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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>
<h2>Instance Methods</h2>
<p class="toc_element">
  <code><a href="#addMeasurement">addMeasurement(name, body=None, x__xgafv=None)</a></code></p>
<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>
<p class="toc_element">
  <code><a href="#checkEarlyStoppingState">checkEarlyStoppingState(name, body=None, x__xgafv=None)</a></code></p>
<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>
<p class="toc_element">
  <code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
  <code><a href="#complete">complete(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Marks a trial as complete.</p>
<p class="toc_element">
  <code><a href="#create">create(parent, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Adds a user provided trial to a study.</p>
<p class="toc_element">
  <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes a trial.</p>
<p class="toc_element">
  <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Gets a trial.</p>
<p class="toc_element">
  <code><a href="#list">list(parent, x__xgafv=None)</a></code></p>
<p class="firstline">Lists the trials associated with a study.</p>
<p class="toc_element">
  <code><a href="#listOptimalTrials">listOptimalTrials(parent, body=None, x__xgafv=None)</a></code></p>
<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>
<p class="toc_element">
  <code><a href="#stop">stop(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Stops a trial.</p>
<p class="toc_element">
  <code><a href="#suggest">suggest(parent, body=None, x__xgafv=None)</a></code></p>
<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>
<h3>Method Details</h3>
<div class="method">
    <code class="details" id="addMeasurement">addMeasurement(name, body=None, x__xgafv=None)</code>
  <pre>Adds a measurement of the objective metrics to a trial. This measurement is assumed to have been taken before the trial is complete.

Args:
  name: string, Required. The trial name. (required)
  body: object, The request body.
    The object takes the form of:

{ # The request message for the AddTrialMeasurement service method.
  &quot;measurement&quot;: { # A message representing a measurement. # Required. The measurement to be added to a trial.
    &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
    &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
      { # A message representing a metric in the measurement.
        &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
        &quot;value&quot;: 3.14, # Required. The value for this metric.
      },
    ],
    &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
  },
}

  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.
  &quot;clientId&quot;: &quot;A String&quot;, # Output only. The identifier of the client that originally requested this trial.
  &quot;endTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial&#x27;s status changed to COMPLETED.
  &quot;finalMeasurement&quot;: { # A message representing a measurement. # The final measurement containing the objective value.
    &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
    &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
      { # A message representing a metric in the measurement.
        &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
        &quot;value&quot;: 3.14, # Required. The value for this metric.
      },
    ],
    &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
  },
  &quot;infeasibleReason&quot;: &quot;A String&quot;, # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
  &quot;measurements&quot;: [ # 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.
      &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
      &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
        { # A message representing a metric in the measurement.
          &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
          &quot;value&quot;: 3.14, # Required. The value for this metric.
        },
      ],
      &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
    },
  ],
  &quot;name&quot;: &quot;A String&quot;, # Output only. Name of the trial assigned by the service.
  &quot;parameters&quot;: [ # 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.
      &quot;floatValue&quot;: 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
      &quot;intValue&quot;: &quot;A String&quot;, # Must be set if ParameterType is INTEGER
      &quot;parameter&quot;: &quot;A String&quot;, # The name of the parameter.
      &quot;stringValue&quot;: &quot;A String&quot;, # Must be set if ParameterTypeis CATEGORICAL
    },
  ],
  &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial was started.
  &quot;state&quot;: &quot;A String&quot;, # The detailed state of a trial.
  &quot;trialInfeasible&quot;: 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="checkEarlyStoppingState">checkEarlyStoppingState(name, body=None, x__xgafv=None)</code>
  <pre>Checks whether a trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.

Args:
  name: string, Required. The trial name. (required)
  body: object, The request body.
    The object takes the form of:

{ # The request message for the CheckTrialEarlyStoppingState service method.
}

  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.
  &quot;done&quot;: 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.
  &quot;error&quot;: { # 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.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # 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.
  },
  &quot;metadata&quot;: { # 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.
    &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
  },
  &quot;name&quot;: &quot;A String&quot;, # 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}`.
  &quot;response&quot;: { # 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`.
    &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
  },
}</pre>
</div>

<div class="method">
    <code class="details" id="close">close()</code>
  <pre>Close httplib2 connections.</pre>
</div>

<div class="method">
    <code class="details" id="complete">complete(name, body=None, x__xgafv=None)</code>
  <pre>Marks a trial as complete.

