1621 lines
66 KiB
Ruby
1621 lines
66 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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# Response message for the ListModels method.
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class GoogleCloudMlV1ListModelsResponse
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include Google::Apis::Core::Hashable
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# The list of models.
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# Corresponds to the JSON property `models`
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# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1Model>]
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attr_accessor :models
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# Optional. Pass this token as the `page_token` field of the request for a
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# subsequent call.
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# Corresponds to the JSON property `nextPageToken`
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# @return [String]
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attr_accessor :next_page_token
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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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@models = args[:models] if args.key?(:models)
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@next_page_token = args[:next_page_token] if args.key?(:next_page_token)
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end
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end
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# Represents input parameters for a training job.
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class GoogleCloudMlV1TrainingInput
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include Google::Apis::Core::Hashable
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# Optional. The number of parameter server replicas to use for the training
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# job. Each replica in the cluster will be of the type specified in
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# `parameter_server_type`.
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# This value can only be used when `scale_tier` is set to `CUSTOM`.If you
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# set this value, you must also set `parameter_server_type`.
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# Corresponds to the JSON property `parameterServerCount`
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# @return [Fixnum]
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attr_accessor :parameter_server_count
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# Required. The Google Cloud Storage location of the packages with
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# the training program and any additional dependencies.
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# The maximum number of package URIs is 100.
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# Corresponds to the JSON property `packageUris`
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# @return [Array<String>]
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attr_accessor :package_uris
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# Optional. The number of worker replicas to use for the training job. Each
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# replica in the cluster will be of the type specified in `worker_type`.
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# This value can only be used when `scale_tier` is set to `CUSTOM`. If you
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# set this value, you must also set `worker_type`.
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# Corresponds to the JSON property `workerCount`
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# @return [Fixnum]
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attr_accessor :worker_count
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# Optional. Specifies the type of virtual machine to use for your training
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# job's master worker.
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# The following types are supported:
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# <dl>
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# <dt>standard</dt>
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# <dd>
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# A basic machine configuration suitable for training simple models with
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# small to moderate datasets.
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# </dd>
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# <dt>large_model</dt>
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# <dd>
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# A machine with a lot of memory, specially suited for parameter servers
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# when your model is large (having many hidden layers or layers with very
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# large numbers of nodes).
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# </dd>
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# <dt>complex_model_s</dt>
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# <dd>
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# A machine suitable for the master and workers of the cluster when your
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# model requires more computation than the standard machine can handle
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# satisfactorily.
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# </dd>
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# <dt>complex_model_m</dt>
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# <dd>
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# A machine with roughly twice the number of cores and roughly double the
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# memory of <code suppresswarning="true">complex_model_s</code>.
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# </dd>
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# <dt>complex_model_l</dt>
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# <dd>
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# A machine with roughly twice the number of cores and roughly double the
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# memory of <code suppresswarning="true">complex_model_m</code>.
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# </dd>
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# <dt>standard_gpu</dt>
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# <dd>
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# A machine equivalent to <code suppresswarning="true">standard</code> that
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# also includes a
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# <a href="/ml-engine/docs/how-tos/using-gpus">
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# GPU that you can use in your trainer</a>.
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# </dd>
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# <dt>complex_model_m_gpu</dt>
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# <dd>
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# A machine equivalent to
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# <code suppresswarning="true">coplex_model_m</code> that also includes
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# four GPUs.
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# </dd>
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# </dl>
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# You must set this value when `scaleTier` is set to `CUSTOM`.
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# Corresponds to the JSON property `masterType`
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# @return [String]
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attr_accessor :master_type
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# Optional. The Google Cloud ML runtime version to use for training. If not
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# set, Google Cloud ML will choose the latest stable version.
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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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# Required. The Python module name to run after installing the packages.
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# Corresponds to the JSON property `pythonModule`
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# @return [String]
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attr_accessor :python_module
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# Optional. Specifies the type of virtual machine to use for your training
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# job's worker nodes.
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# The supported values are the same as those described in the entry for
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# `masterType`.
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# This value must be present when `scaleTier` is set to `CUSTOM` and
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# `workerCount` is greater than zero.
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# Corresponds to the JSON property `workerType`
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# @return [String]
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attr_accessor :worker_type
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# Optional. Command line arguments to pass to the program.
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# Corresponds to the JSON property `args`
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# @return [Array<String>]
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attr_accessor :args
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# Required. The Google Compute Engine region to run the training job in.
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# Corresponds to the JSON property `region`
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# @return [String]
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attr_accessor :region
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# Optional. Specifies the type of virtual machine to use for your training
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# job's parameter server.
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# The supported values are the same as those described in the entry for
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# `master_type`.
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# This value must be present when `scaleTier` is set to `CUSTOM` and
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# `parameter_server_count` is greater than zero.
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# Corresponds to the JSON property `parameterServerType`
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# @return [String]
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attr_accessor :parameter_server_type
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# Required. Specifies the machine types, the number of replicas for workers
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# and parameter servers.
