import ctypes import glob import os import sys import traceback from pathlib import Path import ffmpeg import gradio as gr import numpy as np import pandas as pd from tools.i18n.i18n import I18nAuto i18n = I18nAuto(language=os.environ.get("language", "Auto")) def load_audio(file, sr): try: # https://github.com/openai/whisper/blob/main/whisper/audio.py#L26 # This launches a subprocess to decode audio while down-mixing and resampling as necessary. # Requires the ffmpeg CLI and `ffmpeg-python` package to be installed. file = clean_path(file) # 防止小白拷路径头尾带了空格和"和回车 if os.path.exists(file) == False: raise RuntimeError("You input a wrong audio path that does not exists, please fix it!") out, _ = ( ffmpeg.input(file, threads=0) .output("-", format="f32le", acodec="pcm_f32le", ac=1, ar=sr) .run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True) ) except Exception: traceback.print_exc() raise RuntimeError(i18n("音频加载失败")) return np.frombuffer(out, np.float32).flatten() def clean_path(path_str: str): if path_str.endswith(("\\", "/")): return clean_path(path_str[0:-1]) path_str = path_str.replace("/", os.sep).replace("\\", os.sep) return path_str.strip( " '\n\"\u202a" ) # path_str.strip(" ").strip('\'').strip("\n").strip('"').strip(" ").strip("\u202a") def check_for_existance(file_list: list = None, is_train=False, is_dataset_processing=False): files_status = [] if is_train == True and file_list: file_list.append(os.path.join(file_list[0], "2-name2text.txt")) file_list.append(os.path.join(file_list[0], "3-bert")) file_list.append(os.path.join(file_list[0], "4-cnhubert")) file_list.append(os.path.join(file_list[0], "5-wav32k")) file_list.append(os.path.join(file_list[0], "6-name2semantic.tsv")) for file in file_list: if os.path.exists(file): files_status.append(True) else: files_status.append(False) if sum(files_status) != len(files_status): if is_train: for file, status in zip(file_list, files_status): if status: pass else: gr.Warning(file) gr.Warning(i18n("以下文件或文件夹不存在")) return False elif is_dataset_processing: if files_status[0]: return True elif not files_status[0]: gr.Warning(file_list[0]) elif not files_status[1] and file_list[1]: gr.Warning(file_list[1]) gr.Warning(i18n("以下文件或文件夹不存在")) return False else: if file_list[0]: gr.Warning(file_list[0]) gr.Warning(i18n("以下文件或文件夹不存在")) else: gr.Warning(i18n("路径不能为空")) return False return True def check_details(path_list=None, is_train=False, is_dataset_processing=False): if is_dataset_processing: list_path, audio_path = path_list if not list_path.endswith(".list"): gr.Warning(i18n("请填入正确的List路径")) return if audio_path: if not os.path.isdir(audio_path): gr.Warning(i18n("请填入正确的音频文件夹路径")) return with open(list_path, "r", encoding="utf8") as f: line = f.readline().strip("\n").split("\n") wav_name, _, __, ___ = line[0].split("|") wav_name = clean_path(wav_name) if audio_path != "" and audio_path != None: wav_name = os.path.basename(wav_name) wav_path = "%s/%s" % (audio_path, wav_name) else: wav_path = wav_name if os.path.exists(wav_path): ... else: gr.Warning(i18n("路径错误")) return if is_train: path_list.append(os.path.join(path_list[0], "2-name2text.txt")) path_list.append(os.path.join(path_list[0], "4-cnhubert")) path_list.append(os.path.join(path_list[0], "5-wav32k")) path_list.append(os.path.join(path_list[0], "6-name2semantic.tsv")) phone_path, hubert_path, wav_path, semantic_path = path_list[1:] with open(phone_path, "r", encoding="utf-8") as f: if f.read(1): ... else: gr.Warning(i18n("缺少音素数据集")) if os.listdir(hubert_path): ... else: gr.Warning(i18n("缺少Hubert数据集")) if os.listdir(wav_path): ... else: gr.Warning(i18n("缺少音频数据集")) df = pd.read_csv(semantic_path, delimiter="\t", encoding="utf-8") if len(df) >= 1: ... else: gr.Warning(i18n("缺少语义数据集")) def load_cudnn(): import torch if not torch.cuda.is_available(): print("[INFO] CUDA is not available, skipping cuDNN setup.") return if sys.platform == "win32": torch_lib_dir = Path(torch.__file__).parent / "lib" if torch_lib_dir.exists(): os.add_dll_directory(str(torch_lib_dir)) print(f"[INFO] Added DLL directory: {torch_lib_dir}") matching_files = sorted(torch_lib_dir.glob("cudnn_cnn*.dll")) if not matching_files: print(f"[ERROR] No cudnn_cnn*.dll found in {torch_lib_dir}") return for dll_path in matching_files: dll_name = os.path.basename(dll_path) try: ctypes.CDLL(dll_name) print(f"[INFO] Loaded: {dll_name}") except OSError as e: print(f"[WARNING] Failed to load {dll_name}: {e}") else: print(f"[WARNING] Torch lib directory not found: {torch_lib_dir}") elif sys.platform == "linux": site_packages = Path(torch.__file__).resolve().parents[1] cudnn_dir = site_packages / "nvidia" / "cudnn" / "lib" if not cudnn_dir.exists(): print(f"[ERROR] cudnn dir not found: {cudnn_dir}") return matching_files = sorted(cudnn_dir.glob("libcudnn_cnn*.so*")) if not matching_files: print(f"[ERROR] No libcudnn_cnn*.so* found in {cudnn_dir}") return for so_path in matching_files: try: ctypes.CDLL(so_path, mode=ctypes.RTLD_GLOBAL) # type: ignore print(f"[INFO] Loaded: {so_path}") except OSError as e: print(f"[WARNING] Failed to load {so_path}: {e}") def load_nvrtc(): import torch if not torch.cuda.is_available(): print("[INFO] CUDA is not available, skipping nvrtc setup.") return if sys.platform == "win32": torch_lib_dir = Path(torch.__file__).parent / "lib" if torch_lib_dir.exists(): os.add_dll_directory(str(torch_lib_dir)) print(f"[INFO] Added DLL directory: {torch_lib_dir}") matching_files = sorted(torch_lib_dir.glob("nvrtc*.dll")) if not matching_files: print(f"[ERROR] No nvrtc*.dll found in {torch_lib_dir}") return for dll_path in matching_files: dll_name = os.path.basename(dll_path) try: ctypes.CDLL(dll_name) print(f"[INFO] Loaded: {dll_name}") except OSError as e: print(f"[WARNING] Failed to load {dll_name}: {e}") else: print(f"[WARNING] Torch lib directory not found: {torch_lib_dir}") elif sys.platform == "linux": site_packages = Path(torch.__file__).resolve().parents[1] nvrtc_dir = site_packages / "nvidia" / "cuda_nvrtc" / "lib" if not nvrtc_dir.exists(): print(f"[ERROR] nvrtc dir not found: {nvrtc_dir}") return matching_files = sorted(nvrtc_dir.glob("libnvrtc*.so*")) if not matching_files: print(f"[ERROR] No libnvrtc*.so* found in {nvrtc_dir}") return for so_path in matching_files: try: ctypes.CDLL(so_path, mode=ctypes.RTLD_GLOBAL) # type: ignore print(f"[INFO] Loaded: {so_path}") except OSError as e: print(f"[WARNING] Failed to load {so_path}: {e}")