Args:
  name: string, Required. The trial name.metat (required)
  body: object, The request body.
    The object takes the form of:

{ # The request message for the CompleteTrial service method.
  &quot;finalMeasurement&quot;: { # A message representing a measurement. # Optional. If provided, it will be used as the completed trial&#x27;s final_measurement; Otherwise, the service will auto-select a previously reported measurement as the final-measurement
    &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
    &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
      { # A message representing a metric in the measurement.
        &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
        &quot;value&quot;: 3.14, # Required. The value for this metric.
      },
    ],
    &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
  },
  &quot;infeasibleReason&quot;: &quot;A String&quot;, # Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true.
  &quot;trialInfeasible&quot;: True or False, # Optional. True if the trial cannot be run with the given Parameter, and final_measurement will be ignored.
}

  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.
  &quot;clientId&quot;: &quot;A String&quot;, # Output only. The identifier of the client that originally requested this trial.
  &quot;endTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial&#x27;s status changed to COMPLETED.
  &quot;finalMeasurement&quot;: { # A message representing a measurement. # The final measurement containing the objective value.
    &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
    &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
      { # A message representing a metric in the measurement.
        &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
        &quot;value&quot;: 3.14, # Required. The value for this metric.
      },
    ],
    &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
  },
  &quot;infeasibleReason&quot;: &quot;A String&quot;, # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
  &quot;measurements&quot;: [ # 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.
      &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
      &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
        { # A message representing a metric in the measurement.
          &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
          &quot;value&quot;: 3.14, # Required. The value for this metric.
        },
      ],
      &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
    },
  ],
  &quot;name&quot;: &quot;A String&quot;, # Output only. Name of the trial assigned by the service.
  &quot;parameters&quot;: [ # 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.
      &quot;floatValue&quot;: 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
      &quot;intValue&quot;: &quot;A String&quot;, # Must be set if ParameterType is INTEGER
      &quot;parameter&quot;: &quot;A String&quot;, # The name of the parameter.
      &quot;stringValue&quot;: &quot;A String&quot;, # Must be set if ParameterTypeis CATEGORICAL
    },
  ],
  &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial was started.
  &quot;state&quot;: &quot;A String&quot;, # The detailed state of a trial.
  &quot;trialInfeasible&quot;: 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="create">create(parent, body=None, x__xgafv=None)</code>
  <pre>Adds a user provided trial to a study.

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:

{ # A message representing a trial.
  &quot;clientId&quot;: &quot;A String&quot;, # Output only. The identifier of the client that originally requested this trial.
  &quot;endTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial&#x27;s status changed to COMPLETED.
  &quot;finalMeasurement&quot;: { # A message representing a measurement. # The final measurement containing the objective value.
    &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
    &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
      { # A message representing a metric in the measurement.
        &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
        &quot;value&quot;: 3.14, # Required. The value for this metric.
      },
    ],
    &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
  },
  &quot;infeasibleReason&quot;: &quot;A String&quot;, # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
  &quot;measurements&quot;: [ # 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.
      &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
      &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
        { # A message representing a metric in the measurement.
          &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
          &quot;value&quot;: 3.14, # Required. The value for this metric.
        },
      ],
      &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
    },
  ],
  &quot;name&quot;: &quot;A String&quot;, # Output only. Name of the trial assigned by the service.
  &quot;parameters&quot;: [ # 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.
      &quot;floatValue&quot;: 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
      &quot;intValue&quot;: &quot;A String&quot;, # Must be set if ParameterType is INTEGER
      &quot;parameter&quot;: &quot;A String&quot;, # The name of the parameter.
      &quot;stringValue&quot;: &quot;A String&quot;, # Must be set if ParameterTypeis CATEGORICAL
    },
  ],
  &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial was started.
  &quot;state&quot;: &quot;A String&quot;, # The detailed state of a trial.
  &quot;trialInfeasible&quot;: True or False, # Output only. If true, the parameters in this trial are not attempted again.
}

