added translate

app.py

@@ -1,5 +1,6 @@
 import subprocess, torch, os, traceback, sys, warnings, shutil, numpy as np
 from mega import Mega
+
 os.environ["no_proxy"] = "localhost, 127.0.0.1, ::1"
 import threading
 from time import sleep
@@ -8,6 +9,7 @@ import faiss
 from random import shuffle
 import json, datetime, requests
 from gtts import gTTS
+
 now_dir = os.getcwd()
 sys.path.append(now_dir)
 tmp = os.path.join(now_dir, "TEMP")
@@ -38,12 +40,14 @@ if not os.path.isdir('csvdb/'):
 try:
     DoFormant, Quefrency, Timbre = CSVutil('csvdb/formanting.csv', 'r', 'formanting')
     DoFormant = (
-        lambda DoFormant: True if DoFormant.lower() == 'true' else (False if DoFormant.lower() == 'false' else DoFormant)
+        lambda DoFormant: True if DoFormant.lower() == 'true' else (
+            False if DoFormant.lower() == 'false' else DoFormant)
     )(DoFormant)
 except (ValueError, TypeError, IndexError):
     DoFormant, Quefrency, Timbre = False, 1.0, 1.0
     CSVutil('csvdb/formanting.csv', 'w+', 'formanting', DoFormant, Quefrency, Timbre)
 
+
 def download_models():
     # Download hubert base model if not present
     if not os.path.isfile('./hubert_base.pt'):
@@ -54,11 +58,13 @@ def download_models():
                 f.write(response.content)
             print("Downloaded hubert base model file successfully. File saved to ./hubert_base.pt.")
         else:
-            raise Exception("Failed to download hubert base model file. Status code: " + str(response.status_code) + ".")
-        
+            raise Exception(
+                "Failed to download hubert base model file. Status code: " + str(response.status_code) + ".")
+
     # Download rmvpe model if not present
     if not os.path.isfile('./rmvpe.pt'):
-        response = requests.get('https://drive.usercontent.google.com/download?id=1Hkn4kNuVFRCNQwyxQFRtmzmMBGpQxptI&export=download&authuser=0&confirm=t&uuid=0b3a40de-465b-4c65-8c41-135b0b45c3f7&at=APZUnTV3lA3LnyTbeuduura6Dmi2:1693724254058')
+        response = requests.get(
+            'https://drive.usercontent.google.com/download?id=1Hkn4kNuVFRCNQwyxQFRtmzmMBGpQxptI&export=download&authuser=0&confirm=t&uuid=0b3a40de-465b-4c65-8c41-135b0b45c3f7&at=APZUnTV3lA3LnyTbeuduura6Dmi2:1693724254058')
 
         if response.status_code == 200:
             with open('./rmvpe.pt', 'wb') as f:
@@ -67,40 +73,41 @@ def download_models():
         else:
             raise Exception("Failed to download rmvpe model file. Status code: " + str(response.status_code) + ".")
 
+
 download_models()
 
 print("\n-------------------------------\nRVC v2 Easy GUI (Local Edition)\n-------------------------------\n")
 
+
 def formant_apply(qfrency, tmbre):
     Quefrency = qfrency
     Timbre = tmbre
     DoFormant = True
     CSVutil('csvdb/formanting.csv', 'w+', 'formanting', DoFormant, qfrency, tmbre)
-    
+
     return ({"value": Quefrency, "__type__": "update"}, {"value": Timbre, "__type__": "update"})
 
+
 def get_fshift_presets():
     fshift_presets_list = []
     for dirpath, _, filenames in os.walk("./formantshiftcfg/"):
         for filename in filenames:
             if filename.endswith(".txt"):
-                fshift_presets_list.append(os.path.join(dirpath,filename).replace('\\','/'))
-                
+                fshift_presets_list.append(os.path.join(dirpath, filename).replace('\\', '/'))
+
     if len(fshift_presets_list) > 0:
         return fshift_presets_list
     else:
         return ''
 
 
-
 def formant_enabled(cbox, qfrency, tmbre, frmntapply, formantpreset, formant_refresh_button):
-    
     if (cbox):
 
         DoFormant = True
         CSVutil('csvdb/formanting.csv', 'w+', 'formanting', DoFormant, qfrency, tmbre)
-        #print(f"is checked? - {cbox}\ngot {DoFormant}")
-        
+        # print(f"is checked? - {cbox}\ngot {DoFormant}")
+
         return (
             {"value": True, "__type__": "update"},
             {"visible": True, "__type__": "update"},
@@ -109,14 +116,14 @@ def formant_enabled(cbox, qfrency, tmbre, frmntapply, formantpreset, formant_ref
             {"visible": True, "__type__": "update"},
             {"visible": True, "__type__": "update"},
         )
-        
-        
+
+
     else:
-        
+
         DoFormant = False
         CSVutil('csvdb/formanting.csv', 'w+', 'formanting', DoFormant, qfrency, tmbre)
-        
-        #print(f"is checked? - {cbox}\ngot {DoFormant}")
+
+        # print(f"is checked? - {cbox}\ngot {DoFormant}")
         return (
             {"value": False, "__type__": "update"},
             {"visible": False, "__type__": "update"},
@@ -126,7 +133,6 @@ def formant_enabled(cbox, qfrency, tmbre, frmntapply, formantpreset, formant_ref
             {"visible": False, "__type__": "update"},
             {"visible": False, "__type__": "update"},
         )
-        
 
 
 def preset_apply(preset, qfer, tmbr):
@@ -134,21 +140,21 @@ def preset_apply(preset, qfer, tmbr):
         with open(str(preset), 'r') as p:
             content = p.readlines()
             qfer, tmbr = content[0].split('\n')[0], content[1]
-            
+
             formant_apply(qfer, tmbr)
     else:
         pass
     return ({"value": qfer, "__type__": "update"}, {"value": tmbr, "__type__": "update"})
 
+
 def update_fshift_presets(preset, qfrency, tmbre):
-    
     qfrency, tmbre = preset_apply(preset, qfrency, tmbre)
-    
+
     if (str(preset) != ''):
         with open(str(preset), 'r') as p:
             content = p.readlines()
             qfrency, tmbre = content[0].split('\n')[0], content[1]
-            
+
             formant_apply(qfrency, tmbre)
     else:
         pass
@@ -158,8 +164,9 @@ def update_fshift_presets(preset, qfrency, tmbre):
         {"value": tmbre, "__type__": "update"},
     )
 
