XGBoostModelInference

XGBoost model inference step for prediction generation without metrics

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

Compute

Compute kind	xgboost

Functionality

XGBoost model inference script. Loads trained model, preprocesses evaluation data, generates predictions without metrics computation.

Inputs (dependencies)

Input	Type	Required	Compatible producers
model_input	model_artifacts	yes	XGBoostTraining, PyTorchTraining, DummyTraining, XGBoostModel, PyTorchModel, PyTorchModelInference
processed_data	processing_output	yes	TabularPreprocessing, CradleDataLoading, RiskTableMapping, CurrencyConversion

Outputs

Output	Type
eval_output	processing_output

Consumers (downstream steps)

Steps that declare this step as a compatible input source:

• ActiveSampleSelection

• ModelCalibration

• ModelMetricsComputation

• ModelWikiGenerator

• PercentileModelCalibration

• PiperMetricGeneration

• PseudoLabelMerge

Framework requirements

Package	Version
pandas	>=1.3.0
numpy	>=1.21.0
xgboost	>=1.6.0

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