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| import argparse | |
| import os | |
| import sys | |
| import json | |
| from multiprocessing import cpu_count | |
| import torch | |
| try: | |
| import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import | |
| if torch.xpu.is_available(): | |
| from infer.modules.ipex import ipex_init | |
| ipex_init() | |
| except Exception: | |
| pass | |
| import logging | |
| logger = logging.getLogger(__name__) | |
| version_config_list = [ | |
| "v1/32k.json", | |
| "v1/40k.json", | |
| "v1/48k.json", | |
| "v2/48k.json", | |
| "v2/32k.json", | |
| ] | |
| def singleton_variable(func): | |
| def wrapper(*args, **kwargs): | |
| if not wrapper.instance: | |
| wrapper.instance = func(*args, **kwargs) | |
| return wrapper.instance | |
| wrapper.instance = None | |
| return wrapper | |
| class Config: | |
| def __init__(self): | |
| self.device = "cuda:0" | |
| self.is_half = True | |
| self.n_cpu = 0 | |
| self.gpu_name = None | |
| self.json_config = self.load_config_json() | |
| self.gpu_mem = None | |
| ( | |
| self.python_cmd, | |
| self.listen_port, | |
| self.iscolab, | |
| self.noparallel, | |
| self.noautoopen, | |
| self.paperspace, | |
| self.is_cli, | |
| self.grtheme, | |
| self.dml, | |
| ) = self.arg_parse() | |
| self.instead = "" | |
| self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config() | |
| def load_config_json() -> dict: | |
| d = {} | |
| for config_file in version_config_list: | |
| with open(f"configs/{config_file}", "r") as f: | |
| d[config_file] = json.load(f) | |
| return d | |
| def arg_parse() -> tuple: | |
| exe = sys.executable or "python" | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--port", type=int, default=7865, help="Listen port") | |
| parser.add_argument("--pycmd", type=str, default=exe, help="Python command") | |
| parser.add_argument("--colab", action="store_true", help="Launch in colab") | |
| parser.add_argument( | |
| "--noparallel", action="store_true", help="Disable parallel processing" | |
| ) | |
| parser.add_argument( | |
| "--noautoopen", | |
| action="store_true", | |
| help="Do not open in browser automatically", | |
| ) | |
| parser.add_argument( | |
| "--paperspace", | |
| action="store_true", | |
| help="Note that this argument just shares a gradio link for the web UI. Thus can be used on other non-local CLI systems.", | |
| ) | |
| parser.add_argument( | |
| "--is_cli", | |
| action="store_true", | |
| help="Use the CLI instead of setting up a gradio UI. This flag will launch an RVC text interface where you can execute functions from infer-web.py!", | |
| ) | |
| parser.add_argument( | |
| "-t", | |
| "--theme", | |
| help = "Theme for Gradio. Format - `JohnSmith9982/small_and_pretty` (no backticks)", | |
| default = "JohnSmith9982/small_and_pretty", | |
| type = str | |
| ) | |
| parser.add_argument( | |
| "--dml", | |
| action="store_true", | |
| help="Use DirectML backend instead of CUDA." | |
| ) | |
| cmd_opts = parser.parse_args() | |
| cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865 | |
| return ( | |
| cmd_opts.pycmd, | |
| cmd_opts.port, | |
| cmd_opts.colab, | |
| cmd_opts.noparallel, | |
| cmd_opts.noautoopen, | |
| cmd_opts.paperspace, | |
| cmd_opts.is_cli, | |
| cmd_opts.theme, | |
| cmd_opts.dml, | |
| ) | |
| # has_mps is only available in nightly pytorch (for now) and MasOS 12.3+. | |
| # check `getattr` and try it for compatibility | |
| def has_mps() -> bool: | |
| if not torch.backends.mps.is_available(): | |
| return False | |
| try: | |
| torch.zeros(1).to(torch.device("mps")) | |
| return True | |
| except Exception: | |
| return False | |
| def has_xpu() -> bool: | |
| if hasattr(torch, "xpu") and torch.xpu.is_available(): | |
| return True | |
| else: | |
| return False | |
| def use_fp32_config(self): | |
| for config_file in version_config_list: | |
| self.json_config[config_file]["train"]["fp16_run"] = False | |
| def device_config(self) -> tuple: | |
| if torch.cuda.is_available(): | |
| if self.has_xpu(): | |
| self.device = self.instead = "xpu:0" | |
| self.is_half = True | |
| 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 "P10" in self.gpu_name.upper() | |
| or "1060" in self.gpu_name | |
| or "1070" in self.gpu_name | |
| or "1080" in self.gpu_name | |
| ): | |
| logger.info("Found GPU %s, force to fp32", self.gpu_name) | |
| self.is_half = False | |
| self.use_fp32_config() | |
| else: | |
| logger.info("Found GPU %s", 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("infer/modules/train/preprocess.py", "r") as f: | |
| strr = f.read().replace("3.7", "3.0") | |
| with open("infer/modules/train/preprocess.py", "w") as f: | |
| f.write(strr) | |
| elif self.has_mps(): | |
| logger.info("No supported Nvidia GPU found") | |
| self.device = self.instead = "mps" | |
| self.is_half = False | |
| self.use_fp32_config() | |
| else: | |
| logger.info("No supported Nvidia GPU found") | |
| self.device = self.instead = "cpu" | |
| self.is_half = False | |
| self.use_fp32_config() | |
| if self.n_cpu == 0: | |
| self.n_cpu = cpu_count() | |
| if self.is_half: | |
| # 6G显存配置 | |
| x_pad = 3 | |
| x_query = 10 | |
| x_center = 60 | |
| x_max = 65 | |
| else: | |
| # 5G显存配置 | |
| x_pad = 1 | |
| x_query = 6 | |
| x_center = 38 | |
| x_max = 41 | |
| if self.gpu_mem is not None and self.gpu_mem <= 4: | |
| x_pad = 1 | |
| x_query = 5 | |
| x_center = 30 | |
| x_max = 32 | |
| if self.dml: | |
| logger.info("Use DirectML instead") | |
| if ( | |
| os.path.exists( | |
| "runtime\Lib\site-packages\onnxruntime\capi\DirectML.dll" | |
| ) | |
| == False | |
| ): | |
| try: | |
| os.rename( | |
| "runtime\Lib\site-packages\onnxruntime", | |
| "runtime\Lib\site-packages\onnxruntime-cuda", | |
| ) | |
| except: | |
| pass | |
| try: | |
| os.rename( | |
| "runtime\Lib\site-packages\onnxruntime-dml", | |
| "runtime\Lib\site-packages\onnxruntime", | |
| ) | |
| except: | |
| pass | |
| # if self.device != "cpu": | |
| import torch_directml | |
| self.device = torch_directml.device(torch_directml.default_device()) | |
| self.is_half = False | |
| else: | |
| if self.instead: | |
| logger.info(f"Use {self.instead} instead") | |
| if ( | |
| os.path.exists( | |
| "runtime\Lib\site-packages\onnxruntime\capi\onnxruntime_providers_cuda.dll" | |
| ) | |
| == False | |
| ): | |
| try: | |
| os.rename( | |
| "runtime\Lib\site-packages\onnxruntime", | |
| "runtime\Lib\site-packages\onnxruntime-dml", | |
| ) | |
| except: | |
| pass | |
| try: | |
| os.rename( | |
| "runtime\Lib\site-packages\onnxruntime-cuda", | |
| "runtime\Lib\site-packages\onnxruntime", | |
| ) | |
| except: | |
| pass | |
| return x_pad, x_query, x_center, x_max | |