+
 i18n = I18nAuto()
-#i18n.print()
+# i18n.print()
 # 判断是否有能用来训练和加速推理的N卡
 ngpu = torch.cuda.device_count()
 gpu_infos = []
@@ -171,23 +178,23 @@ else:
     for i in range(ngpu):
         gpu_name = torch.cuda.get_device_name(i)
         if (
-            "10" in gpu_name
-            or "16" in gpu_name
-            or "20" in gpu_name
-            or "30" in gpu_name
-            or "40" in gpu_name
-            or "A2" in gpu_name.upper()
-            or "A3" in gpu_name.upper()
-            or "A4" in gpu_name.upper()
-            or "P4" in gpu_name.upper()
-            or "A50" in gpu_name.upper()
-            or "A60" in gpu_name.upper()
-            or "70" in gpu_name
-            or "80" in gpu_name
-            or "90" in gpu_name
-            or "M4" in gpu_name.upper()
-            or "T4" in gpu_name.upper()
-            or "TITAN" in gpu_name.upper()
+                "10" in gpu_name
+                or "16" in gpu_name
+                or "20" in gpu_name
+                or "30" in gpu_name
+                or "40" in gpu_name
+                or "A2" in gpu_name.upper()
+                or "A3" in gpu_name.upper()
+                or "A4" in gpu_name.upper()
+                or "P4" in gpu_name.upper()
+                or "A50" in gpu_name.upper()
+                or "A60" in gpu_name.upper()
+                or "70" in gpu_name
+                or "80" in gpu_name
+                or "90" in gpu_name
+                or "M4" in gpu_name.upper()
+                or "T4" in gpu_name.upper()
+                or "TITAN" in gpu_name.upper()
         ):  # A10#A100#V100#A40#P40#M40#K80#A4500
             if_gpu_ok = True  # 至少有一张能用的N卡
             gpu_infos.append("%s\t%s" % (i, gpu_name))
@@ -226,6 +233,7 @@ logging.getLogger("numba").setLevel(logging.WARNING)
 
 hubert_model = None
 
+
 def load_hubert():
     global hubert_model
     models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
@@ -254,22 +262,21 @@ for root, dirs, files in os.walk(index_root, topdown=False):
             index_paths.append("%s/%s" % (root, name))
 
 
-
 def vc_single(
-    sid,
-    input_audio_path,
-    f0_up_key,
-    f0_file,
-    f0_method,
-    file_index,
-    #file_index2,
-    # file_big_npy,
-    index_rate,
-    filter_radius,
-    resample_sr,
-    rms_mix_rate,
-    protect,
-    crepe_hop_length,
+        sid,
+        input_audio_path,
+        f0_up_key,
+        f0_file,
+        f0_method,
+        file_index,
+        # file_index2,
+        # file_big_npy,
+        index_rate,
+        filter_radius,
+        resample_sr,
+        rms_mix_rate,
+        protect,
+        crepe_hop_length,
 ):  # spk_item, input_audio0, vc_transform0,f0_file,f0method0
     global tgt_sr, net_g, vc, hubert_model, version
     if input_audio_path is None:
@@ -339,22 +346,22 @@ def vc_single(
 
 
 def vc_multi(
-    sid,
-    dir_path,
-    opt_root,
-    paths,
-    f0_up_key,
-    f0_method,
-    file_index,
-    file_index2,
-    # file_big_npy,
-    index_rate,
-    filter_radius,
-    resample_sr,
-    rms_mix_rate,
-    protect,
-    format1,
-    crepe_hop_length,
+        sid,
+        dir_path,
+        opt_root,
+        paths,
+        f0_up_key,
+        f0_method,
+        file_index,
+        file_index2,
+        # file_big_npy,
+        index_rate,
+        filter_radius,
+        resample_sr,
+        rms_mix_rate,
+        protect,
+        format1,
+        crepe_hop_length,
 ):
     try:
         dir_path = (
@@ -416,6 +423,7 @@ def vc_multi(
     except:
         yield traceback.format_exc()
 
+
 # 一个选项卡全局只能有一个音色
 def get_vc(sid):
     global n_spk, tgt_sr, net_g, vc, cpt, version
@@ -535,10 +543,10 @@ def preprocess_dataset(trainset_dir, exp_dir, sr, n_p):
     f = open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir), "w")
     f.close()
     cmd = (
-        config.python_cmd
-        + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s "
-        % (trainset_dir, sr, n_p, now_dir, exp_dir)
-        + str(config.noparallel)
+            config.python_cmd
+            + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s "
+            % (trainset_dir, sr, n_p, now_dir, exp_dir)
+            + str(config.noparallel)
     )
     print(cmd)
     p = Popen(cmd, shell=True)  # , stdin=PIPE, stdout=PIPE,stderr=PIPE,cwd=now_dir
@@ -562,6 +570,7 @@ def preprocess_dataset(trainset_dir, exp_dir, sr, n_p):
     print(log)
     yield log
 
+
 # but2.click(extract_f0,[gpus6,np7,f0method8,if_f0_3,trainset_dir4],[info2])
 def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19, echl):
     gpus = gpus.split("-")
@@ -589,7 +598,7 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19, echl):
         ).start()
         while 1:
             with open(
-                "%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
+                    "%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
             ) as f:
                 yield (f.read())
             sleep(1)
@@ -611,17 +620,17 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19, echl):
     ps = []
     for idx, n_g in enumerate(gpus):
         cmd = (
-            config.python_cmd
-            + " extract_feature_print.py %s %s %s %s %s/logs/%s %s"
-            % (
-                config.device,
-                leng,
-                idx,
-                n_g,
-                now_dir,
-                exp_dir,
-                version19,
-            )
+                config.python_cmd
+                + " extract_feature_print.py %s %s %s %s %s/logs/%s %s"
+                % (
+                    config.device,
+                    leng,
+                    idx,
+                    n_g,
+                    now_dir,
+                    exp_dir,
+                    version19,
+                )
         )
         print(cmd)
         p = Popen(
@@ -664,6 +673,7 @@ def change_sr2(sr2, if_f0_3, version19):
         {"visible": True, "__type__": "update"}
     )
 
+
 def change_version19(sr2, if_f0_3, version19):
     path_str = "" if version19 == "v1" else "_v2"
     f0_str = "f0" if if_f0_3 else ""
@@ -717,22 +727,23 @@ def set_log_interval(exp_dir, batch_size12):
                 log_interval += 1
     return log_interval
 