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# Corresponds to the JSON property `scaleTier`
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# @return [String]
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attr_accessor :scale_tier
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# Optional. A Google Cloud Storage path in which to store training outputs
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# and other data needed for training. This path is passed to your TensorFlow
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# program as the 'job_dir' command-line argument. The benefit of specifying
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# this field is that Cloud ML validates the path for use in training.
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# Corresponds to the JSON property `jobDir`
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# @return [String]
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attr_accessor :job_dir
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# Represents a set of hyperparameters to optimize.
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# Corresponds to the JSON property `hyperparameters`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1HyperparameterSpec]
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attr_accessor :hyperparameters
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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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@parameter_server_count = args[:parameter_server_count] if args.key?(:parameter_server_count)
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@package_uris = args[:package_uris] if args.key?(:package_uris)
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@worker_count = args[:worker_count] if args.key?(:worker_count)
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@master_type = args[:master_type] if args.key?(:master_type)
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@runtime_version = args[:runtime_version] if args.key?(:runtime_version)
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@python_module = args[:python_module] if args.key?(:python_module)
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@worker_type = args[:worker_type] if args.key?(:worker_type)
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@args = args[:args] if args.key?(:args)
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@region = args[:region] if args.key?(:region)
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@parameter_server_type = args[:parameter_server_type] if args.key?(:parameter_server_type)
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@scale_tier = args[:scale_tier] if args.key?(:scale_tier)
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@job_dir = args[:job_dir] if args.key?(:job_dir)
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@hyperparameters = args[:hyperparameters] if args.key?(:hyperparameters)
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end
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end
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# Represents a training or prediction job.
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class GoogleCloudMlV1Job
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include Google::Apis::Core::Hashable
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# Represents results of a training job. Output only.
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# Corresponds to the JSON property `trainingOutput`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1TrainingOutput]
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attr_accessor :training_output
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# Output only. When the job was created.
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# Corresponds to the JSON property `createTime`
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# @return [String]
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attr_accessor :create_time
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# Represents input parameters for a training job.
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# Corresponds to the JSON property `trainingInput`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1TrainingInput]
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attr_accessor :training_input
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# Output only. The detailed state of a job.
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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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# Represents input parameters for a prediction job.
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# Corresponds to the JSON property `predictionInput`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1PredictionInput]
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attr_accessor :prediction_input
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# Output only. The details of a failure or a cancellation.
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# Corresponds to the JSON property `errorMessage`
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# @return [String]
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attr_accessor :error_message
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# Required. The user-specified id of the job.
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# Corresponds to the JSON property `jobId`
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# @return [String]
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attr_accessor :job_id
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# Output only. When the job processing was completed.
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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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# Output only. When the job processing was started.
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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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# Represents results of a prediction job.
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# Corresponds to the JSON property `predictionOutput`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1PredictionOutput]
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attr_accessor :prediction_output
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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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@training_output = args[:training_output] if args.key?(:training_output)
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@create_time = args[:create_time] if args.key?(:create_time)
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@training_input = args[:training_input] if args.key?(:training_input)
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@state = args[:state] if args.key?(:state)
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@prediction_input = args[:prediction_input] if args.key?(:prediction_input)
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@error_message = args[:error_message] if args.key?(:error_message)
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@job_id = args[:job_id] if args.key?(:job_id)
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@end_time = args[:end_time] if args.key?(:end_time)
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@start_time = args[:start_time] if args.key?(:start_time)
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@prediction_output = args[:prediction_output] if args.key?(:prediction_output)
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end
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end
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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 (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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# HTTP body binary data.
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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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# The HTTP Content-Type string representing 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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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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@data = args[:data] if args.key?(:data)
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@content_type = args[:content_type] if args.key?(:content_type)
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end
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end
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# Represents a version of the model.
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# Each version is a trained model deployed in the cloud, ready to handle
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# prediction requests. A model can have multiple versions. You can get
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# information about all of the versions of a given model by calling
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# [projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.
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# models.versions/list).
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class GoogleCloudMlV1beta1Version
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include Google::Apis::Core::Hashable
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# Optional. The Google Cloud ML runtime version to use for this deployment.
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# If not set, Google Cloud ML will choose a version.
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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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# Output only. The time the version was last used for prediction.
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# Corresponds to the JSON property `lastUseTime`
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# @return [String]
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attr_accessor :last_use_time
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# Optional. The description specified for the version when it was created.
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# Corresponds to the JSON property `description`
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# @return [String]
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attr_accessor :description
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# Required. The Google Cloud Storage location of the trained model used to
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# create the version. See the
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# [overview of model
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# deployment](/ml-engine/docs/concepts/deployment-overview) for more
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# informaiton.
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# When passing Version to
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# [projects.models.versions.create](/ml-engine/reference/rest/v1beta1/projects.
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# models.versions/create)
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# the model service uses the specified location as the source of the model.
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# Once deployed, the model version is hosted by the prediction service, so
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# this location is useful only as a historical record.
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# The total number of model files can't exceed 1000.
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# Corresponds to the JSON property `deploymentUri`
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# @return [String]
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attr_accessor :deployment_uri
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# Output only. If true, this version will be used to handle prediction
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# requests that do not specify a version.
