feat: Add lib allows tensor saving

GPT_SoVITS/VoiceSave/__init__.py

@@ -0,0 +1,140 @@
+import numpy as np
+import torch
+import zipfile
+import file_lib as fl
+import time_lib as tl
+import info_lib as il
+import os
+from typing import Union
+
+POOL:set = set() 
+def get_unique_name(name,MySet:set=set()):
+    _id = 1
+    if name not in POOL and name not in MySet:
+        POOL.add(name)
+        return name
+    while name in POOL or name in MySet:
+        _id += 1
+        name = f'{name}_{_id}'
+    POOL.add(name)
+    return name
+
+TEMP_DIR = fl.merge_dir_txt2(fl.get_my_dir(), "Temp")
+TEMP_ZIP_DIR = fl.merge_dir_txt2(TEMP_DIR, "ZipTemp")
+def _tensor_to_numpy(tensor: torch.Tensor) -> np.ndarray:
+    cloned = tensor.clone().detach()
+    np_array = cloned.cpu().numpy()
+    return np_array
+
+def save_np(path: str, np_array: np.ndarray) -> None:
+    np.save(path, np_array)
+
+class ZIP_File:
+    def __init__(self, path: str,name:str,MySet:set=set()):
+        self.path = path
+        if not os.path.exists(self.path):
+            with zipfile.ZipFile(self.path, 'w') as zipf:
+                pass
+        self.name = get_unique_name(name,MySet=MySet)#MySet用于补充命名集合，防止文件夹混淆
+        self.temp_write = fl.merge_dir_txt2(TEMP_ZIP_DIR, self.name)
+
+        if not os.path.exists(self.temp_write):
+            os.makedirs(self.temp_write)
+
+    def release(self):
+        '''relaese the zip file, extract it to temp dir'''
+        if os.path.exists(self.temp_write):
+            fl.delete_dir(self.temp_write)
+            fl.create_dir(self.temp_write)
+        with zipfile.ZipFile(self.path, 'r') as zipf:
+            zipf.extractall(self.temp_write)
+        #fl.delete_file(self.path)
+    def create_dir(self, dir_:str):
+        dir_path = fl.merge_dir_txt2(self.temp_write, dir_)
+        if not os.path.exists(dir_path):
+            os.makedirs(dir_path,exist_ok=True)
+
+    def create_file(self, file_name:str,location:str=''):
+        if location == '':
+            file_path = fl.merge_dir_txt2(self.temp_write,file_name)
+        else:
+            file_path = fl.merge_dir_txt2(self.temp_write, location, file_name)
+        if not os.path.exists(location):
+            os.makedirs(location,exist_ok=True)
+        with open(file_path, 'x') as f:
+            pass
+
+    def get_file_path(self, file_name:str,location:str=''):
+        if location == '':
+            file_path = fl.merge_dir_txt2(self.temp_write,file_name)
+        else:
+            file_path = fl.merge_dir_txt2(self.temp_write, location, file_name)
+        if not os.path.exists(file_path):
+            raise FileNotFoundError(f"File {file_path} does not exist.")
+        return file_path
+    
+    def get_file_obj(self, file_name:str,location:str,mode:str='r'):
+        file_path = fl.merge_dir_txt2(self.temp_write, location, file_name)
+        if not os.path.exists(file_path):
+            raise FileNotFoundError(f"File {file_path} does not exist.")
+        return open(file_path, mode)
+    
+    def save_file(self, obj):
+        obj.close()
+    
+    def save_zip(self):
+        with zipfile.ZipFile(self.path, 'w', zipfile.ZIP_DEFLATED) as zipf:
+            for root, dirs, files in os.walk(self.temp_write):
+                for file in files:
+                    file_path = os.path.join(root, file)
+                    arcname = os.path.relpath(file_path, self.temp_write)
+                    zipf.write(file_path, arcname)
+        #fl.delete_dir(self.temp_write)
+
+    def close(self):
+        self.save_zip()
+        fl.delete_dir(self.temp_write)
+        POOL.remove(self.name)
+
+def save_tensor(path: str, tensors: Union[torch.Tensor, list],name:str,MySet:set=set(),file_names:Union[str,list,None]=None,**info_save) -> None:
+    if isinstance(tensors, torch.Tensor):
+        tensors = [tensors]
+    if not file_names:
+        return
+    if isinstance(file_names, str):
+        files = [file_names]
+    else:
+        files = file_names
+
+    if len(tensors) != len(files):
+        raise ValueError("The number of tensors and files must be the same.")
+    np_arrays = []
+    for tensor in tensors:
+        np_array = _tensor_to_numpy(tensor)
+        np_arrays.append(np_array)
+    zf = ZIP_File(path, name, MySet=MySet)
+    zf.create_file("voice.json")
+    info = {'name': name}
+    info.update(info_save)
+    il.save_info(str(zf.get_file_path("voice.json")), info)
+    for i in range(len(files)):
+        file_name = files[i]
+        np_array = np_arrays[i]
+        zf.create_file(file_name)
+        save_np(str(zf.get_file_path(file_name)), np_array)
+    zf.close()
+    del zf
+
+def load_tensor(path: str,name:str,find_func,MySet:set=set()) -> list:
+    zf = ZIP_File(path, name, MySet=MySet)
+    zf.release()
+    voice_path = find_func(zf,il)
+    tensors = []
+    for i in range(len(voice_path)):
+        v = voice_path[i]
+        np_array = np.load(v)
+        tensor = torch.from_numpy(np_array)
+        tensors.append(tensor)
+    zf.close()
+    del zf
+    return tensors