+
 # but3.click(click_train,[exp_dir1,sr2,if_f0_3,save_epoch10,total_epoch11,batch_size12,if_save_latest13,pretrained_G14,pretrained_D15,gpus16])
 def click_train(
-    exp_dir1,
-    sr2,
-    if_f0_3,
-    spk_id5,
-    save_epoch10,
-    total_epoch11,
-    batch_size12,
-    if_save_latest13,
-    pretrained_G14,
-    pretrained_D15,
-    gpus16,
-    if_cache_gpu17,
-    if_save_every_weights18,
-    version19,
+        exp_dir1,
+        sr2,
+        if_f0_3,
+        spk_id5,
+        save_epoch10,
+        total_epoch11,
+        batch_size12,
+        if_save_latest13,
+        pretrained_G14,
+        pretrained_D15,
+        gpus16,
+        if_cache_gpu17,
+        if_save_every_weights18,
+        version19,
 ):
     CSVutil('csvdb/stop.csv', 'w+', 'formanting', False)
     # 生成filelist
@@ -744,17 +755,17 @@ def click_train(
         if version19 == "v1"
         else "%s/3_feature768" % (exp_dir)
     )
-    
+
     log_interval = set_log_interval(exp_dir, batch_size12)
-    
+
     if if_f0_3:
         f0_dir = "%s/2a_f0" % (exp_dir)
         f0nsf_dir = "%s/2b-f0nsf" % (exp_dir)
         names = (
-            set([name.split(".")[0] for name in os.listdir(gt_wavs_dir)])
-            & set([name.split(".")[0] for name in os.listdir(feature_dir)])
-            & set([name.split(".")[0] for name in os.listdir(f0_dir)])
-            & set([name.split(".")[0] for name in os.listdir(f0nsf_dir)])
+                set([name.split(".")[0] for name in os.listdir(gt_wavs_dir)])
+                & set([name.split(".")[0] for name in os.listdir(feature_dir)])
+                & set([name.split(".")[0] for name in os.listdir(f0_dir)])
+                & set([name.split(".")[0] for name in os.listdir(f0nsf_dir)])
         )
     else:
         names = set([name.split(".")[0] for name in os.listdir(gt_wavs_dir)]) & set(
@@ -814,51 +825,52 @@ def click_train(
         print("no pretrained Discriminator")
     if gpus16:
         cmd = (
-            config.python_cmd
-            + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s -li %s"
-            % (
-                exp_dir1,
-                sr2,
-                1 if if_f0_3 else 0,
-                batch_size12,
-                gpus16,
-                total_epoch11,
-                save_epoch10,
-                ("-pg %s" % pretrained_G14) if pretrained_G14 != "" else "",
-                ("-pd %s" % pretrained_D15) if pretrained_D15 != "" else "",
-                1 if if_save_latest13 == True else 0,
-                1 if if_cache_gpu17 == True else 0,
-                1 if if_save_every_weights18 == True else 0,
-                version19,
-                log_interval,
-            )
+                config.python_cmd
+                + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s -li %s"
+                % (
+                    exp_dir1,
+                    sr2,
+                    1 if if_f0_3 else 0,
+                    batch_size12,
+                    gpus16,
+                    total_epoch11,
+                    save_epoch10,
+                    ("-pg %s" % pretrained_G14) if pretrained_G14 != "" else "",
+                    ("-pd %s" % pretrained_D15) if pretrained_D15 != "" else "",
+                    1 if if_save_latest13 == True else 0,
+                    1 if if_cache_gpu17 == True else 0,
+                    1 if if_save_every_weights18 == True else 0,
+                    version19,
+                    log_interval,
+                )
         )
     else:
         cmd = (
-            config.python_cmd
-            + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s -li %s"
-            % (
-                exp_dir1,
-                sr2,
-                1 if if_f0_3 else 0,
-                batch_size12,
-                total_epoch11,
-                save_epoch10,
-                ("-pg %s" % pretrained_G14) if pretrained_G14 != "" else "\b",
-                ("-pd %s" % pretrained_D15) if pretrained_D15 != "" else "\b",
-                1 if if_save_latest13 == True else 0,
-                1 if if_cache_gpu17 == True else 0,
-                1 if if_save_every_weights18 == True else 0,
-                version19,
-                log_interval,
-            )
+                config.python_cmd
+                + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s -li %s"
+                % (
+                    exp_dir1,
+                    sr2,
+                    1 if if_f0_3 else 0,
+                    batch_size12,
+                    total_epoch11,
+                    save_epoch10,
+                    ("-pg %s" % pretrained_G14) if pretrained_G14 != "" else "\b",
+                    ("-pd %s" % pretrained_D15) if pretrained_D15 != "" else "\b",
+                    1 if if_save_latest13 == True else 0,
+                    1 if if_cache_gpu17 == True else 0,
+                    1 if if_save_every_weights18 == True else 0,
+                    version19,
+                    log_interval,
+                )
         )
     print(cmd)
     p = Popen(cmd, shell=True, cwd=now_dir)
     global PID
     PID = p.pid
     p.wait()
-    return ("训练结束, 您可查看控制台训练日志或实验文件夹下的train.log", {"visible": False, "__type__": "update"}, {"visible": True, "__type__": "update"})
+    return ("训练结束, 您可查看控制台训练日志或实验文件夹下的train.log", {"visible": False, "__type__": "update"},
+            {"visible": True, "__type__": "update"})
 
 
 # but4.click(train_index, [exp_dir1], info3)
@@ -906,7 +918,7 @@ def train_index(exp_dir1, version19):
     yield "\n".join(infos)
     batch_size_add = 8192
     for i in range(0, big_npy.shape[0], batch_size_add):
-        index.add(big_npy[i : i + batch_size_add])
+        index.add(big_npy[i: i + batch_size_add])
     faiss.write_index(
         index,
         "%s/added_IVF%s_Flat_nprobe_%s_%s_%s.index"
@@ -923,24 +935,24 @@ def train_index(exp_dir1, version19):
 
 # but5.click(train1key, [exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0method8, save_epoch10, total_epoch11, batch_size12, if_save_latest13, pretrained_G14, pretrained_D15, gpus16, if_cache_gpu17], info3)
 def train1key(
-    exp_dir1,
-    sr2,
-    if_f0_3,
-    trainset_dir4,
-    spk_id5,
-    np7,
-    f0method8,
-    save_epoch10,
-    total_epoch11,
-    batch_size12,
-    if_save_latest13,
-    pretrained_G14,
-    pretrained_D15,
-    gpus16,
-    if_cache_gpu17,
-    if_save_every_weights18,
-    version19,
-    echl
+        exp_dir1,
+        sr2,
+        if_f0_3,
+        trainset_dir4,
+        spk_id5,
+        np7,
+        f0method8,
+        save_epoch10,
+        total_epoch11,
+        batch_size12,
+        if_save_latest13,
+        pretrained_G14,
+        pretrained_D15,
+        gpus16,
+        if_cache_gpu17,
+        if_save_every_weights18,
+        version19,
+        echl
 ):
     infos = []
 
