2614 lines
113 KiB
Ruby
2614 lines
113 KiB
Ruby
# Copyright 2015 Google Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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require 'date'
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require 'google/apis/core/base_service'
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require 'google/apis/core/json_representation'
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require 'google/apis/core/hashable'
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require 'google/apis/errors'
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module Google
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module Apis
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module MlV1
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# Message that represents an arbitrary HTTP body. It should only be used for
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# payload formats that can't be represented as JSON, such as raw binary or
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# an HTML page.
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# This message can be used both in streaming and non-streaming API methods in
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# the request as well as the response.
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# It can be used as a top-level request field, which is convenient if one
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# wants to extract parameters from either the URL or HTTP template into the
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# request fields and also want access to the raw HTTP body.
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# Example:
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# message GetResourceRequest `
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# // A unique request id.
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# string request_id = 1;
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# // The raw HTTP body is bound to this field.
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# google.api.HttpBody http_body = 2;
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# `
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# service ResourceService `
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# rpc GetResource(GetResourceRequest) returns (google.api.HttpBody);
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# rpc UpdateResource(google.api.HttpBody) returns
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# (google.protobuf.Empty);
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# `
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# Example with streaming methods:
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# service CaldavService `
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# rpc GetCalendar(stream google.api.HttpBody)
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# returns (stream google.api.HttpBody);
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# rpc UpdateCalendar(stream google.api.HttpBody)
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# returns (stream google.api.HttpBody);
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# `
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# Use of this type only changes how the request and response bodies are
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# handled, all other features will continue to work unchanged.
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class GoogleApiHttpBody
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include Google::Apis::Core::Hashable
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# The HTTP Content-Type header value specifying the content type of the body.
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# Corresponds to the JSON property `contentType`
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# @return [String]
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attr_accessor :content_type
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# The HTTP request/response body as raw binary.
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# Corresponds to the JSON property `data`
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# NOTE: Values are automatically base64 encoded/decoded in the client library.
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# @return [String]
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attr_accessor :data
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# Application specific response metadata. Must be set in the first response
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# for streaming APIs.
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# Corresponds to the JSON property `extensions`
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# @return [Array<Hash<String,Object>>]
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attr_accessor :extensions
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@content_type = args[:content_type] if args.key?(:content_type)
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@data = args[:data] if args.key?(:data)
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@extensions = args[:extensions] if args.key?(:extensions)
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end
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end
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# An observed value of a metric.
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class GoogleCloudMlV1HyperparameterOutputHyperparameterMetric
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include Google::Apis::Core::Hashable
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# The objective value at this training step.
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# Corresponds to the JSON property `objectiveValue`
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# @return [Float]
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attr_accessor :objective_value
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# The global training step for this metric.
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# Corresponds to the JSON property `trainingStep`
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# @return [Fixnum]
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attr_accessor :training_step
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@objective_value = args[:objective_value] if args.key?(:objective_value)
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@training_step = args[:training_step] if args.key?(:training_step)
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end
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end
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# Represents a hardware accelerator request config.
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# Note that the AcceleratorConfig can be used in both Jobs and Versions.
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# Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and
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# [accelerators for online
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# prediction](/ml-engine/docs/machine-types-online-prediction#gpus).
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class GoogleCloudMlV1AcceleratorConfig
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include Google::Apis::Core::Hashable
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# The number of accelerators to attach to each machine running the job.
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# Corresponds to the JSON property `count`
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# @return [Fixnum]
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attr_accessor :count
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# The type of accelerator to use.
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# Corresponds to the JSON property `type`
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# @return [String]
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attr_accessor :type
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@count = args[:count] if args.key?(:count)
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@type = args[:type] if args.key?(:type)
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end
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end
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# Options for automatically scaling a model.
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class GoogleCloudMlV1AutoScaling
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include Google::Apis::Core::Hashable
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# Optional. The minimum number of nodes to allocate for this model. These
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# nodes are always up, starting from the time the model is deployed.
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# Therefore, the cost of operating this model will be at least
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# `rate` * `min_nodes` * number of hours since last billing cycle,
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# where `rate` is the cost per node-hour as documented in the
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# [pricing guide](/ml-engine/docs/pricing),
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# even if no predictions are performed. There is additional cost for each
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# prediction performed.
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# Unlike manual scaling, if the load gets too heavy for the nodes
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# that are up, the service will automatically add nodes to handle the
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# increased load as well as scale back as traffic drops, always maintaining
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# at least `min_nodes`. You will be charged for the time in which additional
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# nodes are used.
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# If `min_nodes` is not specified and AutoScaling is used with a [legacy
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# (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction),
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# `min_nodes` defaults to 0, in which case, when traffic to a model stops
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# (and after a cool-down period), nodes will be shut down and no charges will
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# be incurred until traffic to the model resumes.
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# If `min_nodes` is not specified and AutoScaling is used with a [Compute
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# Engine (N1) machine type](/ml-engine/docs/machine-types-online-prediction),
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# `min_nodes` defaults to 1. `min_nodes` must be at least 1 for use with a
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# Compute Engine machine type.
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# Note that you cannot use AutoScaling if your version uses
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# [GPUs](#Version.FIELDS.accelerator_config). Instead, you must use
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# ManualScaling.
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# You can set `min_nodes` when creating the model version, and you can also
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# update `min_nodes` for an existing version:
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# <pre>
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# update_body.json:
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# `
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# 'autoScaling': `
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# 'minNodes': 5
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# `
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# `
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# </pre>
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# HTTP request:
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# <pre style="max-width: 626px;">
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# PATCH
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# https://ml.googleapis.com/v1/`name=projects/*/models/*/versions/*`?update_mask=
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# autoScaling.minNodes
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# -d @./update_body.json
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# </pre>
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# Corresponds to the JSON property `minNodes`
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# @return [Fixnum]
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attr_accessor :min_nodes
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@min_nodes = args[:min_nodes] if args.key?(:min_nodes)
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end
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end
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# Represents output related to a built-in algorithm Job.
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class GoogleCloudMlV1BuiltInAlgorithmOutput
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include Google::Apis::Core::Hashable
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# Framework on which the built-in algorithm was trained.
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# Corresponds to the JSON property `framework`
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# @return [String]
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attr_accessor :framework
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# The Cloud Storage path to the `model/` directory where the training job
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# saves the trained model. Only set for successful jobs that don't use
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# hyperparameter tuning.
