amazonka-sagemaker-2.0: Amazon SageMaker Service SDK.
Copyright(c) 2013-2023 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellSafe-Inferred
LanguageHaskell2010

Amazonka.SageMaker.Types.TrainingInputMode

Description

 
Synopsis

Documentation

newtype TrainingInputMode Source #

The training input mode that the algorithm supports. For more information about input modes, see Algorithms.

Pipe mode

If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

File mode

If an algorithm supports File mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.

You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.

For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.

FastFile mode

If an algorithm supports FastFile mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.

FastFile mode works best when the data is read sequentially. Augmented manifest files aren't supported. The startup time is lower when there are fewer files in the S3 bucket provided.

Instances

Instances details
FromJSON TrainingInputMode Source # 
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FromJSONKey TrainingInputMode Source # 
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ToJSON TrainingInputMode Source # 
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ToJSONKey TrainingInputMode Source # 
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ToByteString TrainingInputMode Source # 
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ToHeader TrainingInputMode Source # 
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ToLog TrainingInputMode Source # 
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ToQuery TrainingInputMode Source # 
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FromText TrainingInputMode Source # 
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ToText TrainingInputMode Source # 
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FromXML TrainingInputMode Source # 
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ToXML TrainingInputMode Source # 
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Generic TrainingInputMode Source # 
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Associated Types

type Rep TrainingInputMode :: Type -> Type #

Read TrainingInputMode Source # 
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Show TrainingInputMode Source # 
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NFData TrainingInputMode Source # 
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Methods

rnf :: TrainingInputMode -> () #

Eq TrainingInputMode Source # 
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Ord TrainingInputMode Source # 
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Hashable TrainingInputMode Source # 
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type Rep TrainingInputMode Source # 
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type Rep TrainingInputMode = D1 ('MetaData "TrainingInputMode" "Amazonka.SageMaker.Types.TrainingInputMode" "amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3" 'True) (C1 ('MetaCons "TrainingInputMode'" 'PrefixI 'True) (S1 ('MetaSel ('Just "fromTrainingInputMode") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Text)))