upload files

2023-02-16 15:56:03 +08:00
parent 8d0698261c
commit d60c12e9e5
7 changed files with 356 additions and 29 deletions
@@ -0,0 +1,204 @@
+{
+  "train": {
+    "log_interval": 100,
+    "eval_interval": 1000,
+    "seed": 1234,
+    "epochs": 10000,
+    "learning_rate": 2e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 16,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 8192,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "training_files":"final_annotation_train.txt",
+    "validation_files":"final_annotation_val.txt",
+    "text_cleaners":["cjke_cleaners2"],
+    "max_wav_value": 32768.0,
+    "sampling_rate": 22050,
+    "filter_length": 1024,
+    "hop_length": 256,
+    "win_length": 1024,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null,
+    "add_blank": true,
+    "n_speakers": 1001,
+    "cleaned_text": true
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0.1,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [8,8,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16,16,4,4],
+    "n_layers_q": 3,
+    "use_spectral_norm": false,
+    "gin_channels": 256
+  },
+  "symbols": ["_", ",", ".", "!", "?", "-", "~", "\u2026", "N", "Q", "a", "b", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "s", "t", "u", "v", "w", "x", "y", "z", "\u0251", "\u00e6", "\u0283", "\u0291", "\u00e7", "\u026f", "\u026a", "\u0254", "\u025b", "\u0279", "\u00f0", "\u0259", "\u026b", "\u0265", "\u0278", "\u028a", "\u027e", "\u0292", "\u03b8", "\u03b2", "\u014b", "\u0266", "\u207c", "\u02b0", "`", "^", "#", "*", "=", "\u02c8", "\u02cc", "\u2192", "\u2193", "\u2191", " "],
+  "speakers": {"特别周 Special Week (Umamusume Pretty Derby)": 0,
+    "无声铃鹿 Silence Suzuka (Umamusume Pretty Derby)": 1,
+    "东海帝王 Tokai Teio (Umamusume Pretty Derby)": 2,
+    "丸善斯基 Maruzensky (Umamusume Pretty Derby)": 3,
+    "富士奇迹 Fuji Kiseki (Umamusume Pretty Derby)": 4,
+    "小栗帽 Oguri Cap (Umamusume Pretty Derby)": 5,
+    "黄金船 Gold Ship (Umamusume Pretty Derby)": 6,
+    "伏特加 Vodka (Umamusume Pretty Derby)": 7,
+    "大和赤骥 Daiwa Scarlet (Umamusume Pretty Derby)": 8,
+    "大树快车 Taiki Shuttle (Umamusume Pretty Derby)": 9,
+    "草上飞 Grass Wonder (Umamusume Pretty Derby)": 10,
+    "菱亚马逊 Hishi Amazon (Umamusume Pretty Derby)": 11,
+    "目白麦昆 Mejiro Mcqueen (Umamusume Pretty Derby)": 12,
+    "神鹰 El Condor Pasa (Umamusume Pretty Derby)": 13,
+    "好歌剧 T.M. Opera O (Umamusume Pretty Derby)": 14,
+    "成田白仁 Narita Brian (Umamusume Pretty Derby)": 15,
+    "鲁道夫象征 Symboli Rudolf (Umamusume Pretty Derby)": 16,
+    "气槽 Air Groove (Umamusume Pretty Derby)": 17,
+    "爱丽数码 Agnes Digital (Umamusume Pretty Derby)": 18,
+    "青云天空 Seiun Sky (Umamusume Pretty Derby)": 19,
+    "玉藻十字 Tamamo Cross (Umamusume Pretty Derby)": 20,
+    "美妙姿势 Fine Motion (Umamusume Pretty Derby)": 21,
+    "琵琶晨光 Biwa Hayahide (Umamusume Pretty Derby)": 22,
+    "重炮 Mayano Topgun (Umamusume Pretty Derby)": 23,
+    "曼城茶座 Manhattan Cafe (Umamusume Pretty Derby)": 24,
