CaloClusterMLCalibToolLiteCfg Namespace Reference

Functions
	CaloClusterMLCalibToolLiteCfg (flags, name="CaloClusterMLCalibToolLite", config_file="CaloClusterCorrection/config_hgm_mc20.yaml")

Function Documentation

CaloClusterMLCalibToolLiteCfg()

CaloClusterMLCalibToolLiteCfg.CaloClusterMLCalibToolLiteCfg	(		flags,
			name = "CaloClusterMLCalibToolLite",
			config_file = "CaloClusterCorrection/config_hgm_mc20.yaml" )

Definition at line 10 of file CaloClusterMLCalibToolLiteCfg.py.

):
    if flags.Input.MCCampaign.value.startswith("mc23"):
        config_file = "CaloClusterCorrection/config_hgm_mc23.yaml"
 
    with open(PathResolver.FindCalibFile(config_file)) as f:
        config = yaml.safe_load(f)
 
    onnx_model_path = config["model"]["onnx_path"]
    features = config["data"]["features"]
    sorted_features = sorted(features.items(), key=lambda item: item[1]["position"])
    transform_names = [
        item[1]["preprocessing"]["processors"][0] for item in sorted_features
    ]
    transform_params = [
        [float(x) for x in item[1]["preprocessing"]["parameters"]]
        for item in sorted_features
    ]
 
    ca = ComponentAccumulator()
    onnx_tool = ca.popToolsAndMerge(OnnxRuntimeInferenceToolCfg(flags, onnx_model_path))
    CaloClusterMLCalibToolLite = CompFactory.CaloClusterMLCalibToolLite(name)
    CaloClusterMLCalibToolLite.ORTInferenceTool = onnx_tool
    CaloClusterMLCalibToolLite.PreprocessingTransformNames = transform_names
    CaloClusterMLCalibToolLite.PreprocessingTransformParams = transform_params
    ca.setPrivateTools(CaloClusterMLCalibToolLite)
 
    return ca