@@ -962,10 +974,10 @@ def train1key(
     #########step1:处理数据
     open(preprocess_log_path, "w").close()
     cmd = (
-        config.python_cmd
-        + " trainset_preprocess_pipeline_print.py %s %s %s %s "
-        % (trainset_dir4, sr_dict[sr2], np7, model_log_dir)
-        + str(config.noparallel)
+            config.python_cmd
+            + " trainset_preprocess_pipeline_print.py %s %s %s %s "
+            % (trainset_dir4, sr_dict[sr2], np7, model_log_dir)
+            + str(config.noparallel)
     )
     yield get_info_str(i18n("step1:processing data"))
     yield get_info_str(cmd)
@@ -989,9 +1001,9 @@ def train1key(
         with open(extract_f0_feature_log_path, "r") as f:
             print(f.read())
     else:
-        yield get_info_str(i18n("step2a:No need to extract the pitch"))
+        yield get_info_str(i18n("step2a:无需提取音高"))
     #######step2b:提取特征
-    yield get_info_str(i18n("step2b:Extracting features"))
+    yield get_info_str(i18n("step2b:正在提取特征"))
     gpus = gpus16.split("-")
     leng = len(gpus)
     ps = []
@@ -1014,16 +1026,16 @@ def train1key(
     with open(extract_f0_feature_log_path, "r") as f:
         print(f.read())
     #######step3a:训练模型
-    yield get_info_str(i18n("step3a:training model"))
+    yield get_info_str(i18n("step3a:正在训练模型"))
     # 生成filelist
     if if_f0_3:
         f0_dir = "%s/2a_f0" % model_log_dir
         f0nsf_dir = "%s/2b-f0nsf" % model_log_dir
         names = (
-            set([name.split(".")[0] for name in os.listdir(gt_wavs_dir)])
-            & set([name.split(".")[0] for name in os.listdir(feature_dir)])
-            & set([name.split(".")[0] for name in os.listdir(f0_dir)])
-            & set([name.split(".")[0] for name in os.listdir(f0nsf_dir)])
+                set([name.split(".")[0] for name in os.listdir(gt_wavs_dir)])
+                & set([name.split(".")[0] for name in os.listdir(feature_dir)])
+                & set([name.split(".")[0] for name in os.listdir(f0_dir)])
+                & set([name.split(".")[0] for name in os.listdir(f0nsf_dir)])
         )
     else:
         names = set([name.split(".")[0] for name in os.listdir(gt_wavs_dir)]) & set(
@@ -1076,42 +1088,42 @@ def train1key(
     yield get_info_str("write filelist done")
     if gpus16:
         cmd = (
-            config.python_cmd
-            +" train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s"
-            % (
-                exp_dir1,
-                sr2,
-                1 if if_f0_3 else 0,
-                batch_size12,
-                gpus16,
-                total_epoch11,
-                save_epoch10,
-                ("-pg %s" % pretrained_G14) if pretrained_G14 != "" else "",
-                ("-pd %s" % pretrained_D15) if pretrained_D15 != "" else "",
-                1 if if_save_latest13 == True else 0,
-                1 if if_cache_gpu17 == True else 0,
-                1 if if_save_every_weights18 == True else 0,
-                version19,
-            )
+                config.python_cmd
+                + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s"
+                % (
+                    exp_dir1,
+                    sr2,
+                    1 if if_f0_3 else 0,
+                    batch_size12,
+                    gpus16,
+                    total_epoch11,
+                    save_epoch10,
+                    ("-pg %s" % pretrained_G14) if pretrained_G14 != "" else "",
+                    ("-pd %s" % pretrained_D15) if pretrained_D15 != "" else "",
+                    1 if if_save_latest13 == True else 0,
+                    1 if if_cache_gpu17 == True else 0,
+                    1 if if_save_every_weights18 == True else 0,
+                    version19,
+                )
         )
     else:
         cmd = (
-            config.python_cmd
-            + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s"
-            % (
-                exp_dir1,
-                sr2,
-                1 if if_f0_3 else 0,
-                batch_size12,
-                total_epoch11,
-                save_epoch10,
-                ("-pg %s" % pretrained_G14) if pretrained_G14 != "" else "",
-                ("-pd %s" % pretrained_D15) if pretrained_D15 != "" else "",
-                1 if if_save_latest13 == True else 0,
-                1 if if_cache_gpu17 == True else 0,
-                1 if if_save_every_weights18 == True else 0,
-                version19,
-            )
+                config.python_cmd
+                + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s"
+                % (
+                    exp_dir1,
+                    sr2,
+                    1 if if_f0_3 else 0,
+                    batch_size12,
+                    total_epoch11,
+                    save_epoch10,
+                    ("-pg %s" % pretrained_G14) if pretrained_G14 != "" else "",
+                    ("-pd %s" % pretrained_D15) if pretrained_D15 != "" else "",
+                    1 if if_save_latest13 == True else 0,
+                    1 if if_cache_gpu17 == True else 0,
+                    1 if if_save_every_weights18 == True else 0,
+                    version19,
+                )
         )
     yield get_info_str(cmd)
     p = Popen(cmd, shell=True, cwd=now_dir)
@@ -1146,7 +1158,7 @@ def train1key(
     yield get_info_str("adding index")
     batch_size_add = 8192
     for i in range(0, big_npy.shape[0], batch_size_add):
-        index.add(big_npy[i : i + batch_size_add])
+        index.add(big_npy[i: i + batch_size_add])
     faiss.write_index(
         index,
         "%s/added_IVF%s_Flat_nprobe_%s_%s_%s.index"
@@ -1163,16 +1175,17 @@ def whethercrepeornah(radio):
     mango = True if radio == 'mangio-crepe' or radio == 'mangio-crepe-tiny' else False
     return ({"visible": mango, "__type__": "update"})
 
+
 #                    ckpt_path2.change(change_info_,[ckpt_path2],[sr__,if_f0__])
 def change_info_(ckpt_path):
     if (
-        os.path.exists(ckpt_path.replace(os.path.basename(ckpt_path), "train.log"))
-        == False
+            os.path.exists(ckpt_path.replace(os.path.basename(ckpt_path), "train.log"))
+            == False
     ):
         return {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
     try:
         with open(
-            ckpt_path.replace(os.path.basename(ckpt_path), "train.log"), "r"
+                ckpt_path.replace(os.path.basename(ckpt_path), "train.log"), "r"
         ) as f:
             info = eval(f.read().strip("\n").split("\n")[0].split("\t")[-1])
             sr, f0 = info["sample_rate"], info["if_f0"]
@@ -1189,7 +1202,8 @@ from lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM
 def export_onnx(ModelPath, ExportedPath, MoeVS=True):
     cpt = torch.load(ModelPath, map_location="cpu")
     cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
-    hidden_channels = 256 if cpt.get("version","v1")=="v1"else 768#cpt["config"][-2]  # hidden_channels，为768Vec做准备
+    hidden_channels = 256 if cpt.get("version",
+                                     "v1") == "v1" else 768  # cpt["config"][-2]  # hidden_channels，为768Vec做准备
 
     test_phone = torch.rand(1, 200, hidden_channels)  # hidden unit
     test_phone_lengths = torch.tensor([200]).long()  # hidden unit 长度（貌似没啥用）
@@ -1200,9 +1214,8 @@ def export_onnx(ModelPath, ExportedPath, MoeVS=True):
 
     device = "cpu"  # 导出时设备（不影响使用模型）
 
-
     net_g = SynthesizerTrnMsNSFsidM(
-        *cpt["config"], is_half=False,version=cpt.get("version","v1")
+        *cpt["config"], is_half=False, version=cpt.get("version", "v1")
     )  # fp32导出（C++要支持fp16必须手动将内存重新排列所以暂时不用fp16）
     net_g.load_state_dict(cpt["weight"], strict=False)
     input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds", "rnd"]
@@ -1235,7 +1248,8 @@ def export_onnx(ModelPath, ExportedPath, MoeVS=True):
     )
     return "Finished"
 
-#region RVC WebUI App
+
+# region RVC WebUI App
 
 def get_presets():
     data = None
@@ -1244,25 +1258,28 @@ def get_presets():
     preset_names = []
     for preset in data['presets']:
         preset_names.append(preset['name'])
-    
+
     return preset_names
 