+    "美普波旁 Mihono Bourbon (Umamusume Pretty Derby)": 25,
+    "目白雷恩 Mejiro Ryan (Umamusume Pretty Derby)": 26,
+    "雪之美人 Yukino Bijin (Umamusume Pretty Derby)": 28,
+    "米浴 Rice Shower (Umamusume Pretty Derby)": 29,
+    "艾尼斯风神 Ines Fujin (Umamusume Pretty Derby)": 30,
+    "爱丽速子 Agnes Tachyon (Umamusume Pretty Derby)": 31,
+    "爱慕织姬 Admire Vega (Umamusume Pretty Derby)": 32,
+    "稻荷一 Inari One (Umamusume Pretty Derby)": 33,
+    "胜利奖券 Winning Ticket (Umamusume Pretty Derby)": 34,
+    "空中神宫 Air Shakur (Umamusume Pretty Derby)": 35,
+    "荣进闪耀 Eishin Flash (Umamusume Pretty Derby)": 36,
+    "真机伶 Curren Chan (Umamusume Pretty Derby)": 37,
+    "川上公主 Kawakami Princess (Umamusume Pretty Derby)": 38,
+    "黄金城市 Gold City (Umamusume Pretty Derby)": 39,
+    "樱花进王 Sakura Bakushin O (Umamusume Pretty Derby)": 40,
+    "采珠 Seeking the Pearl (Umamusume Pretty Derby)": 41,
+    "新光风 Shinko Windy (Umamusume Pretty Derby)": 42,
+    "东商变革 Sweep Tosho (Umamusume Pretty Derby)": 43,
+    "超级小溪 Super Creek (Umamusume Pretty Derby)": 44,
+    "醒目飞鹰 Smart Falcon (Umamusume Pretty Derby)": 45,
+    "荒漠英雄 Zenno Rob Roy (Umamusume Pretty Derby)": 46,
+    "东瀛佐敦 Tosen Jordan (Umamusume Pretty Derby)": 47,
+    "中山庆典 Nakayama Festa (Umamusume Pretty Derby)": 48,
+    "成田大进 Narita Taishin (Umamusume Pretty Derby)": 49,
+    "西野花 Nishino Flower (Umamusume Pretty Derby)": 50,
+    "春乌拉拉 Haru Urara (Umamusume Pretty Derby)": 51,
+    "青竹回忆 Bamboo Memory (Umamusume Pretty Derby)": 52,
+    "待兼福来 Matikane Fukukitaru (Umamusume Pretty Derby)": 55,
+    "名将怒涛 Meisho Doto (Umamusume Pretty Derby)": 57,
+    "目白多伯 Mejiro Dober (Umamusume Pretty Derby)": 58,
+    "优秀素质 Nice Nature (Umamusume Pretty Derby)": 59,
+    "帝王光环 King Halo (Umamusume Pretty Derby)": 60,
+    "待兼诗歌剧 Matikane Tannhauser (Umamusume Pretty Derby)": 61,
+    "生野狄杜斯 Ikuno Dictus (Umamusume Pretty Derby)": 62,
+    "目白善信 Mejiro Palmer (Umamusume Pretty Derby)": 63,
+    "大拓太阳神 Daitaku Helios (Umamusume Pretty Derby)": 64,
+    "双涡轮 Twin Turbo (Umamusume Pretty Derby)": 65,
+    "里见光钻 Satono Diamond (Umamusume Pretty Derby)": 66,
+    "北部玄驹 Kitasan Black (Umamusume Pretty Derby)": 67,
+    "樱花千代王 Sakura Chiyono O (Umamusume Pretty Derby)": 68,
+    "天狼星象征 Sirius Symboli (Umamusume Pretty Derby)": 69,
+    "目白阿尔丹 Mejiro Ardan (Umamusume Pretty Derby)": 70,
+    "八重无敌 Yaeno Muteki (Umamusume Pretty Derby)": 71,
+    "鹤丸刚志 Tsurumaru Tsuyoshi (Umamusume Pretty Derby)": 72,
+    "目白光明 Mejiro Bright (Umamusume Pretty Derby)": 73,
+    "樱花桂冠 Sakura Laurel (Umamusume Pretty Derby)": 74,
+    "成田路 Narita Top Road (Umamusume Pretty Derby)": 75,
+    "也文摄辉 Yamanin Zephyr (Umamusume Pretty Derby)": 76,
+    "真弓快车 Aston Machan (Umamusume Pretty Derby)": 80,
+    "骏川手纲 Hayakawa Tazuna (Umamusume Pretty Derby)": 81,
+    "小林历奇 Kopano Rickey (Umamusume Pretty Derby)": 83,
+    "奇锐骏 Wonder Acute (Umamusume Pretty Derby)": 85,
+    "秋川理事长 President Akikawa (Umamusume Pretty Derby)": 86,
+    "綾地 寧々 Ayachi Nene (Sanoba Witch)": 87,