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# You can change the default version by calling
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# [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1beta1/
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# projects.models.versions/setDefault).
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# Corresponds to the JSON property `isDefault`
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# @return [Boolean]
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attr_accessor :is_default
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alias_method :is_default?, :is_default
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# Output only. The time the version was created.
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# Corresponds to the JSON property `createTime`
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# @return [String]
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attr_accessor :create_time
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# Options for manually scaling a model.
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# Corresponds to the JSON property `manualScaling`
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# @return [Google::Apis::MlV1::GoogleCloudMlV1beta1ManualScaling]
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attr_accessor :manual_scaling
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# Required.The name specified for the version when it was created.
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# The version name must be unique within the model it is created in.
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# Corresponds to the JSON property `name`
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# @return [String]
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attr_accessor :name
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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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@runtime_version = args[:runtime_version] if args.key?(:runtime_version)
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@last_use_time = args[:last_use_time] if args.key?(:last_use_time)
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@description = args[:description] if args.key?(:description)
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@deployment_uri = args[:deployment_uri] if args.key?(:deployment_uri)
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@is_default = args[:is_default] if args.key?(:is_default)
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@create_time = args[:create_time] if args.key?(:create_time)
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@manual_scaling = args[:manual_scaling] if args.key?(:manual_scaling)
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@name = args[:name] if args.key?(:name)
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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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# 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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# 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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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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@service_account_project = args[:service_account_project] if args.key?(:service_account_project)
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@service_account = args[:service_account] if args.key?(:service_account)
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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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# 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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# 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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# All recorded object metrics for this trial.
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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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# 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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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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@hyperparameters = args[:hyperparameters] if args.key?(:hyperparameters)
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@trial_id = args[:trial_id] if args.key?(:trial_id)
|
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@all_metrics = args[:all_metrics] if args.key?(:all_metrics)
|
|
@final_metric = args[:final_metric] if args.key?(:final_metric)
|
|
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
|
|
|
|
# The output Google Cloud Storage location provided at the job creation time.
|
|
# Corresponds to the JSON property `outputPath`
|
|
# @return [String]
|
|
attr_accessor :output_path
|
|
|
|
# Node hours used by the batch prediction job.
|
|
# Corresponds to the JSON property `nodeHours`
|
|
# @return [Float]
|
|
attr_accessor :node_hours
|
|
|
|
# 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)
|
|
@output_path = args[:output_path] if args.key?(:output_path)
|
|
@node_hours = args[:node_hours] if args.key?(:node_hours)
|
|
@prediction_count = args[:prediction_count] if args.key?(:prediction_count)
|
|
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
|
|
|
|
# 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
|
|
# deployment.
|
|
# 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 results of a training job. Output only.
|
|
class GoogleCloudMlV1TrainingOutput
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# The number of hyperparameter tuning trials that completed successfully.
|
|
# Only set for hyperparameter tuning jobs.
|
|
# Corresponds to the JSON property `completedTrialCount`
|
|
# @return [Fixnum]
|
|
attr_accessor :completed_trial_count
|
|
|
|
# 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
|
|
|
|
# The amount of ML units consumed by the job.
|
|
# Corresponds to the JSON property `consumedMLUnits`
|
|
# @return [Float]
|
|
attr_accessor :consumed_ml_units
|
|
|
|
# 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)
|
|
@completed_trial_count = args[:completed_trial_count] if args.key?(:completed_trial_count)
|
|
@is_hyperparameter_tuning_job = args[:is_hyperparameter_tuning_job] if args.key?(:is_hyperparameter_tuning_job)
|
|
@consumed_ml_units = args[:consumed_ml_units] if args.key?(:consumed_ml_units)
|
|
@trials = args[:trials] if args.key?(:trials)
