docs: docs update (#911)
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Fixes #<issue_number_goes_here> 🦕
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+
+<h1><a href="ml_v1.html">AI Platform Training & Prediction API</a> . <a href="ml_v1.projects.html">projects</a> . <a href="ml_v1.projects.locations.html">locations</a> . <a href="ml_v1.projects.locations.studies.html">studies</a></h1>
+<h2>Instance Methods</h2>
+<p class="toc_element">
+ <code><a href="ml_v1.projects.locations.studies.trials.html">trials()</a></code>
+</p>
+<p class="firstline">Returns the trials Resource.</p>
+
+<p class="toc_element">
+ <code><a href="#create">create(parent, body=None, studyId=None, x__xgafv=None)</a></code></p>
+<p class="firstline">Creates a study.</p>
+<p class="toc_element">
+ <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
+<p class="firstline">Deletes a study.</p>
+<p class="toc_element">
+ <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
+<p class="firstline">Gets a study.</p>
+<p class="toc_element">
+ <code><a href="#list">list(parent, x__xgafv=None)</a></code></p>
+<p class="firstline">Lists all the studies in a region for an associated project.</p>
+<h3>Method Details</h3>
+<div class="method">
+ <code class="details" id="create">create(parent, body=None, studyId=None, x__xgafv=None)</code>
+ <pre>Creates a study.
+
+Args:
+ parent: string, Required. The project and location that the study belongs to.
+Format: projects/{project}/locations/{location} (required)
+ body: object, The request body.
+ The object takes the form of:
+
+{ # A message representing a Study.
+ "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.
+ "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.
+ "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.
+ # Currently, 'performance' refers to the running average of the objective
+ # values reported by the trial in each measurement.
+ "useElapsedTime": True or False, # If true, the median automated stopping rule applies to
+ # measurement.use_elapsed_time, which means the elapsed_time field of
+ # the current trial's
+ # 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.
+ "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.
+ "type": "A String", # Required. The type of the parameter.
+ "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
+ "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
+ "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value 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,
+ ],
+ },
+ "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.
+ },
+ "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",
+ ],
+ },
+ "categoricalValueSpec": { # The value spec for a 'CATEGORICAL' parameter.
+ "values": [ # Must be specified if type is `CATEGORICAL`.
+ # The list of possible categories.
+ "A String",
+ ],
+ },
+ "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
+ "childParameterSpecs": [ # A child node is active if the parameter's value matches the child node's
+ # matching_parent_values.
+ #
+ # If two items in child_parameter_specs have the same name, they must have
+ # disjoint matching_parent_values.
+ # Object with schema name: GoogleCloudMlV1_StudyConfig_ParameterSpec
+ ],
+ "discreteValueSpec": { # The value spec for a 'DISCRETE' parameter.
+ "values": [ # Must be specified if type is `DISCRETE`.
+ # A list of feasible points.
+ # The list should be in strictly increasing order. For instance, this
+ # parameter might have possible settings of 1.5, 2.5, and 4.0. This list
+ # should not contain more than 1,000 values.
+ 3.14,
+ ],
+ },
+ },
+ ],
+ },
+}
+
+ studyId: string, Required. The ID to use for the study, which will become the final component of
+the study's resource name.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A message representing a Study.
+ "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.
+ "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.
+ "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.
+ # Currently, 'performance' refers to the running average of the objective
+ # values reported by the trial in each measurement.
+ "useElapsedTime": True or False, # If true, the median automated stopping rule applies to
+ # measurement.use_elapsed_time, which means the elapsed_time field of
+ # the current trial's
+ # 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.
+ "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.
+ "type": "A String", # Required. The type of the parameter.
+ "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
+ "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
+ "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value 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,
+ ],
+ },
+ "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.
+ },
+ "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",
+ ],
+ },
+ "categoricalValueSpec": { # The value spec for a 'CATEGORICAL' parameter.
+ "values": [ # Must be specified if type is `CATEGORICAL`.
+ # The list of possible categories.
+ "A String",
+ ],
+ },
+ "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
+ "childParameterSpecs": [ # A child node is active if the parameter's value matches the child node's
+ # matching_parent_values.
+ #
+ # If two items in child_parameter_specs have the same name, they must have
+ # disjoint matching_parent_values.
+ # Object with schema name: GoogleCloudMlV1_StudyConfig_ParameterSpec
+ ],
+ "discreteValueSpec": { # The value spec for a 'DISCRETE' parameter.
+ "values": [ # Must be specified if type is `DISCRETE`.
+ # A list of feasible points.
