Blame - docs/dyn/ml_v1.projects.locations.studies.trials.html - platform/external/python/google-api-python-client

<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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<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</p>

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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</p>

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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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<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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<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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<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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<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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<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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<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</p>

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<h3>Method Details</h3>

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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

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is assumed to have been taken before the trial is complete.

Args:

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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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

# this measurement.

},

}

x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

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{ # A message representing a trial.

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"startTime": "A String", # Output only. Time at which the trial was started.

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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

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# this measurement.

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},

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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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"state": "A String", # The detailed state of a trial.

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"measurements": [ # A list of measurements that are strictly lexicographically

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# ordered by their induced tuples (steps, elapsed_time).

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# These are used for early stopping computations.

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{ # A message representing a measurement.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

# this measurement.

},

],

"parameters": [ # The parameters of the trial.

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{ # A message representing a parameter to be tuned. Contains the name of

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# the parameter and the suggested value to use for this trial.

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"parameter": "A String", # The name of the parameter.

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"intValue": "A String", # Must be set if ParameterType is INTEGER

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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.

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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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"name": "A String", # Output only. Name of the trial assigned by the service.

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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.

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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is

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# infeasible. This should only be set if trial_infeasible is true.

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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.

}</pre>

</div>

<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

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long-running operation. When the operation is successful,

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it will contain a

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CheckTrialEarlyStoppingStateResponse.

Args:

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.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

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{ # This resource represents a long-running operation that is the result of a

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# network API call.

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"response": { # The normal response of the operation in case of success. If the original

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# method returns no data on success, such as `Delete`, the response is

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# `google.protobuf.Empty`. If the original method is standard

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# `Get`/`Create`/`Update`, the response should be the resource. For other

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# methods, the response should have the type `XxxResponse`, where `Xxx`

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# is the original method name. For example, if the original method name

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# is `TakeSnapshot()`, the inferred response type is

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# `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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"name": "A String", # The server-assigned name, which is only unique within the same service that

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# originally returns it. If you use the default HTTP mapping, the

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# `name` should be a resource name ending with `operations/{unique_id}`.

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"error": { # The `Status` type defines a logical error model that is suitable for # The error result of the operation in case of failure or cancellation.

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# different programming environments, including REST APIs and RPC APIs. It is

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# used by [gRPC](https://github.com/grpc). Each `Status` message contains

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# three pieces of data: error code, error message, and error details.

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#

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# You can find out more about this error model and how to work with it in the

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# [API Design Guide](https://cloud.google.com/apis/design/errors).

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"details": [ # A list of messages that carry the error details. There is a common set of

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# 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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"code": 42, # The status code, which should be an enum value of google.rpc.Code.

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"message": "A String", # A developer-facing error message, which should be in English. Any

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# user-facing error message should be localized and sent in the

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# 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

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# contains progress information and common metadata such as create time.

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# Some services might not provide such metadata. Any method that returns a

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# 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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"done": True or False, # If the value is `false`, it means the operation is still in progress.

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# If `true`, the operation is completed, and either `error` or `response` is

# available.

}</pre>

</div>

<code class="details" id="complete">complete(name, body=None, x__xgafv=None)</code>

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<pre>Marks a trial as complete.

Args:

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

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# final_measurement; Otherwise, the service will auto-select a

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# previously reported measurement as the final-measurement

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

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# this measurement.

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},

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"infeasibleReason": "A String", # Optional. A human readable reason why the trial was infeasible. This should

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# 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

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# final_measurement will be ignored.

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}

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x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

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{ # A message representing a trial.

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"startTime": "A String", # Output only. Time at which the trial was started.

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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

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# this measurement.

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},

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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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"state": "A String", # The detailed state of a trial.

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"measurements": [ # A list of measurements that are strictly lexicographically

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# ordered by their induced tuples (steps, elapsed_time).

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# These are used for early stopping computations.

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{ # A message representing a measurement.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

# this measurement.

},

],

"parameters": [ # The parameters of the trial.

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{ # A message representing a parameter to be tuned. Contains the name of

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# the parameter and the suggested value to use for this trial.

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"parameter": "A String", # The name of the parameter.

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"intValue": "A String", # Must be set if ParameterType is INTEGER

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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.

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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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"name": "A String", # Output only. Name of the trial assigned by the service.

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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.

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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is

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# infeasible. This should only be set if trial_infeasible is true.

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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.

}</pre>

</div>

<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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"startTime": "A String", # Output only. Time at which the trial was started.

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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

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# this measurement.

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},

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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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"state": "A String", # The detailed state of a trial.