|
|
end
|
|
end
|
|
|
|
# Request for predictions to be issued against a trained model.
|
|
# The body of the request is a single JSON object with a single top-level
|
|
# field:
|
|
# <dl>
|
|
# <dt>instances</dt>
|
|
# <dd>A JSON array containing values representing the instances to use for
|
|
# prediction.</dd>
|
|
# </dl>
|
|
# The structure of each element of the instances list is determined by your
|
|
# model's input definition. Instances can include named inputs or can contain
|
|
# only unlabeled values.
|
|
# Not all data includes named inputs. Some instances will be simple
|
|
# JSON values (boolean, number, or string). However, instances are often lists
|
|
# of simple values, or complex nested lists. Here are some examples of request
|
|
# bodies:
|
|
# CSV data with each row encoded as a string value:
|
|
# <pre>
|
|
# `"instances": ["1.0,true,\\"x\\"", "-2.0,false,\\"y\\""]`
|
|
# </pre>
|
|
# Plain text:
|
|
# <pre>
|
|
# `"instances": ["the quick brown fox", "la bruja le dio"]`
|
|
# </pre>
|
|
# Sentences encoded as lists of words (vectors of strings):
|
|
# <pre>
|
|
# `
|
|
# "instances": [
|
|
# ["the","quick","brown"],
|
|
# ["la","bruja","le"],
|
|
# ...
|
|
# ]
|
|
# `
|
|
# </pre>
|
|
# Floating point scalar values:
|
|
# <pre>
|
|
# `"instances": [0.0, 1.1, 2.2]`
|
|
# </pre>
|
|
# Vectors of integers:
|
|
# <pre>
|
|
# `
|
|
# "instances": [
|
|
# [0, 1, 2],
|
|
# [3, 4, 5],
|
|
# ...
|
|
# ]
|
|
# `
|
|
# </pre>
|
|
# Tensors (in this case, two-dimensional tensors):
|
|
# <pre>
|
|
# `
|
|
# "instances": [
|
|
# [
|
|
# [0, 1, 2],
|
|
# [3, 4, 5]
|
|
# ],
|
|
# ...
|
|
# ]
|
|
# `
|
|
# </pre>
|
|
# Images can be represented different ways. In this encoding scheme the first
|
|
# two dimensions represent the rows and columns of the image, and the third
|
|
# contains lists (vectors) of the R, G, and B values for each pixel.
|
|
# <pre>
|
|
# `
|
|
# "instances": [
|
|
# [
|
|
# [
|
|
# [138, 30, 66],
|
|
# [130, 20, 56],
|
|
# ...
|
|
# ],
|
|
# [
|
|
# [126, 38, 61],
|
|
# [122, 24, 57],
|
|
# ...
|
|
# ],
|
|
# ...
|
|
# ],
|
|
# ...
|
|
# ]
|
|
# `
|
|
# </pre>
|
|
# JSON strings must be encoded as UTF-8. To send binary data, you must
|
|
# base64-encode the data and mark it as binary. To mark a JSON string
|
|
# as binary, replace it with a JSON object with a single attribute named `b64`:
|
|
# <pre>`"b64": "..."` </pre>
|
|
# For example:
|
|
# Two Serialized tf.Examples (fake data, for illustrative purposes only):
|
|
# <pre>
|
|
# `"instances": [`"b64": "X5ad6u"`, `"b64": "IA9j4nx"`]`
|
|
# </pre>
|
|
# Two JPEG image byte strings (fake data, for illustrative purposes only):
|
|
# <pre>
|
|
# `"instances": [`"b64": "ASa8asdf"`, `"b64": "JLK7ljk3"`]`
|
|
# </pre>
|
|
# If your data includes named references, format each instance as a JSON object
|
|
# with the named references as the keys:
|
|
# JSON input data to be preprocessed:
|
|
# <pre>
|
|
# `
|
|
# "instances": [
|
|
# `
|
|
# "a": 1.0,
|
|
# "b": true,
|
|
# "c": "x"
|
|
# `,
|
|
# `
|
|
# "a": -2.0,
|
|
# "b": false,
|
|
# "c": "y"
|
|
# `
|
|
# ]
|
|
# `
|
|
# </pre>
|
|
# Some models have an underlying TensorFlow graph that accepts multiple input
|
|
# tensors. In this case, you should use the names of JSON name/value pairs to
|
|
# identify the input tensors, as shown in the following exmaples:
|
|
# For a graph with input tensor aliases "tag" (string) and "image"
|
|
# (base64-encoded string):
|
|
# <pre>
|
|
# `
|
|
# "instances": [
|
|
# `
|
|
# "tag": "beach",
|
|
# "image": `"b64": "ASa8asdf"`
|
|
# `,
|
|
# `
|
|
# "tag": "car",
|
|
# "image": `"b64": "JLK7ljk3"`
|
|
# `
|
|
# ]
|
|
# `
|
|
# </pre>
|
|
# For a graph with input tensor aliases "tag" (string) and "image"
|
|
# (3-dimensional array of 8-bit ints):
|
|
# <pre>
|
|
# `
|
|
# "instances": [
|
|
# `
|
|
# "tag": "beach",
|
|
# "image": [
|
|
# [
|
|
# [138, 30, 66],
|
|
# [130, 20, 56],
|
|
# ...
|
|
# ],
|
|
# [
|
|
# [126, 38, 61],
|
|
# [122, 24, 57],
|
|
# ...
|
|
# ],
|
|
# ...
|
|
# ]
|
|
# `,
|
|
# `
|
|
# "tag": "car",
|
|
# "image": [
|
|
# [
|
|
# [255, 0, 102],
|
|
# [255, 0, 97],
|
|
# ...
|
|
# ],
|
|
# [
|
|
# [254, 1, 101],
|
|
# [254, 2, 93],
|
|
# ...
|
|
# ],
|
|
# ...
|
|
# ]
|
|
# `,
|
|
# ...
|
|
# ]
|
|
# `
|
|
# </pre>
|
|
# If the call is successful, the response body will contain one prediction
|
|
# entry per instance in the request body. If prediction fails for any
|
|
# instance, the response body will contain no predictions and will contian
|
|
# a single error entry instead.
|
|
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
|
|
|
|
# An observed value of a metric.
|
|
class GoogleCloudMlV1HyperparameterOutputHyperparameterMetric
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# The objective value at this training step.