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# Corresponds to the JSON property `modelPath`
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# @return [String]
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attr_accessor :model_path
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# Python version on which the built-in algorithm was trained.
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# Corresponds to the JSON property `pythonVersion`
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# @return [String]
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attr_accessor :python_version
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# AI Platform runtime version on which the built-in algorithm was
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# trained.
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# Corresponds to the JSON property `runtimeVersion`
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# @return [String]
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attr_accessor :runtime_version
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@framework = args[:framework] if args.key?(:framework)
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@model_path = args[:model_path] if args.key?(:model_path)
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@python_version = args[:python_version] if args.key?(:python_version)
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@runtime_version = args[:runtime_version] if args.key?(:runtime_version)
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end
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end
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# Request message for the CancelJob method.
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class GoogleCloudMlV1CancelJobRequest
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include Google::Apis::Core::Hashable
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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end
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end
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#
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class GoogleCloudMlV1Capability
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include Google::Apis::Core::Hashable
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# Available accelerators for the capability.
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# Corresponds to the JSON property `availableAccelerators`
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# @return [Array<String>]
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attr_accessor :available_accelerators
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#
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# Corresponds to the JSON property `type`
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# @return [String]
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attr_accessor :type
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@available_accelerators = args[:available_accelerators] if args.key?(:available_accelerators)
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@type = args[:type] if args.key?(:type)
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end
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end
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#
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class GoogleCloudMlV1Config
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include Google::Apis::Core::Hashable
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# The service account Cloud ML uses to run on TPU node.
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# Corresponds to the JSON property `tpuServiceAccount`
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# @return [String]
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attr_accessor :tpu_service_account
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@tpu_service_account = args[:tpu_service_account] if args.key?(:tpu_service_account)
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end
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end
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# Request for explanations to be issued against a trained model.
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class GoogleCloudMlV1ExplainRequest
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include Google::Apis::Core::Hashable
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# Message that represents an arbitrary HTTP body. It should only be used for
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# payload formats that can't be represented as JSON, such as raw binary or
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# an HTML page.
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# This message can be used both in streaming and non-streaming API methods in
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# the request as well as the response.
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# It can be used as a top-level request field, which is convenient if one
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# wants to extract parameters from either the URL or HTTP template into the
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# request fields and also want access to the raw HTTP body.
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# Example:
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# message GetResourceRequest `
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# // A unique request id.
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# string request_id = 1;
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# // The raw HTTP body is bound to this field.
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# google.api.HttpBody http_body = 2;
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# `
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# service ResourceService `
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# rpc GetResource(GetResourceRequest) returns (google.api.HttpBody);
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# rpc UpdateResource(google.api.HttpBody) returns
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# (google.protobuf.Empty);
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# `
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# Example with streaming methods:
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# service CaldavService `
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# rpc GetCalendar(stream google.api.HttpBody)
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# returns (stream google.api.HttpBody);
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# rpc UpdateCalendar(stream google.api.HttpBody)
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# returns (stream google.api.HttpBody);
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# `
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# Use of this type only changes how the request and response bodies are
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# handled, all other features will continue to work unchanged.
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# Corresponds to the JSON property `httpBody`
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# @return [Google::Apis::MlV1::GoogleApiHttpBody]
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attr_accessor :http_body
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@http_body = args[:http_body] if args.key?(:http_body)
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end
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end
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# Message holding configuration options for explaining model predictions.
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# There are two feature attribution methods supported for TensorFlow models:
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# integrated gradients and sampled Shapley.
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# <a href="/ml-engine/docs/ai-explanations/overview">Learn more about feature
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# attributions</a>.
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class GoogleCloudMlV1ExplanationConfig
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include Google::Apis::Core::Hashable
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# Attributes credit by computing the Aumann-Shapley value taking advantage
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# of the model's fully differentiable structure. Refer to this paper for
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# more details: http://proceedings.mlr.press/v70/sundararajan17a.html
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# Corresponds to the JSON property `integratedGradientsAttribution`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1IntegratedGradientsAttribution]
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attr_accessor :integrated_gradients_attribution
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# An attribution method that approximates Shapley values for features that
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# contribute to the label being predicted. A sampling strategy is used to
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# approximate the value rather than considering all subsets of features.
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# Corresponds to the JSON property `sampledShapleyAttribution`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1SampledShapleyAttribution]
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attr_accessor :sampled_shapley_attribution
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@integrated_gradients_attribution = args[:integrated_gradients_attribution] if args.key?(:integrated_gradients_attribution)
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@sampled_shapley_attribution = args[:sampled_shapley_attribution] if args.key?(:sampled_shapley_attribution)
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end
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end
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# Returns service account information associated with a project.
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class GoogleCloudMlV1GetConfigResponse
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include Google::Apis::Core::Hashable
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#
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# Corresponds to the JSON property `config`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1Config]
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attr_accessor :config
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# The service account Cloud ML uses to access resources in the project.
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# Corresponds to the JSON property `serviceAccount`
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# @return [String]
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attr_accessor :service_account
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# The project number for `service_account`.
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# Corresponds to the JSON property `serviceAccountProject`
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# @return [Fixnum]
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attr_accessor :service_account_project
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@config = args[:config] if args.key?(:config)
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@service_account = args[:service_account] if args.key?(:service_account)
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@service_account_project = args[:service_account_project] if args.key?(:service_account_project)
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end
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end
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# Represents the result of a single hyperparameter tuning trial from a
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# training job. The TrainingOutput object that is returned on successful
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# completion of a training job with hyperparameter tuning includes a list
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# of HyperparameterOutput objects, one for each successful trial.
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class GoogleCloudMlV1HyperparameterOutput
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include Google::Apis::Core::Hashable
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# All recorded object metrics for this trial. This field is not currently
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# populated.
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# Corresponds to the JSON property `allMetrics`
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# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1HyperparameterOutputHyperparameterMetric>]
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attr_accessor :all_metrics
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# Represents output related to a built-in algorithm Job.
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# Corresponds to the JSON property `builtInAlgorithmOutput`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1BuiltInAlgorithmOutput]
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attr_accessor :built_in_algorithm_output
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# Output only. End time for the trial.
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# Corresponds to the JSON property `endTime`
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# @return [String]
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attr_accessor :end_time
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# An observed value of a metric.
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# Corresponds to the JSON property `finalMetric`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1HyperparameterOutputHyperparameterMetric]
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attr_accessor :final_metric
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# The hyperparameters given to this trial.