+
 def change_choices2():
-    audio_files=[]
+    audio_files = []
     for filename in os.listdir("./audios"):
-        if filename.endswith(('.wav','.mp3','.ogg','.flac','.m4a','.aac','.mp4')):
-            audio_files.append(os.path.join('./audios',filename).replace('\\', '/'))
+        if filename.endswith(('.wav', '.mp3', '.ogg', '.flac', '.m4a', '.aac', '.mp4')):
+            audio_files.append(os.path.join('./audios', filename).replace('\\', '/'))
     return {"choices": sorted(audio_files), "__type__": "update"}, {"__type__": "update"}
-    
-audio_files=[]
+
+
+audio_files = []
 for filename in os.listdir("./audios"):
-    if filename.endswith(('.wav','.mp3','.ogg','.flac','.m4a','.aac','.mp4')):
-        audio_files.append(os.path.join('./audios',filename).replace('\\', '/'))
-        
+    if filename.endswith(('.wav', '.mp3', '.ogg', '.flac', '.m4a', '.aac', '.mp4')):
+        audio_files.append(os.path.join('./audios', filename).replace('\\', '/'))
+
+
 def get_index():
     if check_for_name() != '':
-        chosen_model=sorted(names)[0].split(".")[0]
-        logs_path="./logs/"+chosen_model
+        chosen_model = sorted(names)[0].split(".")[0]
+        logs_path = "./logs/" + chosen_model
         if os.path.exists(logs_path):
             for file in os.listdir(logs_path):
                 if file.endswith(".index"):
@@ -1270,60 +1287,67 @@ def get_index():
             return ''
         else:
             return ''
-        
+
+
 def get_indexes():
-    indexes_list=[]
+    indexes_list = []
     for dirpath, dirnames, filenames in os.walk("./logs/"):
         for filename in filenames:
             if filename.endswith(".index"):
-                indexes_list.append(os.path.join(dirpath,filename))
+                indexes_list.append(os.path.join(dirpath, filename))
     if len(indexes_list) > 0:
         return indexes_list
     else:
         return ''
-        
+
+
 def get_name():
     if len(audio_files) > 0:
         return sorted(audio_files)[0]
     else:
         return ''
-        
+
+
 def save_to_wav(record_button):
     if record_button is None:
         pass
     else:
-        path_to_file=record_button
-        new_name = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")+'.wav'
-        new_path='./audios/'+new_name
-        shutil.move(path_to_file,new_path)
+        path_to_file = record_button
+        new_name = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S") + '.wav'
+        new_path = './audios/' + new_name
+        shutil.move(path_to_file, new_path)
         return new_path
-    
+
+
 def save_to_wav2(dropbox):
-    file_path=dropbox.name
-    shutil.move(file_path,'./audios')
-    return os.path.join('./audios',os.path.basename(file_path))
-    
+    file_path = dropbox.name
+    shutil.move(file_path, './audios')
+    return os.path.join('./audios', os.path.basename(file_path))
+
+
 def match_index(sid0):
-    folder=sid0.split(".")[0]
-    parent_dir="./logs/"+folder
+    folder = sid0.split(".")[0]
+    parent_dir = "./logs/" + folder
     if os.path.exists(parent_dir):
         for filename in os.listdir(parent_dir):
             if filename.endswith(".index"):
-                index_path=os.path.join(parent_dir,filename)
+                index_path = os.path.join(parent_dir, filename)
                 return index_path
     else:
         return ''
-                
+
+
 def check_for_name():
     if len(names) > 0:
         return sorted(names)[0]
     else:
         return ''
-            
+
+
 def download_from_url(url, model):
     if url == '':
         return "URL cannot be left empty."
-    if model =='':
+    if model == '':
         return "You need to name your model. For example: My-Model"
     url = url.strip()
     zip_dirs = ["zips", "unzips"]
@@ -1344,7 +1368,7 @@ def download_from_url(url, model):
             subprocess.run(["wget", url, "-O", zipfile_path])
         for filename in os.listdir("./zips"):
             if filename.endswith(".zip"):
-                zipfile_path = os.path.join("./zips/",filename)
+                zipfile_path = os.path.join("./zips/", filename)
                 shutil.unpack_archive(zipfile_path, "./unzips", 'zip')
             else:
                 return "No zipfile found."
@@ -1353,16 +1377,20 @@ def download_from_url(url, model):
                 file_path = os.path.join(root, file)
                 if file.endswith(".index"):
                     os.mkdir(f'./logs/{model}')
-                    shutil.copy2(file_path,f'./logs/{model}')
+                    shutil.copy2(file_path, f'./logs/{model}')
                 elif "G_" not in file and "D_" not in file and file.endswith(".pth"):
-                    shutil.copy(file_path,f'./weights/{model}.pth')
+                    shutil.copy(file_path, f'./weights/{model}.pth')
         shutil.rmtree("zips")
         shutil.rmtree("unzips")
         return "Success."
     except:
         return "There's been an error."
+
+
 def success_message(face):
     return f'{face.name} has been uploaded.', 'None'
+
+
 def mouth(size, face, voice, faces):
     if size == 'Half':
         size = 2
@@ -1376,21 +1404,26 @@ def mouth(size, face, voice, faces):
         elif faces == 'Andrew Tate':
             character = '/content/wav2lip-HD/inputs/tate-7.mp4'
     command = "python inference.py " \
-            "--checkpoint_path checkpoints/wav2lip.pth " \
-            f"--face {character} " \
-            f"--audio {voice} " \
-            "--pads 0 20 0 0 " \
-            "--outfile /content/wav2lip-HD/outputs/result.mp4 " \
-            "--fps 24 " \
-            f"--resize_factor {size}"
+              "--checkpoint_path checkpoints/wav2lip.pth " \
+              f"--face {character} " \
+              f"--audio {voice} " \
+              "--pads 0 20 0 0 " \
+              "--outfile /content/wav2lip-HD/outputs/result.mp4 " \
+              "--fps 24 " \
+              f"--resize_factor {size}"
     process = subprocess.Popen(command, shell=True, cwd='/content/wav2lip-HD/Wav2Lip-master')
     stdout, stderr = process.communicate()
     return '/content/wav2lip-HD/outputs/result.mp4', 'Animation completed.'
-eleven_voices = ['Adam','Antoni','Josh','Arnold','Sam','Bella','Rachel','Domi','Elli']
-eleven_voices_ids=['pNInz6obpgDQGcFmaJgB','ErXwobaYiN019PkySvjV','TxGEqnHWrfWFTfGW9XjX','VR6AewLTigWG4xSOukaG','yoZ06aMxZJJ28mfd3POQ','EXAVITQu4vr4xnSDxMaL','21m00Tcm4TlvDq8ikWAM','AZnzlk1XvdvUeBnXmlld','MF3mGyEYCl7XYWbV9V6O']
+
+
+eleven_voices = ['Adam', 'Antoni', 'Josh', 'Arnold', 'Sam', 'Bella', 'Rachel', 'Domi', 'Elli']
+eleven_voices_ids = ['pNInz6obpgDQGcFmaJgB', 'ErXwobaYiN019PkySvjV', 'TxGEqnHWrfWFTfGW9XjX', 'VR6AewLTigWG4xSOukaG',
+                     'yoZ06aMxZJJ28mfd3POQ', 'EXAVITQu4vr4xnSDxMaL', '21m00Tcm4TlvDq8ikWAM', 'AZnzlk1XvdvUeBnXmlld',
+                     'MF3mGyEYCl7XYWbV9V6O']
 chosen_voice = dict(zip(eleven_voices, eleven_voices_ids))
 
-def stoptraining(mim): 
+
+def stoptraining(mim):
     if int(mim) == 1:
         try:
             CSVutil('csvdb/stop.csv', 'w+', 'stop', 'True')
@@ -1398,45 +1431,45 @@ def stoptraining(mim):
         except Exception as e:
             print(f"Couldn't click due to {e}")
     return (
-        {"visible": False, "__type__": "update"}, 
+        {"visible": False, "__type__": "update"},
         {"visible": True, "__type__": "update"},
     )
 
 
 def elevenTTS(xiapi, text, id, lang):
-    if xiapi!= '' and id !='': 
+    if xiapi != '' and id != '':
         choice = chosen_voice[id]
         CHUNK_SIZE = 1024
         url = f"https://api.elevenlabs.io/v1/text-to-speech/{choice}"
         headers = {
-        "Accept": "audio/mpeg",
-        "Content-Type": "application/json",
-        "xi-api-key": xiapi
+            "Accept": "audio/mpeg",
+            "Content-Type": "application/json",
+            "xi-api-key": xiapi
         }
         if lang == 'en':
             data = {
-            "text": text,
-            "model_id": "eleven_monolingual_v1",
-            "voice_settings": {
-            "stability": 0.5,
-            "similarity_boost": 0.5
-            }
+                "text": text,
+                "model_id": "eleven_monolingual_v1",
+                "voice_settings": {
+                    "stability": 0.5,
+                    "similarity_boost": 0.5
+                }
             }
         else:
             data = {
-            "text": text,
-            "model_id": "eleven_multilingual_v1",
-            "voice_settings": {
-            "stability": 0.5,
-            "similarity_boost": 0.5
-            }
+                "text": text,
+                "model_id": "eleven_multilingual_v1",
+                "voice_settings": {
+                    "stability": 0.5,
+                    "similarity_boost": 0.5
+                }
             }
 
