec-mocks 3.10.1 Fetching rspec 3.10.0 Installing rspec 3.10.0 Fetching json_spec 1.1.5 Installing json_spec 1.1.5 Fetching launchy 2.5.0 Installing launchy 2.5.0 Fetching little-plugger 1.1.4 Installing little-plugger 1.1.4 Fetching logging 2.3.0 Installing logging 2.3.0 Fetching method_source 1.0.0 Installing method_source 1.0.0 Fetching opencensus 0.5.0 Installing opencensus 0.5.0 Fetching parallel 1.20.1 Installing parallel 1.20.1 Fetching parser 2.7.2.0 Installing parser 2.7.2.0 Fetching powerpack 0.1.3 Installing powerpack 0.1.3 Fetching pry 0.13.1 Installing pry 0.13.1 Fetching pry-byebug 3.9.0 Installing pry-byebug 3.9.0 Fetching yard 0.9.26 Installing yard 0.9.26 Fetching pry-doc 0.13.5 Installing pry-doc 0.13.5 Fetching rainbow 2.2.2 Installing rainbow 2.2.2 with native extensions Fetching redcarpet 3.5.1 Installing redcarpet 3.5.1 with native extensions Fetching redis 3.3.5 Installing redis 3.3.5 Fetching rmail 1.1.4 Installing rmail 1.1.4 Fetching ruby-progressbar 1.11.0 Installing ruby-progressbar 1.11.0 Fetching unicode-display_width 1.7.0 Installing unicode-display_width 1.7.0 Fetching rubocop 0.49.1 Installing rubocop 0.49.1 Fetching webmock 2.3.2 Installing webmock 2.3.2 Bundle complete! 25 Gemfile dependencies, 81 gems now installed. Use `bundle info [gemname]` to see where a bundled gem is installed. Post-install message from i18n: HEADS UP! i18n 1.1 changed fallbacks to exclude default locale. But that may break your application. If you are upgrading your Rails application from an older version of Rails: Please check your Rails app for 'config.i18n.fallbacks = true'. If you're using I18n (>= 1.1.0) and Rails (< 5.2.2), this should be 'config.i18n.fallbacks = [I18n.default_locale]'. If not, fallbacks will be broken in your app by I18n 1.1.x. If you are starting a NEW Rails application, you can ignore this notice. For more info see: https://github.com/svenfuchs/i18n/releases/tag/v1.1.0 Post-install message from httparty: When you HTTParty, you must party hard! echo a | bundle exec bin/generate-api gen /workspace/generated --api=ml.v1 --names=/workspace/api_names.yaml --names-out=/workspace/api_names_out.yaml --spot-check Loading ml, version v1 from https://raw.githubusercontent.com/googleapis/discovery-artifact-manager/master/discoveries/ml.v1.json conflict google-apis-ml_v1/lib/google/apis/ml_v1/classes.rb <s/ml_v1/classes.rb? (enter "h" for help) [Ynaqdhm] a force google-apis-ml_v1/lib/google/apis/ml_v1/classes.rb conflict google-apis-ml_v1/lib/google/apis/ml_v1/gem_version.rb force google-apis-ml_v1/lib/google/apis/ml_v1/gem_version.rb conflict google-apis-ml_v1/CHANGELOG.md force google-apis-ml_v1/CHANGELOG.md Don't run Bundler as root. Bundler can ask for sudo if it is needed, and installing your bundle as root will break this application for all non-root users on this machine. The dependency jruby-openssl (>= 0) will be unused by any of the platforms Bundler is installing for. Bundler is installing for ruby but the dependency is only for java. To add those platforms to the bundle, run `bundle lock --add-platform java`. Fetching gem metadata from https://rubygems.org/......... Fetching gem metadata from https://rubygems.org/. Resolving dependencies... Fetching rake 13.0.3 Installing rake 13.0.3 Using public_suffix 4.0.6 Using addressable 2.7.0 Using bundler 2.1.4 Using declarative 0.0.20 Using declarative-option 0.1.0 Using diff-lcs 1.4.4 Using faraday-net_http 1.0.1 Using multipart-post 2.1.1 Using ruby2_keywords 0.0.2 Using faraday 1.3.0 Using jwt 2.2.2 Using memoist 0.16.2 Using multi_json 1.15.0 Fetching os 1.1.1 Installing os 1.1.1 Using signet 0.14.0 Using googleauth 0.14.0 Using httpclient 2.8.3 Using mini_mime 1.0.2 Using uber 0.1.0 Using representable 3.0.4 Using retriable 3.1.2 Using rexml 3.2.4 Using google-apis-core 0.2.0 Using google-apis-ml_v1 0.2.0 from source at `.` Using opencensus 0.5.0 Using redcarpet 3.5.1 Using rspec-support 3.10.1 Using rspec-core 3.10.1 Using rspec-expectations 3.10.1 Using rspec-mocks 3.10.1 Using rspec 3.10.0 Using yard 0.9.26 Bundle complete! 8 Gemfile dependencies, 33 gems now installed. Use `bundle info [gemname]` to see where a bundled gem is installed. /root/.rbenv/versions/2.6.6/bin/ruby -I/root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-core-3.10.1/lib:/root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-support-3.10.1/lib /root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-core-3.10.1/exe/rspec --pattern spec/\*\*\{,/\*/\*\*\}/\*_spec.rb Google::Apis::MlV1 should load Finished in 0.32051 seconds (files took 0.10628 seconds to load) 1 example, 0 failures Files: 4 Modules: 3 ( 1 undocumented) Classes: 87 ( 11 undocumented) Constants: 6 ( 0 undocumented) Attributes: 209 ( 0 undocumented) Methods: 219 ( 0 undocumented) 97.71% documented google-apis-ml_v1 0.2.0 built to pkg/google-apis-ml_v1-0.2.0.gem. identical /workspace/api_names_out.yaml 2021-01-13 03:02:44,210 synthtool [DEBUG] > Wrote metadata to generated/google-apis-ml_v1/synth.metadata. DEBUG:synthtool:Wrote metadata to generated/google-apis-ml_v1/synth.metadata. ``` </details> Full log will be available here: https://source.cloud.google.com/results/invocations/2c9a7f94-8490-460d-bb8a-c9c25cb6fec9/targets - [ ] To automatically regenerate this PR, check this box.
