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700 lines
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<h1><a href="ml_v1.html">AI Platform Training & Prediction API</a> . <a href="ml_v1.projects.html">projects</a> . <a href="ml_v1.projects.locations.html">locations</a> . <a href="ml_v1.projects.locations.studies.html">studies</a> . <a href="ml_v1.projects.locations.studies.trials.html">trials</a></h1>
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<h2>Instance Methods</h2>
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<p class="toc_element">
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<code><a href="#addMeasurement">addMeasurement(name, body=None, x__xgafv=None)</a></code></p>
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<p class="firstline">Adds a measurement of the objective metrics to a trial. This measurement is assumed to have been taken before the trial is complete.</p>
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<p class="toc_element">
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<code><a href="#checkEarlyStoppingState">checkEarlyStoppingState(name, body=None, x__xgafv=None)</a></code></p>
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<p class="firstline">Checks whether a trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.</p>
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<p class="toc_element">
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<code><a href="#close">close()</a></code></p>
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<p class="firstline">Close httplib2 connections.</p>
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<p class="toc_element">
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<code><a href="#complete">complete(name, body=None, x__xgafv=None)</a></code></p>
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<p class="firstline">Marks a trial as complete.</p>
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<p class="toc_element">
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<code><a href="#create">create(parent, body=None, x__xgafv=None)</a></code></p>
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<p class="firstline">Adds a user provided trial to a study.</p>
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<p class="toc_element">
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<code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
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<p class="firstline">Deletes a trial.</p>
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<p class="toc_element">
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<code><a href="#get">get(name, x__xgafv=None)</a></code></p>
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<p class="firstline">Gets a trial.</p>
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<p class="toc_element">
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<code><a href="#list">list(parent, x__xgafv=None)</a></code></p>
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<p class="firstline">Lists the trials associated with a study.</p>
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<p class="toc_element">
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<code><a href="#listOptimalTrials">listOptimalTrials(parent, body=None, x__xgafv=None)</a></code></p>
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<p class="firstline">Lists the pareto-optimal trials for multi-objective study or the optimal trials for single-objective study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency</p>
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<p class="toc_element">
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<code><a href="#stop">stop(name, body=None, x__xgafv=None)</a></code></p>
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<p class="firstline">Stops a trial.</p>
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<p class="toc_element">
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<code><a href="#suggest">suggest(parent, body=None, x__xgafv=None)</a></code></p>
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<p class="firstline">Adds one or more trials to a study, with parameter values suggested by AI Platform Vizier. Returns a long-running operation associated with the generation of trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.</p>
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<h3>Method Details</h3>
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<div class="method">
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<code class="details" id="addMeasurement">addMeasurement(name, body=None, x__xgafv=None)</code>
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<pre>Adds a measurement of the objective metrics to a trial. This measurement is assumed to have been taken before the trial is complete.
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Args:
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name: string, Required. The trial name. (required)
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body: object, The request body.
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The object takes the form of:
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{ # The request message for the AddTrialMeasurement service method.
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"measurement": { # A message representing a measurement. # Required. The measurement to be added to a trial.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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}
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x__xgafv: string, V1 error format.
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Allowed values
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1 - v1 error format
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2 - v2 error format
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Returns:
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An object of the form:
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{ # A message representing a trial.
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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
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"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
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{ # A message representing a measurement.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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],
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"name": "A String", # Output only. Name of the trial assigned by the service.
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"parameters": [ # The parameters of the trial.
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{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
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"intValue": "A String", # Must be set if ParameterType is INTEGER
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"parameter": "A String", # The name of the parameter.
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"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
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},
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],
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"startTime": "A String", # Output only. Time at which the trial was started.
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"state": "A String", # The detailed state of a trial.
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"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
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}</pre>
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</div>
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<div class="method">
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<code class="details" id="checkEarlyStoppingState">checkEarlyStoppingState(name, body=None, x__xgafv=None)</code>
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<pre>Checks whether a trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.
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Args:
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name: string, Required. The trial name. (required)
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body: object, The request body.
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The object takes the form of:
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{ # The request message for the CheckTrialEarlyStoppingState service method.
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}
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x__xgafv: string, V1 error format.
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Allowed values
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1 - v1 error format
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2 - v2 error format
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Returns:
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An object of the form:
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{ # This resource represents a long-running operation that is the result of a network API call.
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"done": True or False, # 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.
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"error": { # 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). # The error result of the operation in case of failure or cancellation.
