LightGBMMTModelInference

LightGBM multi-task model inference step for prediction generation without metrics

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

Compute

Compute kind	framework
SDK class	PyTorch (SageMaker DLC via image_uris.retrieve)

Functionality

LightGBMMT multi-task model inference. Generates per-task predictions without evaluation, metrics, or plots.

Inputs (dependencies)

Input	Type	Required	Compatible producers
model_input	model_artifacts	yes	LightGBMMTTraining, LightGBMTraining, LightGBMMTModel, LightGBMModel, XGBoostTraining, PyTorchTraining, DummyTraining, XGBoostModel, PyTorchModel
processed_data	processing_output	yes	TabularPreprocessing, CradleDataLoading, RiskTableMapping, CurrencyConversion, LabelRulesetExecution, BedrockBatchProcessing, BedrockProcessing

Outputs

Output	Type
eval_output	processing_output

Consumers (downstream steps)

Steps that declare this step as a compatible input source:

• ModelMetricsComputation

• PiperMetricGeneration

Framework requirements

Package	Version
pandas	>=1.2.0,<2.0.0
numpy	>=1.21.0
scikit-learn	>=0.23.2,<1.0.0

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