def convert_int8_jit()

in mobile_cv/model_zoo/tools/create_model.py [0:0]

• 32 lines of code
• 5 McCabe index (conditional complexity)

def convert_int8_jit(args, model, data, folder_name="int8_jit"):
    if not args.convert_int8:
        return None, None, None
    try:
        print("Converting to int8 jit...")
        if args.int8_backend is not None:
            torch.backends.quantized.engine = args.int8_backend
        if not USE_GRAPH_MODE_QUANT:
            # trace model
            traced_model, traced_output = model_utils.convert_int8_jit(
                model, data, int8_backend=args.int8_backend, add_quant_stub=False
            )
        else:
            quant = qu.PostQuantizationFX(model)
            quant_model = (
                quant.set_quant_backend("default")
                .prepare()
                .calibrate_model([data], 1)
                .convert_model()
            )
            traced_model, traced_output = model_utils.convert_torch_script(
                quant_model,
                data,
                fuse_bn=args.fuse_bn,
                use_get_traceable=bool(args.use_get_traceable),
            )

        print(traced_model)

        output_dir = os.path.join(args.output_dir, folder_name)
        model_utils.save_model(output_dir, traced_model, data)
        return traced_model, traced_output, output_dir
    except Exception as e:
        print(f"Converting to int8 jit failed. {e}")
        return None, None, None