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"code": 42, # The status code, which should be an enum value of google.rpc.Code.
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"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
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{
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"a_key": "", # Properties of the object. Contains field @type with type URL.
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},
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],
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"message": "A String", # 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.
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},
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"metadata": { # 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.
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"a_key": "", # Properties of the object. Contains field @type with type URL.
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},
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"name": "A String", # 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}`.
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"response": { # 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`.
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"a_key": "", # Properties of the object. Contains field @type with type URL.
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},
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}</pre>
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</div>
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<div class="method">
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<code class="details" id="close">close()</code>
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<pre>Close httplib2 connections.</pre>
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</div>
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<div class="method">
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<code class="details" id="complete">complete(name, body=None, x__xgafv=None)</code>
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<pre>Marks a trial as complete.
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Args:
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name: string, Required. The trial name.metat (required)
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body: object, The request body.
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The object takes the form of:
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{ # The request message for the CompleteTrial service method.
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"finalMeasurement": { # A message representing a measurement. # Optional. If provided, it will be used as the completed trial's final_measurement; Otherwise, the service will auto-select a previously reported measurement as the final-measurement
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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"infeasibleReason": "A String", # Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true.
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"trialInfeasible": True or False, # Optional. True if the trial cannot be run with the given Parameter, and final_measurement will be ignored.
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}
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x__xgafv: string, V1 error format.
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Allowed values
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1 - v1 error format
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2 - v2 error format
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Returns:
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An object of the form:
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{ # A message representing a trial.
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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
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"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
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{ # A message representing a measurement.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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],
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"name": "A String", # Output only. Name of the trial assigned by the service.
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"parameters": [ # The parameters of the trial.
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{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
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"intValue": "A String", # Must be set if ParameterType is INTEGER
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"parameter": "A String", # The name of the parameter.
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"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
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},
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],
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"startTime": "A String", # Output only. Time at which the trial was started.
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"state": "A String", # The detailed state of a trial.
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"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
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}</pre>
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</div>
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<div class="method">
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<code class="details" id="create">create(parent, body=None, x__xgafv=None)</code>
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<pre>Adds a user provided trial to a study.
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Args:
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parent: string, Required. The name of the study that the trial belongs to. (required)
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body: object, The request body.
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The object takes the form of:
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{ # A message representing a trial.
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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
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"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
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{ # A message representing a measurement.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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],
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"name": "A String", # Output only. Name of the trial assigned by the service.
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"parameters": [ # The parameters of the trial.
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{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
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"intValue": "A String", # Must be set if ParameterType is INTEGER
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"parameter": "A String", # The name of the parameter.
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"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
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},
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],
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"startTime": "A String", # Output only. Time at which the trial was started.
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"state": "A String", # The detailed state of a trial.
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"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
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}
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x__xgafv: string, V1 error format.
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Allowed values
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1 - v1 error format
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2 - v2 error format
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Returns:
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An object of the form:
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{ # A message representing a trial.
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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
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"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
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{ # A message representing a measurement.
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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
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"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
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{ # A message representing a metric in the measurement.
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"metric": "A String", # Required. Metric name.
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"value": 3.14, # Required. The value for this metric.
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},
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],
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"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
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},
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],
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"name": "A String", # Output only. Name of the trial assigned by the service.
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"parameters": [ # The parameters of the trial.
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{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
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"intValue": "A String", # Must be set if ParameterType is INTEGER
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"parameter": "A String", # The name of the parameter.
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"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
|
|
},
|
|
],
|
|
"startTime": "A String", # Output only. Time at which the trial was started.
|
|
"state": "A String", # The detailed state of a trial.
|
|
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
|
|
}</pre>
|
|
</div>
|
|
|
|
<div class="method">
|
|
<code class="details" id="delete">delete(name, x__xgafv=None)</code>
|
|
<pre>Deletes a trial.
|
|
|
|
Args:
|
|
name: string, Required. The trial name. (required)
|
|
x__xgafv: string, V1 error format.
|
|
Allowed values
|
|
1 - v1 error format
|
|
2 - v2 error format
|
|
|
|
Returns:
|
|
An object of the form:
|
|
|
|
{ # 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 `{}`.
|
|
}</pre>
|
|
</div>
|
|
|
|
<div class="method">
|
|
<code class="details" id="get">get(name, x__xgafv=None)</code>
|
|
<pre>Gets a trial.
|
|
|
|
Args:
|
|
name: string, Required. The trial name. (required)
|
|
x__xgafv: string, V1 error format.
