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 |
Synopsis
- data HyperParameterTuningResourceConfig = HyperParameterTuningResourceConfig' {}
- newHyperParameterTuningResourceConfig :: HyperParameterTuningResourceConfig
- hyperParameterTuningResourceConfig_allocationStrategy :: Lens' HyperParameterTuningResourceConfig (Maybe HyperParameterTuningAllocationStrategy)
- hyperParameterTuningResourceConfig_instanceConfigs :: Lens' HyperParameterTuningResourceConfig (Maybe (NonEmpty HyperParameterTuningInstanceConfig))
- hyperParameterTuningResourceConfig_instanceCount :: Lens' HyperParameterTuningResourceConfig (Maybe Natural)
- hyperParameterTuningResourceConfig_instanceType :: Lens' HyperParameterTuningResourceConfig (Maybe TrainingInstanceType)
- hyperParameterTuningResourceConfig_volumeKmsKeyId :: Lens' HyperParameterTuningResourceConfig (Maybe Text)
- hyperParameterTuningResourceConfig_volumeSizeInGB :: Lens' HyperParameterTuningResourceConfig (Maybe Natural)
Documentation
data HyperParameterTuningResourceConfig Source #
The configuration of resources, including compute instances and storage
volumes for use in training jobs launched by hyperparameter tuning jobs.
HyperParameterTuningResourceConfig
is similar to ResourceConfig
, but
has the additional InstanceConfigs
and AllocationStrategy
fields to
allow for flexible instance management. Specify one or more instance
types, count, and the allocation strategy for instance selection.
HyperParameterTuningResourceConfig
supports the capabilities of
ResourceConfig
with the exception of KeepAlivePeriodInSeconds
.
Hyperparameter tuning jobs use warm pools by default, which reuse
clusters between training jobs.
See: newHyperParameterTuningResourceConfig
smart constructor.
HyperParameterTuningResourceConfig' | |
|
Instances
newHyperParameterTuningResourceConfig :: HyperParameterTuningResourceConfig Source #
Create a value of HyperParameterTuningResourceConfig
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:allocationStrategy:HyperParameterTuningResourceConfig'
, hyperParameterTuningResourceConfig_allocationStrategy
- The strategy that determines the order of preference for resources
specified in InstanceConfigs
used in hyperparameter optimization.
$sel:instanceConfigs:HyperParameterTuningResourceConfig'
, hyperParameterTuningResourceConfig_instanceConfigs
- A list containing the configuration(s) for one or more resources for
processing hyperparameter jobs. These resources include compute
instances and storage volumes to use in model training jobs launched by
hyperparameter tuning jobs. The AllocationStrategy
controls the order
in which multiple configurations provided in InstanceConfigs
are used.
If you only want to use a single instance configuration inside the
HyperParameterTuningResourceConfig
API, do not provide a value for
InstanceConfigs
. Instead, use InstanceType
, VolumeSizeInGB
and
InstanceCount
. If you use InstanceConfigs
, do not provide values for
InstanceType
, VolumeSizeInGB
or InstanceCount
.
HyperParameterTuningResourceConfig
, hyperParameterTuningResourceConfig_instanceCount
- The number of compute instances of type InstanceType
to use. For
distributed training,
select a value greater than 1.
HyperParameterTuningResourceConfig
, hyperParameterTuningResourceConfig_instanceType
- The instance type used to run hyperparameter optimization tuning jobs.
See
descriptions of instance types
for more information.
$sel:volumeKmsKeyId:HyperParameterTuningResourceConfig'
, hyperParameterTuningResourceConfig_volumeKmsKeyId
- A key used by Amazon Web Services Key Management Service to encrypt data
on the storage volume attached to the compute instances used to run the
training job. You can use either of the following formats to specify a
key.
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Some instances use local storage, which use a
hardware module to encrypt
storage volumes. If you choose one of these instance types, you cannot
request a VolumeKmsKeyId
. For a list of instance types that use local
storage, see
instance store volumes.
For more information about Amazon Web Services Key Management Service,
see
KMS encryption
for more information.
HyperParameterTuningResourceConfig
, hyperParameterTuningResourceConfig_volumeSizeInGB
- The volume size in GB for the storage volume to be used in processing
hyperparameter optimization jobs (optional). These volumes store model
artifacts, incremental states and optionally, scratch space for training
algorithms. Do not provide a value for this parameter if a value for
InstanceConfigs
is also specified.
Some instance types have a fixed total local storage size. If you select
one of these instances for training, VolumeSizeInGB
cannot be greater
than this total size. For a list of instance types with local instance
storage and their sizes, see
instance store volumes.
SageMaker supports only the General Purpose SSD (gp2) storage volume type.
hyperParameterTuningResourceConfig_allocationStrategy :: Lens' HyperParameterTuningResourceConfig (Maybe HyperParameterTuningAllocationStrategy) Source #
The strategy that determines the order of preference for resources
specified in InstanceConfigs
used in hyperparameter optimization.
hyperParameterTuningResourceConfig_instanceConfigs :: Lens' HyperParameterTuningResourceConfig (Maybe (NonEmpty HyperParameterTuningInstanceConfig)) Source #
A list containing the configuration(s) for one or more resources for
processing hyperparameter jobs. These resources include compute
instances and storage volumes to use in model training jobs launched by
hyperparameter tuning jobs. The AllocationStrategy
controls the order
in which multiple configurations provided in InstanceConfigs
are used.
If you only want to use a single instance configuration inside the
HyperParameterTuningResourceConfig
API, do not provide a value for
InstanceConfigs
. Instead, use InstanceType
, VolumeSizeInGB
and
InstanceCount
. If you use InstanceConfigs
, do not provide values for
InstanceType
, VolumeSizeInGB
or InstanceCount
.
hyperParameterTuningResourceConfig_instanceCount :: Lens' HyperParameterTuningResourceConfig (Maybe Natural) Source #
The number of compute instances of type InstanceType
to use. For
distributed training,
select a value greater than 1.
hyperParameterTuningResourceConfig_instanceType :: Lens' HyperParameterTuningResourceConfig (Maybe TrainingInstanceType) Source #
The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.
hyperParameterTuningResourceConfig_volumeKmsKeyId :: Lens' HyperParameterTuningResourceConfig (Maybe Text) Source #
A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Some instances use local storage, which use a
hardware module to encrypt
storage volumes. If you choose one of these instance types, you cannot
request a VolumeKmsKeyId
. For a list of instance types that use local
storage, see
instance store volumes.
For more information about Amazon Web Services Key Management Service,
see
KMS encryption
for more information.
hyperParameterTuningResourceConfig_volumeSizeInGB :: Lens' HyperParameterTuningResourceConfig (Maybe Natural) Source #
The volume size in GB for the storage volume to be used in processing
hyperparameter optimization jobs (optional). These volumes store model
artifacts, incremental states and optionally, scratch space for training
algorithms. Do not provide a value for this parameter if a value for
InstanceConfigs
is also specified.
Some instance types have a fixed total local storage size. If you select
one of these instances for training, VolumeSizeInGB
cannot be greater
than this total size. For a list of instance types with local instance
storage and their sizes, see
instance store volumes.
SageMaker supports only the General Purpose SSD (gp2) storage volume type.