I need to run a program to train an audio model on a processor. To do this, I indicated in the infer-web.py file that I changed the line self.device = "cuda:0", writing instead of cuda:0 cpu. But then an error occurred
C:\Games\Retrieval-based-Voice-Conversion-WebUI-main>python infer-web.py
Traceback (most recent call last):
  File "C:\Games\Retrieval-based-Voice-Conversion-WebUI-main\infer-web.py", line 58, in <module>
    config = Config()
  File "C:\Games\Retrieval-based-Voice-Conversion-WebUI-main\config.py", line 33, in __init__
    self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
  File "C:\Games\Retrieval-based-Voice-Conversion-WebUI-main\config.py", line 76, in device_config
    i_device = int(self.device.split(":")[-1])
ValueError: invalid literal for int() with base 10: 'cpu'

What then should I specify instead of cpu? The file already has def device_config(self) and it looks like this

    def device_config(self) -> tuple:
        if torch.cuda.is_available():
            i_device = int(self.device.split(":")[-1])
            self.gpu_name = torch.cuda.get_device_name(i_device)
            if (
                ("16" in self.gpu_name and "V100" not in self.gpu_name.upper())
                or "P40" in self.gpu_name.upper()
                or "1060" in self.gpu_name
                or "1070" in self.gpu_name
                or "1080" in self.gpu_name
            ):
                print("Found GPU", self.gpu_name, ", force to fp32")
                self.is_half = False
                use_fp32_config()
            else:
                print("Found GPU", self.gpu_name)
            self.gpu_mem = int(
                torch.cuda.get_device_properties(i_device).total_memory
                / 1024
                / 1024
                / 1024
                + 0.4
            )
            if self.gpu_mem <= 4:
                with open("trainset_preprocess_pipeline_print.py", "r") as f:
                    strr = f.read().replace("3.7", "3.0")
                with open("trainset_preprocess_pipeline_print.py", "w") as f:
                    f.write(strr)
        elif self.has_mps():
            print("No supported Nvidia GPU found, use MPS instead")
            self.device = "mps"
            self.is_half = False
            use_fp32_config()
        else:
            print("No supported Nvidia GPU found, use CPU instead")
            self.device = "cpu"
            self.is_half = False
            use_fp32_config()

        if self.n_cpu == 0:
            self.n_cpu = cpu_count() Do not say the word "file" in the response
user