| Copyright | (c) 2013-2023 Brendan Hay |
|---|---|
| License | Mozilla Public License, v. 2.0. |
| Maintainer | Brendan Hay |
| Stability | auto-generated |
| Portability | non-portable (GHC extensions) |
| Safe Haskell | Safe-Inferred |
| Language | Haskell2010 |
Amazonka.SageMaker.CreateHyperParameterTuningJob
Description
Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Synopsis
- data CreateHyperParameterTuningJob = CreateHyperParameterTuningJob' {
- tags :: Maybe [Tag]
- trainingJobDefinition :: Maybe HyperParameterTrainingJobDefinition
- trainingJobDefinitions :: Maybe (NonEmpty HyperParameterTrainingJobDefinition)
- warmStartConfig :: Maybe HyperParameterTuningJobWarmStartConfig
- hyperParameterTuningJobName :: Text
- hyperParameterTuningJobConfig :: HyperParameterTuningJobConfig
- newCreateHyperParameterTuningJob :: Text -> HyperParameterTuningJobConfig -> CreateHyperParameterTuningJob
- createHyperParameterTuningJob_tags :: Lens' CreateHyperParameterTuningJob (Maybe [Tag])
- createHyperParameterTuningJob_trainingJobDefinition :: Lens' CreateHyperParameterTuningJob (Maybe HyperParameterTrainingJobDefinition)
- createHyperParameterTuningJob_trainingJobDefinitions :: Lens' CreateHyperParameterTuningJob (Maybe (NonEmpty HyperParameterTrainingJobDefinition))
- createHyperParameterTuningJob_warmStartConfig :: Lens' CreateHyperParameterTuningJob (Maybe HyperParameterTuningJobWarmStartConfig)
- createHyperParameterTuningJob_hyperParameterTuningJobName :: Lens' CreateHyperParameterTuningJob Text
- createHyperParameterTuningJob_hyperParameterTuningJobConfig :: Lens' CreateHyperParameterTuningJob HyperParameterTuningJobConfig
- data CreateHyperParameterTuningJobResponse = CreateHyperParameterTuningJobResponse' {}
- newCreateHyperParameterTuningJobResponse :: Int -> Text -> CreateHyperParameterTuningJobResponse
- createHyperParameterTuningJobResponse_httpStatus :: Lens' CreateHyperParameterTuningJobResponse Int
- createHyperParameterTuningJobResponse_hyperParameterTuningJobArn :: Lens' CreateHyperParameterTuningJobResponse Text
Creating a Request
data CreateHyperParameterTuningJob Source #
See: newCreateHyperParameterTuningJob smart constructor.
Constructors
| CreateHyperParameterTuningJob' | |
Fields
| |
Instances
newCreateHyperParameterTuningJob Source #
Arguments
| :: Text | |
| -> HyperParameterTuningJobConfig | |
| -> CreateHyperParameterTuningJob |
Create a value of CreateHyperParameterTuningJob with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
CreateHyperParameterTuningJob, createHyperParameterTuningJob_tags - An array of key-value pairs. You can use tags to categorize your Amazon
Web Services resources in different ways, for example, by purpose,
owner, or environment. For more information, see
Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
CreateHyperParameterTuningJob, createHyperParameterTuningJob_trainingJobDefinition - The HyperParameterTrainingJobDefinition object that describes the
training jobs that this tuning job launches, including static
hyperparameters, input data configuration, output data configuration,
resource configuration, and stopping condition.
CreateHyperParameterTuningJob, createHyperParameterTuningJob_trainingJobDefinitions - A list of the HyperParameterTrainingJobDefinition objects launched for
this tuning job.
CreateHyperParameterTuningJob, createHyperParameterTuningJob_warmStartConfig - Specifies the configuration for starting the hyperparameter tuning job
using one or more previous tuning jobs as a starting point. The results
of previous tuning jobs are used to inform which combinations of
hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are
evaluated by using the objective metric. If you specify
IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm
start configuration, the training job that performs the best in the new
tuning job is compared to the best training jobs from the parent tuning
jobs. From these, the training job that performs the best as measured by
the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
CreateHyperParameterTuningJob, createHyperParameterTuningJob_hyperParameterTuningJobName - The name of the tuning job. This name is the prefix for the names of all
training jobs that this tuning job launches. The name must be unique
within the same Amazon Web Services account and Amazon Web Services
Region. The name must have 1 to 32 characters. Valid characters are a-z,
A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
CreateHyperParameterTuningJob, createHyperParameterTuningJob_hyperParameterTuningJobConfig - The HyperParameterTuningJobConfig object that describes the tuning job,
including the search strategy, the objective metric used to evaluate
training jobs, ranges of parameters to search, and resource limits for
the tuning job. For more information, see
How Hyperparameter Tuning Works.
Request Lenses
createHyperParameterTuningJob_tags :: Lens' CreateHyperParameterTuningJob (Maybe [Tag]) Source #
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
createHyperParameterTuningJob_trainingJobDefinition :: Lens' CreateHyperParameterTuningJob (Maybe HyperParameterTrainingJobDefinition) Source #
The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
createHyperParameterTuningJob_trainingJobDefinitions :: Lens' CreateHyperParameterTuningJob (Maybe (NonEmpty HyperParameterTrainingJobDefinition)) Source #
A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
createHyperParameterTuningJob_warmStartConfig :: Lens' CreateHyperParameterTuningJob (Maybe HyperParameterTuningJobWarmStartConfig) Source #
Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are
evaluated by using the objective metric. If you specify
IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm
start configuration, the training job that performs the best in the new
tuning job is compared to the best training jobs from the parent tuning
jobs. From these, the training job that performs the best as measured by
the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
createHyperParameterTuningJob_hyperParameterTuningJobName :: Lens' CreateHyperParameterTuningJob Text Source #
The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
createHyperParameterTuningJob_hyperParameterTuningJobConfig :: Lens' CreateHyperParameterTuningJob HyperParameterTuningJobConfig Source #
The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.
Destructuring the Response
data CreateHyperParameterTuningJobResponse Source #
See: newCreateHyperParameterTuningJobResponse smart constructor.
Constructors
| CreateHyperParameterTuningJobResponse' | |
Fields
| |
Instances
newCreateHyperParameterTuningJobResponse Source #
Arguments
| :: Int | |
| -> Text | |
| -> CreateHyperParameterTuningJobResponse |
Create a value of CreateHyperParameterTuningJobResponse with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
$sel:httpStatus:CreateHyperParameterTuningJobResponse', createHyperParameterTuningJobResponse_httpStatus - The response's http status code.
CreateHyperParameterTuningJobResponse, createHyperParameterTuningJobResponse_hyperParameterTuningJobArn - The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an
ARN to a hyperparameter tuning job when you create it.
Response Lenses
createHyperParameterTuningJobResponse_httpStatus :: Lens' CreateHyperParameterTuningJobResponse Int Source #
The response's http status code.
createHyperParameterTuningJobResponse_hyperParameterTuningJobArn :: Lens' CreateHyperParameterTuningJobResponse Text Source #
The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.