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| import torch | |
| import json | |
| import os | |
| version_config_paths = [ | |
| os.path.join("v1", "32000.json"), | |
| os.path.join("v1", "40000.json"), | |
| os.path.join("v1", "48000.json"), | |
| os.path.join("v2", "48000.json"), | |
| os.path.join("v2", "40000.json"), | |
| os.path.join("v2", "32000.json"), | |
| ] | |
| def singleton(cls): | |
| instances = {} | |
| def get_instance(*args, **kwargs): | |
| if cls not in instances: | |
| instances[cls] = cls(*args, **kwargs) | |
| return instances[cls] | |
| return get_instance | |
| class Config: | |
| def __init__(self): | |
| self.device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
| self.is_half = self.device != "cpu" | |
| self.gpu_name = ( | |
| torch.cuda.get_device_name(int(self.device.split(":")[-1])) | |
| if self.device.startswith("cuda") | |
| else None | |
| ) | |
| self.gpu_mem = None | |
| self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config() | |
| def has_mps(self) -> bool: | |
| # Check if Metal Performance Shaders are available - for macOS 12.3+. | |
| return torch.backends.mps.is_available() | |
| def set_precision(self, precision): | |
| if precision not in ["fp32", "fp16"]: | |
| raise ValueError("Invalid precision type. Must be 'fp32' or 'fp16'.") | |
| fp16_run_value = precision == "fp16" | |
| preprocess_target_version = "3.7" if precision == "fp16" else "3.0" | |
| preprocess_path = os.path.join( | |
| os.path.dirname(__file__), | |
| os.pardir, | |
| "rvc", | |
| "train", | |
| "preprocess", | |
| "preprocess.py", | |
| ) | |
| for config_path in version_config_paths: | |
| full_config_path = os.path.join("rvc", "configs", config_path) | |
| try: | |
| with open(full_config_path, "r") as f: | |
| config = json.load(f) | |
| config["train"]["fp16_run"] = fp16_run_value | |
| with open(full_config_path, "w") as f: | |
| json.dump(config, f, indent=4) | |
| except FileNotFoundError: | |
| print(f"File not found: {full_config_path}") | |
| if os.path.exists(preprocess_path): | |
| with open(preprocess_path, "r") as f: | |
| preprocess_content = f.read() | |
| preprocess_content = preprocess_content.replace( | |
| "3.0" if precision == "fp16" else "3.7", preprocess_target_version | |
| ) | |
| with open(preprocess_path, "w") as f: | |
| f.write(preprocess_content) | |
| return f"Overwritten preprocess and config.json to use {precision}." | |
| def device_config(self) -> tuple: | |
| if self.device.startswith("cuda"): | |
| self.set_cuda_config() | |
| elif self.has_mps(): | |
| self.device = "mps" | |
| self.is_half = False | |
| self.set_precision("fp32") | |
| else: | |
| self.device = "cpu" | |
| self.is_half = False | |
| self.set_precision("fp32") | |
| # Configuration for 6GB GPU memory | |
| x_pad, x_query, x_center, x_max = ( | |
| (3, 10, 60, 65) if self.is_half else (1, 6, 38, 41) | |
| ) | |
| if self.gpu_mem is not None and self.gpu_mem <= 4: | |
| # Configuration for 5GB GPU memory | |
| x_pad, x_query, x_center, x_max = (1, 5, 30, 32) | |
| return x_pad, x_query, x_center, x_max | |
| def set_cuda_config(self): | |
| i_device = int(self.device.split(":")[-1]) | |
| self.gpu_name = torch.cuda.get_device_name(i_device) | |
| low_end_gpus = ["16", "P40", "P10", "1060", "1070", "1080"] | |
| if ( | |
| any(gpu in self.gpu_name for gpu in low_end_gpus) | |
| and "V100" not in self.gpu_name.upper() | |
| ): | |
| self.is_half = False | |
| self.set_precision("fp32") | |
| self.gpu_mem = torch.cuda.get_device_properties(i_device).total_memory // ( | |
| 1024**3 | |
| ) | |