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# Corresponds to the JSON property `hyperparameters`
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# @return [Hash<String,String>]
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attr_accessor :hyperparameters
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# True if the trial is stopped early.
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# Corresponds to the JSON property `isTrialStoppedEarly`
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# @return [Boolean]
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attr_accessor :is_trial_stopped_early
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alias_method :is_trial_stopped_early?, :is_trial_stopped_early
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# Output only. Start time for the trial.
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# Corresponds to the JSON property `startTime`
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# @return [String]
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attr_accessor :start_time
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# Output only. The detailed state of the trial.
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# Corresponds to the JSON property `state`
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# @return [String]
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attr_accessor :state
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# The trial id for these results.
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# Corresponds to the JSON property `trialId`
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# @return [String]
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attr_accessor :trial_id
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@all_metrics = args[:all_metrics] if args.key?(:all_metrics)
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@built_in_algorithm_output = args[:built_in_algorithm_output] if args.key?(:built_in_algorithm_output)
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@end_time = args[:end_time] if args.key?(:end_time)
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@final_metric = args[:final_metric] if args.key?(:final_metric)
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@hyperparameters = args[:hyperparameters] if args.key?(:hyperparameters)
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@is_trial_stopped_early = args[:is_trial_stopped_early] if args.key?(:is_trial_stopped_early)
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@start_time = args[:start_time] if args.key?(:start_time)
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@state = args[:state] if args.key?(:state)
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@trial_id = args[:trial_id] if args.key?(:trial_id)
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end
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end
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# Represents a set of hyperparameters to optimize.
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class GoogleCloudMlV1HyperparameterSpec
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include Google::Apis::Core::Hashable
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# Optional. The search algorithm specified for the hyperparameter
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# tuning job.
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# Uses the default AI Platform hyperparameter tuning
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# algorithm if unspecified.
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# Corresponds to the JSON property `algorithm`
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# @return [String]
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attr_accessor :algorithm
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# Optional. Indicates if the hyperparameter tuning job enables auto trial
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# early stopping.
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# Corresponds to the JSON property `enableTrialEarlyStopping`
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# @return [Boolean]
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attr_accessor :enable_trial_early_stopping
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alias_method :enable_trial_early_stopping?, :enable_trial_early_stopping
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# Required. The type of goal to use for tuning. Available types are
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# `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: http://proceedings.mlr.press/v70/sundararajan17a.html
|
|
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
|
|
# <a href="/ml-engine/docs/tensorflow/resource-labels">using labels</a>.
|
|
# 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
|
|
# <a href="/ml-engine/docs/tensorflow/training-jobs">submitting a training
|
|
# job</a>.
|
|
# 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
|
|
|
|
# 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
|
|
|
|
# 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
|
|
# <a href="/ml-engine/docs/tensorflow/resource-labels">using labels</a>.
|
|
# 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 Stackdriver Logging. These can be more verbose than the standard
|
|
# access logs (see `onlinePredictionLogging`) and can incur higher cost.
|
|
# However, they are helpful for debugging. Note that
|
|
# [Stackdriver logs may incur a cost](/stackdriver/pricing), especially if
|
|
# your project receives prediction requests at a high QPS. Estimate your
|
|
# costs before enabling this option.
|
|
# Default is false.
|
|
# Corresponds to the JSON property `onlinePredictionConsoleLogging`
|
|
# @return [Boolean]
|
|
attr_accessor :online_prediction_console_logging
|
|
alias_method :online_prediction_console_logging?, :online_prediction_console_logging
|
|
|
|
# Optional. If true, online prediction access logs are sent to StackDriver
|
|
# Logging. These logs are like standard server access logs, containing
|
|
# information like timestamp and latency for each request. Note that
|
|
# [Stackdriver logs may incur a cost](/stackdriver/pricing), especially if
|
|
# your project receives prediction requests at a high queries per second rate
|
|
# (QPS). Estimate your costs before enabling this option.
|
|
# Default is false.
|
|
# Corresponds to the JSON property `onlinePredictionLogging`
|
|
# @return [Boolean]
|
|
attr_accessor :online_prediction_logging
|
|
alias_method :online_prediction_logging?, :online_prediction_logging
|
|
|
|
# Optional. The list of regions where the model is going to be deployed.
|
|
# Currently only one region per model is supported.
|
|
# Defaults to 'us-central1' if nothing is set.
|
|
# See the <a href="/ml-engine/docs/tensorflow/regions">available regions</a>
|
|
# 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
|
|
# <a href="/storage/docs/gsutil/addlhelp/WildcardNames">wildcards</a>.
|
|
# 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 <a href="/ml-engine/docs/tensorflow/regions">available regions</a>
|
|
# for AI Platform services.
|
|
# Corresponds to the JSON property `region`
|
|
# @return [String]
|
|
attr_accessor :region
|
|
|
|
# Optional. The AI Platform runtime version to use for this batch
|
|
# prediction. If not set, AI Platform will pick the runtime version used
|
|
# during the CreateVersion request for this model version, or choose the
|
|
# latest stable version when model version information is not available
|
|
# such as when the model is specified by uri.
|
|
# Corresponds to the JSON property `runtimeVersion`
|
|
# @return [String]
|
|
attr_accessor :runtime_version
|
|
|
|
# Optional. The name of the signature defined in the SavedModel to use for
|
|
# this job. Please refer to
|
|
# [SavedModel](https://tensorflow.github.io/serving/serving_basic.html)
|
|
# for information about how to use signatures.
|
|
# Defaults to
|
|
# [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/
|
|
# tf/saved_model/signature_constants)
|
|
# , which is "serving_default".
|
|
# Corresponds to the JSON property `signatureName`
|
|
# @return [String]
|
|
attr_accessor :signature_name
|
|
|
|
# Use this field if you want to specify a Google Cloud Storage path for
|
|
# the model to use.
|
|
# Corresponds to the JSON property `uri`
|
|
# @return [String]
|
|
attr_accessor :uri
|
|
|
|
# Use this field if you want to specify a version of the model to use. The
|
|
# string is formatted the same way as `model_version`, with the addition
|
|
# of the version information:
|
|
# `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"`
|
|
# Corresponds to the JSON property `versionName`
|
|
# @return [String]
|
|
attr_accessor :version_name
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@batch_size = args[:batch_size] if args.key?(:batch_size)
|
|
@data_format = args[:data_format] if args.key?(:data_format)
|
|
@input_paths = args[:input_paths] if args.key?(:input_paths)
|
|
@max_worker_count = args[:max_worker_count] if args.key?(:max_worker_count)
|
|
@model_name = args[:model_name] if args.key?(:model_name)
|
|
@output_data_format = args[:output_data_format] if args.key?(:output_data_format)
|
|
@output_path = args[:output_path] if args.key?(:output_path)
|
|
@region = args[:region] if args.key?(:region)
|
|
@runtime_version = args[:runtime_version] if args.key?(:runtime_version)
|
|
@signature_name = args[:signature_name] if args.key?(:signature_name)
|
|
@uri = args[:uri] if args.key?(:uri)
|
|
@version_name = args[:version_name] if args.key?(:version_name)
|
|
end
|
|
end
|
|
|
|
# Represents results of a prediction job.
|
|
class GoogleCloudMlV1PredictionOutput
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# The number of data instances which resulted in errors.
