docs: update generated docs (#1053)
Updates for both discovery docs and epydoc API Documentation
Fixes: #1049
diff --git a/docs/dyn/ml_v1.projects.locations.studies.trials.html b/docs/dyn/ml_v1.projects.locations.studies.trials.html
index f6c69d9..9e28f58 100644
--- a/docs/dyn/ml_v1.projects.locations.studies.trials.html
+++ b/docs/dyn/ml_v1.projects.locations.studies.trials.html
@@ -76,10 +76,13 @@
<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</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</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>
@@ -100,12 +103,11 @@
<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</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.
+ <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)
@@ -114,12 +116,9 @@
{ # 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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
@@ -137,19 +136,35 @@
An object of the form:
{ # A message representing a 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.
+ "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.
- "measurements": [ # A list of measurements that are strictly lexicographically
- # ordered by their induced tuples (steps, elapsed_time).
- # These are used for early stopping computations.
+ "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "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
+ },
+ ],
+ "finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ "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.
- "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
@@ -157,42 +172,13 @@
],
},
],
- "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
- "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
- "stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
- "parameter": "A String", # The name of the parameter.
- "floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
- },
- ],
"state": "A String", # The detailed state of a trial.
- "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.
- "value": 3.14, # Required. The value for this metric.
- "metric": "A String", # Required. Metric name.
- },
- ],
- },
- "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
- "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.
}</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.
+ <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)
@@ -210,52 +196,33 @@
Returns:
An object of the form:
- { # This resource represents a long-running operation that is the result of a
- # network API call.
- "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.
- # 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).
- "details": [ # A list of messages that carry the error details. There is a common set of
- # message types for APIs to use.
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "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.
+ },
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
- "message": "A String", # A developer-facing error message, which should be in English. Any
- # user-facing error message should be localized and sent in the
- # google.rpc.Status.details field, or localized by the client.
- "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "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.
},
- "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`.
+ "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.
},
- "metadata": { # Service-specific metadata associated with the operation. It typically
- # contains progress information and common metadata such as create time.
- # Some services might not provide such metadata. Any method that returns a
- # long-running operation should document the metadata type, if any.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "name": "A String", # The server-assigned name, which is only unique within the same service that
- # originally returns it. If you use the default HTTP mapping, the
- # `name` should be a resource name ending with `operations/{unique_id}`.
}</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.
@@ -265,25 +232,18 @@
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.
+ "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
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
},
],
},
+ "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.
@@ -295,19 +255,35 @@
An object of the form:
{ # A message representing a 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.
+ "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.
- "measurements": [ # A list of measurements that are strictly lexicographically
- # ordered by their induced tuples (steps, elapsed_time).
- # These are used for early stopping computations.
+ "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "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
+ },
+ ],
+ "finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ "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.
- "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
@@ -315,33 +291,7 @@
],
},
],
- "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
- "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
- "stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
- "parameter": "A String", # The name of the parameter.
- "floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
- },
- ],
"state": "A String", # The detailed state of a trial.
- "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.
- "value": 3.14, # Required. The value for this metric.
- "metric": "A String", # Required. Metric name.
- },
- ],
- },
- "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
- "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.
}</pre>
</div>
@@ -355,19 +305,35 @@
The object takes the form of:
{ # A message representing a 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.
+ "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.
- "measurements": [ # A list of measurements that are strictly lexicographically
- # ordered by their induced tuples (steps, elapsed_time).
- # These are used for early stopping computations.
+ "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "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
+ },
+ ],
+ "finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ "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.
- "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
@@ -375,33 +341,7 @@
],
},
],
- "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
- "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
- "stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
- "parameter": "A String", # The name of the parameter.
- "floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
- },
- ],
"state": "A String", # The detailed state of a trial.
- "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.
- "value": 3.14, # Required. The value for this metric.
- "metric": "A String", # Required. Metric name.
- },
- ],
- },
- "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
- "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.
}
x__xgafv: string, V1 error format.
@@ -413,19 +353,35 @@
An object of the form:
{ # A message representing a 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.
+ "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.
- "measurements": [ # A list of measurements that are strictly lexicographically
- # ordered by their induced tuples (steps, elapsed_time).
- # These are used for early stopping computations.
+ "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "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
+ },
+ ],
+ "finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ "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.
- "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
@@ -433,33 +389,7 @@
],
},
],
- "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
- "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
- "stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
- "parameter": "A String", # The name of the parameter.
- "floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
- },
- ],
"state": "A String", # The detailed state of a trial.