+ # The list should be in strictly increasing order. For instance, this
+ # parameter might have possible settings of 1.5, 2.5, and 4.0. This list
+ # should not contain more than 1,000 values.
+ 3.14,
+ ],
+ },
+ },
+ ],
+ },
+ }</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="delete">delete(name, x__xgafv=None)</code>
+ <pre>Deletes a study.
+
+Args:
+ name: string, Required. The study name. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated
+ # empty messages in your APIs. A typical example is to use it as the request
+ # or the response type of an API method. For instance:
+ #
+ # service Foo {
+ # rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);
+ # }
+ #
+ # The JSON representation for `Empty` is empty JSON object `{}`.
+ }</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="get">get(name, x__xgafv=None)</code>
+ <pre>Gets a study.
+
+Args:
+ name: string, Required. The study name. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A message representing a Study.
+ "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.
+ "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.
+ "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.
+ # Currently, 'performance' refers to the running average of the objective
+ # values reported by the trial in each measurement.
+ "useElapsedTime": True or False, # If true, the median automated stopping rule applies to
+ # measurement.use_elapsed_time, which means the elapsed_time field of
+ # the current trial's
+ # 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.
+ "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.
+ "type": "A String", # Required. The type of the parameter.
+ "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
+ "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
+ "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value 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,
+ ],
+ },
+ "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.
+ },
+ "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",
+ ],
+ },
+ "categoricalValueSpec": { # The value spec for a 'CATEGORICAL' parameter.
+ "values": [ # Must be specified if type is `CATEGORICAL`.
+ # The list of possible categories.
+ "A String",
+ ],
+ },
+ "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
+ "childParameterSpecs": [ # A child node is active if the parameter's value matches the child node's
+ # matching_parent_values.
+ #
+ # If two items in child_parameter_specs have the same name, they must have
+ # disjoint matching_parent_values.
+ # Object with schema name: GoogleCloudMlV1_StudyConfig_ParameterSpec
+ ],
+ "discreteValueSpec": { # The value spec for a 'DISCRETE' parameter.
+ "values": [ # Must be specified if type is `DISCRETE`.
+ # A list of feasible points.
+ # The list should be in strictly increasing order. For instance, this
+ # parameter might have possible settings of 1.5, 2.5, and 4.0. This list
+ # should not contain more than 1,000 values.
+ 3.14,
+ ],
+ },
+ },
+ ],
+ },
+ }</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="list">list(parent, x__xgafv=None)</code>
+ <pre>Lists all the studies in a region for an associated project.
+
+Args:
+ parent: string, Required. The project and location that the study belongs to.
+Format: projects/{project}/locations/{location} (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ {
+ "studies": [ # The studies associated with the project.
+ { # A message representing a Study.
+ "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.
+ "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.
+ "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.
+ # Currently, 'performance' refers to the running average of the objective
+ # values reported by the trial in each measurement.
+ "useElapsedTime": True or False, # If true, the median automated stopping rule applies to
+ # measurement.use_elapsed_time, which means the elapsed_time field of
+ # the current trial's
+ # 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.
+ "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.
+ "type": "A String", # Required. The type of the parameter.
+ "doubleValueSpec": { # The value spec for a 'DOUBLE' parameter.
+ "minValue": 3.14, # Must be specified if type is `DOUBLE`. Minimum value of the parameter.
+ "maxValue": 3.14, # Must be specified if type is `DOUBLE`. Maximum value 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,
+ ],
+ },
+ "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.
+ },
+ "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",
+ ],
+ },
+ "categoricalValueSpec": { # The value spec for a 'CATEGORICAL' parameter.
+ "values": [ # Must be specified if type is `CATEGORICAL`.
+ # The list of possible categories.
+ "A String",
+ ],
+ },
+ "parameter": "A String", # Required. The parameter name must be unique amongst all ParameterSpecs.
+ "childParameterSpecs": [ # A child node is active if the parameter's value matches the child node's
+ # matching_parent_values.
+ #
+ # If two items in child_parameter_specs have the same name, they must have
+ # disjoint matching_parent_values.
+ # Object with schema name: GoogleCloudMlV1_StudyConfig_ParameterSpec
+ ],
+ "discreteValueSpec": { # The value spec for a 'DISCRETE' parameter.
+ "values": [ # Must be specified if type is `DISCRETE`.
+ # A list of feasible points.
+ # The list should be in strictly increasing order. For instance, this
+ # parameter might have possible settings of 1.5, 2.5, and 4.0. This list
+ # should not contain more than 1,000 values.
+ 3.14,
+ ],
+ },
+ },
+ ],
+ },
+ },
+ ],
+ }</pre>
+</div>
+
+</body></html>
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