|
|
# Corresponds to the JSON property `errorCount`
|
|
# @return [Fixnum]
|
|
attr_accessor :error_count
|
|
|
|
# Node hours used by the batch prediction job.
|
|
# Corresponds to the JSON property `nodeHours`
|
|
# @return [Float]
|
|
attr_accessor :node_hours
|
|
|
|
# The output Google Cloud Storage location provided at the job creation time.
|
|
# Corresponds to the JSON property `outputPath`
|
|
# @return [String]
|
|
attr_accessor :output_path
|
|
|
|
# The number of generated predictions.
|
|
# Corresponds to the JSON property `predictionCount`
|
|
# @return [Fixnum]
|
|
attr_accessor :prediction_count
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@error_count = args[:error_count] if args.key?(:error_count)
|
|
@node_hours = args[:node_hours] if args.key?(:node_hours)
|
|
@output_path = args[:output_path] if args.key?(:output_path)
|
|
@prediction_count = args[:prediction_count] if args.key?(:prediction_count)
|
|
end
|
|
end
|
|
|
|
# Represents the configuration for a replica in a cluster.
|
|
class GoogleCloudMlV1ReplicaConfig
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# Represents a hardware accelerator request config.
|
|
# Note that the AcceleratorConfig can be used in both Jobs and Versions.
|
|
# Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and
|
|
# [accelerators for online
|
|
# prediction](/ml-engine/docs/machine-types-online-prediction#gpus).
|
|
# Corresponds to the JSON property `acceleratorConfig`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1AcceleratorConfig]
|
|
attr_accessor :accelerator_config
|
|
|
|
# The Docker image to run on the replica. This image must be in Container
|
|
# Registry. Learn more about [configuring custom
|
|
# containers](/ml-engine/docs/distributed-training-containers).
|
|
# Corresponds to the JSON property `imageUri`
|
|
# @return [String]
|
|
attr_accessor :image_uri
|
|
|
|
# The AI Platform runtime version that includes a TensorFlow version matching
|
|
# the one used in the custom container. This field is required if the replica
|
|
# is a TPU worker that uses a custom container. Otherwise, do not specify
|
|
# this field. This must be a [runtime version that currently supports
|
|
# training with
|
|
# TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support).
|
|
# Note that the version of TensorFlow included in a runtime version may
|
|
# differ from the numbering of the runtime version itself, because it may
|
|
# have a different [patch
|
|
# version](https://www.tensorflow.org/guide/version_compat#
|
|
# semantic_versioning_20).
|
|
# In this field, you must specify the runtime version (TensorFlow minor
|
|
# version). For example, if your custom container runs TensorFlow `1.x.y`,
|
|
# specify `1.x`.
|
|
# Corresponds to the JSON property `tpuTfVersion`
|
|
# @return [String]
|
|
attr_accessor :tpu_tf_version
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@accelerator_config = args[:accelerator_config] if args.key?(:accelerator_config)
|
|
@image_uri = args[:image_uri] if args.key?(:image_uri)
|
|
@tpu_tf_version = args[:tpu_tf_version] if args.key?(:tpu_tf_version)
|
|
end
|
|
end
|
|
|
|
# Configuration for logging request-response pairs to a BigQuery table.
|
|
# Online prediction requests to a model version and the responses to these
|
|
# requests are converted to raw strings and saved to the specified BigQuery
|
|
# table. Logging is constrained by [BigQuery quotas and
|
|
# limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits,
|
|
# AI Platform Prediction does not log request-response pairs, but it continues
|
|
# to serve predictions.
|
|
# If you are using [continuous
|
|
# evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to
|
|
# specify this configuration manually. Setting up continuous evaluation
|
|
# automatically enables logging of request-response pairs.
|
|
class GoogleCloudMlV1RequestLoggingConfig
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# Required. Fully qualified BigQuery table name in the following format:
|
|
# "<var>project_id</var>.<var>dataset_name</var>.<var>table_name</var>"
|
|
# The specifcied table must already exist, and the "Cloud ML Service Agent"
|
|
# for your project must have permission to write to it. The table must have
|
|
# the following [schema](/bigquery/docs/schemas):
|
|
# <table>
|
|
# <tr><th>Field name</th><th style="display: table-cell">Type</th>
|
|
# <th style="display: table-cell">Mode</th></tr>
|
|
# <tr><td>model</td><td>STRING</td><td>REQUIRED</td></tr>
|
|
# <tr><td>model_version</td><td>STRING</td><td>REQUIRED</td></tr>
|
|
# <tr><td>time</td><td>TIMESTAMP</td><td>REQUIRED</td></tr>
|
|
# <tr><td>raw_data</td><td>STRING</td><td>REQUIRED</td></tr>
|
|
# <tr><td>raw_prediction</td><td>STRING</td><td>NULLABLE</td></tr>
|
|
# <tr><td>groundtruth</td><td>STRING</td><td>NULLABLE</td></tr>
|
|
# </table>
|
|
# 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
|
|
|
|
# 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
|
|
|
|
# Request message for the SetDefaultVersion request.
|
|
class GoogleCloudMlV1SetDefaultVersionRequest
|
|
include Google::Apis::Core::Hashable
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
end
|
|
end
|
|
|
|
# Represents input parameters for a training job. When using the
|
|
# gcloud command to submit your training job, you can specify
|
|
# the input parameters as command-line arguments and/or in a YAML configuration
|
|
# file referenced from the --config command-line argument. For
|
|
# details, see the guide to
|
|
# <a href="/ml-engine/docs/tensorflow/training-jobs">submitting a training
|
|
# job</a>.
|
|
class GoogleCloudMlV1TrainingInput
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# Optional. Command line arguments to pass to the program.
