Training failed (?) - Githubissues

Hi i try to run the google colab you attached in the ReadMe, I have converted the audio file into wav 16bit 22050hz mono, and none of the files are bigger than 1mb since it got lowered after i convert it into 16bit. i can't tell where did i went wrong, can i get help where did i miss?
INFO:checkpoints:{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, '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': 'filelists/ui_train.txt.cleaned', 'validation_files': 'filelists/ui_val.txt.cleaned', 'text_cleaners': ['japanese_cleaners'], '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': None, 'add_blank': True, 'n_speakers': 804, '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}, 'speakers': ['特别周', '无声铃鹿', '东海帝皇（帝宝，帝王）', '丸善斯基', '富士奇迹', '小栗帽', '黄金船', '伏特加', '大和赤骥', '大树快车', '草上飞', '菱亚马逊', '目白麦昆', '神鹰', '好歌剧', '成田白仁', '鲁道夫象征（皇帝）', '气槽', '爱丽数码', '星云天空', '玉藻十字', '美妙姿势', '琵琶晨光', '摩耶重炮', '曼城茶座', '美浦波旁', '目白赖恩', '菱曙', '雪中美人', '米浴', '艾尼斯风神', '爱丽速子（爱丽快子）', '爱慕织姬', '稻荷一', '胜利奖券', '空中神宫', '荣进闪耀', '真机伶', '川上公主', '黄金城（黄金城市）', '樱花进王', '采珠', '新光风', '东商变革', '超级小海湾', '醒目飞鹰（寄寄子）', '荒漠英雄', '东瀛佐敦', '中山庆典', '成田大进', '西野花', '春丽（乌拉拉）', '青竹回忆', '微光飞驹', '美丽周日', '待兼福来', 'mr cb（cb先生）', '名将怒涛（名将户仁）', '目白多伯', '优秀素质', '帝王光辉', '待兼诗歌剧', '生野狄杜斯', '目白善信', '大拓太阳神', '双涡轮（两立直，两喷射，二锅头，逆喷射）', '里见光钻（萨托诺金刚石）', '北部玄驹', '樱花千代王', '天狼星象征', '目白阿尔丹', '八重无敌', '鹤丸刚志', '目白光明', '成田拜仁（成田路）', '也文摄辉', '小林历奇', '北港火山', '奇锐骏', '苦涩糖霜', '小小蚕茧', '骏川手纲（绿帽恶魔）', '秋川弥生（小小理事长）', '乙名史悦子（乙名记者）', '桐生院葵', '安心泽刺刺美', '樫本理子', '神里绫华（龟龟）', '琴', '空（空哥）', '丽莎', '荧（荧妹）', '芭芭拉', '凯亚', '迪卢克', '雷泽', '安柏', '温迪', '香菱', '北斗', '行秋', '魈', '凝光', '可莉', '钟离', '菲谢尔（皇女）', '班尼特', '达达利亚（公子）', '诺艾尔（女仆）', '七七', '重云', '甘雨（椰羊）', '阿贝多', '迪奥娜（猫猫）', '莫娜', '刻晴', '砂糖', '辛焱', '罗莎莉亚', '胡桃', '枫原万叶（万叶）', '烟绯', '宵宫', '托马', '优菈', '雷电将军（雷神）', '早柚', '珊瑚宫心海（心海，扣扣米）', '五郎', '九条裟罗', '荒泷一斗（一斗）', '埃洛伊', '申鹤', '八重神子（神子）', '神里绫人（绫人）', '夜兰', '久岐忍', '鹿野苑平藏', '提纳里', '柯莱', '多莉', '云堇', '纳西妲（草神）', '深渊使徒', '妮露', '赛诺', '债务处理人', '坎蒂丝', '真弓快车', '秋人', '望族', '艾尔菲', '艾莉丝', '艾伦', '阿洛瓦', '天野', '天目十五', '愚人众-安德烈', '安顺', '安西', '葵', '青木', '荒川幸次', '荒谷', '有泽', '浅川', '麻美', '凝光助手', '阿托', '竺子', '百识', '百闻', '百晓', '白术', '贝雅特丽奇', '丽塔', '失落迷迭', '缭乱星棘', '伊甸', '伏特加女孩', '狂热蓝调', '莉莉娅', '萝莎莉娅', '八重樱', '八重霞', '卡莲', '第六夜想曲', '卡萝尔', '姬子', '极地战刃', '布洛妮娅', '次生银翼', '理之律者%26希儿', '理之律者', '迷城骇兔', '希儿', '魇夜星渊', '黑希儿', '帕朵菲莉丝', '不灭星锚', '天元骑英', '幽兰黛尔', '派蒙bh3', '爱酱', '绯玉丸', '德丽莎', '月下初拥', '朔夜观星', '暮光骑士', '格蕾修', '留云借风真君', '梅比乌斯', '仿犹大', '克莱因', '圣剑幽兰黛尔', '妖精爱莉', '特斯拉zero', '苍玄', '若水', '西琳', '戴因斯雷布', '贝拉