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"measurements": [ # A list of measurements that are strictly lexicographically

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# ordered by their induced tuples (steps, elapsed_time).

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# These are used for early stopping computations.

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{ # A message representing a measurement.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

# this measurement.

},

],

"parameters": [ # The parameters of the trial.

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{ # A message representing a parameter to be tuned. Contains the name of

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# the parameter and the suggested value to use for this trial.

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"parameter": "A String", # The name of the parameter.

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"intValue": "A String", # Must be set if ParameterType is INTEGER

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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.

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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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"name": "A String", # Output only. Name of the trial assigned by the service.

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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.

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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is

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# infeasible. This should only be set if trial_infeasible is true.

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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.

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}

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x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

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{ # A message representing a trial.

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"startTime": "A String", # Output only. Time at which the trial was started.

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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

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# this measurement.

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},

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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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"state": "A String", # The detailed state of a trial.

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"measurements": [ # A list of measurements that are strictly lexicographically

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# ordered by their induced tuples (steps, elapsed_time).

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# These are used for early stopping computations.

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{ # A message representing a measurement.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

# this measurement.

},

],

"parameters": [ # The parameters of the trial.

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{ # A message representing a parameter to be tuned. Contains the name of

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# the parameter and the suggested value to use for this trial.

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"parameter": "A String", # The name of the parameter.

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"intValue": "A String", # Must be set if ParameterType is INTEGER

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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.

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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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"name": "A String", # Output only. Name of the trial assigned by the service.

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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.

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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is

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# infeasible. This should only be set if trial_infeasible is true.

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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.

}</pre>

</div>

<code class="details" id="delete">delete(name, x__xgafv=None)</code>

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<pre>Deletes a trial.

Args:

x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

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{ # A generic empty message that you can re-use to avoid defining duplicated

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# empty messages in your APIs. A typical example is to use it as the request

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# or the response type of an API method. For instance:

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#

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# service Foo {

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# rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);

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# }

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#

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# The JSON representation for `Empty` is empty JSON object `{}`.

}</pre>

</div>

<code class="details" id="get">get(name, x__xgafv=None)</code>

<pre>Gets a trial.

Args:

x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

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{ # A message representing a trial.

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"startTime": "A String", # Output only. Time at which the trial was started.

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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

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"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

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# this measurement.

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},

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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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"state": "A String", # The detailed state of a trial.

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"measurements": [ # A list of measurements that are strictly lexicographically

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# ordered by their induced tuples (steps, elapsed_time).

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# These are used for early stopping computations.

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{ # A message representing a measurement.

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"metrics": [ # Provides a list of metrics that act as inputs into the objective

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# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

531

"metric": "A String", # Required. Metric name.

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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.

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# Must be non-negative.

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"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

# this measurement.

},

],

"parameters": [ # The parameters of the trial.

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{ # A message representing a parameter to be tuned. Contains the name of

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# the parameter and the suggested value to use for this trial.

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"parameter": "A String", # The name of the parameter.

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"intValue": "A String", # Must be set if ParameterType is INTEGER

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"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.

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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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"name": "A String", # Output only. Name of the trial assigned by the service.

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"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.

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"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is

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# infeasible. This should only be set if trial_infeasible is true.

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"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.

}</pre>

</div>

<code class="details" id="list">list(parent, x__xgafv=None)</code>

559

<pre>Lists the trials associated with 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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x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

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{ # The response message for the ListTrials method.

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"trials": [ # The trials associated with the study.

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{ # A message representing a trial.

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"startTime": "A String", # Output only. Time at which the trial was started.

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"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.

576

"metrics": [ # Provides a list of metrics that act as inputs into the objective

577

# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

580

"metric": "A String", # Required. Metric name.

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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.

584

# Must be non-negative.

585

"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

586

# this measurement.

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},

588

"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.

589

"state": "A String", # The detailed state of a trial.

590

"measurements": [ # A list of measurements that are strictly lexicographically

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# ordered by their induced tuples (steps, elapsed_time).

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# These are used for early stopping computations.

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{ # A message representing a measurement.

594

"metrics": [ # Provides a list of metrics that act as inputs into the objective

595

# function.

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{ # A message representing a metric in the measurement.

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"value": 3.14, # Required. The value for this metric.

598

"metric": "A String", # Required. Metric name.

599

},

600

],

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"stepCount": "A String", # The number of steps a machine learning model has been trained for.

602

# Must be non-negative.

603

"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

# this measurement.

},

],

"parameters": [ # The parameters of the trial.

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{ # A message representing a parameter to be tuned. Contains the name of

609

# the parameter and the suggested value to use for this trial.

610

"parameter": "A String", # The name of the parameter.