|
|
# Corresponds to the JSON property `args`
|
|
# @return [Array<String>]
|
|
attr_accessor :args
|
|
|
|
# Represents a set of hyperparameters to optimize.
|
|
# Corresponds to the JSON property `hyperparameters`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1HyperparameterSpec]
|
|
attr_accessor :hyperparameters
|
|
|
|
# Optional. A Google Cloud Storage path in which to store training outputs
|
|
# and other data needed for training. This path is passed to your TensorFlow
|
|
# program as the '--job-dir' command-line argument. The benefit of specifying
|
|
# this field is that Cloud ML validates the path for use in training.
|
|
# Corresponds to the JSON property `jobDir`
|
|
# @return [String]
|
|
attr_accessor :job_dir
|
|
|
|
# Represents the configuration for a replica in a cluster.
|
|
# Corresponds to the JSON property `masterConfig`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig]
|
|
attr_accessor :master_config
|
|
|
|
# Optional. Specifies the type of virtual machine to use for your training
|
|
# job's master worker. You must specify this field when `scaleTier` is set to
|
|
# `CUSTOM`.
|
|
# You can use certain Compute Engine machine types directly in this field.
|
|
# The following types are supported:
|
|
# - `n1-standard-4`
|
|
# - `n1-standard-8`
|
|
# - `n1-standard-16`
|
|
# - `n1-standard-32`
|
|
# - `n1-standard-64`
|
|
# - `n1-standard-96`
|
|
# - `n1-highmem-2`
|
|
# - `n1-highmem-4`
|
|
# - `n1-highmem-8`
|
|
# - `n1-highmem-16`
|
|
# - `n1-highmem-32`
|
|
# - `n1-highmem-64`
|
|
# - `n1-highmem-96`
|
|
# - `n1-highcpu-16`
|
|
# - `n1-highcpu-32`
|
|
# - `n1-highcpu-64`
|
|
# - `n1-highcpu-96`
|
|
# Learn more about [using Compute Engine machine
|
|
# types](/ml-engine/docs/machine-types#compute-engine-machine-types).
|
|
# Alternatively, you can use the following legacy machine types:
|
|
# - `standard`
|
|
# - `large_model`
|
|
# - `complex_model_s`
|
|
# - `complex_model_m`
|
|
# - `complex_model_l`
|
|
# - `standard_gpu`
|
|
# - `complex_model_m_gpu`
|
|
# - `complex_model_l_gpu`
|
|
# - `standard_p100`
|
|
# - `complex_model_m_p100`
|
|
# - `standard_v100`
|
|
# - `large_model_v100`
|
|
# - `complex_model_m_v100`
|
|
# - `complex_model_l_v100`
|
|
# Learn more about [using legacy machine
|
|
# types](/ml-engine/docs/machine-types#legacy-machine-types).
|
|
# Finally, if you want to use a TPU for training, specify `cloud_tpu` in this
|
|
# field. Learn more about the [special configuration options for training
|
|
# with
|
|
# TPUs](/ml-engine/docs/tensorflow/using-tpus#configuring_a_custom_tpu_machine).
|
|
# Corresponds to the JSON property `masterType`
|
|
# @return [String]
|
|
attr_accessor :master_type
|
|
|
|
# Required. The Google Cloud Storage location of the packages with
|
|
# the training program and any additional dependencies.
|
|
# The maximum number of package URIs is 100.
|
|
# Corresponds to the JSON property `packageUris`
|
|
# @return [Array<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. If not set, the default
|
|
# version is '2.7'. Python '3.5' is available when `runtime_version` is set
|
|
# to '1.4' and above. Python '2.7' works with all supported
|
|
# <a href="/ml-engine/docs/runtime-version-list">runtime versions</a>.
|
|
# Corresponds to the JSON property `pythonVersion`
|
|
# @return [String]
|
|
attr_accessor :python_version
|
|
|
|
# Required. The Google Compute Engine region to run the training job in.
|
|
# See the <a href="/ml-engine/docs/tensorflow/regions">available regions</a>
|
|
# for AI Platform services.
|
|
# Corresponds to the JSON property `region`
|
|
# @return [String]
|
|
attr_accessor :region
|
|
|
|
# Optional. The AI Platform runtime version to use for training. If not
|
|
# set, AI Platform uses the default stable version, 1.0. For more
|
|
# information, see the
|
|
# <a href="/ml-engine/docs/runtime-version-list">runtime version list</a>
|
|
# and
|
|
# <a href="/ml-engine/docs/versioning">how to manage runtime versions</a>.
|
|
# Corresponds to the JSON property `runtimeVersion`
|
|
# @return [String]
|
|
attr_accessor :runtime_version
|
|
|
|
# Required. Specifies the machine types, the number of replicas for workers
|
|
# and parameter servers.
|
|
# Corresponds to the JSON property `scaleTier`
|
|
# @return [String]
|
|
attr_accessor :scale_tier
|
|
|
|
# Optional. Use 'chief' instead of 'master' in TF_CONFIG when Custom
|
|
# Container is used and evaluator is not specified.
|
|
# Defaults to false.
|
|
# Corresponds to the JSON property `useChiefInTfConfig`
|
|
# @return [Boolean]
|
|
attr_accessor :use_chief_in_tf_config
|
|
alias_method :use_chief_in_tf_config?, :use_chief_in_tf_config
|
|
|
|
# Represents the configuration for a replica in a cluster.
|
|
# Corresponds to the JSON property `workerConfig`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig]
|
|
attr_accessor :worker_config
|
|
|
|
# Optional. The number of worker replicas to use for the training job. Each
|
|
# replica in the cluster will be of the type specified in `worker_type`.
|
|
# This value can only be used when `scale_tier` is set to `CUSTOM`. If you
|
|
# set this value, you must also set `worker_type`.
|
|
# The default value is zero.
|
|
# Corresponds to the JSON property `workerCount`
|
|
# @return [Fixnum]
|
|
attr_accessor :worker_count
|
|
|
|
# Optional. Specifies the type of virtual machine to use for your training
|
|
# job's worker nodes.
|
|
# The supported values are the same as those described in the entry for
|
|
# `masterType`.
|
|
# This value must be consistent with the category of machine type that
|
|
# `masterType` uses. In other words, both must be Compute Engine machine
|
|
# types or both must be legacy machine types.
|
|
# If you use `cloud_tpu` for this value, see special instructions for
|
|
# [configuring a custom TPU
|
|
# machine](/ml-engine/docs/tensorflow/using-tpus#
|
|
# configuring_a_custom_tpu_machine).
|
|
# This value must be present when `scaleTier` is set to `CUSTOM` and
|
|
# `workerCount` is greater than zero.
|
|
# Corresponds to the JSON property `workerType`
|
|
# @return [String]
|
|
attr_accessor :worker_type
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@args = args[:args] if args.key?(:args)
|
|
@hyperparameters = args[:hyperparameters] if args.key?(:hyperparameters)
|
|
@job_dir = args[:job_dir] if args.key?(:job_dir)
|
|
@master_config = args[:master_config] if args.key?(:master_config)
|
|
@master_type = args[:master_type] if args.key?(:master_type)
|
|
@package_uris = args[:package_uris] if args.key?(:package_uris)
|
|
@parameter_server_config = args[:parameter_server_config] if args.key?(:parameter_server_config)
|
|
@parameter_server_count = args[:parameter_server_count] if args.key?(:parameter_server_count)
|
|
@parameter_server_type = args[:parameter_server_type] if args.key?(:parameter_server_type)
|
|
@python_module = args[:python_module] if args.key?(:python_module)
|
|
@python_version = args[:python_version] if args.key?(:python_version)
|
|
@region = args[:region] if args.key?(:region)
|
|
@runtime_version = args[:runtime_version] if args.key?(:runtime_version)
|
|
@scale_tier = args[:scale_tier] if args.key?(:scale_tier)
|
|
@use_chief_in_tf_config = args[:use_chief_in_tf_config] if args.key?(:use_chief_in_tf_config)
|
|
@worker_config = args[:worker_config] if args.key?(:worker_config)
|
|
@worker_count = args[:worker_count] if args.key?(:worker_count)
|
|
@worker_type = args[:worker_type] if args.key?(:worker_type)
|
|
end
|
|
end
|
|
|
|
# Represents results of a training job. Output only.
|
|
class GoogleCloudMlV1TrainingOutput
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# Represents output related to a built-in algorithm Job.
|
|
# Corresponds to the JSON property `builtInAlgorithmOutput`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1BuiltInAlgorithmOutput]
