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 ModelPackageContainerDefinition = ModelPackageContainerDefinition' {}
- newModelPackageContainerDefinition :: Text -> ModelPackageContainerDefinition
- modelPackageContainerDefinition_containerHostname :: Lens' ModelPackageContainerDefinition (Maybe Text)
- modelPackageContainerDefinition_environment :: Lens' ModelPackageContainerDefinition (Maybe (HashMap Text Text))
- modelPackageContainerDefinition_framework :: Lens' ModelPackageContainerDefinition (Maybe Text)
- modelPackageContainerDefinition_frameworkVersion :: Lens' ModelPackageContainerDefinition (Maybe Text)
- modelPackageContainerDefinition_imageDigest :: Lens' ModelPackageContainerDefinition (Maybe Text)
- modelPackageContainerDefinition_modelDataUrl :: Lens' ModelPackageContainerDefinition (Maybe Text)
- modelPackageContainerDefinition_modelInput :: Lens' ModelPackageContainerDefinition (Maybe ModelInput)
- modelPackageContainerDefinition_nearestModelName :: Lens' ModelPackageContainerDefinition (Maybe Text)
- modelPackageContainerDefinition_productId :: Lens' ModelPackageContainerDefinition (Maybe Text)
- modelPackageContainerDefinition_image :: Lens' ModelPackageContainerDefinition Text
Documentation
data ModelPackageContainerDefinition Source #
Describes the Docker container for the model package.
See: newModelPackageContainerDefinition
smart constructor.
ModelPackageContainerDefinition' | |
|
Instances
newModelPackageContainerDefinition Source #
Create a value of ModelPackageContainerDefinition
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:containerHostname:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_containerHostname
- The DNS host name for the Docker container.
$sel:environment:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_environment
- The environment variables to set in the Docker container. Each key and
value in the Environment
string to string map can have length of up to
1024. We support up to 16 entries in the map.
$sel:framework:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_framework
- The machine learning framework of the model package container image.
$sel:frameworkVersion:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_frameworkVersion
- The framework version of the Model Package Container Image.
$sel:imageDigest:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_imageDigest
- An MD5 hash of the training algorithm that identifies the Docker image
used for training.
$sel:modelDataUrl:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_modelDataUrl
- The Amazon S3 path where the model artifacts, which result from model
training, are stored. This path must point to a single gzip
compressed
tar archive (.tar.gz
suffix).
The model artifacts must be in an S3 bucket that is in the same region as the model package.
$sel:modelInput:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_modelInput
- A structure with Model Input details.
$sel:nearestModelName:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_nearestModelName
- The name of a pre-trained machine learning benchmarked by Amazon
SageMaker Inference Recommender model that matches your model. You can
find a list of benchmarked models by calling ListModelMetadata
.
$sel:productId:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_productId
- The Amazon Web Services Marketplace product ID of the model package.
$sel:image:ModelPackageContainerDefinition'
, modelPackageContainerDefinition_image
- The Amazon EC2 Container Registry (Amazon ECR) path where inference code
is stored.
If you are using your own custom algorithm instead of an algorithm
provided by SageMaker, the inference code must meet SageMaker
requirements. SageMaker supports both registry/repository[:tag]
and
registry/repository[@digest]
image path formats. For more
information, see
Using Your Own Algorithms with Amazon SageMaker.
modelPackageContainerDefinition_containerHostname :: Lens' ModelPackageContainerDefinition (Maybe Text) Source #
The DNS host name for the Docker container.
modelPackageContainerDefinition_environment :: Lens' ModelPackageContainerDefinition (Maybe (HashMap Text Text)) Source #
The environment variables to set in the Docker container. Each key and
value in the Environment
string to string map can have length of up to
1024. We support up to 16 entries in the map.
modelPackageContainerDefinition_framework :: Lens' ModelPackageContainerDefinition (Maybe Text) Source #
The machine learning framework of the model package container image.
modelPackageContainerDefinition_frameworkVersion :: Lens' ModelPackageContainerDefinition (Maybe Text) Source #
The framework version of the Model Package Container Image.
modelPackageContainerDefinition_imageDigest :: Lens' ModelPackageContainerDefinition (Maybe Text) Source #
An MD5 hash of the training algorithm that identifies the Docker image used for training.
modelPackageContainerDefinition_modelDataUrl :: Lens' ModelPackageContainerDefinition (Maybe Text) Source #
The Amazon S3 path where the model artifacts, which result from model
training, are stored. This path must point to a single gzip
compressed
tar archive (.tar.gz
suffix).
The model artifacts must be in an S3 bucket that is in the same region as the model package.
modelPackageContainerDefinition_modelInput :: Lens' ModelPackageContainerDefinition (Maybe ModelInput) Source #
A structure with Model Input details.
modelPackageContainerDefinition_nearestModelName :: Lens' ModelPackageContainerDefinition (Maybe Text) Source #
The name of a pre-trained machine learning benchmarked by Amazon
SageMaker Inference Recommender model that matches your model. You can
find a list of benchmarked models by calling ListModelMetadata
.
modelPackageContainerDefinition_productId :: Lens' ModelPackageContainerDefinition (Maybe Text) Source #
The Amazon Web Services Marketplace product ID of the model package.
modelPackageContainerDefinition_image :: Lens' ModelPackageContainerDefinition Text Source #
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm
provided by SageMaker, the inference code must meet SageMaker
requirements. SageMaker supports both registry/repository[:tag]
and
registry/repository[@digest]
image path formats. For more
information, see
Using Your Own Algorithms with Amazon SageMaker.