| import argparse |
| import torch |
| from multiprocessing import cpu_count |
|
|
|
|
| def config_file_change_fp32(): |
| for config_file in ["32k.json", "40k.json", "48k.json"]: |
| with open(f"configs/{config_file}", "r") as f: |
| strr = f.read().replace("true", "false") |
| with open(f"configs/{config_file}", "w") as f: |
| f.write(strr) |
| 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) |
|
|
|
|
| class Config: |
| def __init__(self): |
| self.device = "cuda:0" |
| self.is_half = True |
| self.n_cpu = 0 |
| self.gpu_name = None |
| self.gpu_mem = None |
| ( |
| self.python_cmd, |
| self.listen_port, |
| self.iscolab, |
| self.noparallel, |
| self.noautoopen, |
| self.paperspace, |
| self.is_cli, |
| ) = self.arg_parse() |
| |
| self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config() |
|
|
| @staticmethod |
| def arg_parse() -> tuple: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--port", type=int, default=7860, help="Listen port") |
| parser.add_argument( |
| "--pycmd", type=str, default="python", 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!" |
| ) |
| cmd_opts = parser.parse_args() |
|
|
| cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7860 |
|
|
| return ( |
| cmd_opts.pycmd, |
| cmd_opts.port, |
| cmd_opts.colab, |
| cmd_opts.noparallel, |
| cmd_opts.noautoopen, |
| cmd_opts.paperspace, |
| cmd_opts.is_cli, |
| ) |
|
|
| 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("16 series/10 series graphics cards and P40 force single precision") |
| self.is_half = False |
| config_file_change_fp32() |
| else: |
| self.gpu_name = None |
| 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 torch.backends.mps.is_available(): |
| print("No supported N card found, use MPS for inference") |
| self.device = "mps" |
| self.is_half = False |
| config_file_change_fp32() |
| else: |
| print("No supported N card found, using CPU for inference") |
| self.device = "cpu" |
| self.is_half = False |
| config_file_change_fp32() |
|
|
| if self.n_cpu == 0: |
| self.n_cpu = cpu_count() |
|
|
| if self.is_half: |
| |
| x_pad = 3 |
| x_query = 10 |
| x_center = 60 |
| x_max = 65 |
| else: |
| |
| x_pad = 1 |
| x_query = 6 |
| x_center = 38 |
| x_max = 41 |
|
|
| if self.gpu_mem != None and self.gpu_mem <= 4: |
| x_pad = 1 |
| x_query = 5 |
| x_center = 30 |
| x_max = 32 |
|
|
| return x_pad, x_query, x_center, x_max |
|
|