611

"intValue": "A String", # Must be set if ParameterType is INTEGER

612

"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.

613

"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL

614

},

615

],

616

"name": "A String", # Output only. Name of the trial assigned by the service.

617

"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.

618

"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is

619

# infeasible. This should only be set if trial_infeasible is true.

620

"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.

},

],

}</pre>

</div>

<code class="details" id="stop">stop(name, body=None, x__xgafv=None)</code>

<pre>Stops a trial.

Args:

body: object, The request body.

633

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:

645

646

{ # A message representing a trial.

647

"startTime": "A String", # Output only. Time at which the trial was started.

648

"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.

649

"metrics": [ # Provides a list of metrics that act as inputs into the objective

650

# function.

651

{ # A message representing a metric in the measurement.

652

"value": 3.14, # Required. The value for this metric.

653

"metric": "A String", # Required. Metric name.

654

},

655

],

656

"stepCount": "A String", # The number of steps a machine learning model has been trained for.

657

# Must be non-negative.

658

"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

659

# this measurement.

660

},

661

"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.

662

"state": "A String", # The detailed state of a trial.

663

"measurements": [ # A list of measurements that are strictly lexicographically

664

# ordered by their induced tuples (steps, elapsed_time).

665

# These are used for early stopping computations.

666

{ # A message representing a measurement.

667

"metrics": [ # Provides a list of metrics that act as inputs into the objective

668

# function.

669

{ # A message representing a metric in the measurement.

670

"value": 3.14, # Required. The value for this metric.

671

"metric": "A String", # Required. Metric name.

672

},

673

],

674

"stepCount": "A String", # The number of steps a machine learning model has been trained for.

675

# Must be non-negative.

676

"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of

# this measurement.

},

],

"parameters": [ # The parameters of the trial.

681

{ # A message representing a parameter to be tuned. Contains the name of

682

# the parameter and the suggested value to use for this trial.

683

"parameter": "A String", # The name of the parameter.

684

"intValue": "A String", # Must be set if ParameterType is INTEGER

685

"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.

686

"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL

687

},

688

],

689

"name": "A String", # Output only. Name of the trial assigned by the service.

690

"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.

691

"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is

692

# infeasible. This should only be set if trial_infeasible is true.

693

"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.

}</pre>

</div>

<code class="details" id="suggest">suggest(parent, body=None, x__xgafv=None)</code>

699

<pre>Adds one or more trials to a study, with parameter values

700

suggested by AI Platform Optimizer. Returns a long-running

701

operation associated with the generation of trial suggestions.

702

When this long-running operation succeeds, it will contain

703

a SuggestTrialsResponse.

704

705

Args:

706

parent: string, Required. The name of the study that the trial belongs to. (required)

707

body: object, The request body.

708

The object takes the form of:

709

710

{ # The request message for the SuggestTrial service method.

711

"clientId": "A String", # Required. The identifier of the client that is requesting the suggestion.

712

#

713

# If multiple SuggestTrialsRequests have the same `client_id`,

714

# the service will return the identical suggested trial if the trial is

715

# pending, and provide a new trial if the last suggested trial was completed.

716

"suggestionCount": 42, # Required. The number of suggestions requested.

717

}

718

719

x__xgafv: string, V1 error format.

Allowed values

1 - v1 error format

2 - v2 error format

Returns:

An object of the form:

726

727

{ # This resource represents a long-running operation that is the result of a

728

# network API call.

729

"response": { # The normal response of the operation in case of success. If the original

730

# method returns no data on success, such as `Delete`, the response is

731

# `google.protobuf.Empty`. If the original method is standard

732

# `Get`/`Create`/`Update`, the response should be the resource. For other

733

# methods, the response should have the type `XxxResponse`, where `Xxx`

734

# is the original method name. For example, if the original method name

735

# is `TakeSnapshot()`, the inferred response type is

736

# `TakeSnapshotResponse`.

737

"a_key": "", # Properties of the object. Contains field @type with type URL.

738

},

739

"name": "A String", # The server-assigned name, which is only unique within the same service that

740

# originally returns it. If you use the default HTTP mapping, the

741

# `name` should be a resource name ending with `operations/{unique_id}`.

742

"error": { # The `Status` type defines a logical error model that is suitable for # The error result of the operation in case of failure or cancellation.

743

# different programming environments, including REST APIs and RPC APIs. It is

744

# used by [gRPC](https://github.com/grpc). Each `Status` message contains

745

# three pieces of data: error code, error message, and error details.

746

#

747

# You can find out more about this error model and how to work with it in the

748

# [API Design Guide](https://cloud.google.com/apis/design/errors).