|
|
attr_accessor :built_in_algorithm_output
|
|
|
|
# The number of hyperparameter tuning trials that completed successfully.
|
|
# Only set for hyperparameter tuning jobs.
|
|
# Corresponds to the JSON property `completedTrialCount`
|
|
# @return [Fixnum]
|
|
attr_accessor :completed_trial_count
|
|
|
|
# The amount of ML units consumed by the job.
|
|
# Corresponds to the JSON property `consumedMLUnits`
|
|
# @return [Float]
|
|
attr_accessor :consumed_ml_units
|
|
|
|
# The TensorFlow summary tag name used for optimizing hyperparameter tuning
|
|
# trials. See
|
|
# [`HyperparameterSpec.hyperparameterMetricTag`](#HyperparameterSpec.FIELDS.
|
|
# hyperparameter_metric_tag)
|
|
# for more information. Only set for hyperparameter tuning jobs.
|
|
# Corresponds to the JSON property `hyperparameterMetricTag`
|
|
# @return [String]
|
|
attr_accessor :hyperparameter_metric_tag
|
|
|
|
# Whether this job is a built-in Algorithm job.
|
|
# Corresponds to the JSON property `isBuiltInAlgorithmJob`
|
|
# @return [Boolean]
|
|
attr_accessor :is_built_in_algorithm_job
|
|
alias_method :is_built_in_algorithm_job?, :is_built_in_algorithm_job
|
|
|
|
# Whether this job is a hyperparameter tuning job.
|
|
# Corresponds to the JSON property `isHyperparameterTuningJob`
|
|
# @return [Boolean]
|
|
attr_accessor :is_hyperparameter_tuning_job
|
|
alias_method :is_hyperparameter_tuning_job?, :is_hyperparameter_tuning_job
|
|
|
|
# Results for individual Hyperparameter trials.
|
|
# Only set for hyperparameter tuning jobs.
|
|
# Corresponds to the JSON property `trials`
|
|
# @return [Array<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
|
|
|
|
# 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
|
|
|
|
# Output only. The time the version was created.
|
|
# Corresponds to the JSON property `createTime`
|
|
# @return [String]
|
|
attr_accessor :create_time
|
|
|
|
# Required. The Cloud Storage location of the trained model used to
|
|
# create the version. See the
|
|
# [guide to model
|
|
# deployment](/ml-engine/docs/tensorflow/deploying-models) for more
|
|
# information.
|
|
# When passing Version to
|
|
# projects.models.versions.create
|
|
# the model service uses the specified location as the source of the model.
|
|
# Once deployed, the model version is hosted by the prediction service, so
|
|
# this location is useful only as a historical record.
|
|
# The total number of model files can't exceed 1000.
|
|
# Corresponds to the JSON property `deploymentUri`
|
|
# @return [String]
|
|
attr_accessor :deployment_uri
|
|
|
|
# Optional. The description specified for the version when it was created.
|
|
# Corresponds to the JSON property `description`
|
|
# @return [String]
|
|
attr_accessor :description
|
|
|
|
# Output only. The details of a failure or a cancellation.
|
|
# Corresponds to the JSON property `errorMessage`
|
|
# @return [String]
|
|
attr_accessor :error_message
|
|
|
|
# `etag` is used for optimistic concurrency control as a way to help
|
|
# prevent simultaneous updates of a model from overwriting each other.
|
|
# It is strongly suggested that systems make use of the `etag` in the
|
|
# read-modify-write cycle to perform model updates in order to avoid race
|
|
# conditions: An `etag` is returned in the response to `GetVersion`, and
|
|
# systems are expected to put that etag in the request to `UpdateVersion` to
|
|
# ensure that their change will be applied to the model as intended.
|
|
# Corresponds to the JSON property `etag`
|
|
# NOTE: Values are automatically base64 encoded/decoded in the client library.
|
|
# @return [String]
|
|
attr_accessor :etag
|
|
|
|
# Message holding configuration options for explaining model predictions.
|
|
# There are two feature attribution methods supported for TensorFlow models:
|
|
# integrated gradients and sampled Shapley.
|
|
# <a href="/ml-engine/docs/ai-explanations/overview">Learn more about feature
|
|
# attributions</a>.
|
|
# 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](/ml-engine/docs/tensorflow/custom-prediction-routines).
|
|
# If you specify a [Compute Engine (N1) machine
|
|
# type](/ml-engine/docs/machine-types-online-prediction) in the
|
|
# `machineType` field, you must specify `TENSORFLOW`
|
|
# for the framework.
|
|
# Corresponds to the JSON property `framework`
|
|
# @return [String]
|
|
attr_accessor :framework
|
|
|
|
# Output only. If true, this version will be used to handle prediction
|
|
# requests that do not specify a version.
|
|