|
|
# Corresponds to the JSON property `objectiveValue`
|
|
# @return [Float]
|
|
attr_accessor :objective_value
|
|
|
|
# The global training step for this metric.
|
|
# Corresponds to the JSON property `trainingStep`
|
|
# @return [Fixnum]
|
|
attr_accessor :training_step
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@objective_value = args[:objective_value] if args.key?(:objective_value)
|
|
@training_step = args[:training_step] if args.key?(:training_step)
|
|
end
|
|
end
|
|
|
|
# Represents a version of the model.
|
|
# Each version is a trained model deployed in the cloud, ready to handle
|
|
# prediction requests. A model can have multiple versions. You can get
|
|
# information about all of the versions of a given model by calling
|
|
# [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.
|
|
# versions/list).
|
|
class GoogleCloudMlV1Version
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# 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 Google Cloud ML runtime version to use for this deployment.
|
|
# If not set, Google Cloud ML will choose a version.
|
|
# Corresponds to the JSON property `runtimeVersion`
|
|
# @return [String]
|
|
attr_accessor :runtime_version
|
|
|
|
# Optional. The description specified for the version when it was created.
|
|
# Corresponds to the JSON property `description`
|
|
# @return [String]
|
|
attr_accessor :description
|
|
|
|
# Required. The Google Cloud Storage location of the trained model used to
|
|
# create the version. See the
|
|
# [overview of model
|
|
# deployment](/ml-engine/docs/concepts/deployment-overview) for more
|
|
# informaiton.
|
|
# When passing Version to
|
|
# [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.
|
|
# versions/create)
|
|
# the model service uses the specified location as the source of the model.
|
|
# Once deployed, the model version is hosted by the prediction service, so
|
|
# this location is useful only as a historical record.
|
|
# The total number of model files can't exceed 1000.
|
|
# Corresponds to the JSON property `deploymentUri`
|
|
# @return [String]
|
|
attr_accessor :deployment_uri
|
|
|
|
# Output only. If true, this version will be used to handle prediction
|
|
# requests that do not specify a version.
|
|
# You can change the default version by calling
|
|
# [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.
|
|
# models.versions/setDefault).
|
|
# Corresponds to the JSON property `isDefault`
|
|
# @return [Boolean]
|
|
attr_accessor :is_default
|
|
alias_method :is_default?, :is_default
|
|
|
|
# Output only. The time the version was created.
|
|
# Corresponds to the JSON property `createTime`
|
|
# @return [String]
|
|
attr_accessor :create_time
|
|
|
|
# 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
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@last_use_time = args[:last_use_time] if args.key?(:last_use_time)
|
|
@runtime_version = args[:runtime_version] if args.key?(:runtime_version)
|
|
@description = args[:description] if args.key?(:description)
|
|
@deployment_uri = args[:deployment_uri] if args.key?(:deployment_uri)
|
|
@is_default = args[:is_default] if args.key?(:is_default)
|
|
@create_time = args[:create_time] if args.key?(:create_time)
|
|
@manual_scaling = args[:manual_scaling] if args.key?(:manual_scaling)
|
|
@name = args[:name] if args.key?(:name)
|
|
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. 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
|
|
|
|
# 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 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
|
|
|
|
# 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 if typeis `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. 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)
|
|
@parameter_name = args[:parameter_name] if args.key?(:parameter_name)
|
|
@min_value = args[:min_value] if args.key?(:min_value)
|
|
@discrete_values = args[:discrete_values] if args.key?(:discrete_values)
|
|
@scale_type = args[:scale_type] if args.key?(:scale_type)
|
|
@max_value = args[:max_value] if args.key?(:max_value)
|
|
@type = args[:type] if args.key?(:type)
|
|
end
|
|
end
|
|
|
|
# Represents input parameters for a prediction job.
|
|
class GoogleCloudMlV1PredictionInput
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# 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/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[
