docs: update generated docs (#981)
diff --git a/docs/dyn/ml_v1.projects.locations.studies.html b/docs/dyn/ml_v1.projects.locations.studies.html
index 0044b90..290eef2 100644
--- a/docs/dyn/ml_v1.projects.locations.studies.html
+++ b/docs/dyn/ml_v1.projects.locations.studies.html
@@ -103,14 +103,20 @@
The object takes the form of:
{ # A message representing a Study.
+ "name": "A String", # Output only. The name of a study.
+ "state": "A String", # Output only. The detailed state of a study.
+ "createTime": "A String", # Output only. Time at which the study was created.
"inactiveReason": "A String", # Output only. A human readable reason why the Study is inactive.
# This should be empty if a study is ACTIVE or COMPLETED.
- "createTime": "A String", # Output only. Time at which the study was created.
- "state": "A String", # Output only. The detailed state of a study.
- "name": "A String", # Output only. The name of a study.
"studyConfig": { # Represents configuration of a study. # Required. Configuration of the study.
+ "algorithm": "A String", # The search algorithm specified for the study.
"automatedStoppingConfig": { # Configuration for Automated Early Stopping of Trials. If no # Configuration for automated stopping of unpromising Trials.
# implementation_config is set, automated early stopping will not be run.
+ "decayCurveStoppingConfig": {
+ "useElapsedTime": True or False, # If true, measurement.elapsed_time is used as the x-axis of each
+ # Trials Decay Curve. Otherwise, Measurement.steps will be used as the
+ # x-axis.
+ },
"medianAutomatedStoppingConfig": { # The median automated stopping rule stops a pending trial if the trial's
# best objective_value is strictly below the median 'performance' of all
# completed trials reported up to the trial's last measurement.
@@ -122,49 +128,16 @@
# latest measurement is used to compute the median objective
# value for each completed trial.
},
- "decayCurveStoppingConfig": {
- "useElapsedTime": True or False, # If true, measurement.elapsed_time is used as the x-axis of each
- # Trials Decay Curve. Otherwise, Measurement.steps will be used as the
- # x-axis.
- },
},
- "metrics": [ # Metric specs for the study.
- { # Represents a metric to optimize.
- "goal": "A String", # Required. The optimization goal of the metric.
- "metric": "A String", # Required. The name of the metric.
- },
- ],
- "algorithm": "A String", # The search algorithm specified for the study.
"parameters": [ # Required. The set of parameters to tune.
{ # Represents a single parameter to optimize.
- "type": "A String", # Required. The type of the parameter.
- "parentDiscreteValues": { # Represents the spec to match discrete values from parent parameter.
- "values": [ # Matches values of the parent parameter with type 'DISCRETE'.
- # All values must exist in `discrete_value_spec` of parent parameter.
- 3.14,
- ],
- },
- "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
- "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value of the parameter.
- "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
- },
- "integerValueSpec": { # The value spec for an 'INTEGER' parameter.
- "minValue": "A String", # Must be specified if type is `INTEGER`. Minimum value of the parameter.
- "maxValue": "A String", # Must be specified if type is `INTEGER`. Maximum value of the parameter.
- },
"categoricalValueSpec": { # The value spec for a 'CATEGORICAL' parameter.
"values": [ # Must be specified if type is `CATEGORICAL`.
# The list of possible categories.
"A String",
],
},
- "parentIntValues": { # Represents the spec to match integer values from parent parameter.
- "values": [ # Matches values of the parent parameter with type 'INTEGER'.
- # All values must lie in `integer_value_spec` of parent parameter.
- "A String",
- ],
- },
- "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
+ "type": "A String", # Required. The type of the parameter.
"childParameterSpecs": [ # A child node is active if the parameter's value matches the child node's
# matching_parent_values.
#
@@ -172,6 +145,19 @@
# disjoint matching_parent_values.
# Object with schema name: GoogleCloudMlV1_StudyConfig_ParameterSpec
],
+ "parentIntValues": { # Represents the spec to match integer values from parent parameter.
+ "values": [ # Matches values of the parent parameter with type 'INTEGER'.
+ # All values must lie in `integer_value_spec` of parent parameter.
+ "A String",
+ ],
+ },
+ "scaleType": "A String", # How the parameter should be scaled.
+ # Leave unset for categorical parameters.
+ "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
+ "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value of the parameter.
+ "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
+ },
+ "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
"discreteValueSpec": { # The value spec for a 'DISCRETE' parameter.