+    "因幡 めぐる Inaba Meguru (Sanoba Witch)": 88,
+    "椎葉 紬 Shiiba Tsumugi (Sanoba Witch)": 89,
+    "仮屋 和奏 Kariya Wakama (Sanoba Witch)": 90,
+    "戸隠 憧子 Togakushi Touko (Sanoba Witch)": 91,
+    "九条裟罗 Kujou Sara (Genshin Impact)": 92,
+    "芭芭拉 Barbara (Genshin Impact)": 93,
+    "派蒙 Paimon (Genshin Impact)": 94,
+    "荒泷一斗 Arataki Itto (Genshin Impact)": 96,
+    "早柚 Sayu (Genshin Impact)": 97,
+    "香菱 Xiangling (Genshin Impact)": 98,
+    "神里绫华 Kamisato Ayaka (Genshin Impact)": 99,
+    "重云 Chongyun (Genshin Impact)": 100,
+    "流浪者 Wanderer (Genshin Impact)": 102,
+    "优菈 Eula (Genshin Impact)": 103,
+    "凝光 Ningguang (Genshin Impact)": 105,
+    "钟离 Zhongli (Genshin Impact)": 106,
+    "雷电将军 Raiden Shogun (Genshin Impact)": 107,
+    "枫原万叶 Kaedehara Kazuha (Genshin Impact)": 108,
+    "赛诺 Cyno (Genshin Impact)": 109,
+    "诺艾尔 Noelle (Genshin Impact)": 112,
+    "八重神子 Yae Miko (Genshin Impact)": 113,
+    "凯亚 Kaeya (Genshin Impact)": 114,
+    "魈 Xiao (Genshin Impact)": 115,
+    "托马 Thoma (Genshin Impact)": 116,
+    "可莉 Klee (Genshin Impact)": 117,
+    "迪卢克 Diluc (Genshin Impact)": 120,
+    "夜兰 Yelan (Genshin Impact)": 121,
+    "鹿野院平藏 Shikanoin Heizou (Genshin Impact)": 123,
+    "辛焱 Xinyan (Genshin Impact)": 124,
+    "丽莎 Lisa (Genshin Impact)": 125,
+    "云堇 Yun Jin (Genshin Impact)": 126,
+    "坎蒂丝 Candace (Genshin Impact)": 127,
+    "罗莎莉亚 Rosaria (Genshin Impact)": 128,
+    "北斗 Beidou (Genshin Impact)": 129,
+    "珊瑚宫心海 Sangonomiya Kokomi (Genshin Impact)": 132,
+    "烟绯 Yanfei (Genshin Impact)": 133,
+    "久岐忍 Kuki Shinobu (Genshin Impact)": 136,
+    "宵宫 Yoimiya (Genshin Impact)": 139,
+    "安柏 Amber (Genshin Impact)": 143,
+    "迪奥娜 Diona (Genshin Impact)": 144,
+    "班尼特 Bennett (Genshin Impact)": 146,
+    "雷泽 Razor (Genshin Impact)": 147,
+    "阿贝多 Albedo (Genshin Impact)": 151,
+    "温迪 Venti (Genshin Impact)": 152,
+    "空 Player Male (Genshin Impact)": 153,
+    "神里绫人 Kamisato Ayato (Genshin Impact)": 154,
+    "琴 Jean (Genshin Impact)": 155,
+    "艾尔海森 Alhaitham (Genshin Impact)": 156,
+    "莫娜 Mona (Genshin Impact)": 157,
+    "妮露 Nilou (Genshin Impact)": 159,
+    "胡桃 Hu Tao (Genshin Impact)": 160,
+    "甘雨 Ganyu (Genshin Impact)": 161,
+    "纳西妲 Nahida (Genshin Impact)": 162,
+    "刻晴 Keqing (Genshin Impact)": 165,
+    "荧 Player Female (Genshin Impact)": 169,
+    "埃洛伊 Aloy (Genshin Impact)": 179,
+    "柯莱 Collei (Genshin Impact)": 182,
+    "多莉 Dori (Genshin Impact)": 184,
+    "提纳里 Tighnari (Genshin Impact)": 186,
+    "砂糖 Sucrose (Genshin Impact)": 188,
+    "行秋 Xingqiu (Genshin Impact)": 190,
+    "奥兹 Oz (Genshin Impact)": 193,
+    "五郎 Gorou (Genshin Impact)": 198,
+    "达达利亚 Tartalia (Genshin Impact)": 202,
+    "七七 Qiqi (Genshin Impact)": 207,
+    "申鹤 Shenhe (Genshin Impact)": 217,
+    "莱依拉 Layla (Genshin Impact)": 228,
+    "菲谢尔 Fishl (Genshin Impact)": 230,
+    "User": 999
+  }
+
+}
@@ -1,23 +1,31 @@
 import os
 import torch
 import torchaudio
+import argparse
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--denoise_user', type=bool, default=False,