|
|
# YOUR_VERSION]</var>"`
|
|
# Corresponds to the JSON property `versionName`
|
|
# @return [String]
|
|
attr_accessor :version_name
|
|
|
|
# Use this field if you want to use the default version for the specified
|
|
# model. The string must use the following format:
|
|
# `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
|
|
# Corresponds to the JSON property `modelName`
|
|
# @return [String]
|
|
attr_accessor :model_name
|
|
|
|
# Required. The output Google Cloud Storage location.
|
|
# Corresponds to the JSON property `outputPath`
|
|
# @return [String]
|
|
attr_accessor :output_path
|
|
|
|
# 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 specify a Google Cloud Storage path for
|
|
# the model to use.
|
|
# Corresponds to the JSON property `uri`
|
|
# @return [String]
|
|
attr_accessor :uri
|
|
|
|
# Required. The format of the input data files.
|
|
# Corresponds to the JSON property `dataFormat`
|
|
# @return [String]
|
|
attr_accessor :data_format
|
|
|
|
# Optional. The Google Cloud ML runtime version to use for this batch
|
|
# prediction. If not set, Google Cloud ML will pick the runtime version used
|
|
# during the CreateVersion request for this model version, or choose the
|
|
# latest stable version when model version information is not available
|
|
# such as when the model is specified by uri.
|
|
# Corresponds to the JSON property `runtimeVersion`
|
|
# @return [String]
|
|
attr_accessor :runtime_version
|
|
|
|
# Required. The Google Cloud Storage location of the input data files.
|
|
# May contain wildcards.
|
|
# Corresponds to the JSON property `inputPaths`
|
|
# @return [Array<String>]
|
|
attr_accessor :input_paths
|
|
|
|
# Required. The Google Compute Engine region to run the prediction job in.
|
|
# Corresponds to the JSON property `region`
|
|
# @return [String]
|
|
attr_accessor :region
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@version_name = args[:version_name] if args.key?(:version_name)
|
|
@model_name = args[:model_name] if args.key?(:model_name)
|
|
@output_path = args[:output_path] if args.key?(:output_path)
|
|
@max_worker_count = args[:max_worker_count] if args.key?(:max_worker_count)
|
|
@uri = args[:uri] if args.key?(:uri)
|
|
@data_format = args[:data_format] if args.key?(:data_format)
|
|
@runtime_version = args[:runtime_version] if args.key?(:runtime_version)
|
|
@input_paths = args[:input_paths] if args.key?(:input_paths)
|
|
@region = args[:region] if args.key?(:region)
|
|
end
|
|
end
|
|
|
|
# Represents the metadata of the long-running operation.
|
|
class GoogleCloudMlV1beta1OperationMetadata
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# 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 time the operation was submitted.
|
|
# Corresponds to the JSON property `createTime`
|
|
# @return [String]
|
|
attr_accessor :create_time
|
|
|
|
# Contains the name of the model associated with the operation.
|
|
# Corresponds to the JSON property `modelName`
|
|
# @return [String]
|
|
attr_accessor :model_name
|
|
|
|
# Represents a version of the model.
|
|
# Each version is a trained model deployed in the cloud, ready to handle
|
|
# prediction requests. A model can have multiple versions. You can get
|
|
# information about all of the versions of a given model by calling
|
|
# [projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.
|
|
# models.versions/list).
|
|
# Corresponds to the JSON property `version`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1beta1Version]
|
|
attr_accessor :version
|
|
|
|
# The time operation processing completed.
|
|
# Corresponds to the JSON property `endTime`
|
|
# @return [String]
|
|
attr_accessor :end_time
|
|
|
|
# The operation type.
|
|
# Corresponds to the JSON property `operationType`
|
|
# @return [String]
|
|
attr_accessor :operation_type
|
|
|
|
# The time operation processing started.
|
|
# Corresponds to the JSON property `startTime`
|
|
# @return [String]
|
|
attr_accessor :start_time
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@is_cancellation_requested = args[:is_cancellation_requested] if args.key?(:is_cancellation_requested)
|
|
@create_time = args[:create_time] if args.key?(:create_time)
|
|
@model_name = args[:model_name] if args.key?(:model_name)
|
|
@version = args[:version] if args.key?(:version)
|
|
@end_time = args[:end_time] if args.key?(:end_time)
|
|
@operation_type = args[:operation_type] if args.key?(:operation_type)
|
|
@start_time = args[:start_time] if args.key?(:start_time)
|
|
end
|
|
end
|
|
|
|
# Represents the metadata of the long-running operation.
|
|
class GoogleCloudMlV1OperationMetadata
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# The time operation processing started.
|
|
# Corresponds to the JSON property `startTime`
|
|
# @return [String]
|
|
attr_accessor :start_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 time the operation was submitted.
|
|
# Corresponds to the JSON property `createTime`
|
|
# @return [String]
|
|
attr_accessor :create_time
|
|
|
|
# Contains the name of the model associated with the operation.
|
|
# Corresponds to the JSON property `modelName`
|
|
# @return [String]
|
|
attr_accessor :model_name
|
|
|
|
# Represents a version of the model.
|
|
# Each version is a trained model deployed in the cloud, ready to handle
|
|
# prediction requests. A model can have multiple versions. You can get
|
|
# information about all of the versions of a given model by calling
|
|
# [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.
|
|
# versions/list).
|
|
# Corresponds to the JSON property `version`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1Version]
|
|
attr_accessor :version
|
|
|
|
# The time operation processing completed.
|
|
# Corresponds to the JSON property `endTime`
|
|
# @return [String]
|
|
attr_accessor :end_time
|
|
|
|
# The operation type.
|
|
# Corresponds to the JSON property `operationType`
|
|
# @return [String]
|
|
attr_accessor :operation_type
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@start_time = args[:start_time] if args.key?(:start_time)
|
|
@is_cancellation_requested = args[:is_cancellation_requested] if args.key?(:is_cancellation_requested)
|
|
@create_time = args[:create_time] if args.key?(:create_time)
|
|
@model_name = args[:model_name] if args.key?(:model_name)
|
|
@version = args[:version] if args.key?(:version)
|
|
@end_time = args[:end_time] if args.key?(:end_time)
|
|
@operation_type = args[:operation_type] if args.key?(:operation_type)
|
|
end
|
|
end
|
|
|
|
# Represents a set of hyperparameters to optimize.
|
|
class GoogleCloudMlV1HyperparameterSpec
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# Required. The set of parameters to tune.