         response = requests.post(url, json=data, headers=headers)
         with open('./temp_eleven.mp3', 'wb') as f:
-          for chunk in response.iter_content(chunk_size=CHUNK_SIZE):
-              if chunk:
-                  f.write(chunk)
+            for chunk in response.iter_content(chunk_size=CHUNK_SIZE):
+                if chunk:
+                    f.write(chunk)
         aud_path = save_to_wav('./temp_eleven.mp3')
         return aud_path, aud_path
     else:
@@ -1445,6 +1478,7 @@ def elevenTTS(xiapi, text, id, lang):
         aud_path = save_to_wav('./temp_gTTS.mp3')
         return aud_path, aud_path
 
+
 def upload_to_dataset(files, dir):
     if dir == '':
         dir = './dataset'
@@ -1452,11 +1486,12 @@ def upload_to_dataset(files, dir):
         os.makedirs(dir)
     count = 0
     for file in files:
-        path=file.name
-        shutil.copy2(path,dir)
+        path = file.name
+        shutil.copy2(path, dir)
         count += 1
-    return f' {count} files uploaded to {dir}.'     
-    
+    return f' {count} files uploaded to {dir}.'
+
+
 def zip_downloader(model):
     if not os.path.exists(f'./weights/{model}.pth'):
         return {"__type__": "update"}, f'Make sure the Voice Name is correct. I could not find {model}.pth'
@@ -1470,11 +1505,12 @@ def zip_downloader(model):
     else:
         return f'./weights/{model}.pth', "Could not find Index file."
 
