Hi. I have an audio processing model that uses functions from TorchLibrosa (GitHub - qiuqiangkong/torchlibrosa) that I want to quantize and save. I get the following error:

RuntimeError:
_pad(Tensor input, int[] pad, str mode=“constant”, float value=0.) → (Tensor):
Expected a value of type ‘float’ for argument ‘value’ but instead found type ‘int’.
:
input_1 = input
getitem = input_1[(slice(None, None, None), None, slice(None, None, None))];  input_1 = None
_pad_1 = torch.nn.functional._pad(getitem, (256, 256), mode = ‘reflect’, value = 0);  getitem = None
~~~~~~~~~~~~~~~~~~~~~~~~ <— HERE
base_spectrogram_extractor_stft_conv_real_input_scale_0 = self.base_spectrogram_extractor_stft_conv_real_input_scale_0
base_spectrogram_extractor_stft_conv_real_input_zero_point_0 = self.base_spectrogram_extractor_stft_conv_real_input_zero_point_0

I tried ignoring these modules using the following config for quantization in FX Graph mode:
qconfig = get_default_qconfig("fbgemm")
qconfig_dict = {"": qconfig}

prep_config_dict = {
    "non_traceable_module_name": ["spectrogram_extractor", "logmel_extractor"]
}
prepared_model = prepare_fx(
    model_to_quantize, qconfig_dict, prepare_custom_config_dict=prep_config_dict)

What can I do to fix this issue? I really appreciate any help you can provide.