2021-01-13 11:20:01 +00:00
# Output only. The [AI Platform (Unified) `Model`](https://cloud.google.com/ai-
# platform-unified/docs/reference/rest/v1beta1/projects.locations.models) ID for
# the last [model migration](https://cloud.google.com/ai-platform-unified/docs/
# start/migrating-to-ai-platform-unified).
feat: Automated regeneration of ml v1 client (#2255)
2021-01-08 16:44:10 +00:00
# Corresponds to the JSON property `lastMigrationModelId`
# @return [String]
attr_accessor :last_migration_model_id
feat: Automated regeneration of ml v1 client (#2380) This PR was generated using Autosynth. :rainbow: <details><summary>Log from Synthtool</summary> ``` 2021-01-13 03:02:07,628 synthtool [DEBUG] > Executing /home/kbuilder/.cache/synthtool/google-api-ruby-client/synth.py. On branch autosynth-ml-v1 nothing to commit, working tree clean 2021-01-13 03:02:07,699 synthtool [DEBUG] > Running: docker run --rm -v/home/kbuilder/.cache/synthtool/google-api-ruby-client:/workspace -v/var/run/docker.sock:/var/run/docker.sock -w /workspace --entrypoint script/synth.rb gcr.io/cloud-devrel-kokoro-resources/yoshi-ruby/autosynth ml v1 DEBUG:synthtool:Running: docker run --rm -v/home/kbuilder/.cache/synthtool/google-api-ruby-client:/workspace -v/var/run/docker.sock:/var/run/docker.sock -w /workspace --entrypoint script/synth.rb gcr.io/cloud-devrel-kokoro-resources/yoshi-ruby/autosynth ml v1 git clean -df bundle install Don't run Bundler as root. Bundler can ask for sudo if it is needed, and installing your bundle as root will break this application for all non-root users on this machine. The dependency jruby-openssl (>= 0) will be unused by any of the platforms Bundler is installing for. Bundler is installing for ruby but the dependency is only for java. To add those platforms to the bundle, run `bundle lock --add-platform java`. Fetching gem metadata from https://rubygems.org/......... Fetching gem metadata from https://rubygems.org/. Resolving dependencies... Fetching rake 11.3.0 Installing rake 11.3.0 Fetching concurrent-ruby 1.1.7 Installing concurrent-ruby 1.1.7 Fetching i18n 1.8.7 Installing i18n 1.8.7 Fetching minitest 5.14.3 Installing minitest 5.14.3 Fetching tzinfo 2.0.4 Installing tzinfo 2.0.4 Fetching zeitwerk 2.4.2 Installing zeitwerk 2.4.2 Fetching activesupport 6.1.1 Installing activesupport 6.1.1 Fetching public_suffix 4.0.6 Installing public_suffix 4.0.6 Fetching addressable 2.7.0 Installing addressable 2.7.0 Fetching ast 2.4.1 Installing ast 2.4.1 Using bundler 2.1.4 Fetching byebug 11.1.3 Installing byebug 11.1.3 with native extensions Fetching coderay 1.1.3 Installing coderay 1.1.3 Fetching json 2.5.1 Installing json 2.5.1 with native extensions Fetching docile 1.3.4 Installing docile 1.3.4 Fetching simplecov-html 0.10.2 Installing simplecov-html 0.10.2 Fetching simplecov 0.16.1 Installing simplecov 0.16.1 Using sync 0.5.0 Fetching tins 1.28.0 Installing tins 1.28.0 Fetching term-ansicolor 1.7.1 Installing term-ansicolor 1.7.1 Fetching thor 0.20.3 Installing thor 0.20.3 Fetching coveralls 0.8.23 Installing coveralls 0.8.23 Fetching rexml 3.2.4 Installing rexml 3.2.4 Fetching crack 0.4.5 Installing crack 0.4.5 Fetching declarative 0.0.20 Installing declarative 0.0.20 Fetching declarative-option 0.1.0 Installing declarative-option 0.1.0 Fetching diff-lcs 1.4.4 Installing diff-lcs 1.4.4 Fetching dotenv 2.7.6 Installing dotenv 2.7.6 Fetching fakefs 0.20.1 Installing fakefs 0.20.1 Fetching faraday-net_http 1.0.1 Installing faraday-net_http 1.0.1 Fetching multipart-post 2.1.1 Installing multipart-post 2.1.1 Fetching ruby2_keywords 0.0.2 Installing ruby2_keywords 0.0.2 Fetching faraday 1.3.0 Installing faraday 1.3.0 Fetching gems 1.2.0 Installing gems 1.2.0 Fetching github-markup 1.7.0 Installing github-markup 1.7.0 Fetching jwt 2.2.2 Installing jwt 2.2.2 Fetching memoist 0.16.2 Installing memoist 0.16.2 Fetching multi_json 1.15.0 Installing multi_json 1.15.0 Fetching os 0.9.6 Installing os 0.9.6 Fetching signet 0.14.0 Installing signet 0.14.0 Fetching googleauth 0.14.0 Installing googleauth 0.14.0 Fetching httpclient 2.8.3 Installing httpclient 2.8.3 Fetching mini_mime 1.0.2 Installing mini_mime 1.0.2 Fetching uber 0.1.0 Installing uber 0.1.0 Fetching representable 3.0.4 Installing representable 3.0.4 Fetching retriable 3.1.2 Installing retriable 3.1.2 Fetching google-apis-core 0.2.0 Installing google-apis-core 0.2.0 Fetching google-apis-discovery_v1 0.1.0 Installing google-apis-discovery_v1 0.1.0 Using google-apis-generator 0.1.1 from source at `.