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.

Parameters:

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) → None

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

Parameters:

• 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.