|
|
# Corresponds to the JSON property `params`
|
|
# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1ParameterSpec>]
|
|
attr_accessor :params
|
|
|
|
# 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
|
|
|
|
# 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
|
|
|
|
# Required. The type of goal to use for tuning. Available types are
|
|
# `MAXIMIZE` and `MINIMIZE`.
|
|
# Defaults to `MAXIMIZE`.
|
|
# Corresponds to the JSON property `goal`
|
|
# @return [String]
|
|
attr_accessor :goal
|
|
|
|
# Optional. The Tensorflow summary tag name to use for optimizing trials. For
|
|
# current versions of Tensorflow, this tag name should exactly match what is
|
|
# shown in Tensorboard, including all scopes. For versions of Tensorflow
|
|
# prior to 0.12, this should be only the tag passed to tf.Summary.
|
|
# By default, "training/hptuning/metric" will be used.
|
|
# Corresponds to the JSON property `hyperparameterMetricTag`
|
|
# @return [String]
|
|
attr_accessor :hyperparameter_metric_tag
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@params = args[:params] if args.key?(:params)
|
|
@max_trials = args[:max_trials] if args.key?(:max_trials)
|
|
@max_parallel_trials = args[:max_parallel_trials] if args.key?(:max_parallel_trials)
|
|
@goal = args[:goal] if args.key?(:goal)
|
|
@hyperparameter_metric_tag = args[:hyperparameter_metric_tag] if args.key?(:hyperparameter_metric_tag)
|
|
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
|
|
|
|
# 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
|
|
|
|
# This resource represents a long-running operation that is the result of a
|
|
# network API call.
|
|
class GoogleLongrunningOperation
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# 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
|
|
|
|
# The server-assigned name, which is only unique within the same service that
|
|
# originally returns it. If you use the default HTTP mapping, the
|
|
# `name` should have the format of `operations/some/unique/name`.
|
|
# Corresponds to the JSON property `name`
|
|
# @return [String]
|
|
attr_accessor :name
|
|
|
|
# The `Status` type defines a logical error model that is suitable for different
|
|
# programming environments, including REST APIs and RPC APIs. It is used by
|
|
# [gRPC](https://github.com/grpc). The error model is designed to be:
|
|
# - Simple to use and understand for most users
|
|
# - Flexible enough to meet unexpected needs
|
|
# # Overview
|
|
# The `Status` message contains three pieces of data: error code, error message,
|
|
# and error details. The error code should be an enum value of
|
|
# google.rpc.Code, but it may accept additional error codes if needed. The
|
|
# error message should be a developer-facing English message that helps
|
|
# developers *understand* and *resolve* the error. If a localized user-facing
|
|
# error message is needed, put the localized message in the error details or
|
|
# localize it in the client. The optional error details may contain arbitrary
|
|
# information about the error. There is a predefined set of error detail types
|
|
# in the package `google.rpc` which can be used for common error conditions.
|
|
# # Language mapping
|
|
# The `Status` message is the logical representation of the error model, but it
|
|
# is not necessarily the actual wire format. When the `Status` message is
|
|
# exposed in different client libraries and different wire protocols, it can be
|
|
# mapped differently. For example, it will likely be mapped to some exceptions
|
|
# in Java, but more likely mapped to some error codes in C.
|
|
# # Other uses
|
|
# The error model and the `Status` message can be used in a variety of
|
|
# environments, either with or without APIs, to provide a
|
|
# consistent developer experience across different environments.
|
|
# Example uses of this error model include:
|
|
# - Partial errors. If a service needs to return partial errors to the client,
|
|
# it may embed the `Status` in the normal response to indicate the partial
|
|
# errors.
|
|
# - Workflow errors. A typical workflow has multiple steps. Each step may
|
|
# have a `Status` message for error reporting purpose.
|
|
# - Batch operations. If a client uses batch request and batch response, the
|
|
# `Status` message should be used directly inside batch response, one for
|
|
# each error sub-response.
|
|
# - Asynchronous operations. If an API call embeds asynchronous operation
|
|
# results in its response, the status of those operations should be
|
|
# represented directly using the `Status` message.
|
|
# - Logging. If some API errors are stored in logs, the message `Status` could
|
|
# be used directly after any stripping needed for security/privacy reasons.
|
|
# Corresponds to the JSON property `error`
|
|
# @return [Google::Apis::MlV1::GoogleRpcStatus]
|
|
attr_accessor :error
|
|
|
|
# Service-specific metadata associated with the operation. It typically
|
|
# contains progress information and common metadata such as create time.
|
|
# Some services might not provide such metadata. Any method that returns a
|
|
# long-running operation should document the metadata type, if any.
|
|
# Corresponds to the JSON property `metadata`
|
|
# @return [Hash<String,Object>]
|
|
attr_accessor :metadata
|
|
|
|
# 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
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@response = args[:response] if args.key?(:response)
|
|
@name = args[:name] if args.key?(:name)
|
|
@error = args[:error] if args.key?(:error)
|
|
@metadata = args[:metadata] if args.key?(:metadata)
|
|
@done = args[:done] if args.key?(:done)