+
 with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
-   # gr.LogoutButton()
+    # gr.LogoutButton()
     with gr.Tabs():
         with gr.TabItem("Interfeys"):
-            gr.HTML ("<center><h1>  Voice DeepFake   </h1></span>")
+            gr.HTML("<center><h1>  Voice DeepFake   </h1></span>")
             # gr.HTML("<center><h3>  Если вы хотите использовать это пространство в частном порядке, я рекомендую продублировать его.  </h3></span>")
             # with gr.Row():
             #     gr.Markdown(
@@ -1497,8 +1533,10 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                 refresh_button = gr.Button("Yangilash", variant="primary")
                 if check_for_name() != '':
                     get_vc(sorted(names)[0])
-                vc_transform0 = gr.Number(label="Kengaytirilgan: Bu yerda siz ovoz balandligini o'zgartirishingiz yoki uni 0 da qoldirishingiz mumkin.", value=0)
-                #clean_button = gr.Button(i18n("卸载音色省显存"), variant="primary")
+                vc_transform0 = gr.Number(
+                    label="Kengaytirilgan: Bu yerda siz ovoz balandligini o'zgartirishingiz yoki uni 0 da qoldirishingiz mumkin.",
+                    value=0)
+                # clean_button = gr.Button(i18n("卸载音色省显存"), variant="primary")
                 spk_item = gr.Slider(
                     minimum=0,
                     maximum=2333,
@@ -1508,7 +1546,7 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                     visible=False,
                     interactive=True,
                 )
-                #clean_button.click(fn=clean, inputs=[], outputs=[sid0])
+                # clean_button.click(fn=clean, inputs=[], outputs=[sid0])
                 sid0.change(
                     fn=get_vc,
                     inputs=[sid0],
@@ -1518,15 +1556,17 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
             with gr.Row():
                 with gr.Column():
                     with gr.Row():
-                        dropbox = gr.File(label='Ovoz yozishingizni shu yerga yuboring va "Qayta yuklash" tugmasini bosing.')
+                        dropbox = gr.File(
+                            label='Ovoz yozishingizni shu yerga yuboring va "Qayta yuklash" tugmasini bosing.')
                     with gr.Row():
-                        record_button=gr.Audio(source="microphone", label="Ovozni mikrofondan yozib oling.", type="filepath")
+                        record_button = gr.Audio(source="microphone", label="Ovozni mikrofondan yozib oling.",
+                                                 type="filepath")
                     with gr.Row():
                         input_audio0 = gr.Dropdown(
                             label="2.Audio yozuvni tanlang.",
                             value="./audios/someguy.mp3",
                             choices=audio_files
-                            )
+                        )
                         dropbox.upload(fn=save_to_wav2, inputs=[dropbox], outputs=[input_audio0])
                         dropbox.upload(fn=change_choices2, inputs=[], outputs=[input_audio0])
                         refresh_button2 = gr.Button("Yangilash", variant="primary", size='sm')
@@ -1544,12 +1584,13 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                     with gr.Row():
                         with gr.Accordion('Wav2Lip', open=False, visible=False):
                             with gr.Row():
-                                size = gr.Radio(label='Resolution:',choices=['Half','Full'])
-                                face = gr.UploadButton("Upload A Character",type='file')
-                                faces = gr.Dropdown(label="OR Choose one:", choices=['None','Ben Shapiro','Andrew Tate'])
+                                size = gr.Radio(label='Resolution:', choices=['Half', 'Full'])
+                                face = gr.UploadButton("Upload A Character", type='file')
+                                faces = gr.Dropdown(label="OR Choose one:",
+                                                    choices=['None', 'Ben Shapiro', 'Andrew Tate'])
                             with gr.Row():
-                                preview = gr.Textbox(label="Status:",interactive=False)
-                                face.upload(fn=success_message,inputs=[face], outputs=[preview, faces])
+                                preview = gr.Textbox(label="Status:", interactive=False)
+                                face.upload(fn=success_message, inputs=[face], outputs=[preview, faces])
                             with gr.Row():
                                 animation = gr.Video(type='filepath')
                                 refresh_button2.click(fn=change_choices2, inputs=[], outputs=[input_audio0, animation])
@@ -1563,11 +1604,11 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             choices=get_indexes(),
                             value=get_index(),
                             interactive=True,
-                            )
-                        sid0.change(fn=match_index, inputs=[sid0],outputs=[file_index1])
+                        )
+                        sid0.change(fn=match_index, inputs=[sid0], outputs=[file_index1])
                         refresh_button.click(
                             fn=change_choices, inputs=[], outputs=[sid0, file_index1]
-                            )
+                        )
                         # file_big_npy1 = gr.Textbox(
                         #     label=i18n("特征文件路径"),
                         #     value="E:\\codes\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
@@ -1579,7 +1620,7 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             label=i18n("Qidiruv funksiyasining nisbati (men uni 0 ga o'rnatishni tavsiya qilaman):"),
                             value=0.66,
                             interactive=True,
-                            )
+                        )
                     vc_output2 = gr.Audio(
                         label="Audio ma'lumotlarni chiqarish (yuklab olish uchun o'ng burchakdagi uchta nuqta ustiga bosing)",
                         type='filepath',
@@ -1589,11 +1630,12 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                     with gr.Accordion("Qo'shimcha sozlamalar", open=False):
                         f0method0 = gr.Radio(
                             label='Majburiy emas: Ovozni ajratib olish algoritmini o\'zgartiring.',
-                            choices=["pm", "dio", "crepe-tiny", "mangio-crepe-tiny", "crepe", "harvest", "mangio-crepe", "rmvpe"], # Fork Feature. Add Crepe-Tiny
+                            choices=["pm", "dio", "crepe-tiny", "mangio-crepe-tiny", "crepe", "harvest", "mangio-crepe",
+                                     "rmvpe"],  # Fork Feature. Add Crepe-Tiny
                             value="rmvpe",
                             interactive=True,
                         )
-                        
+
                         crepe_hop_length = gr.Slider(
                             minimum=1,
                             maximum=512,
@@ -1602,16 +1644,17 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             value=120,
                             interactive=True,
                             visible=False,
-                            )
+                        )
                         f0method0.change(fn=whethercrepeornah, inputs=[f0method0], outputs=[crepe_hop_length])
                         filter_radius0 = gr.Slider(
                             minimum=0,
                             maximum=7,
-                            label=i18n("Agar >=3 boʻlsa: toʻplangan ovoz balandligi natijalariga median filtrlashni qoʻllang. Qiymat filtrlash radiusini ifodalaydi va nafas olishni qisqartirishi mumkin"),
+                            label=i18n(
+                                "Agar >=3 boʻlsa: toʻplangan ovoz balandligi natijalariga median filtrlashni qoʻllang. Qiymat filtrlash radiusini ifodalaydi va nafas olishni qisqartirishi mumkin"),
                             value=3,
                             step=1,
                             interactive=True,
-                            )
+                        )
                         resample_sr0 = gr.Slider(
                             minimum=0,
                             maximum=48000,
@@ -1620,22 +1663,24 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             step=1,
                             interactive=True,
                             visible=False
-                            )
+                        )
                         rms_mix_rate0 = gr.Slider(
                             minimum=0,
                             maximum=1,
-                            label=i18n("Chiqish ovozi konvertini almashtirish yoki aralashtirish uchun kirish ovozi konvertidan foydalaning. Bu nisbat 1 ga qanchalik yaqin bo'lsa, chiqish signali konvertidan shunchalik ko'p foydalaniladi:"),
+                            label=i18n(
+                                "Chiqish ovozi konvertini almashtirish yoki aralashtirish uchun kirish ovozi konvertidan foydalaning. Bu nisbat 1 ga qanchalik yaqin bo'lsa, chiqish signali konvertidan shunchalik ko'p foydalaniladi:"),
                             value=0.21,
                             interactive=True,
-                            )
+                        )
                         protect0 = gr.Slider(
                             minimum=0,
                             maximum=0.5,
-                            label=i18n("Elektron musiqadagi tanaffuslar kabi artefaktlarning oldini olish uchun ovozsiz undosh tovushlarni va nafas tovushlarini himoya qiladi. O'chirish uchun qiymatni 0,5 ga o'rnating. Xavfsizlikni oshirish uchun qiymatni kamaytiring, lekin bu indekslash aniqligini kamaytirishi mumkin:"),
+                            label=i18n(
+                                "Elektron musiqadagi tanaffuslar kabi artefaktlarning oldini olish uchun ovozsiz undosh tovushlarni va nafas tovushlarini himoya qiladi. O'chirish uchun qiymatni 0,5 ga o'rnating. Xavfsizlikni oshirish uchun qiymatni kamaytiring, lekin bu indekslash aniqligini kamaytirishi mumkin:"),
                             value=0.33,
                             step=0.01,
                             interactive=True,
-                            )
+                        )
                         formanting = gr.Checkbox(
                             value=bool(DoFormant),
                             label="[EXPERIMENTAL] Formant shift inference audio",
@@ -1643,7 +1688,7 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             interactive=True,
                             visible=False,
                         )
-                        
+
                         formant_preset = gr.Dropdown(
                             value='',
                             choices=get_fshift_presets(),
@@ -1655,19 +1700,19 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             visible=bool(DoFormant),
                             variant='primary',
                         )
-                        #formant_refresh_button = ToolButton( elem_id='1')
-                        #create_refresh_button(formant_preset, lambda: {"choices": formant_preset}, "refresh_list_shiftpresets")
-                        
+                        # formant_refresh_button = ToolButton( elem_id='1')
+                        # create_refresh_button(formant_preset, lambda: {"choices": formant_preset}, "refresh_list_shiftpresets")
+
                         qfrency = gr.Slider(
-                                value=Quefrency,
-                                info="Default value is 1.0",
-                                label="Quefrency for formant shifting",
-                                minimum=0.0,
-                                maximum=16.0,
-                                step=0.1,
-                                visible=bool(DoFormant),
-                                interactive=True,
-                            )
+                            value=Quefrency,
+                            info="Default value is 1.0",
+                            label="Quefrency for formant shifting",
+                            minimum=0.0,
+                            maximum=16.0,
+                            step=0.1,
+                            visible=bool(DoFormant),
+                            interactive=True,
+                        )
                         tmbre = gr.Slider(
                             value=Timbre,
                             info="Default value is 1.0",
@@ -1678,16 +1723,22 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             visible=bool(DoFormant),
                             interactive=True,
                         )
-                        
-                        formant_preset.change(fn=preset_apply, inputs=[formant_preset, qfrency, tmbre], outputs=[qfrency, tmbre])
+
+                        formant_preset.change(fn=preset_apply, inputs=[formant_preset, qfrency, tmbre],
+                                              outputs=[qfrency, tmbre])
                         frmntbut = gr.Button("Apply", variant="primary", visible=bool(DoFormant))
-                        formanting.change(fn=formant_enabled,inputs=[formanting,qfrency,tmbre,frmntbut,formant_preset,formant_refresh_button],outputs=[formanting,qfrency,tmbre,frmntbut,formant_preset,formant_refresh_button])
-                        frmntbut.click(fn=formant_apply,inputs=[qfrency, tmbre], outputs=[qfrency, tmbre])
-                        formant_refresh_button.click(fn=update_fshift_presets,inputs=[formant_preset, qfrency, tmbre],outputs=[formant_preset, qfrency, tmbre])
+                        formanting.change(fn=formant_enabled,
+                                          inputs=[formanting, qfrency, tmbre, frmntbut, formant_preset,
+                                                  formant_refresh_button],
+                                          outputs=[formanting, qfrency, tmbre, frmntbut, formant_preset,
+                                                   formant_refresh_button])
+                        frmntbut.click(fn=formant_apply, inputs=[qfrency, tmbre], outputs=[qfrency, tmbre])
+                        formant_refresh_button.click(fn=update_fshift_presets, inputs=[formant_preset, qfrency, tmbre],
+                                                     outputs=[formant_preset, qfrency, tmbre])
             with gr.Row():
                 vc_output1 = gr.Textbox("")
                 f0_file = gr.File(label=i18n("F0曲线文件, 可选, 一行一个音高, 代替默认F0及升降调"), visible=False)
-                
+
                 but0.click(
                     vc_single,
                     [
@@ -1708,8 +1759,8 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                     ],
                     [vc_output1, vc_output2],
                 )
-                        
-            with gr.Accordion("Batch Conversion",open=False, visible=False):
+
+            with gr.Accordion("Batch Conversion", open=False, visible=False):
                 with gr.Row():
                     with gr.Column():
                         vc_transform1 = gr.Number(
@@ -1834,14 +1885,16 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
             #     """
             #     )
             with gr.Row():
-                url=gr.Textbox(label="Model URL manzilini kiriting:", placeholder=".pth va .index fayllarni o'z ichiga olgan zipga havolani kiriting")
+                url = gr.Textbox(label="Model URL manzilini kiriting:",
+                                 placeholder=".pth va .index fayllarni o'z ichiga olgan zipga havolani kiriting")
             with gr.Row():
                 model = gr.Textbox(label="Model nomi:")
-                download_button=gr.Button("Yuklash")
+                download_button = gr.Button("Yuklash")
             with gr.Row():
-                status_bar=gr.Textbox(label="")
+                status_bar = gr.Textbox(label="")
                 download_button.click(fn=download_from_url, inputs=[url, model], outputs=[status_bar])
 