"values": [ # Must be specified if type is `DISCRETE`.
# A list of feasible points.
@@ -181,14 +167,28 @@
3.14,
],
},
+ "parentDiscreteValues": { # Represents the spec to match discrete values from parent parameter.
+ "values": [ # Matches values of the parent parameter with type 'DISCRETE'.
+ # All values must exist in `discrete_value_spec` of parent parameter.
+ 3.14,
+ ],
+ },
+ "integerValueSpec": { # The value spec for an 'INTEGER' parameter.
+ "maxValue": "A String", # Must be specified if type is `INTEGER`. Maximum value of the parameter.
+ "minValue": "A String", # Must be specified if type is `INTEGER`. Minimum value of the parameter.
+ },
"parentCategoricalValues": { # Represents the spec to match categorical values from parent parameter.
"values": [ # Matches values of the parent parameter with type 'CATEGORICAL'.
# All values must exist in `categorical_value_spec` of parent parameter.
"A String",
],
},
- "scaleType": "A String", # How the parameter should be scaled.
- # Leave unset for categorical parameters.
+ },
+ ],
+ "metrics": [ # Metric specs for the study.
+ { # Represents a metric to optimize.
+ "goal": "A String", # Required. The optimization goal of the metric.
+ "metric": "A String", # Required. The name of the metric.
},
],
},
@@ -205,14 +205,20 @@
An object of the form:
{ # A message representing a Study.
+ "name": "A String", # Output only. The name of a study.
+ "state": "A String", # Output only. The detailed state of a study.
+ "createTime": "A String", # Output only. Time at which the study was created.
"inactiveReason": "A String", # Output only. A human readable reason why the Study is inactive.
# This should be empty if a study is ACTIVE or COMPLETED.
- "createTime": "A String", # Output only. Time at which the study was created.
- "state": "A String", # Output only. The detailed state of a study.
- "name": "A String", # Output only. The name of a study.
"studyConfig": { # Represents configuration of a study. # Required. Configuration of the study.
+ "algorithm": "A String", # The search algorithm specified for the study.
"automatedStoppingConfig": { # Configuration for Automated Early Stopping of Trials. If no # Configuration for automated stopping of unpromising Trials.
# implementation_config is set, automated early stopping will not be run.
+ "decayCurveStoppingConfig": {
+ "useElapsedTime": True or False, # If true, measurement.elapsed_time is used as the x-axis of each
+ # Trials Decay Curve. Otherwise, Measurement.steps will be used as the
+ # x-axis.
+ },
"medianAutomatedStoppingConfig": { # The median automated stopping rule stops a pending trial if the trial's
# best objective_value is strictly below the median 'performance' of all
# completed trials reported up to the trial's last measurement.
@@ -224,49 +230,16 @@
# latest measurement is used to compute the median objective
# value for each completed trial.
},
- "decayCurveStoppingConfig": {
- "useElapsedTime": True or False, # If true, measurement.elapsed_time is used as the x-axis of each
- # Trials Decay Curve. Otherwise, Measurement.steps will be used as the
- # x-axis.
- },
},
- "metrics": [ # Metric specs for the study.
- { # Represents a metric to optimize.
- "goal": "A String", # Required. The optimization goal of the metric.
- "metric": "A String", # Required. The name of the metric.
- },
- ],
- "algorithm": "A String", # The search algorithm specified for the study.
"parameters": [ # Required. The set of parameters to tune.
{ # Represents a single parameter to optimize.
- "type": "A String", # Required. The type of the parameter.
- "parentDiscreteValues": { # Represents the spec to match discrete values from parent parameter.
- "values": [ # Matches values of the parent parameter with type 'DISCRETE'.
- # All values must exist in `discrete_value_spec` of parent parameter.
- 3.14,
- ],
- },
- "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
- "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value of the parameter.
- "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
- },
- "integerValueSpec": { # The value spec for an 'INTEGER' parameter.
- "minValue": "A String", # Must be specified if type is `INTEGER`. Minimum value of the parameter.
- "maxValue": "A String", # Must be specified if type is `INTEGER`. Maximum value of the parameter.
- },
"categoricalValueSpec": { # The value spec for a 'CATEGORICAL' parameter.
"values": [ # Must be specified if type is `CATEGORICAL`.
# The list of possible categories.
"A String",
],
},
- "parentIntValues": { # Represents the spec to match integer values from parent parameter.