` Fetching google-id-token 1.4.2 Installing google-id-token 1.4.2 Fetching hashdiff 1.0.1 Installing hashdiff 1.0.1 Fetching mime-types-data 3.2020.1104 Installing mime-types-data 3.2020.1104 Fetching mime-types 3.3.1 Installing mime-types 3.3.1 Fetching multi_xml 0.6.0 Installing multi_xml 0.6.0 Fetching httparty 0.18.1 Installing httparty 0.18.1 Fetching rspec-support 3.10.1 Installing rspec-support 3.10.1 Fetching rspec-core 3.10.1 Installing rspec-core 3.10.1 Fetching rspec-expectations 3.10.1 Installing rspec-expectations 3.10.1 Fetching rspec-mocks 3.10.1 Installing rspec-mocks 3.10.1 Fetching rspec 3.10.0 Installing rspec 3.10.0 Fetching json_spec 1.1.5 Installing json_spec 1.1.5 Fetching launchy 2.5.0 Installing launchy 2.5.0 Fetching little-plugger 1.1.4 Installing little-plugger 1.1.4 Fetching logging 2.3.0 Installing logging 2.3.0 Fetching method_source 1.0.0 Installing method_source 1.0.0 Fetching opencensus 0.5.0 Installing opencensus 0.5.0 Fetching parallel 1.20.1 Installing parallel 1.20.1 Fetching parser 2.7.2.0 Installing parser 2.7.2.0 Fetching powerpack 0.1.3 Installing powerpack 0.1.3 Fetching pry 0.13.1 Installing pry 0.13.1 Fetching pry-byebug 3.9.0 Installing pry-byebug 3.9.0 Fetching yard 0.9.26 Installing yard 0.9.26 Fetching pry-doc 0.13.5 Installing pry-doc 0.13.5 Fetching rainbow 2.2.2 Installing rainbow 2.2.2 with native extensions Fetching redcarpet 3.5.1 Installing redcarpet 3.5.1 with native extensions Fetching redis 3.3.5 Installing redis 3.3.5 Fetching rmail 1.1.4 Installing rmail 1.1.4 Fetching ruby-progressbar 1.11.0 Installing ruby-progressbar 1.11.0 Fetching unicode-display_width 1.7.0 Installing unicode-display_width 1.7.0 Fetching rubocop 0.49.1 Installing rubocop 0.49.1 Fetching webmock 2.3.2 Installing webmock 2.3.2 Bundle complete! 25 Gemfile dependencies, 81 gems now installed. Use `bundle info [gemname]` to see where a bundled gem is installed. Post-install message from i18n: HEADS UP! i18n 1.1 changed fallbacks to exclude default locale. But that may break your application. If you are upgrading your Rails application from an older version of Rails: Please check your Rails app for 'config.i18n.fallbacks = true'. If you're using I18n (>= 1.1.0) and Rails (< 5.2.2), this should be 'config.i18n.fallbacks = [I18n.default_locale]'. If not, fallbacks will be broken in your app by I18n 1.1.x. If you are starting a NEW Rails application, you can ignore this notice. For more info see: https://github.com/svenfuchs/i18n/releases/tag/v1.1.0 Post-install message from httparty: When you HTTParty, you must party hard! echo a | bundle exec bin/generate-api gen /workspace/generated --api=ml.v1 --names=/workspace/api_names.yaml --names-out=/workspace/api_names_out.yaml --spot-check Loading ml, version v1 from https://raw.githubusercontent.com/googleapis/discovery-artifact-manager/master/discoveries/ml.v1.json conflict google-apis-ml_v1/lib/google/apis/ml_v1/classes.rb <s/ml_v1/classes.rb? (enter "h" for help) [Ynaqdhm] a force google-apis-ml_v1/lib/google/apis/ml_v1/classes.rb conflict google-apis-ml_v1/lib/google/apis/ml_v1/gem_version.rb force google-apis-ml_v1/lib/google/apis/ml_v1/gem_version.rb conflict google-apis-ml_v1/CHANGELOG.md force google-apis-ml_v1/CHANGELOG.md Don't run Bundler as root. Bundler can ask for sudo if it is needed, and installing your bundle as root will break this application for all non-root users on this machine. The dependency jruby-openssl (>= 0) will be unused by any of the platforms Bundler is installing for. Bundler is installing for ruby but the dependency is only for java. To add those platforms to the bundle, run `bundle lock --add-platform java`. Fetching gem metadata from https://rubygems.org/......... Fetching gem metadata from https://rubygems.org/. Resolving dependencies... Fetching rake 13.0.3 Installing rake 13.0.3 Using public_suffix 4.0.6 Using addressable 2.7.0 Using bundler 2.1.4 Using declarative 0.0.20 Using declarative-option 0.1.0 Using diff-lcs 1.4.4 Using faraday-net_http 1.0.1 Using multipart-post 2.1.1 Using ruby2_keywords 0.0.2 Using faraday 1.3.0 Using jwt 2.2.2 Using memoist 0.16.2 Using multi_json 1.15.0 Fetching os 1.1.1 Installing os 1.1.1 Using signet 0.14.0 Using googleauth 0.14.0 Using httpclient 2.8.3 Using mini_mime 1.0.2 Using uber 0.1.0 Using representable 3.0.4 Using retriable 3.1.2 Using rexml 3.2.4 Using google-apis-core 0.2.0 Using google-apis-ml_v1 0.2.0 from source at `.` Using opencensus 0.5.0 Using redcarpet 3.5.1 Using rspec-support 3.10.1 Using rspec-core 3.10.1 Using rspec-expectations 3.10.1 Using rspec-mocks 3.10.1 Using rspec 3.10.0 Using yard 0.9.26 Bundle complete! 8 Gemfile dependencies, 33 gems now installed. Use `bundle info [gemname]` to see where a bundled gem is installed. /root/.rbenv/versions/2.6.6/bin/ruby -I/root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-core-3.10.1/lib:/root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-support-3.10.1/lib /root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-core-3.10.1/exe/rspec --pattern spec/\*\*\{,/\*/\*\*\}/\*_spec.rb Google::Apis::MlV1 should load Finished in 0.32051 seconds (files took 0.10628 seconds to load) 1 example, 0 failures Files: 4 Modules: 3 ( 1 undocumented) Classes: 87 ( 11 undocumented) Constants: 6 ( 0 undocumented) Attributes: 209 ( 0 undocumented) Methods: 219 ( 0 undocumented) 97.71% documented google-apis-ml_v1 0.2.0 built to pkg/google-apis-ml_v1-0.2.0.gem. identical /workspace/api_names_out.yaml 2021-01-13 03:02:44,210 synthtool [DEBUG] > Wrote metadata to generated/google-apis-ml_v1/synth.metadata. DEBUG:synthtool:Wrote metadata to generated/google-apis-ml_v1/synth.metadata. ``` </details> Full log will be available here: https://source.cloud.google.com/results/invocations/2c9a7f94-8490-460d-bb8a-c9c25cb6fec9/targets - [ ] To automatically regenerate this PR, check this box.
