def METHOD_NAME(data):
    input_quantizer = model._bn.input_quantizers[0]
    if isinstance(input_quantizer, StaticGridTensorQuantizer):
        return input_quantizer.quantize_dequantize(data, input_quantizer.round_mode)
    assert isinstance(input_quantizer, LearnedGridTensorQuantizer)
    encoding = input_quantizer.encoding
    encoding_min = torch.tensor([encoding.min])
    encoding_max = torch.tensor([encoding.max])
    return input_quantizer.quantize_dequantize(data, encoding_min, encoding_max)