  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.
  &quot;clientId&quot;: &quot;A String&quot;, # Output only. The identifier of the client that originally requested this trial.
  &quot;endTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial&#x27;s status changed to COMPLETED.
  &quot;finalMeasurement&quot;: { # A message representing a measurement. # The final measurement containing the objective value.
    &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
    &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
      { # A message representing a metric in the measurement.
        &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
        &quot;value&quot;: 3.14, # Required. The value for this metric.
      },
    ],
    &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
  },
  &quot;infeasibleReason&quot;: &quot;A String&quot;, # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
  &quot;measurements&quot;: [ # 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.
      &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
      &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
        { # A message representing a metric in the measurement.
          &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
          &quot;value&quot;: 3.14, # Required. The value for this metric.
        },
      ],
      &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
    },
  ],
  &quot;name&quot;: &quot;A String&quot;, # Output only. Name of the trial assigned by the service.
  &quot;parameters&quot;: [ # 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.
      &quot;floatValue&quot;: 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
      &quot;intValue&quot;: &quot;A String&quot;, # Must be set if ParameterType is INTEGER
      &quot;parameter&quot;: &quot;A String&quot;, # The name of the parameter.
      &quot;stringValue&quot;: &quot;A String&quot;, # Must be set if ParameterTypeis CATEGORICAL
    },
  ],
  &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial was started.
  &quot;state&quot;: &quot;A String&quot;, # The detailed state of a trial.
  &quot;trialInfeasible&quot;: 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.
  &quot;clientId&quot;: &quot;A String&quot;, # Output only. The identifier of the client that originally requested this trial.
  &quot;endTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial&#x27;s status changed to COMPLETED.
  &quot;finalMeasurement&quot;: { # A message representing a measurement. # The final measurement containing the objective value.
    &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
    &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
      { # A message representing a metric in the measurement.
        &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
        &quot;value&quot;: 3.14, # Required. The value for this metric.
      },
    ],
    &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
  },
  &quot;infeasibleReason&quot;: &quot;A String&quot;, # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
  &quot;measurements&quot;: [ # 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.
      &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
      &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
        { # A message representing a metric in the measurement.
          &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
          &quot;value&quot;: 3.14, # Required. The value for this metric.
        },
      ],
      &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
    },
  ],
  &quot;name&quot;: &quot;A String&quot;, # Output only. Name of the trial assigned by the service.
  &quot;parameters&quot;: [ # 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.
      &quot;floatValue&quot;: 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
      &quot;intValue&quot;: &quot;A String&quot;, # Must be set if ParameterType is INTEGER
      &quot;parameter&quot;: &quot;A String&quot;, # The name of the parameter.
      &quot;stringValue&quot;: &quot;A String&quot;, # Must be set if ParameterTypeis CATEGORICAL
    },
  ],
  &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial was started.
  &quot;state&quot;: &quot;A String&quot;, # The detailed state of a trial.
  &quot;trialInfeasible&quot;: 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.
  &quot;trials&quot;: [ # The trials associated with the study.
    { # A message representing a trial.
      &quot;clientId&quot;: &quot;A String&quot;, # Output only. The identifier of the client that originally requested this trial.
      &quot;endTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial&#x27;s status changed to COMPLETED.
      &quot;finalMeasurement&quot;: { # A message representing a measurement. # The final measurement containing the objective value.
        &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
        &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
          { # A message representing a metric in the measurement.
            &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
            &quot;value&quot;: 3.14, # Required. The value for this metric.
          },
        ],
        &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
      },
      &quot;infeasibleReason&quot;: &quot;A String&quot;, # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
      &quot;measurements&quot;: [ # 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.
          &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
          &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
            { # A message representing a metric in the measurement.
              &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
              &quot;value&quot;: 3.14, # Required. The value for this metric.
            },
          ],
          &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
        },
      ],
      &quot;name&quot;: &quot;A String&quot;, # Output only. Name of the trial assigned by the service.
      &quot;parameters&quot;: [ # 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.
          &quot;floatValue&quot;: 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