2021-01-13 11:20:01 +00:00
# Output only. The last time this version was successfully [migrated to AI
# Platform (Unified)](https://cloud.google.com/ai-platform-unified/docs/start/
# migrating-to-ai-platform-unified).
feat: Automated regeneration of ml v1 client (#2255)
2021-01-08 16:44:10 +00:00
# Corresponds to the JSON property `lastMigrationTime`
# @return [String]
attr_accessor :last_migration_time
chore: Initial generation of separate libraries (#2139)
2021-01-01 03:01:13 +00:00
# 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
feat: Automated regeneration of ml v1 client (#2380) This PR was generated using Autosynth. :rainbow: <details><summary>Log from Synthtool</summary> ``` 2021-01-13 03:02:07,628 synthtool [DEBUG] > Executing /home/kbuilder/.cache/synthtool/google-api-ruby-client/synth.py. On branch autosynth-ml-v1 nothing to commit, working tree clean 2021-01-13 03:02:07,699 synthtool [DEBUG] > Running: docker run --rm -v/home/kbuilder/.cache/synthtool/google-api-ruby-client:/workspace -v/var/run/docker.sock:/var/run/docker.sock -w /workspace --entrypoint script/synth.rb gcr.io/cloud-devrel-kokoro-resources/yoshi-ruby/autosynth ml v1 DEBUG:synthtool:Running: docker run --rm -v/home/kbuilder/.cache/synthtool/google-api-ruby-client:/workspace -v/var/run/docker.sock:/var/run/docker.sock -w /workspace --entrypoint script/synth.rb gcr.io/cloud-devrel-kokoro-resources/yoshi-ruby/autosynth ml v1 git clean -df bundle install Don't run Bundler as root. Bundler can ask for sudo if it is needed, and installing your bundle as root will break this application for all non-root users on this machine. The dependency jruby-openssl (>= 0) will be unused by any of the platforms Bundler is installing for. Bundler is installing for ruby but the dependency is only for java. To add those platforms to the bundle, run `bundle lock --add-platform java`. Fetching gem metadata from https://rubygems.org/......... Fetching gem metadata from https://rubygems.org/. Resolving dependencies... Fetching rake 11.3.0 Installing rake 11.3.0 Fetching concurrent-ruby 1.1.7 Installing concurrent-ruby 1.1.7 Fetching i18n 1.8.7 Installing i18n 1.8.7 Fetching minitest 5.14.3 Installing minitest 5.14.3 Fetching tzinfo 2.0.4 Installing tzinfo 2.0.4 Fetching zeitwerk 2.4.2 Installing zeitwerk 2.4.2 Fetching activesupport 6.1.1 Installing activesupport 6.1.1 Fetching public_suffix 4.0.6 Installing public_suffix 4.0.6 Fetching addressable 2.7.0 Installing addressable 2.7.0 Fetching ast 2.4.1 Installing ast 2.4.1 Using bundler 2.1.4 Fetching byebug 11.1.3 Installing byebug 11.1.3 with native extensions Fetching coderay 1.1.3 Installing coderay 1.1.3 Fetching json 2.5.1 Installing json 2.5.1 with native extensions Fetching docile 1.3.4 Installing docile 1.3.4 Fetching simplecov-html 0.10.2 Installing simplecov-html 0.10.2 Fetching simplecov 0.16.1 Installing simplecov 0.16.1 Using sync 0.5.0 Fetching tins 1.28.0 Installing tins 1.28.0 Fetching term-ansicolor 1.7.1 Installing term-ansicolor 1.7.1 Fetching thor 0.20.3 Installing thor 0.20.3 Fetching coveralls 0.8.23 Installing coveralls 0.8.23 Fetching rexml 3.2.4 Installing rexml 3.2.4 Fetching crack 0.4.5 Installing crack 0.4.5 Fetching declarative 0.0.20 Installing declarative 0.0.20 Fetching declarative-option 0.1.0 Installing declarative-option 0.1.0 Fetching diff-lcs 1.4.4 Installing diff-lcs 1.4.4 Fetching dotenv 2.7.6 Installing dotenv 2.7.6 Fetching fakefs 0.20.1 Installing fakefs 0.20.1 Fetching