+                        help='whether to denoise user recorded voice')
+    parser.add_argument('--denoise_character', type=bool, default=False,
+                        help='whether to denoise uploaded character voice')
+    args = parser.parse_args()
+    if args.denoise_user:
+        audio_dir = "./user_voice/"
+        wavfiles = []
+        for filename in list(os.walk(audio_dir))[0][2]:
+            if filename.endswith(".wav"):
+                wavfiles.append(filename)

-audio_dir = "./user_voice/"
-wavfiles = []
-for filename in list(os.walk(audio_dir))[0][2]:
-    if filename.endswith(".wav"):
-        wavfiles.append(filename)
+        # denoise with demucs
+        for i, wavfile in enumerate(wavfiles):
+            os.system(f"demucs --two-stems=vocals {audio_dir}{wavfile}")

-# denoise with demucs
-for i, wavfile in enumerate(wavfiles):
-    os.system(f"demucs --two-stems=vocals {audio_dir}{wavfile}")
-
-# read & store the denoised vocals back
-for wavfile in wavfiles:
-    i = wavfile.strip(".wav")
-    wav, sr = torchaudio.load(f"./separated/htdemucs/{i}/vocals.wav", frame_offset=0, num_frames=-1, normalize=True, channels_first=True)
-    # merge two channels into one
-    wav = wav.mean(dim=0).unsqueeze(0)
-    if sr != 22050:
-        wav = torchaudio.transforms.Resample(orig_freq=sr, new_freq=22050)(wav)
-    torchaudio.save(f"./user_voice/{i}.wav", wav, 22050, channels_first=True)
+        # read & store the denoised vocals back
+        for wavfile in wavfiles:
+            i = wavfile.strip(".wav")
+            wav, sr = torchaudio.load(f"./separated/htdemucs/{i}/vocals.wav", frame_offset=0, num_frames=-1, normalize=True, channels_first=True)
+            # merge two channels into one
+            wav = wav.mean(dim=0).unsqueeze(0)
+            if sr != 22050:
+                wav = torchaudio.transforms.Resample(orig_freq=sr, new_freq=22050)(wav)
+            torchaudio.save(f"./user_voice/{i}.wav", wav, 22050, channels_first=True)
@@ -150,7 +150,7 @@ def train_and_evaluate(rank, epoch, hps, nets, optims, schedulers, scaler, loade

  net_g.train()
  net_d.train()
-  for batch_idx, (x, x_lengths, spec, spec_lengths, y, y_lengths, speakers) in enumerate(tqdm(train_loader)):
+  for batch_idx, (x, x_lengths, spec, spec_lengths, y, y_lengths, speakers) in enumerate(train_loader):
    x, x_lengths = x.cuda(rank, non_blocking=True), x_lengths.cuda(rank, non_blocking=True)
    spec, spec_lengths = spec.cuda(rank, non_blocking=True), spec_lengths.cuda(rank, non_blocking=True)
    y, y_lengths = y.cuda(rank, non_blocking=True), y_lengths.cuda(rank, non_blocking=True)
@@ -250,7 +250,8 @@ def train_and_evaluate(rank, epoch, hps, nets, optims, schedulers, scaler, loade
        # if os.path.exists(old_d):
        #   os.remove(old_d)
    global_step += 1
-    if global_step == hps.n_steps + 1:
+    if epoch > hps.max_epochs:
+        print("Maximum epoch reached, closing training...")