GPT_SoVITS/VoiceSave/file_lib.py

@@ -0,0 +1,35 @@
+import os
+import shutil
+from pathlib import Path
+
+def get_my_dir():
+    return os.path.dirname(os.path.abspath(__file__))
+
+def get_parent_dir(dir_path,depth=1):
+    parent_path = Path(dir_path)
+    for _ in range(depth):
+        parent_path = parent_path.parent
+    return parent_path
+
+def merge_dir_txt(a,b):
+    c=os.path.join(a,b)
+    return c
+def merge_dir_txt2(*TXT):
+    return Path(os.path.join(*TXT))
+def create_dir(path: Path, overwrite=False) -> bool:
+    if overwrite and path.exists():
+        shutil.rmtree(path)
+    path = Path(path)
+    path.mkdir(parents=True, exist_ok=True)
+    return path.exists()
+def get_dir_children_dirs(path: Path):
+    return [item for item in path.iterdir() if item.is_dir()]
+def get_dir_children_files(path: Path):
+    return [item for item in path.iterdir() if item.is_file()]
+def delete_dir(path: Path):
+    return shutil.rmtree(path)
+def delete_file(path: Path):
+    return os.remove(path)
+def file_exists(path: Path):
+    path = Path(path)
+    return path.exists()

GPT_SoVITS/VoiceSave/info_lib.py

@@ -0,0 +1,10 @@
+import json
+
+def load_info(info_path):
+    with open(info_path, 'r', encoding='utf-8') as f:
+        info = json.load(f)
+    return info
+
+def save_info(info, info_path):
+    with open(info_path, 'w', encoding='utf-8') as f:
+        json.dump(info, f, ensure_ascii=False, indent=4)

GPT_SoVITS/VoiceSave/time_lib.py

@@ -0,0 +1,38 @@
+import time
+#time styles
+STYLE_Y = "%Y"
+STYLE_M = "%m"
+STYLE_D = "%d"
+STYLE_H = "%H"
+STYLE_MIN = "%M"
+STYLE_S = "%S"
+STYLE_FULL = "%Y-%m-%d_%H.%M.%S"
+#quick calls
+def get_time_y(STYLE = STYLE_Y):
+    return time.strftime(STYLE, time.localtime())
+def get_time_m(STYLE = STYLE_M):
+    return time.strftime(STYLE, time.localtime())
+def get_time_d(STYLE = STYLE_D):
+    return time.strftime(STYLE, time.localtime())
+def get_time_h(STYLE = STYLE_H):
+    return time.strftime(STYLE, time.localtime())
+def get_time_min(STYLE = STYLE_MIN):
+    return time.strftime(STYLE, time.localtime())
+def get_time_s(STYLE = STYLE_S):
+    return time.strftime(STYLE, time.localtime())
+def get_time_full(STYLE = STYLE_FULL):
+    return time.strftime(STYLE, time.localtime())
+
+def s(t:float):
+    time.sleep(t)
+    return 
+###
+
+if __name__ == '__main__':
+    print(get_time_y())
+    print(get_time_m())
+    print(get_time_d())
+    print(get_time_h())
+    print(get_time_min())
+    print(get_time_s())
+    print(get_time_full())