docs: update docs/dyn (#1096)
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diff --git a/docs/dyn/ml_v1.projects.locations.studies.trials.html b/docs/dyn/ml_v1.projects.locations.studies.trials.html
index 933756d..1909207 100644
--- a/docs/dyn/ml_v1.projects.locations.studies.trials.html
+++ b/docs/dyn/ml_v1.projects.locations.studies.trials.html
@@ -119,14 +119,14 @@
{ # The request message for the AddTrialMeasurement service method.
"measurement": { # A message representing a measurement. # Required. The measurement to be added to a trial.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
}
@@ -139,42 +139,42 @@
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.
- "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.
- "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
- "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.
- },
- ],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
- },
- ],
- "startTime": "A String", # Output only. Time at which the trial was started.
- "name": "A String", # Output only. Name of the trial assigned by the service.
"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.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ ],
+ "name": "A String", # Output only. Name of the trial assigned by the service.
+ "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"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.
- "intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
+ "intValue": "A String", # Must be set if ParameterType is INTEGER
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
+ "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.
"state": "A String", # The detailed state of a trial.
- "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
+ "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
@@ -200,23 +200,23 @@
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.
"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.
+ "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.
},
],
- "code": 42, # The status code, which should be an enum value of google.rpc.Code.
- },
- "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.
},
"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.
},
- "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.
+ "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.
+ },
+ "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}`.
}</pre>
</div>
@@ -235,18 +235,18 @@
The object takes the form of:
{ # The request message for the CompleteTrial service method.
- "infeasibleReason": "A String", # Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true.
"trialInfeasible": True or False, # Optional. True if the trial cannot be run with the given Parameter, and final_measurement will be ignored.
"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
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "infeasibleReason": "A String", # Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true.
}
x__xgafv: string, V1 error format.
@@ -258,42 +258,42 @@
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.
- "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.
- "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
- "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.
- },
- ],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
- },
- ],
- "startTime": "A String", # Output only. Time at which the trial was started.
- "name": "A String", # Output only. Name of the trial assigned by the service.
"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.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ ],
+ "name": "A String", # Output only. Name of the trial assigned by the service.
+ "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"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.
- "intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
+ "intValue": "A String", # Must be set if ParameterType is INTEGER
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
+ "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.
"state": "A String", # The detailed state of a trial.
- "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
+ "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
@@ -308,42 +308,42 @@
The object takes the form of:
{ # A message representing a trial.
- "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
- "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.
- "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
- "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.
- },
- ],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
- },
- ],
- "startTime": "A String", # Output only. Time at which the trial was started.
- "name": "A String", # Output only. Name of the trial assigned by the service.
"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.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ ],
+ "name": "A String", # Output only. Name of the trial assigned by the service.
+ "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"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.
- "intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
+ "intValue": "A String", # Must be set if ParameterType is INTEGER
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
+ "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.
"state": "A String", # The detailed state of a trial.
- "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
+ "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}
@@ -356,42 +356,42 @@
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.
- "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.
- "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
- "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.
- },
- ],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
- },
- ],
- "startTime": "A String", # Output only. Time at which the trial was started.
- "name": "A String", # Output only. Name of the trial assigned by the service.
"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.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ ],
+ "name": "A String", # Output only. Name of the trial assigned by the service.
+ "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"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.
- "intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
+ "intValue": "A String", # Must be set if ParameterType is INTEGER
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
+ "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.
"state": "A String", # The detailed state of a trial.
- "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
+ "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
@@ -429,42 +429,42 @@
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.
- "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.
- "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
- "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.
- },
- ],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
- },
- ],
- "startTime": "A String", # Output only. Time at which the trial was started.
- "name": "A String", # Output only. Name of the trial assigned by the service.
"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.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ ],
+ "name": "A String", # Output only. Name of the trial assigned by the service.
+ "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"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.
- "intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
+ "intValue": "A String", # Must be set if ParameterType is INTEGER
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
+ "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.
"state": "A String", # The detailed state of a trial.
- "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
+ "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
@@ -486,42 +486,42 @@
{ # 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.
- "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.
- "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
- "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.
- },
- ],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
- },
- ],
- "startTime": "A String", # Output only. Time at which the trial was started.
- "name": "A String", # Output only. Name of the trial assigned by the service.
"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.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ ],
+ "name": "A String", # Output only. Name of the trial assigned by the service.
+ "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"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.
- "intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
+ "intValue": "A String", # Must be set if ParameterType is INTEGER
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
+ "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.
"state": "A String", # The detailed state of a trial.
- "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
+ "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
},
],
@@ -551,42 +551,42 @@
{ # 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.
- "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.
- "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
- "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.
- },
- ],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
- },
- ],
- "startTime": "A String", # Output only. Time at which the trial was started.
- "name": "A String", # Output only. Name of the trial assigned by the service.
"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.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ ],
+ "name": "A String", # Output only. Name of the trial assigned by the service.
+ "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"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.
- "intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
+ "intValue": "A String", # Must be set if ParameterType is INTEGER
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
+ "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.
"state": "A String", # The detailed state of a trial.
- "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
+ "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
},
],
@@ -614,42 +614,42 @@
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.
- "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.
- "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
- "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.
- },
- ],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
- },
- ],
- "startTime": "A String", # Output only. Time at which the trial was started.
- "name": "A String", # Output only. Name of the trial assigned by the service.
"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.
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
"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.
+ "metric": "A String", # Required. Metric name.
},
],
- "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
},
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ ],
+ "name": "A String", # Output only. Name of the trial assigned by the service.
+ "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"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.
- "intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
+ "intValue": "A String", # Must be set if ParameterType is INTEGER
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
+ "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.
"state": "A String", # The detailed state of a trial.
- "endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
+ "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
@@ -664,8 +664,8 @@
The object takes the form of:
{ # The request message for the SuggestTrial service method.
- "suggestionCount": 42, # Required. The number of suggestions requested.
"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.
@@ -677,23 +677,23 @@
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.
"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.
+ "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.
},
],
- "code": 42, # The status code, which should be an enum value of google.rpc.Code.
- },
- "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.
},
"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.
},
- "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.
+ "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.
+ },
+ "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}`.
}</pre>
</div>