- "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.
- "value": 3.14, # Required. The value for this metric.
- "metric": "A String", # Required. Metric name.
- },
- ],
- },
- "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
- "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.
}</pre>
</div>
@@ -477,15 +407,7 @@
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 `{}`.
+ { # 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>
@@ -504,19 +426,35 @@
An object of the form:
{ # A message representing a 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.
+ "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.
- "measurements": [ # A list of measurements that are strictly lexicographically
- # ordered by their induced tuples (steps, elapsed_time).
- # These are used for early stopping computations.
+ "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "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
+ },
+ ],
+ "finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ "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.
- "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
@@ -524,33 +462,7 @@
],
},
],
- "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
- "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
- "stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
- "parameter": "A String", # The name of the parameter.
- "floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
- },
- ],
"state": "A String", # The detailed state of a trial.
- "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.
- "value": 3.14, # Required. The value for this metric.
- "metric": "A String", # Required. Metric name.
- },
- ],
- },
- "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
- "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.
}</pre>
</div>
@@ -571,19 +483,35 @@
{ # The response message for the ListTrials method.
"trials": [ # The trials associated with the study.
{ # A message representing a 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.
+ "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.
- "measurements": [ # A list of measurements that are strictly lexicographically
- # ordered by their induced tuples (steps, elapsed_time).
- # These are used for early stopping computations.
+ "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "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
+ },
+ ],
+ "finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ "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.
- "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
@@ -591,33 +519,7 @@
],
},
],
- "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
- "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
- "stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
- "parameter": "A String", # The name of the parameter.
- "floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
- },
- ],
"state": "A String", # The detailed state of a trial.
- "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.
- "value": 3.14, # Required. The value for this metric.
- "metric": "A String", # Required. Metric name.
- },
- ],
- },
- "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
- "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.
},
],
}</pre>
@@ -644,19 +546,35 @@
An object of the form:
{ # A message representing a 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.
+ "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.
- "measurements": [ # A list of measurements that are strictly lexicographically
- # ordered by their induced tuples (steps, elapsed_time).
- # These are used for early stopping computations.
+ "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
+ "startTime": "A String", # Output only. Time at which the trial was started.
+ "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.
+ "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
+ },
+ ],
+ "finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
+ { # A message representing a metric in the measurement.
+ "value": 3.14, # Required. The value for this metric.
+ "metric": "A String", # Required. Metric name.
+ },
+ ],
+ },
+ "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.
- "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.
+ "stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
+ "elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
+ "metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"value": 3.14, # Required. The value for this metric.
"metric": "A String", # Required. Metric name.
@@ -664,43 +582,13 @@
],
},
],
- "clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
- "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
- "stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
- "parameter": "A String", # The name of the parameter.
- "floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
- },
- ],
"state": "A String", # The detailed state of a trial.
- "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.
- "value": 3.14, # Required. The value for this metric.
- "metric": "A String", # Required. Metric name.
- },
- ],
- },
- "trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
- "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.
}</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 Optimizer. Returns a long-running
-operation associated with the generation of trial suggestions.
-When this long-running operation succeeds, it will contain
-a SuggestTrialsResponse.
+ <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)
@@ -708,11 +596,7 @@
The object takes the form of:
{ # The request message for the SuggestTrial service method.
- "clientId": "A String", # Required. The identifier of the client that is requesting the suggestion.
- #
- # If multiple SuggestTrialsRequests have the same `client_id`,
- # the service will return the identical suggested trial if the trial is
- # pending, and provide a new trial if the last suggested trial was completed.
+ "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.
}
@@ -724,48 +608,24 @@
Returns:
An object of the form:
- { # This resource represents a long-running operation that is the result of a
- # network API call.
- "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.
- # 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).
- "details": [ # A list of messages that carry the error details. There is a common set of
- # message types for APIs to use.
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "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.
+ },
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
- "message": "A String", # A developer-facing error message, which should be in English. Any
- # user-facing error message should be localized and sent in the
- # google.rpc.Status.details field, or localized by the client.
- "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "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.
},
- "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`.
+ "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.
},
- "metadata": { # Service-specific metadata associated with the operation. It typically
- # contains progress information and common metadata such as create time.
- # Some services might not provide such metadata. Any method that returns a
- # long-running operation should document the metadata type, if any.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "name": "A String", # The server-assigned name, which is only unique within the same service that
- # originally returns it. If you use the default HTTP mapping, the
- # `name` should be a resource name ending with `operations/{unique_id}`.
}</pre>
</div>