quantize_model

Function Usage

Quantizes a graph based on the quantization configuration file, inserts weight and activation quantization operators, generates a quantization factor record file record_file, and returns an ONNX model ready for calibration.

Prototype

quantize_model(config_file, model_file, modified_onnx_file, record_file)

Command-Line Options

Option	Input/Return	Meaning	Restriction
config_file	Input	User-defined quantization configuration file, which specifies the configuration of each layer to be quantized.	A string
model_file	Input	Source ONNX model file or updated ONNX model file generated by create_quant_config.	A string
modified_onnx_file	Input	File name of the ONNX model ready for calibration, whose activations are to be quantized.	A string
record_file	Input	Directory of the quantization factor record file, including the file name.	A string.

Return Value

None

Example

import amct_onnx as amct

model_file = "resnet101.onnx"
scale_offset_record_file = os.path.join(TMP, 'scale_offset_record.txt')
modified_model = os.path.join(TMP, 'modified_model.onnx')
config_file="./configs/config.json"
# Insert the quantization API.
amct.quantize_model(config_file,
                    model_file,
                    modified_model,
                    scale_offset_record_file)

Parent topic: PTQ APIs