- "values": [ # Matches values of the parent parameter with type 'INTEGER'.
- # All values must lie in `integer_value_spec` of parent parameter.
- "A String",
- ],
- },
- "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
+ "type": "A String", # Required. The type of the parameter.
"childParameterSpecs": [ # A child node is active if the parameter's value matches the child node's
# matching_parent_values.
#
@@ -274,6 +247,19 @@
# disjoint matching_parent_values.
# Object with schema name: GoogleCloudMlV1_StudyConfig_ParameterSpec
],
+ "parentIntValues": { # Represents the spec to match integer values from parent parameter.
+ "values": [ # Matches values of the parent parameter with type 'INTEGER'.
+ # All values must lie in `integer_value_spec` of parent parameter.
+ "A String",
+ ],
+ },
+ "scaleType": "A String", # How the parameter should be scaled.
+ # Leave unset for categorical parameters.
+ "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
+ "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value of the parameter.
+ "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
+ },
+ "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
"discreteValueSpec": { # The value spec for a 'DISCRETE' parameter.
"values": [ # Must be specified if type is `DISCRETE`.
# A list of feasible points.
@@ -283,14 +269,28 @@
3.14,
],
},
+ "parentDiscreteValues": { # Represents the spec to match discrete values from parent parameter.
+ "values": [ # Matches values of the parent parameter with type 'DISCRETE'.
+ # All values must exist in `discrete_value_spec` of parent parameter.
+ 3.14,
+ ],
+ },
+ "integerValueSpec": { # The value spec for an 'INTEGER' parameter.
+ "maxValue": "A String", # Must be specified if type is `INTEGER`. Maximum value of the parameter.
+ "minValue": "A String", # Must be specified if type is `INTEGER`. Minimum value of the parameter.
+ },
"parentCategoricalValues": { # Represents the spec to match categorical values from parent parameter.
"values": [ # Matches values of the parent parameter with type 'CATEGORICAL'.
# All values must exist in `categorical_value_spec` of parent parameter.
"A String",
],
},
- "scaleType": "A String", # How the parameter should be scaled.
- # Leave unset for categorical parameters.
+ },
+ ],
+ "metrics": [ # Metric specs for the study.
+ { # Represents a metric to optimize.
+ "goal": "A String", # Required. The optimization goal of the metric.
+ "metric": "A String", # Required. The name of the metric.
},
],
},
@@ -338,14 +338,20 @@
An object of the form:
{ # A message representing a Study.
+ "name": "A String", # Output only. The name of a study.
+ "state": "A String", # Output only. The detailed state of a study.
+ "createTime": "A String", # Output only. Time at which the study was created.
"inactiveReason": "A String", # Output only. A human readable reason why the Study is inactive.
# This should be empty if a study is ACTIVE or COMPLETED.
- "createTime": "A String", # Output only. Time at which the study was created.
- "state": "A String", # Output only. The detailed state of a study.
- "name": "A String", # Output only. The name of a study.
"studyConfig": { # Represents configuration of a study. # Required. Configuration of the study.
+ "algorithm": "A String", # The search algorithm specified for the study.
"automatedStoppingConfig": { # Configuration for Automated Early Stopping of Trials. If no # Configuration for automated stopping of unpromising Trials.
# implementation_config is set, automated early stopping will not be run.
+ "decayCurveStoppingConfig": {
+ "useElapsedTime": True or False, # If true, measurement.elapsed_time is used as the x-axis of each
+ # Trials Decay Curve. Otherwise, Measurement.steps will be used as the
+ # x-axis.
+ },
"medianAutomatedStoppingConfig": { # The median automated stopping rule stops a pending trial if the trial's
# best objective_value is strictly below the median 'performance' of all
# completed trials reported up to the trial's last measurement.
@@ -357,49 +363,16 @@
# latest measurement is used to compute the median objective
# value for each completed trial.
},
- "decayCurveStoppingConfig": {
- "useElapsedTime": True or False, # If true, measurement.elapsed_time is used as the x-axis of each
- # Trials Decay Curve. Otherwise, Measurement.steps will be used as the
- # x-axis.
- },
},
- "metrics": [ # Metric specs for the study.
- { # Represents a metric to optimize.
- "goal": "A String", # Required. The optimization goal of the metric.
- "metric": "A String", # Required. The name of the metric.
- },
- ],
- "algorithm": "A String", # The search algorithm specified for the study.