|
|
Allowed values
|
|
1 - v1 error format
|
|
2 - v2 error format
|
|
|
|
Returns:
|
|
An object of the form:
|
|
|
|
{ # A message representing a trial.
|
|
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
|
|
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
|
|
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
|
|
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
|
|
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
|
|
{ # A message representing a metric in the measurement.
|
|
"metric": "A String", # Required. Metric name.
|
|
"value": 3.14, # Required. The value for this metric.
|
|
},
|
|
],
|
|
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
|
|
},
|
|
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
|
|
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
|
|
{ # A message representing a measurement.
|
|
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
|
|
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
|
|
{ # A message representing a metric in the measurement.
|
|
"metric": "A String", # Required. Metric name.
|
|
"value": 3.14, # Required. The value for this metric.
|
|
},
|
|
],
|
|
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
|
|
},
|
|
],
|
|
"name": "A String", # Output only. Name of the trial assigned by the service.
|
|
"parameters": [ # The parameters of the trial.
|
|
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
|
|
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
|
|
"intValue": "A String", # Must be set if ParameterType is INTEGER
|
|
"parameter": "A String", # The name of the parameter.
|
|
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
|
|
},
|
|
],
|
|
"startTime": "A String", # Output only. Time at which the trial was started.
|
|
"state": "A String", # The detailed state of a trial.
|
|
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
|
|
}</pre>
|
|
</div>
|
|
|
|
<div class="method">
|
|
<code class="details" id="list">list(parent, x__xgafv=None)</code>
|
|
<pre>Lists the trials associated with a study.
|
|
|
|
Args:
|
|
parent: string, Required. The name of the study that the trial belongs to. (required)
|
|
x__xgafv: string, V1 error format.
|
|
Allowed values
|
|
1 - v1 error format
|
|
2 - v2 error format
|
|
|
|
Returns:
|
|
An object of the form:
|
|
|
|
{ # The response message for the ListTrials method.
|
|
"trials": [ # The trials associated with the study.
|
|
{ # A message representing a trial.
|
|
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
|
|
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
|
|
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
|
|
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
|
|
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
|
|
{ # A message representing a metric in the measurement.
|
|
"metric": "A String", # Required. Metric name.
|
|
"value": 3.14, # Required. The value for this metric.
|
|
},
|
|
],
|
|
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
|
|
},
|
|
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
|
|
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
|
|
{ # A message representing a measurement.
|
|
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
|
|
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
|
|
{ # A message representing a metric in the measurement.
|
|
"metric": "A String", # Required. Metric name.
|
|
"value": 3.14, # Required. The value for this metric.
|
|
},
|
|
],
|
|
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
|
|
},
|
|
],
|
|
"name": "A String", # Output only. Name of the trial assigned by the service.
|
|
"parameters": [ # The parameters of the trial.
|
|
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
|
|
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
|
|
"intValue": "A String", # Must be set if ParameterType is INTEGER
|
|
"parameter": "A String", # The name of the parameter.
|
|
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
|
|
},
|
|
],
|
|
"startTime": "A String", # Output only. Time at which the trial was started.
|
|
"state": "A String", # The detailed state of a trial.
|
|
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
|
|
},
|
|
],
|
|
}</pre>
|
|
</div>
|
|
|
|
<div class="method">
|
|
<code class="details" id="listOptimalTrials">listOptimalTrials(parent, body=None, x__xgafv=None)</code>
|
|
<pre>Lists the pareto-optimal trials for multi-objective study or the optimal trials for single-objective study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency
|
|
|
|
Args:
|
|
parent: string, Required. The name of the study that the pareto-optimal trial belongs to. (required)
|
|
body: object, The request body.
|
|
The object takes the form of:
|
|
|
|
{ # The request message for the ListTrials service method.
|
|
}
|
|
|
|
x__xgafv: string, V1 error format.
|
|
Allowed values
|
|
1 - v1 error format
|
|
2 - v2 error format
|
|
|
|
Returns:
|
|
An object of the form:
|
|
|
|
{ # The response message for the ListOptimalTrials method.
|
|
"trials": [ # The pareto-optimal trials for multiple objective study or the optimal trial for single objective study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency
|
|
{ # A message representing a trial.
|
|
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
|
|
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
|
|
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
|
|
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
|
|
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
|
|
{ # A message representing a metric in the measurement.
|
|
"metric": "A String", # Required. Metric name.
|
|
"value": 3.14, # Required. The value for this metric.