+
         def has_two_files_in_pretrained_folder():
             pretrained_folder = "./pretrained/"
             if not os.path.exists(pretrained_folder):
@@ -1851,8 +1904,9 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
             num_files = len(files_in_folder)
             return num_files >= 2
 
-        if has_two_files_in_pretrained_folder():    
-            print("Pretrained weights are downloaded. Training tab enabled!\n-------------------------------")       
+
+        if has_two_files_in_pretrained_folder():
+            print("Pretrained weights are downloaded. Training tab enabled!\n-------------------------------")
             with gr.TabItem("Train", visible=False):
                 with gr.Row():
                     with gr.Column():
@@ -1888,10 +1942,13 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             visible=True
                         )
                         trainset_dir4 = gr.Textbox(label="Path to your dataset (audios, not zip):", value="./dataset")
-                        easy_uploader = gr.Files(label='OR Drop your audios here. They will be uploaded in your dataset path above.',file_types=['audio'])
+                        easy_uploader = gr.Files(
+                            label='OR Drop your audios here. They will be uploaded in your dataset path above.',
+                            file_types=['audio'])
                         but1 = gr.Button("1. Process The Dataset", variant="primary")
                         info1 = gr.Textbox(label="Status (wait until it says 'end preprocess'):", value="")
-                        easy_uploader.upload(fn=upload_to_dataset, inputs=[easy_uploader, trainset_dir4], outputs=[info1])
+                        easy_uploader.upload(fn=upload_to_dataset, inputs=[easy_uploader, trainset_dir4],
+                                             outputs=[info1])
                         but1.click(
                             preprocess_dataset, [trainset_dir4, exp_dir1, sr2, np7], [info1]
                         )
@@ -1917,11 +1974,12 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             label=i18n(
                                 "选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢"
                             ),
-                            choices=["harvest","crepe", "mangio-crepe", "rmvpe"], # Fork feature: Crepe on f0 extraction for training.
+                            choices=["harvest", "crepe", "mangio-crepe", "rmvpe"],
+                            # Fork feature: Crepe on f0 extraction for training.
                             value="rmvpe",
                             interactive=True,
                         )
-                        
+
                         extraction_crepe_hop_length = gr.Slider(
                             minimum=1,
                             maximum=512,
@@ -1931,15 +1989,17 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                             interactive=True,
                             visible=False,
                         )
-                        f0method8.change(fn=whethercrepeornah, inputs=[f0method8], outputs=[extraction_crepe_hop_length])
+                        f0method8.change(fn=whethercrepeornah, inputs=[f0method8],
+                                         outputs=[extraction_crepe_hop_length])
                         but2 = gr.Button("2. Pitch Extraction", variant="primary")
-                        info2 = gr.Textbox(label="Status(Check the Colab Notebook's cell output):", value="", max_lines=8)
+                        info2 = gr.Textbox(label="Status(Check the Colab Notebook's cell output):", value="",
+                                           max_lines=8)
                         but2.click(
-                                extract_f0_feature,
-                                [gpus6, np7, f0method8, if_f0_3, exp_dir1, version19, extraction_crepe_hop_length],
-                                [info2],
-                            )
-                    with gr.Row():      
+                            extract_f0_feature,
+                            [gpus6, np7, f0method8, if_f0_3, exp_dir1, version19, extraction_crepe_hop_length],
+                            [info2],
+                        )
+                    with gr.Row():
                         with gr.Column():
                             total_epoch11 = gr.Slider(
                                 minimum=1,
@@ -1955,15 +2015,17 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                                 visible=False,
                             )
                             but3 = gr.Button("3. Train Model", variant="primary", visible=True)
-                            
-                            but3.click(fn=stoptraining, inputs=[gr.Number(value=0, visible=False)], outputs=[but3, butstop])
-                            butstop.click(fn=stoptraining, inputs=[gr.Number(value=1, visible=False)], outputs=[butstop, but3])
-                            
-                            
+
+                            but3.click(fn=stoptraining, inputs=[gr.Number(value=0, visible=False)],
+                                       outputs=[but3, butstop])
+                            butstop.click(fn=stoptraining, inputs=[gr.Number(value=1, visible=False)],
+                                          outputs=[butstop, but3])
+
                             but4 = gr.Button("4.Train Index", variant="primary")
-                            info3 = gr.Textbox(label="Status(Check the Colab Notebook's cell output):", value="", max_lines=10)
+                            info3 = gr.Textbox(label="Status(Check the Colab Notebook's cell output):", value="",
+                                               max_lines=10)
                             with gr.Accordion("Training Preferences (You can leave these as they are)", open=False):
-                                #gr.Markdown(value=i18n("step3: 填写训练设置, 开始训练模型和索引"))
+                                # gr.Markdown(value=i18n("step3: 填写训练设置, 开始训练模型和索引"))
                                 with gr.Column():
                                     save_epoch10 = gr.Slider(
                                         minimum=1,
@@ -2082,13 +2144,5 @@ with gr.Blocks(theme=gr.themes.Base(), title='Voice DeepFake 💻') as app:
                         info3,
                     )
 
-        # else:
-
-            # print(
-            #     "Pretrained weights not downloaded. Disabling training tab.\n"
-            #     "Wondering how to train a voice? Visit here for the RVC model training guide: https://t.ly/RVC_Training_Guide\n"
-            #     "-------------------------------\n"
-            # )
-                
     app.queue(concurrency_count=511, max_size=1022).launch(auth=("admin", "admin"), share=False, quiet=True)
-#endregion
+# endregion

i18n/uz_UZ.json

@@ -2,8 +2,8 @@
     "Unfortunately, you do not have a working graphics card to support your training": "Afsuski, mashg'ulotingizni qo'llab-quvvatlash uchun mos keladigan GPU mavjud emas.",
     "是": "Ha",
     "step1:processing data": "1-qadam: Ma'lumotlarni qayta ishlash",
-    "step2a: No need to extract the pitch": "2a-qadam: Ohangni chiqarishni o'tkazib yuborish",
-    "step2b:Extracting features": "2b-qadam: Xususiyatlarni ajratib olish",
+    "step2a:无需提取音高": "2a-qadam: Ohangni chiqarishni o'tkazib yuborish",
+    "step2b:正在提取特征": "2b-qadam: Xususiyatlarni ajratib olish",
     "step3a:正在训练模型": "3a qadam: Modelni o'qitish boshlandi",
     "训练结束, 您可查看控制台训练日志或实验文件夹下的train.log": "O'qish yakunlandi. O'quv jurnalini konsolda yoki eksperiment jildi ichidagi 'train.log' faylida tekshirishingiz mumkin.",
     "全流程结束！": "Barcha jarayonlar bajarildi!",