faraday-net_http 1.0.1 Installing faraday-net_http 1.0.1 Fetching multipart-post 2.1.1 Installing multipart-post 2.1.1 Fetching ruby2_keywords 0.0.2 Installing ruby2_keywords 0.0.2 Fetching faraday 1.3.0 Installing faraday 1.3.0 Fetching gems 1.2.0 Installing gems 1.2.0 Fetching github-markup 1.7.0 Installing github-markup 1.7.0 Fetching jwt 2.2.2 Installing jwt 2.2.2 Fetching memoist 0.16.2 Installing memoist 0.16.2 Fetching multi_json 1.15.0 Installing multi_json 1.15.0 Fetching os 0.9.6 Installing os 0.9.6 Fetching signet 0.14.0 Installing signet 0.14.0 Fetching googleauth 0.14.0 Installing googleauth 0.14.0 Fetching httpclient 2.8.3 Installing httpclient 2.8.3 Fetching mini_mime 1.0.2 Installing mini_mime 1.0.2 Fetching uber 0.1.0 Installing uber 0.1.0 Fetching representable 3.0.4 Installing representable 3.0.4 Fetching retriable 3.1.2 Installing retriable 3.1.2 Fetching google-apis-core 0.2.0 Installing google-apis-core 0.2.0 Fetching google-apis-discovery_v1 0.1.0 Installing google-apis-discovery_v1 0.1.0 Using google-apis-generator 0.1.1 from source at `.` Fetching google-id-token 1.4.2 Installing google-id-token 1.4.2 Fetching hashdiff 1.0.1 Installing hashdiff 1.0.1 Fetching mime-types-data 3.2020.1104 Installing mime-types-data 3.2020.1104 Fetching mime-types 3.3.1 Installing mime-types 3.3.1 Fetching multi_xml 0.6.0 Installing multi_xml 0.6.0 Fetching httparty 0.18.1 Installing httparty 0.18.1 Fetching rspec-support 3.10.1 Installing rspec-support 3.10.1 Fetching rspec-core 3.10.1 Installing rspec-core 3.10.1 Fetching rspec-expectations 3.10.1 Installing rspec-expectations 3.10.1 Fetching rspec-mocks 3.10.1 Installing rspec-mocks 3.10.1 Fetching rspec 3.10.0 Installing rspec 3.10.0 Fetching json_spec 1.1.5 Installing json_spec 1.1.5 Fetching launchy 2.5.0 Installing launchy 2.5.0 Fetching little-plugger 1.1.4 Installing little-plugger 1.1.4 Fetching logging 2.3.0 Installing logging 2.3.0 Fetching method_source 1.0.0 Installing method_source 1.0.0 Fetching opencensus 0.5.0 Installing opencensus 0.5.0 Fetching parallel 1.20.1 Installing parallel 1.20.1 Fetching parser 2.7.2.0 Installing parser 2.7.2.0 Fetching powerpack 0.1.3 Installing powerpack 0.1.3 Fetching pry 0.13.1 Installing pry 0.13.1 Fetching pry-byebug 3.9.0 Installing pry-byebug 3.9.0 Fetching yard 0.9.26 Installing yard 0.9.26 Fetching pry-doc 0.13.5 Installing pry-doc 0.13.5 Fetching rainbow 2.2.2 Installing rainbow 2.2.2 with native extensions Fetching redcarpet 3.5.1 Installing redcarpet 3.5.1 with native extensions Fetching redis 3.3.5 Installing redis 3.3.5 Fetching rmail 1.1.4 Installing rmail 1.1.4 Fetching ruby-progressbar 1.11.0 Installing ruby-progressbar 1.11.0 Fetching unicode-display_width 1.7.0 Installing unicode-display_width 1.7.0 Fetching rubocop 0.49.1 Installing rubocop 0.49.1 Fetching webmock 2.3.2 Installing webmock 2.3.2 Bundle complete! 25 Gemfile dependencies, 81 gems now installed. Use `bundle info [gemname]` to see where a bundled gem is installed. Post-install message from i18n: HEADS UP! i18n 1.1 changed fallbacks to exclude default locale. But that may break your application. If you are upgrading your Rails application from an older version of Rails: Please check your Rails app for 'config.i18n.fallbacks = true'. If you're using I18n (>= 1.1.0) and Rails (< 5.2.2), this should be 'config.i18n.fallbacks = [I18n.default_locale]'. If not, fallbacks will be broken in your app by I18n 1.1.x. If you are starting a NEW Rails