|
|
},
|
|
],
|
|
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
|
|
},
|
|
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
|
|
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
|
|
{ # A message representing a measurement.
|
|
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
|
|
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
|
|
{ # A message representing a metric in the measurement.
|
|
"metric": "A String", # Required. Metric name.
|
|
"value": 3.14, # Required. The value for this metric.
|
|
},
|
|
],
|
|
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
|
|
},
|
|
],
|
|
"name": "A String", # Output only. Name of the trial assigned by the service.
|
|
"parameters": [ # The parameters of the trial.
|
|
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
|
|
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
|
|
"intValue": "A String", # Must be set if ParameterType is INTEGER
|
|
"parameter": "A String", # The name of the parameter.
|
|
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
|
|
},
|
|
],
|
|
"startTime": "A String", # Output only. Time at which the trial was started.
|
|
"state": "A String", # The detailed state of a trial.
|
|
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
|
|
},
|
|
],
|
|
}</pre>
|
|
</div>
|
|
|
|
<div class="method">
|
|
<code class="details" id="stop">stop(name, body=None, x__xgafv=None)</code>
|
|
<pre>Stops a trial.
|
|
|
|
Args:
|
|
name: string, Required. The trial name. (required)
|
|
body: object, The request body.
|
|
The object takes the form of:
|
|
|
|
{
|
|
}
|
|
|
|
x__xgafv: string, V1 error format.
|
|
Allowed values
|
|
1 - v1 error format
|
|
2 - v2 error format
|
|
|
|
Returns:
|
|
An object of the form:
|
|
|
|
{ # A message representing a trial.
|
|
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
|
|
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
|
|
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
|
|
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
|
|
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
|
|
{ # A message representing a metric in the measurement.
|
|
"metric": "A String", # Required. Metric name.
|
|
"value": 3.14, # Required. The value for this metric.
|
|
},
|
|
],
|
|
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
|
|
},
|
|
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
|
|
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
|
|
{ # A message representing a measurement.
|
|
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
|
|
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
|
|
{ # A message representing a metric in the measurement.
|
|
"metric": "A String", # Required. Metric name.
|
|
"value": 3.14, # Required. The value for this metric.
|
|
},
|
|
],
|
|
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
|
|
},
|
|
],
|
|
"name": "A String", # Output only. Name of the trial assigned by the service.
|
|
"parameters": [ # The parameters of the trial.
|
|
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
|
|
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
|
|
"intValue": "A String", # Must be set if ParameterType is INTEGER
|
|
"parameter": "A String", # The name of the parameter.
|
|
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
|
|
},
|
|
],
|
|
"startTime": "A String", # Output only. Time at which the trial was started.
|
|
"state": "A String", # The detailed state of a trial.
|
|
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
|
|
}</pre>
|
|
</div>
|
|
|
|
<div class="method">
|
|
<code class="details" id="suggest">suggest(parent, body=None, x__xgafv=None)</code>
|
|
<pre>Adds one or more trials to a study, with parameter values suggested by AI Platform Vizier. Returns a long-running operation associated with the generation of trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.
|
|
|
|
Args:
|
|
parent: string, Required. The name of the study that the trial belongs to. (required)
|
|
body: object, The request body.
|
|
The object takes the form of:
|
|
|
|
{ # The request message for the SuggestTrial service method.
|
|
"clientId": "A String", # Required. The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested trial if the trial is pending, and provide a new trial if the last suggested trial was completed.
|
|
"suggestionCount": 42, # Required. The number of suggestions requested.
|
|
}
|
|
|
|
x__xgafv: string, V1 error format.
|
|
Allowed values
|
|
1 - v1 error format
|
|
2 - v2 error format
|
|
|
|
Returns:
|
|
An object of the form:
|
|
|
|
{ # This resource represents a long-running operation that is the result of a network API call.
|
|
"done": True or False, # 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.
|
|
"error": { # 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). # The error result of the operation in case of failure or cancellation.
|
|
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
|
|
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
|
|
{
|
|
"a_key": "", # Properties of the object. Contains field @type with type URL.
|
|
},
|
|
],
|
|
"message": "A String", # 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.
|
|
},
|
|
"metadata": { # 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.
|
|
"a_key": "", # Properties of the object. Contains field @type with type URL.
|
|
},
|
|
"name": "A String", # 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}`.
|
|
"response": { # 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`.
|
|
"a_key": "", # Properties of the object. Contains field @type with type URL.
|
|
},
|
|
}</pre>
|
|
</div>
|
|
|
|
</body></html> |