# You can change the default version by calling
|
|
# projects.methods.versions.setDefault.
|
|
# 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
|
|
# <a href="/ml-engine/docs/tensorflow/resource-labels">using labels</a>.
|
|
# Corresponds to the JSON property `labels`
|
|
# @return [Hash<String,String>]
|
|
attr_accessor :labels
|
|
|
|
# Output only. The time the version was last used for prediction.
|
|
# Corresponds to the JSON property `lastUseTime`
|
|
# @return [String]
|
|
attr_accessor :last_use_time
|
|
|
|
# Optional. The type of machine on which to serve the model. Currently only
|
|
# applies to online prediction service. If this field is not specified, it
|
|
# defaults to `mls1-c1-m2`.
|
|
# Online prediction supports the following machine types:
|
|
# * `mls1-c1-m2`
|
|
# * `mls1-c4-m2`
|
|
# * `n1-standard-2`
|
|
# * `n1-standard-4`
|
|
# * `n1-standard-8`
|
|
# * `n1-standard-16`
|
|
# * `n1-standard-32`
|
|
# * `n1-highmem-2`
|
|
# * `n1-highmem-4`
|
|
# * `n1-highmem-8`
|
|
# * `n1-highmem-16`
|
|
# * `n1-highmem-32`
|
|
# * `n1-highcpu-2`
|
|
# * `n1-highcpu-4`
|
|
# * `n1-highcpu-8`
|
|
# * `n1-highcpu-16`
|
|
# * `n1-highcpu-32`
|
|
# `mls1-c1-m2` is generally available. All other machine types are available
|
|
# in beta. Learn more about the [differences between machine
|
|
# types](/ml-engine/docs/machine-types-online-prediction).
|
|
# Corresponds to the JSON property `machineType`
|
|
# @return [String]
|
|
attr_accessor :machine_type
|
|
|
|
# Options for manually scaling a model.
|
|
# Corresponds to the JSON property `manualScaling`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1ManualScaling]
|
|
attr_accessor :manual_scaling
|
|
|
|
# Required. The name specified for the version when it was created.
|
|
# The version name must be unique within the model it is created in.
|
|
# Corresponds to the JSON property `name`
|
|
# @return [String]
|
|
attr_accessor :name
|
|
|
|
# Optional. Cloud Storage paths (`gs://…`) of packages for [custom
|
|
# prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines)
|
|
# or [scikit-learn pipelines with custom
|
|
# code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code).
|
|
# For a custom prediction routine, one of these packages must contain your
|
|
# Predictor class (see
|
|
# [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally,
|
|
# include any dependencies used by your Predictor or scikit-learn pipeline
|
|
# uses that are not already included in your selected [runtime
|
|
# version](/ml-engine/docs/tensorflow/runtime-version-list).
|
|
# If you specify this field, you must also set
|
|
# [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
|
|
# Corresponds to the JSON property `packageUris`
|
|
# @return [Array<String>]
|
|
attr_accessor :package_uris
|
|
|
|
# Optional. The fully qualified name
|
|
# (<var>module_name</var>.<var>class_name</var>) 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:
|
|
# <pre style="max-width: 626px;">
|
|
# 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()
|
|
# </pre>
|
|
# Learn more about [the Predictor interface and custom prediction
|
|
# routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
|
|
# Corresponds to the JSON property `predictionClass`
|
|
# @return [String]
|
|
attr_accessor :prediction_class
|
|
|
|
# Optional. The version of Python used in prediction. If not set, the default
|
|
# version is '2.7'. Python '3.5' is available when `runtime_version` is set
|
|
# to '1.4' and above. Python '2.7' works with all supported runtime versions.
|
|
# Corresponds to the JSON property `pythonVersion`
|
|
# @return [String]
|
|
attr_accessor :python_version
|
|
|
|
# Configuration for logging request-response pairs to a BigQuery table.
|
|
# Online prediction requests to a model version and the responses to these
|
|
# requests are converted to raw strings and saved to the specified BigQuery
|
|
# table. Logging is constrained by [BigQuery quotas and
|
|
# limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits,
|
|
# AI Platform Prediction does not log request-response pairs, but it continues
|
|
# to serve predictions.
|
|
# If you are using [continuous
|
|
# evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to
|
|
# specify this configuration manually. Setting up continuous evaluation
|
|
# automatically enables logging of request-response pairs.
|
|
# Corresponds to the JSON property `requestLoggingConfig`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1RequestLoggingConfig]