"parameters": [ # Required. The set of parameters to tune.
{ # Represents a single parameter to optimize.
- "type": "A String", # Required. The type of the parameter.
- "parentDiscreteValues": { # Represents the spec to match discrete values from parent parameter.
- "values": [ # Matches values of the parent parameter with type 'DISCRETE'.
- # All values must exist in `discrete_value_spec` of parent parameter.
- 3.14,
- ],
- },
- "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
- "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value of the parameter.
- "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
- },
- "integerValueSpec": { # The value spec for an 'INTEGER' parameter.
- "minValue": "A String", # Must be specified if type is `INTEGER`. Minimum value of the parameter.
- "maxValue": "A String", # Must be specified if type is `INTEGER`. Maximum value of the parameter.
- },
"categoricalValueSpec": { # The value spec for a 'CATEGORICAL' parameter.
"values": [ # Must be specified if type is `CATEGORICAL`.
# The list of possible categories.
"A String",
],
},
- "parentIntValues": { # Represents the spec to match integer values from parent parameter.
- "values": [ # Matches values of the parent parameter with type 'INTEGER'.
- # All values must lie in `integer_value_spec` of parent parameter.
- "A String",
- ],
- },
- "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
+ "type": "A String", # Required. The type of the parameter.
"childParameterSpecs": [ # A child node is active if the parameter's value matches the child node's
# matching_parent_values.
#
@@ -407,6 +380,19 @@
# disjoint matching_parent_values.
# Object with schema name: GoogleCloudMlV1_StudyConfig_ParameterSpec
],
+ "parentIntValues": { # Represents the spec to match integer values from parent parameter.
+ "values": [ # Matches values of the parent parameter with type 'INTEGER'.
+ # All values must lie in `integer_value_spec` of parent parameter.
+ "A String",
+ ],
+ },
+ "scaleType": "A String", # How the parameter should be scaled.
+ # Leave unset for categorical parameters.
+ "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
+ "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value of the parameter.
+ "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
+ },
+ "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
"discreteValueSpec": { # The value spec for a 'DISCRETE' parameter.
"values": [ # Must be specified if type is `DISCRETE`.
# A list of feasible points.
@@ -416,14 +402,28 @@
3.14,
],
},
+ "parentDiscreteValues": { # Represents the spec to match discrete values from parent parameter.
+ "values": [ # Matches values of the parent parameter with type 'DISCRETE'.
+ # All values must exist in `discrete_value_spec` of parent parameter.
+ 3.14,
+ ],
+ },
+ "integerValueSpec": { # The value spec for an 'INTEGER' parameter.
+ "maxValue": "A String", # Must be specified if type is `INTEGER`. Maximum value of the parameter.
+ "minValue": "A String", # Must be specified if type is `INTEGER`. Minimum value of the parameter.
+ },
"parentCategoricalValues": { # Represents the spec to match categorical values from parent parameter.
"values": [ # Matches values of the parent parameter with type 'CATEGORICAL'.
# All values must exist in `categorical_value_spec` of parent parameter.
"A String",
],
},
- "scaleType": "A String", # How the parameter should be scaled.
- # Leave unset for categorical parameters.
+ },
+ ],
+ "metrics": [ # Metric specs for the study.
+ { # Represents a metric to optimize.
+ "goal": "A String", # Required. The optimization goal of the metric.
+ "metric": "A String", # Required. The name of the metric.
},
],
},
@@ -448,14 +448,20 @@
{
"studies": [ # The studies associated with the project.
{ # A message representing a Study.
+ "name": "A String", # Output only. The name of a study.
+ "state": "A String", # Output only. The detailed state of a study.
+ "createTime": "A String", # Output only. Time at which the study was created.
"inactiveReason": "A String", # Output only. A human readable reason why the Study is inactive.
# This should be empty if a study is ACTIVE or COMPLETED.
- "createTime": "A String", # Output only. Time at which the study was created.
- "state": "A String", # Output only. The detailed state of a study.
- "name": "A String", # Output only. The name of a study.
"studyConfig": { # Represents configuration of a study. # Required. Configuration of the study.
+ "algorithm": "A String", # The search algorithm specified for the study.
"automatedStoppingConfig": { # Configuration for Automated Early Stopping of Trials. If no # Configuration for automated stopping of unpromising Trials.