          &quot;intValue&quot;: &quot;A String&quot;, # Must be set if ParameterType is INTEGER
          &quot;parameter&quot;: &quot;A String&quot;, # The name of the parameter.
          &quot;stringValue&quot;: &quot;A String&quot;, # Must be set if ParameterTypeis CATEGORICAL
        },
      ],
      &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial was started.
      &quot;state&quot;: &quot;A String&quot;, # The detailed state of a trial.
      &quot;trialInfeasible&quot;: 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.
  &quot;trials&quot;: [ # 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.
      &quot;clientId&quot;: &quot;A String&quot;, # Output only. The identifier of the client that originally requested this trial.
      &quot;endTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial&#x27;s status changed to COMPLETED.
      &quot;finalMeasurement&quot;: { # A message representing a measurement. # The final measurement containing the objective value.
        &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
        &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
          { # A message representing a metric in the measurement.
            &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
            &quot;value&quot;: 3.14, # Required. The value for this metric.
          },
        ],
        &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
      },
      &quot;infeasibleReason&quot;: &quot;A String&quot;, # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
      &quot;measurements&quot;: [ # 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.
          &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
          &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
            { # A message representing a metric in the measurement.
              &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
              &quot;value&quot;: 3.14, # Required. The value for this metric.
            },
          ],
          &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
        },
      ],
      &quot;name&quot;: &quot;A String&quot;, # Output only. Name of the trial assigned by the service.
      &quot;parameters&quot;: [ # 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.
          &quot;floatValue&quot;: 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
          &quot;intValue&quot;: &quot;A String&quot;, # Must be set if ParameterType is INTEGER
          &quot;parameter&quot;: &quot;A String&quot;, # The name of the parameter.
          &quot;stringValue&quot;: &quot;A String&quot;, # Must be set if ParameterTypeis CATEGORICAL
        },
      ],
      &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial was started.
      &quot;state&quot;: &quot;A String&quot;, # The detailed state of a trial.
      &quot;trialInfeasible&quot;: 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.
  &quot;clientId&quot;: &quot;A String&quot;, # Output only. The identifier of the client that originally requested this trial.
  &quot;endTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial&#x27;s status changed to COMPLETED.
  &quot;finalMeasurement&quot;: { # A message representing a measurement. # The final measurement containing the objective value.
    &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
    &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
      { # A message representing a metric in the measurement.
        &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
        &quot;value&quot;: 3.14, # Required. The value for this metric.
      },
    ],
    &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
  },
  &quot;infeasibleReason&quot;: &quot;A String&quot;, # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
  &quot;measurements&quot;: [ # 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.
      &quot;elapsedTime&quot;: &quot;A String&quot;, # Output only. Time that the trial has been running at the point of this measurement.
      &quot;metrics&quot;: [ # Provides a list of metrics that act as inputs into the objective function.
        { # A message representing a metric in the measurement.
          &quot;metric&quot;: &quot;A String&quot;, # Required. Metric name.
          &quot;value&quot;: 3.14, # Required. The value for this metric.
        },
      ],
      &quot;stepCount&quot;: &quot;A String&quot;, # The number of steps a machine learning model has been trained for. Must be non-negative.
    },
  ],
  &quot;name&quot;: &quot;A String&quot;, # Output only. Name of the trial assigned by the service.
  &quot;parameters&quot;: [ # 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.
      &quot;floatValue&quot;: 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
      &quot;intValue&quot;: &quot;A String&quot;, # Must be set if ParameterType is INTEGER
      &quot;parameter&quot;: &quot;A String&quot;, # The name of the parameter.
      &quot;stringValue&quot;: &quot;A String&quot;, # Must be set if ParameterTypeis CATEGORICAL
    },
  ],
  &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time at which the trial was started.
  &quot;state&quot;: &quot;A String&quot;, # The detailed state of a trial.
  &quot;trialInfeasible&quot;: 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.
  &quot;clientId&quot;: &quot;A String&quot;, # 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.
  &quot;suggestionCount&quot;: 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.
  &quot;done&quot;: 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.
  &quot;error&quot;: { # 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.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # 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.
  },
  &quot;metadata&quot;: { # 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.
    &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
  },
  &quot;name&quot;: &quot;A String&quot;, # 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}`.
  &quot;response&quot;: { # 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`.
    &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
  },
}</pre>
</div>

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