        exit()

  if rank == 0:
@@ -1,5 +1,4 @@
 import os
-MIN_VOICE_NUM = 10
 if __name__ == "__main__":
    # load sampled_audio4ft
    with open("sampled_audio4ft.txt", 'r', encoding='utf-8') as f:
@@ -8,16 +7,27 @@ if __name__ == "__main__":
    # load user text
    with open("./user_voice/user_voice.txt.cleaned", 'r', encoding='utf-8') as f:
        user_annos = f.readlines()
+
    # check how many voices are recorded
    wavfiles = [file for file in list(os.walk("./user_voice"))[0][2] if file.endswith(".wav")]
    num_user_voices = len(wavfiles)
-    if num_user_voices < MIN_VOICE_NUM:
-        raise Exception(f"You need to record at least {MIN_VOICE_NUM} voices for fine-tuning!")
    # user voices need to occupy 1/4 of the total dataset
-    duplicate = num_old_voices // num_user_voices // 3
+    if num_user_voices:
+        user_duplicate = num_old_voices // num_user_voices // 3
+    else:
+        user_duplicate = 0
+
    # find corresponding existing annotation lines
    actual_user_annos = ["./user_voice/" + line for line in user_annos if line.split("|")[0] in wavfiles]
-    final_annos = old_annos + actual_user_annos * duplicate
+    final_annos = old_annos + actual_user_annos * user_duplicate
+
+    # load custom characters
+    with open("custom_character_anno.txt", 'r', encoding='utf-8') as f:
+        custom_character_anno = f.readlines()
+    # custom character voices need to be at least equal to number of sample_audio4ft
+    num_character_voices = len(custom_character_anno)
+    cc_duplicate = num_old_voices // num_character_voices
+    final_annos = final_annos + custom_character_anno * cc_duplicate
    # save annotation file
    with open("final_annotation_train.txt", 'w', encoding='utf-8') as f:
        for line in final_annos:
@@ -26,3 +36,5 @@ if __name__ == "__main__":
    with open("final_annotation_val.txt", 'w', encoding='utf-8') as f:
        for line in actual_user_annos:
            f.write(line)
+        for line in custom_character_anno:
+            f.write(line)
@@ -148,12 +148,12 @@ def load_filepaths_and_text(filename, split="|"):

 def get_hparams(init=True):
    parser = argparse.ArgumentParser()
-    parser.add_argument('-c', '--config', type=str, default="./configs/finetune_speaker.json",
+    parser.add_argument('-c', '--config', type=str, default="./configs/modified_finetune_speaker.json",
                        help='JSON file for configuration')
    parser.add_argument('-m', '--model', type=str, default="pretrained_models",
                        help='Model name')
-    parser.add_argument('-n', '--n_steps', type=int, default="2000",
-                        help='finetune steps')
+    parser.add_argument('-n', '--max_epochs', type=int, default="50",
+                        help='finetune epochs')

    args = parser.parse_args()
    model_dir = os.path.join("./", args.model)
@@ -175,7 +175,7 @@ def get_hparams(init=True):

    hparams = HParams(**config)
    hparams.model_dir = model_dir
-    hparams.n_steps = args.n_steps
+    hparams.max_epochs = args.max_epochs
    return hparams


@@ -0,0 +1,11 @@
+from google.colab import files
+import shutil
+import os
+basepath = os.getcwd()
+uploaded = files.upload() # 上传文件
+upload_path = "./custom_character_voice/"
+if not os.path.exists(upload_path):
+  os.mkdir(upload_path)
+for filename in uploaded.keys():
+    #将上传的文件移动到指定的位置上
+    shutil.move(os.path.join(basepath, filename), os.path.join(upload_path, filename))
@@ -0,0 +1,91 @@
+import whisper