|
|
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
|
|
|
|
# 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.
|
|
# 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
|
|
|
|
# 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. The description specified for the model when it was created.
|
|
# Corresponds to the JSON property `description`
|
|
# @return [String]
|
|
attr_accessor :description
|
|
|
|
# Optional. If true, enables StackDriver Logging for online prediction.
|
|
# Default is false.
|
|
# Corresponds to the JSON property `onlinePredictionLogging`
|
|
# @return [Boolean]
|
|
attr_accessor :online_prediction_logging
|
|
alias_method :online_prediction_logging?, :online_prediction_logging
|
|
|
|
# Represents a version of the model.
|
|
# Each version is a trained model deployed in the cloud, ready to handle
|
|
# prediction requests. A model can have multiple versions. You can get
|
|
# information about all of the versions of a given model by calling
|
|
# [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.
|
|
# versions/list).
|
|
# Corresponds to the JSON property `defaultVersion`
|
|
# @return [Google::Apis::MlV1::GoogleCloudMlV1Version]
|
|
attr_accessor :default_version
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@regions = args[:regions] if args.key?(:regions)
|
|
@name = args[:name] if args.key?(:name)
|
|
@description = args[:description] if args.key?(:description)
|
|
@online_prediction_logging = args[:online_prediction_logging] if args.key?(:online_prediction_logging)
|
|
@default_version = args[:default_version] if args.key?(:default_version)
|
|
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
|
|
|
|
# Request message for the CancelJob method.
|
|
class GoogleCloudMlV1CancelJobRequest
|
|
include Google::Apis::Core::Hashable
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
end
|
|
end
|
|
|
|
# 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
|
|
|
|
# Options for manually scaling a model.
|
|
class GoogleCloudMlV1beta1ManualScaling
|
|
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
|
|
# deployment.
|
|
# 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
|
|
|
|
# The `Status` type defines a logical error model that is suitable for different
|
|
# programming environments, including REST APIs and RPC APIs. It is used by
|
|
# [gRPC](https://github.com/grpc). The error model is designed to be:
|
|
# - Simple to use and understand for most users
|
|
# - Flexible enough to meet unexpected needs
|
|
# # Overview
|
|
# The `Status` message contains three pieces of data: error code, error message,
|
|
# and error details. The error code should be an enum value of
|
|
# google.rpc.Code, but it may accept additional error codes if needed. The
|
|
# error message should be a developer-facing English message that helps
|
|
# developers *understand* and *resolve* the error. If a localized user-facing
|
|
# error message is needed, put the localized message in the error details or
|
|
# localize it in the client. The optional error details may contain arbitrary
|
|
# information about the error. There is a predefined set of error detail types
|
|
# in the package `google.rpc` which can be used for common error conditions.
|
|
# # Language mapping
|
|
# The `Status` message is the logical representation of the error model, but it
|
|
# is not necessarily the actual wire format. When the `Status` message is
|
|
# exposed in different client libraries and different wire protocols, it can be
|
|
# mapped differently. For example, it will likely be mapped to some exceptions
|
|
# in Java, but more likely mapped to some error codes in C.
|
|
# # Other uses
|
|
# The error model and the `Status` message can be used in a variety of
|
|
# environments, either with or without APIs, to provide a
|
|
# consistent developer experience across different environments.
|
|
# Example uses of this error model include:
|
|
# - Partial errors. If a service needs to return partial errors to the client,
|
|
# it may embed the `Status` in the normal response to indicate the partial
|
|
# errors.
|
|
# - Workflow errors. A typical workflow has multiple steps. Each step may
|
|
# have a `Status` message for error reporting purpose.
|
|
# - Batch operations. If a client uses batch request and batch response, the
|
|
# `Status` message should be used directly inside batch response, one for
|
|
# each error sub-response.
|
|
# - Asynchronous operations. If an API call embeds asynchronous operation
|
|
# results in its response, the status of those operations should be
|
|
# represented directly using the `Status` message.
|
|
# - Logging. If some API errors are stored in logs, the message `Status` could
|
|
# be used directly after any stripping needed for security/privacy reasons.
|
|
class GoogleRpcStatus
|
|
include Google::Apis::Core::Hashable
|
|
|
|
# The status code, which should be an enum value of google.rpc.Code.
|
|
# Corresponds to the JSON property `code`
|
|
# @return [Fixnum]
|
|
attr_accessor :code
|
|
|
|
# A 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
|
|
|
|
# A list of messages that carry the error details. There will be a
|
|
# common set of message types for APIs to use.
|
|
# Corresponds to the JSON property `details`
|
|
# @return [Array<Hash<String,Object>>]
|
|
attr_accessor :details
|
|
|
|
def initialize(**args)
|
|
update!(**args)
|
|
end
|
|
|
|
# Update properties of this object
|
|
def update!(**args)
|
|
@code = args[:code] if args.key?(:code)
|
|
@message = args[:message] if args.key?(:message)
|
|
@details = args[:details] if args.key?(:details)
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|