|
|
attr_accessor :request_logging_config
|
|
|
|
# Optional. The AI Platform runtime version to use for this deployment.
|
|
# If not set, AI Platform uses the default stable version, 1.0. For more
|
|
# information, see the
|
|
# [runtime version list](/ml-engine/docs/runtime-version-list) and
|
|
# [how to manage runtime versions](/ml-engine/docs/versioning).
|
|
# Corresponds to the JSON property `runtimeVersion`
|
|
# @return [String]
|
|
attr_accessor :runtime_version
|
|
|
|
# Optional. Specifies the service account for resource access control.
|
|
# Corresponds to the JSON property `serviceAccount`
|
|
# @return [String]
|
|
attr_accessor :service_account
|
|
|
|
# Output only. The state of a version.
|
|
# Corresponds to the JSON property `state`
|
|
# @return [String]
|
|
attr_accessor :state
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@accelerator_config = args[:accelerator_config] if args.key?(:accelerator_config)
|
|
@auto_scaling = args[:auto_scaling] if args.key?(:auto_scaling)
|
|
@create_time = args[:create_time] if args.key?(:create_time)
|
|
@deployment_uri = args[:deployment_uri] if args.key?(:deployment_uri)
|
|
@description = args[:description] if args.key?(:description)
|
|
@error_message = args[:error_message] if args.key?(:error_message)
|
|
@etag = args[:etag] if args.key?(:etag)
|
|
@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)
|
|
@last_use_time = args[:last_use_time] if args.key?(:last_use_time)
|
|
@machine_type = args[:machine_type] if args.key?(:machine_type)
|
|
@manual_scaling = args[:manual_scaling] if args.key?(:manual_scaling)
|
|
@name = args[:name] if args.key?(:name)
|
|
@package_uris = args[:package_uris] if args.key?(:package_uris)
|
|
@prediction_class = args[:prediction_class] if args.key?(:prediction_class)
|
|
@python_version = args[:python_version] if args.key?(:python_version)
|
|
@request_logging_config = args[:request_logging_config] if args.key?(:request_logging_config)
|
|
@runtime_version = args[:runtime_version] if args.key?(:runtime_version)
|
|
@service_account = args[:service_account] if args.key?(:service_account)
|
|
@state = args[:state] if args.key?(:state)
|
|
end
|
|
end
|
|
|
|
# Specifies the audit configuration for a service.
|
|
# The configuration determines which permission types are logged, and what
|
|
# identities, if any, are exempted from logging.
|
|
# An AuditConfig must have one or more AuditLogConfigs.
|
|
# If there are AuditConfigs for both `allServices` and a specific service,
|
|
# the union of the two AuditConfigs is used for that service: the log_types
|
|
# specified in each AuditConfig are enabled, and the exempted_members in each
|
|
# AuditLogConfig are exempted.
|
|
# Example Policy with multiple AuditConfigs:
|
|
# `
|
|
# "audit_configs": [
|
|
# `
|
|
# "service": "allServices"
|
|
# "audit_log_configs": [
|
|
# `
|
|
# "log_type": "DATA_READ",
|
|
# "exempted_members": [
|
|
# "user:jose@example.com"
|
|
# ]
|
|
# `,
|
|
# `
|
|
# "log_type": "DATA_WRITE",
|
|
# `,
|
|
# `
|
|
# "log_type": "ADMIN_READ",
|
|
# `
|
|
# ]
|
|
# `,
|
|
# `
|
|
# "service": "sampleservice.googleapis.com"
|
|
# "audit_log_configs": [
|
|
# `
|
|
# "log_type": "DATA_READ",
|
|
# `,
|
|
# `
|
|
# "log_type": "DATA_WRITE",
|
|
# "exempted_members": [
|
|
# "user:aliya@example.com"
|
|
# ]
|
|
# `
|
|
# ]
|
|
# `
|
|
# ]
|
|
# `
|
|
# For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ
|
|
# logging. It also exempts jose@example.com from DATA_READ logging, and
|
|
# aliya@example.com from DATA_WRITE logging.
|
|
class GoogleIamV1AuditConfig
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# The configuration for logging of each type of permission.
|
|
# Corresponds to the JSON property `auditLogConfigs`
|
|
# @return [Array<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 an expression text. Example:
|
|
# title: "User account presence"
|
|
# description: "Determines whether the request has a user account"
|
|
# expression: "size(request.user) > 0"
|
|
# Corresponds to the JSON property `condition`
|
|
# @return [Google::Apis::MlV1::GoogleTypeExpr]
|
|
attr_accessor :condition
|
|
|
|
# Specifies the identities requesting access for a Cloud Platform resource.
|
|
# `members` can have the following values:
|
|
# * `allUsers`: A special identifier that represents anyone who is
|
|
# on the internet; with or without a Google account.
|
|
# * `allAuthenticatedUsers`: A special identifier that represents anyone
|
|
# who is authenticated with a Google account or a service account.
|
|
# * `user:`emailid``: An email address that represents a specific Google
|
|
# account. For example, `alice@example.com` .
|
|
# * `serviceAccount:`emailid``: An email address that represents a service
|
|
# account. For example, `my-other-app@appspot.gserviceaccount.com`.
|
|
# * `group:`emailid``: An email address that represents a Google group.
|
|
# For example, `admins@example.com`.
|
|
# * `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.
|
|
# Optionally, a `binding` can 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.
|
|
# **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.
|
|
# 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.
|
|
# Optionally, a `binding` can 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.
|
|
# **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"
|
|
# This field is only used by Cloud IAM.
|
|
# Corresponds to the JSON property `updateMask`
|
|
# @return [String]
|
|
attr_accessor :update_mask
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@policy = args[:policy] if args.key?(:policy)
|
|
@update_mask = args[:update_mask] if args.key?(:update_mask)
|
|
end
|
|
end
|
|
|
|
# Request message for `TestIamPermissions` method.
|
|
class GoogleIamV1TestIamPermissionsRequest
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# The set of permissions to check for the `resource`. Permissions with
|
|
# wildcards (such as '*' or 'storage.*') are not allowed. For more
|
|
# information see
|
|
# [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).
|
|
# Corresponds to the JSON property `permissions`
|
|
# @return [Array<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 an expression text. Example:
|
|
# title: "User account presence"
|
|
# description: "Determines whether the request has a user account"
|
|
# expression: "size(request.user) > 0"
|
|
class GoogleTypeExpr
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# An optional description of the expression. This is a longer text which
|
|
# describes the expression, e.g. when hovered over it in a UI.
|
|
# Corresponds to the JSON property `description`
|
|
# @return [String]
|
|
attr_accessor :description
|
|
|
|
# Textual representation of an expression in
|
|
# Common Expression Language syntax.
|
|
# The application context of the containing message determines which
|
|
# well-known feature set of CEL is supported.
|
|
# Corresponds to the JSON property `expression`
|
|
# @return [String]
|
|
attr_accessor :expression
|
|
|
|
# An optional string indicating the location of the expression for error
|
|
# reporting, e.g. a file name and a position in the file.
|
|
# Corresponds to the JSON property `location`
|
|
# @return [String]
|
|
attr_accessor :location
|
|
|
|
# An optional title for the expression, i.e. a short string describing
|
|
# its purpose. This can be used e.g. in UIs which allow to enter the
|
|
# expression.
|
|
# Corresponds to the JSON property `title`
|
|
# @return [String]
|
|
attr_accessor :title
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@description = args[:description] if args.key?(:description)
|
|
@expression = args[:expression] if args.key?(:expression)
|
|
@location = args[:location] if args.key?(:location)
|
|
@title = args[:title] if args.key?(:title)
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|