application, you can ignore this notice. For more info see: https://github.com/svenfuchs/i18n/releases/tag/v1.1.0 Post-install message from httparty: When you HTTParty, you must party hard! echo a | bundle exec bin/generate-api gen /workspace/generated --api=ml.v1 --names=/workspace/api_names.yaml --names-out=/workspace/api_names_out.yaml --spot-check Loading ml, version v1 from https://raw.githubusercontent.com/googleapis/discovery-artifact-manager/master/discoveries/ml.v1.json conflict google-apis-ml_v1/lib/google/apis/ml_v1/classes.rb <s/ml_v1/classes.rb? (enter "h" for help) [Ynaqdhm] a force google-apis-ml_v1/lib/google/apis/ml_v1/classes.rb conflict google-apis-ml_v1/lib/google/apis/ml_v1/gem_version.rb force google-apis-ml_v1/lib/google/apis/ml_v1/gem_version.rb conflict google-apis-ml_v1/CHANGELOG.md force google-apis-ml_v1/CHANGELOG.md Don't run Bundler as root. Bundler can ask for sudo if it is needed, and installing your bundle as root will break this application for all non-root users on this machine. The dependency jruby-openssl (>= 0) will be unused by any of the platforms Bundler is installing for. Bundler is installing for ruby but the dependency is only for java. To add those platforms to the bundle, run `bundle lock --add-platform java`. Fetching gem metadata from https://rubygems.org/......... Fetching gem metadata from https://rubygems.org/. Resolving dependencies... Fetching rake 13.0.3 Installing rake 13.0.3 Using public_suffix 4.0.6 Using addressable 2.7.0 Using bundler 2.1.4 Using declarative 0.0.20 Using declarative-option 0.1.0 Using diff-lcs 1.4.4 Using faraday-net_http 1.0.1 Using multipart-post 2.1.1 Using ruby2_keywords 0.0.2 Using faraday 1.3.0 Using jwt 2.2.2 Using memoist 0.16.2 Using multi_json 1.15.0 Fetching os 1.1.1 Installing os 1.1.1 Using signet 0.14.0 Using googleauth 0.14.0 Using httpclient 2.8.3 Using mini_mime 1.0.2 Using uber 0.1.0 Using representable 3.0.4 Using retriable 3.1.2 Using rexml 3.2.4 Using google-apis-core 0.2.0 Using google-apis-ml_v1 0.2.0 from source at `.` Using opencensus 0.5.0 Using redcarpet 3.5.1 Using rspec-support 3.10.1 Using rspec-core 3.10.1 Using rspec-expectations 3.10.1 Using rspec-mocks 3.10.1 Using rspec 3.10.0 Using yard 0.9.26 Bundle complete! 8 Gemfile dependencies, 33 gems now installed. Use `bundle info [gemname]` to see where a bundled gem is installed. /root/.rbenv/versions/2.6.6/bin/ruby -I/root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-core-3.10.1/lib:/root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-support-3.10.1/lib /root/.rbenv/versions/2.6.6/lib/ruby/gems/2.6.0/gems/rspec-core-3.10.1/exe/rspec --pattern spec/\*\*\{,/\*/\*\*\}/\*_spec.rb Google::Apis::MlV1 should load Finished in 0.32051 seconds (files took 0.10628 seconds to load) 1 example, 0 failures Files: 4 Modules: 3 ( 1 undocumented) Classes: 87 ( 11 undocumented) Constants: 6 ( 0 undocumented) Attributes: 209 ( 0 undocumented) Methods: 219 ( 0 undocumented) 97.71% documented google-apis-ml_v1 0.2.0 built to pkg/google-apis-ml_v1-0.2.0.gem. identical /workspace/api_names_out.yaml 2021-01-13 03:02:44,210 synthtool [DEBUG] > Wrote metadata to generated/google-apis-ml_v1/synth.metadata. DEBUG:synthtool:Wrote metadata to generated/google-apis-ml_v1/synth.metadata. ``` </details> Full log will be available here: https://source.cloud.google.com/results/invocations/2c9a7f94-8490-460d-bb8a-c9c25cb6fec9/targets - [ ] To automatically regenerate this PR, check this box.
