#[non_exhaustive]pub struct HyperParameterTuningJobWarmStartConfigBuilder { /* private fields */ }
Expand description
A builder for HyperParameterTuningJobWarmStartConfig
.
Implementations§
Source§impl HyperParameterTuningJobWarmStartConfigBuilder
impl HyperParameterTuningJobWarmStartConfigBuilder
Sourcepub fn parent_hyper_parameter_tuning_jobs(
self,
input: ParentHyperParameterTuningJob,
) -> Self
pub fn parent_hyper_parameter_tuning_jobs( self, input: ParentHyperParameterTuningJob, ) -> Self
Appends an item to parent_hyper_parameter_tuning_jobs
.
To override the contents of this collection use set_parent_hyper_parameter_tuning_jobs
.
An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
Sourcepub fn set_parent_hyper_parameter_tuning_jobs(
self,
input: Option<Vec<ParentHyperParameterTuningJob>>,
) -> Self
pub fn set_parent_hyper_parameter_tuning_jobs( self, input: Option<Vec<ParentHyperParameterTuningJob>>, ) -> Self
An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
Sourcepub fn get_parent_hyper_parameter_tuning_jobs(
&self,
) -> &Option<Vec<ParentHyperParameterTuningJob>>
pub fn get_parent_hyper_parameter_tuning_jobs( &self, ) -> &Option<Vec<ParentHyperParameterTuningJob>>
An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
Sourcepub fn warm_start_type(
self,
input: HyperParameterTuningJobWarmStartType,
) -> Self
pub fn warm_start_type( self, input: HyperParameterTuningJobWarmStartType, ) -> Self
Specifies one of the following:
- IDENTICAL_DATA_AND_ALGORITHM
-
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
- TRANSFER_LEARNING
-
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
Sourcepub fn set_warm_start_type(
self,
input: Option<HyperParameterTuningJobWarmStartType>,
) -> Self
pub fn set_warm_start_type( self, input: Option<HyperParameterTuningJobWarmStartType>, ) -> Self
Specifies one of the following:
- IDENTICAL_DATA_AND_ALGORITHM
-
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
- TRANSFER_LEARNING
-
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
Sourcepub fn get_warm_start_type(
&self,
) -> &Option<HyperParameterTuningJobWarmStartType>
pub fn get_warm_start_type( &self, ) -> &Option<HyperParameterTuningJobWarmStartType>
Specifies one of the following:
- IDENTICAL_DATA_AND_ALGORITHM
-
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
- TRANSFER_LEARNING
-
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
Sourcepub fn build(self) -> HyperParameterTuningJobWarmStartConfig
pub fn build(self) -> HyperParameterTuningJobWarmStartConfig
Consumes the builder and constructs a HyperParameterTuningJobWarmStartConfig
.
Trait Implementations§
Source§impl Clone for HyperParameterTuningJobWarmStartConfigBuilder
impl Clone for HyperParameterTuningJobWarmStartConfigBuilder
Source§fn clone(&self) -> HyperParameterTuningJobWarmStartConfigBuilder
fn clone(&self) -> HyperParameterTuningJobWarmStartConfigBuilder
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moreSource§impl Default for HyperParameterTuningJobWarmStartConfigBuilder
impl Default for HyperParameterTuningJobWarmStartConfigBuilder
Source§fn default() -> HyperParameterTuningJobWarmStartConfigBuilder
fn default() -> HyperParameterTuningJobWarmStartConfigBuilder
Source§impl PartialEq for HyperParameterTuningJobWarmStartConfigBuilder
impl PartialEq for HyperParameterTuningJobWarmStartConfigBuilder
Source§fn eq(&self, other: &HyperParameterTuningJobWarmStartConfigBuilder) -> bool
fn eq(&self, other: &HyperParameterTuningJobWarmStartConfigBuilder) -> bool
self
and other
values to be equal, and is used by ==
.impl StructuralPartialEq for HyperParameterTuningJobWarmStartConfigBuilder
Auto Trait Implementations§
impl Freeze for HyperParameterTuningJobWarmStartConfigBuilder
impl RefUnwindSafe for HyperParameterTuningJobWarmStartConfigBuilder
impl Send for HyperParameterTuningJobWarmStartConfigBuilder
impl Sync for HyperParameterTuningJobWarmStartConfigBuilder
impl Unpin for HyperParameterTuningJobWarmStartConfigBuilder
impl UnwindSafe for HyperParameterTuningJobWarmStartConfigBuilder
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