Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::StudySpec::StudyStoppingConfig (v0.44.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::StudySpec::StudyStoppingConfig.

The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#max_duration_no_progress

def max_duration_no_progress() -> ::Google::Protobuf::Duration
Returns
  • (::Google::Protobuf::Duration) — If the objective value has not improved for this much time, stop the study.

    WARNING: Effective only for single-objective studies.

#max_duration_no_progress=

def max_duration_no_progress=(value) -> ::Google::Protobuf::Duration
Parameter
  • value (::Google::Protobuf::Duration) — If the objective value has not improved for this much time, stop the study.

    WARNING: Effective only for single-objective studies.

Returns
  • (::Google::Protobuf::Duration) — If the objective value has not improved for this much time, stop the study.

    WARNING: Effective only for single-objective studies.

#max_num_trials

def max_num_trials() -> ::Google::Protobuf::Int32Value
Returns

#max_num_trials=

def max_num_trials=(value) -> ::Google::Protobuf::Int32Value
Parameter
Returns

#max_num_trials_no_progress

def max_num_trials_no_progress() -> ::Google::Protobuf::Int32Value
Returns
  • (::Google::Protobuf::Int32Value) — If the objective value has not improved for this many consecutive trials, stop the study.

    WARNING: Effective only for single-objective studies.

#max_num_trials_no_progress=

def max_num_trials_no_progress=(value) -> ::Google::Protobuf::Int32Value
Parameter
  • value (::Google::Protobuf::Int32Value) — If the objective value has not improved for this many consecutive trials, stop the study.

    WARNING: Effective only for single-objective studies.

Returns
  • (::Google::Protobuf::Int32Value) — If the objective value has not improved for this many consecutive trials, stop the study.

    WARNING: Effective only for single-objective studies.

#maximum_runtime_constraint

def maximum_runtime_constraint() -> ::Google::Cloud::AIPlatform::V1::StudyTimeConstraint
Returns

#maximum_runtime_constraint=

def maximum_runtime_constraint=(value) -> ::Google::Cloud::AIPlatform::V1::StudyTimeConstraint
Parameter
Returns

#min_num_trials

def min_num_trials() -> ::Google::Protobuf::Int32Value
Returns

#min_num_trials=

def min_num_trials=(value) -> ::Google::Protobuf::Int32Value
Parameter
Returns

#minimum_runtime_constraint

def minimum_runtime_constraint() -> ::Google::Cloud::AIPlatform::V1::StudyTimeConstraint
Returns
  • (::Google::Cloud::AIPlatform::V1::StudyTimeConstraint) — Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting min_num_trials=5 and always_stop_after= 1 hour means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to resume a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.

#minimum_runtime_constraint=

def minimum_runtime_constraint=(value) -> ::Google::Cloud::AIPlatform::V1::StudyTimeConstraint
Parameter
  • value (::Google::Cloud::AIPlatform::V1::StudyTimeConstraint) — Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting min_num_trials=5 and always_stop_after= 1 hour means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to resume a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.
Returns
  • (::Google::Cloud::AIPlatform::V1::StudyTimeConstraint) — Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting min_num_trials=5 and always_stop_after= 1 hour means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to resume a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.

#should_stop_asap

def should_stop_asap() -> ::Google::Protobuf::BoolValue
Returns
  • (::Google::Protobuf::BoolValue) — If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state.

    The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).

#should_stop_asap=

def should_stop_asap=(value) -> ::Google::Protobuf::BoolValue
Parameter
  • value (::Google::Protobuf::BoolValue) — If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state.

    The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).

Returns
  • (::Google::Protobuf::BoolValue) — If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state.

    The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).