2021-01-13 11:20:01 +00:00
# applies to online prediction service. To learn about valid values for this
# field, read [Choosing a machine type for online prediction](/ai-platform/
# prediction/docs/machine-types-online-prediction). If this field is not
# specified and you are using a [regional endpoint](/ai-platform/prediction/docs/
# regional-endpoints), then the machine type defaults to `n1-standard-2`. If
# this field is not specified and you are using the global endpoint (`ml.
# googleapis.com`), then the machine type defaults to `mls1-c1-m2`.
chore: Initial generation of separate libraries (#2139)
2021-01-01 03:01:13 +00:00
# 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<String>]
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
# Required. The version of Python used in prediction. The following Python
# versions are available: * Python '3.7' is available when `runtime_version` is
# set to '1.15' or later. * Python '3.5' is available when `runtime_version` is
# set to a version from '1.4' to '1.14'. * Python '2.7' is available when `
# runtime_version` is set to '1.15' or earlier. Read more about the Python
# versions available for [each runtime version](/ml-engine/docs/runtime-version-
# list).
# 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
# Specifies HTTP paths served by a custom container. AI Platform Prediction
# sends requests to these paths on the container; the custom container must run
# an HTTP server that responds to these requests with appropriate responses.
# Read [Custom container requirements](/ai-platform/prediction/docs/custom-
# container-requirements) for details on how to create your container image to
# meet these requirements.
# Corresponds to the JSON property `routes`
# @return [Google::Apis::MlV1::GoogleCloudMlV1RouteMap]
attr_accessor :routes
# Required. The AI Platform runtime version to use for this deployment. 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. If you
# specify this field, then you must also specify either the `containerSpec` or
# the `predictionClass` field. Learn more about [using a custom service account](
# /ai-platform/prediction/docs/custom-service-account).
# 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)
@container = args[:container] if args.key?(:container)
@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)
@explanation_config = args[:explanation_config] if args.key?(:explanation_config)
@framework = args[:framework] if args.key?(:framework)
@is_default = args[:is_default] if args.key?(:is_default)
@labels = args[:labels] if args.key?(:labels)
feat: Automated regeneration of ml v1 client (#2255)
2021-01-08 16:44:10 +00:00
@last_migration_model_id = args[:last_migration_model_id] if args.key?(:last_migration_model_id)
@last_migration_time = args[:last_migration_time] if args.key?(:last_migration_time)
chore: Initial generation of separate libraries (#2139)
2021-01-01 03:01:13 +00:00
@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)
@routes = args[:routes] if args.key?(:routes)
@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
# Attributes credit by computing the XRAI taking advantage of the model's fully
# differentiable structure. Refer to this paper for more details: https://arxiv.
# org/abs/1906.02825 Currently only implemented for models with natural image
# inputs.
class GoogleCloudMlV1XraiAttribution
include Google::Apis::Core::Hashable
# Number of steps for approximating the path integral. A good value to start is
# 50 and gradually increase until the sum to diff property is met within the
# desired error range.
# Corresponds to the JSON property `numIntegralSteps`
# @return [Fixnum]
attr_accessor :num_integral_steps
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@num_integral_steps = args[:num_integral_steps] if args.key?(:num_integral_steps)
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<Google::Apis::MlV1::GoogleIamV1AuditLogConfig>]
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<String>]
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 a textual expression in the Common Expression Language (CEL) syntax.