+import os
+import torchaudio
+
+lang2token = {
+    'zh': "[ZH]",
+    'ja': "[JA]",
+    "en": "[EN]",
+}
+
+
+
+
+def transcribe_one(audio_path):
+    # load audio and pad/trim it to fit 30 seconds
+    audio = whisper.load_audio(audio_path)
+    audio = whisper.pad_or_trim(audio)
+
+    # make log-Mel spectrogram and move to the same device as the model
+    mel = whisper.log_mel_spectrogram(audio).to(model.device)
+
+    # detect the spoken language
+    _, probs = model.detect_language(mel)
+    print(f"Detected language: {max(probs, key=probs.get)}")
+    lang = max(probs, key=probs.get)
+    # decode the audio
+    options = whisper.DecodingOptions()
+    result = whisper.decode(model, mel, options)
+
+    # print the recognized text
+    print(result.text)
+    return lang, result.text
+if __name__ == "__main__":
+    model = whisper.load_model("medium")
+    parent_dir = "./custom_character_voice/"
+    speaker_names = list(os.walk(parent_dir))[0][1]
+    speaker2id = {}
+    speaker_annos = []
+    # resample audios
+    for speaker in speaker_names:
+        speaker2id[speaker] = 1000 + len(speaker2id)
+        for i, wavfile in enumerate(list(os.walk(parent_dir + speaker))[0][2]):
+            # try to load file as audio
+            if wavfile.startswith("processed_"):
+                continue
+            try:
+                wav, sr = torchaudio.load(parent_dir + speaker + "/" + wavfile, frame_offset=0, num_frames=-1, normalize=True,
+                                          channels_first=True)
+                wav = wav.mean(dim=0).unsqueeze(0)
+                if sr != 22050:
+                    wav = torchaudio.transforms.Resample(orig_freq=sr, new_freq=22050)(wav)
+                if wav.shape[1] / sr > 20:
+                    print(f"{wavfile} too long, ignoring\n")
+                save_path = parent_dir + speaker + "/" + f"processed_{i}.wav"
+                torchaudio.save(save_path, wav, 22050, channels_first=True)
+                # transcribe text
+                lang, text = transcribe_one(save_path)
+                if lang not in ['zh', 'en', 'ja']:
+                    print(f"{lang} not supported, ignoring\n")
+                text = lang2token[lang] + text + lang2token[lang] + "\n"
+                speaker_annos.append(save_path + "|" + str(speaker2id[speaker]) + "|" + text)
+            except:
+                continue
+
+    # clean annotation
+    import argparse
+    import text
+    from utils import load_filepaths_and_text
+    for i, line in enumerate(speaker_annos):
+        path, sid, txt = line.split("|")
+        cleaned_text = text._clean_text(txt, ["cjke_cleaners2"])
+        cleaned_text += "\n" if not cleaned_text.endswith("\n") else ""
+        speaker_annos[i] = path + "|" + sid + "|" + cleaned_text
+    # write into annotation
+    with open("custom_character_anno.txt", 'w', encoding='utf-8') as f:
+        for line in speaker_annos:
+            f.write(line)
+
+    import json
+    # generate new config
+    with open("./configs/finetune_speaker.json", 'r', encoding='utf-8') as f:
+        hps = json.load(f)
+    # modify n_speakers
+    hps['data']["n_speakers"] = 999 + len(speaker2id)
+    # add speaker names
+    for speaker in speaker_names:
+        hps['speakers'][speaker] = speaker2id[speaker]
+    # save modified config
+    with open("./configs/modified_finetune_speaker.json", 'w', encoding='utf-8') as f:
+        json.dump(hps, f, indent=2)
+    print("finished")