# implementation_config is set, automated early stopping will not be run.
+ "decayCurveStoppingConfig": {
+ "useElapsedTime": True or False, # If true, measurement.elapsed_time is used as the x-axis of each
+ # Trials Decay Curve. Otherwise, Measurement.steps will be used as the
+ # x-axis.
+ },
"medianAutomatedStoppingConfig": { # The median automated stopping rule stops a pending trial if the trial's
# best objective_value is strictly below the median 'performance' of all
# completed trials reported up to the trial's last measurement.
@@ -467,49 +473,16 @@
# latest measurement is used to compute the median objective
# value for each completed trial.
},
- "decayCurveStoppingConfig": {
- "useElapsedTime": True or False, # If true, measurement.elapsed_time is used as the x-axis of each
- # Trials Decay Curve. Otherwise, Measurement.steps will be used as the
- # x-axis.
- },
},
- "metrics": [ # Metric specs for the study.
- { # Represents a metric to optimize.
- "goal": "A String", # Required. The optimization goal of the metric.
- "metric": "A String", # Required. The name of the metric.
- },
- ],
- "algorithm": "A String", # The search algorithm specified for the study.
"parameters": [ # Required. The set of parameters to tune.
{ # Represents a single parameter to optimize.
- "type": "A String", # Required. The type of the parameter.
- "parentDiscreteValues": { # Represents the spec to match discrete values from parent parameter.
- "values": [ # Matches values of the parent parameter with type 'DISCRETE'.
- # All values must exist in `discrete_value_spec` of parent parameter.
- 3.14,
- ],
- },
- "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
- "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value of the parameter.
- "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
- },
- "integerValueSpec": { # The value spec for an 'INTEGER' parameter.
- "minValue": "A String", # Must be specified if type is `INTEGER`. Minimum value of the parameter.
- "maxValue": "A String", # Must be specified if type is `INTEGER`. Maximum value of the parameter.
- },
"categoricalValueSpec": { # The value spec for a 'CATEGORICAL' parameter.
"values": [ # Must be specified if type is `CATEGORICAL`.
# The list of possible categories.
"A String",
],
},
- "parentIntValues": { # Represents the spec to match integer values from parent parameter.
- "values": [ # Matches values of the parent parameter with type 'INTEGER'.
- # All values must lie in `integer_value_spec` of parent parameter.
- "A String",
- ],
- },
- "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
+ "type": "A String", # Required. The type of the parameter.
"childParameterSpecs": [ # A child node is active if the parameter's value matches the child node's
# matching_parent_values.
#
@@ -517,6 +490,19 @@
# disjoint matching_parent_values.
# Object with schema name: GoogleCloudMlV1_StudyConfig_ParameterSpec
],
+ "parentIntValues": { # Represents the spec to match integer values from parent parameter.
+ "values": [ # Matches values of the parent parameter with type 'INTEGER'.
+ # All values must lie in `integer_value_spec` of parent parameter.
+ "A String",
+ ],
+ },
+ "scaleType": "A String", # How the parameter should be scaled.
+ # Leave unset for categorical parameters.
+ "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
+ "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value of the parameter.
+ "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
+ },
+ "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
"discreteValueSpec": { # The value spec for a 'DISCRETE' parameter.
"values": [ # Must be specified if type is `DISCRETE`.
# A list of feasible points.
@@ -526,14 +512,28 @@
3.14,
],
},
+ "parentDiscreteValues": { # Represents the spec to match discrete values from parent parameter.
+ "values": [ # Matches values of the parent parameter with type 'DISCRETE'.
+ # All values must exist in `discrete_value_spec` of parent parameter.
+ 3.14,
+ ],
+ },
+ "integerValueSpec": { # The value spec for an 'INTEGER' parameter.
+ "maxValue": "A String", # Must be specified if type is `INTEGER`. Maximum value of the parameter.
+ "minValue": "A String", # Must be specified if type is `INTEGER`. Minimum value of the parameter.
+ },
"parentCategoricalValues": { # Represents the spec to match categorical values from parent parameter.
"values": [ # Matches values of the parent parameter with type 'CATEGORICAL'.
# All values must exist in `categorical_value_spec` of parent parameter.
"A String",
],
},
- "scaleType": "A String", # How the parameter should be scaled.
- # Leave unset for categorical parameters.
+ },
+ ],
+ "metrics": [ # Metric specs for the study.
+ { # Represents a metric to optimize.
+ "goal": "A String", # Required. The optimization goal of the metric.
+ "metric": "A String", # Required. The name of the metric.
},
],
},