# CEL is a C-like expression language. The syntax and semantics of CEL are
# documented at https://github.com/google/cel-spec. Example (Comparison): title:
# "Summary size limit" description: "Determines if a summary is less than 100
# chars" expression: "document.summary.size() < 100" Example (Equality): title: "
# Requestor is owner" description: "Determines if requestor is the document
# owner" expression: "document.owner == request.auth.claims.email" Example (
# Logic): title: "Public documents" description: "Determine whether the document
# should be publicly visible" expression: "document.type != 'private' &&
# document.type != 'internal'" Example (Data Manipulation): title: "Notification
# string" description: "Create a notification string with a timestamp."
# expression: "'New message received at ' + string(document.create_time)" The
# exact variables and functions that may be referenced within an expression are
# determined by the service that evaluates it. See the service documentation for
# additional information.
# 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`. * `deleted:user:`emailid`?uid=
# `uniqueid``: An email address (plus unique identifier) representing a user
# that has been recently deleted. For example, `alice@example.com?uid=
# 123456789012345678901`. If the user is recovered, this value reverts to `user:`
# emailid`` and the recovered user retains the role in the binding. * `deleted:
# serviceAccount:`emailid`?uid=`uniqueid``: An email address (plus unique
# identifier) representing a service account that has been recently deleted. For
# example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`.
# If the service account is undeleted, this value reverts to `serviceAccount:`
# emailid`` and the undeleted service account retains the role in the binding. *
# `deleted:group:`emailid`?uid=`uniqueid``: An email address (plus unique
# identifier) representing a Google group that has been recently deleted. For
# example, `admins@example.com?uid=123456789012345678901`. If the group is
# recovered, this value reverts to `group:`emailid`` and the recovered group
# retains the role in the binding. * `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<String>]
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
# An Identity and Access Management (IAM) policy, which specifies access
# controls for Google Cloud 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; each `role` can be an IAM predefined
# role or a user-created custom role. For some types of Google Cloud resources,
# a `binding` can also specify a `condition`, which is a logical expression that
# allows access to a resource only if the expression evaluates to `true`. A
# condition can add constraints based on attributes of the request, the resource,
# or both. To learn which resources support conditions in their IAM policies,
# see the [IAM documentation](https://cloud.google.com/iam/help/conditions/
# resource-policies). **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')", `
# ` ], "etag": "BwWWja0YfJA=", "version": 3 ` **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') - etag: BwWWja0YfJA= - version: 3 For a
# description of IAM and its features, see the [IAM documentation](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<Google::Apis::MlV1::GoogleIamV1AuditConfig>]
attr_accessor :audit_configs
# Associates a list of `members` to a `role`. Optionally, may specify a `
# condition` that determines how and when the `bindings` are applied. Each of
# the `bindings` must contain at least one member.
# Corresponds to the JSON property `bindings`
# @return [Array<Google::Apis::MlV1::GoogleIamV1Binding>]
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. **Important:** If you use IAM
# Conditions, you must include the `etag` field whenever you call `setIamPolicy`.
# If you omit this field, then IAM allows you to overwrite a version `3` policy
# with a version `1` policy, and all of the conditions in the version `3` policy
# are lost.
# 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 that specify an invalid value are rejected. Any operation that
# affects conditional role bindings must specify version `3`. This requirement
# applies to the following operations: * Getting a policy that includes a
# conditional role binding * Adding a conditional role binding to a policy *
# Changing a conditional role binding in a policy * Removing any role binding,
# with or without a condition, from a policy that includes conditions **
# Important:** If you use IAM Conditions, you must include the `etag` field
# whenever you call `setIamPolicy`. If you omit this field, then IAM allows you
# to overwrite a version `3` policy with a version `1` policy, and all of the
# conditions in the version `3` policy are lost. If a policy does not include
# any conditions, operations on that policy may specify any valid version or
# leave the field unset. To learn which resources support conditions in their
# IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/
# conditions/resource-policies).
# 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
# An Identity and Access Management (IAM) policy, which specifies access
# controls for Google Cloud 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; each `role` can be an IAM predefined
# role or a user-created custom role. For some types of Google Cloud resources,
# a `binding` can also specify a `condition`, which is a logical expression that
# allows access to a resource only if the expression evaluates to `true`. A
# condition can add constraints based on attributes of the request, the resource,
# or both. To learn which resources support conditions in their IAM policies,
# see the [IAM documentation](https://cloud.google.com/iam/help/conditions/
# resource-policies). **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')", `
# ` ], "etag": "BwWWja0YfJA=", "version": 3 ` **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') - etag: BwWWja0YfJA= - version: 3 For a
# description of IAM and its features, see the [IAM documentation](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"`
# 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<String>]
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<String>]
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<Google::Apis::MlV1::GoogleLongrunningOperation>]
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<String,Object>]
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<String,Object>]
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<Hash<String,Object>>]
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 a textual expression in the Common Expression Language (CEL) syntax.
# CEL is a C-like expression language. The syntax and semantics of CEL are
# documented at https://github.com/google/cel-spec. Example (Comparison): title:
# "Summary size limit" description: "Determines if a summary is less than 100
# chars" expression: "document.summary.size() < 100" Example (Equality): title: "
# Requestor is owner" description: "Determines if requestor is the document
# owner" expression: "document.owner == request.auth.claims.email" Example (
# Logic): title: "Public documents" description: "Determine whether the document
# should be publicly visible" expression: "document.type != 'private' &&
# document.type != 'internal'" Example (Data Manipulation): title: "Notification
# string" description: "Create a notification string with a timestamp."
# expression: "'New message received at ' + string(document.create_time)" The
# exact variables and functions that may be referenced within an expression are
# determined by the service that evaluates it. See the service documentation for
# additional information.
class GoogleTypeExpr
include Google::Apis::Core::Hashable
# 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.
# Corresponds to the JSON property `expression`
# @return [String]
attr_accessor :expression
# 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
# 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