quark.onnx.quantization.api

Module Contents

Classes

class quark.onnx.quantization.api.ModelQuantizer(config: quark.onnx.quantization.config.config.Config)

Provides an API for quantizing deep learning models using ONNX. This class handles the configuration and processing of the model for quantization based on user-defined parameters.

Args:

config (Config): Configuration object containing settings for quantization.

Note:

It is essential to ensure that the ‘config’ provided has all necessary quantization parameters defined. This class assumes that the model is compatible with the quantization settings specified in ‘config’.

quantize_model(model_input: str, model_output: str, calibration_data_reader: Union[onnxruntime.quantization.calibrate.CalibrationDataReader, None] = None, calibration_data_path: Optional[str] = None) → None

Quantizes the given ONNX model and saves the output to the specified path.

Args:

model_input (str): Path to the input ONNX model file. model_output (str): Path where the quantized ONNX model will be saved. calibration_data_reader (Union[CalibrationDataReader, None], optional): Data reader for model calibration. Defaults to None.

Returns:

None

Raises:

ValueError: If the input model path is invalid or the file does not exist.