TemporalSequenceNormalization

Temporal sequence normalization step for machine learning models with configurable sequence operations

SageMaker step type	Processing
Node type	internal (consumes upstream, produces downstream)
Container entry point	temporal_sequence_normalization.py
Interface file	steps/interfaces/temporal_sequence_normalization.step.yaml

Compute

Compute kind	sklearn

Functionality

Temporal sequence normalization script. Handles temporal sequence data loading, validation, normalization, and padding/truncation for ML models.

Inputs (dependencies)

Input	Type	Required	Compatible producers
DATA	processing_output	yes	CradleDataLoading, DummyDataLoading, DataLoad, ProcessingStep, TabularPreprocessing
SIGNATURE	processing_output	no	CradleDataLoading, DummyDataLoading

Outputs

Output	Type
normalized_sequences	processing_output

Consumers (downstream steps)

Steps that declare this step as a compatible input source:

• BedrockBatchProcessing

• BedrockProcessing

• LabelRulesetExecution

• PseudoLabelMerge

• TSATraining

• TemporalFeatureEngineering

Framework requirements

Package	Version
pandas	>=1.3.0
numpy	>=1.21.0

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