', '赤鸢', '镇魂歌', '渡鸦', '人之律者', '爱莉希雅', '天穹游侠', '琪亚娜', '空之律者', '薪炎之律者', '云墨丹心', '符华', '识之律者', '特瓦林', '维尔薇', '芽衣', '雷之律者', '断罪影舞', '阿波尼亚', '榎本', '厄尼斯特', '恶龙', '范二爷', '法拉', '愚人众士兵', '愚人众士兵a', '愚人众士兵b', '愚人众士兵c', '愚人众a', '愚人众b', '飞飞', '菲利克斯', '女性跟随者', '逢岩', '摆渡人', '狂躁的男人', '奥兹', '芙萝拉', '跟随者', '蜜汁生物', '黄麻子', '渊上', '藤木', '深见', '福本', '芙蓉', '古泽', '古田', '古山', '古谷昇', '傅三儿', '高老六', '矿工冒', '元太', '德安公', '茂才公', '杰拉德', '葛罗丽', '金忽律', '公俊', '锅巴', '歌德', '阿豪', '狗三儿', '葛瑞丝', '若心', '阿山婆', '怪鸟', '广竹', '观海', '关宏', '蜜汁卫兵', '守卫1', '傲慢的守卫', '害怕的守卫', '贵安', '盖伊', '阿创', '哈夫丹', '日语阿贝多（野岛健儿）', '日语埃洛伊（高垣彩阳）', '日语安柏（石见舞菜香）', '日语神里绫华（早见沙织）', '日语神里绫人（石田彰）', '日语白术（游佐浩二）', '日语芭芭拉（鬼头明里）', '日语北斗（小清水亚美）', '日语班尼特（逢坂良太）', '日语坎蒂丝（柚木凉香）', '日语重云（齐藤壮马）', '日语柯莱（前川凉子）', '日语赛诺（入野自由）', '日语戴因斯雷布（津田健次郎）', '日语迪卢克（小野贤章）', '日语迪奥娜（井泽诗织）', '日语多莉（金田朋子）', '日语优菈（佐藤利奈）', '日语菲谢尔（内田真礼）', '日语甘雨（上田丽奈）', '日语（畠中祐）', '日语鹿野院平藏（井口祐一）', '日语空（堀江瞬）', '日语荧（悠木碧）', '日语胡桃（高桥李依）', '日语一斗（西川贵教）', '日语凯亚（鸟海浩辅）', '日语万叶（岛崎信长）', '日语刻晴（喜多村英梨）', '日语可莉（久野美咲）', '日语心海（三森铃子）', '日语九条裟罗（濑户麻沙美）', '日语丽莎（田中理惠）', '日语莫娜（小原好美）', '日语纳西妲（田村由加莉）', '日语妮露（金元寿子）', '日语凝光（大原沙耶香）', '日语诺艾尔（高尾奏音）', '日语奥兹（增谷康纪）', '日语派蒙（古贺葵）', '日语琴（斋藤千和）', '日语七七（田村由加莉）', '日语雷电将军（泽城美雪）', '日语雷泽（内山昂辉）', '日语罗莎莉亚（加隈亚衣）', '日语早柚（洲崎绫）', '日语散兵（柿原彻也）', '日语申鹤（川澄绫子）', '日语久岐忍（水桥香织）', '日语女士（庄子裕衣）', '日语砂糖（藤田茜）', '日语达达利亚（木村良平）', '日语托马（森田成一）', '日语提纳里（小林沙苗）', '日语温迪（村濑步）', '日语香菱（小泽亚李）', '日语魈（松冈祯丞）', '日语行秋（皆川纯子）', '日语辛焱（高桥智秋）', '日语八重神子（佐仓绫音）', '日语烟绯（花守由美里）', '日语夜兰（远藤绫）', '日语宵宫（植田佳奈）', '日语云堇（小岩井小鸟）', '日语钟离（前野智昭）', '杰克', '阿吉', '江舟', '鉴秋', '嘉义', '纪芳', '景澄', '经纶', '景明', '晋优', '阿鸠', '酒客', '乔尔', '乔瑟夫', '约顿', '乔伊斯', '居安', '君君', '顺吉', '纯也', '重佐', '大岛纯平', '蒲泽', '勘解由小路健三郎', '枫', '枫原义庆', '荫山', '甲斐田龍馬', '海斗', '惟神晴之介', '鹿野奈奈', '卡琵莉亚', '凯瑟琳', '加藤信悟', '加藤洋平', '胜家', '茅葺一庆', '和昭', '一正', '一道', '桂一', '庆次郎', '阿贤', '健司', '健次郎', '健三郎', '天理', '杀手a', '杀手b', '木南杏奈', '木村', '国王', '木下', '北村', '清惠', '清人', '克列门特', '骑士', '小林', '小春', '康拉德', '大肉丸', '琴美', '宏一', '康介', '幸德', '高善', '梢', '克罗索', '久保', '九条镰治', '久木田', '昆钧', '菊地君', '久利须', '黑田', '黑泽京之介', '响太', '岚姐', '兰溪', '澜阳', '劳伦斯', '乐明', '莱诺', '莲', '良子', '李当', '李丁', '小乐', '灵', '小玲', '琳琅a', '琳琅b', '小彬', '小德', '小楽', '小龙', '小吴', '小吴的记忆', '理正', '阿龙', '卢卡', '洛成', '罗巧', '北风狼', '卢正', '萍姥姥', '前田', '真昼', '麻纪', '真', '愚人众-马克西姆', '女性a', '女性b', '女性a的跟随者', '阿守', '玛格丽特', '真理', '玛乔丽', '玛文', '正胜', '昌信', '将司', '正人', '路爷', '老章', '松田', '松本', '松浦', '松坂', '老孟', '孟丹', '商人随从', '传令兵', '米歇尔', '御舆源一郎', '御舆源次郎', '千岩军教头', '千岩军士兵', '明博', '明俊', '美铃', '美和', '阿幸', '削月筑阳真君', '钱眼儿', '森彦', '元助', '理水叠山真君', '理水疊山真君', '朱老板', '木木', '村上', '村田', '永野', '长野原龙之介', '长濑', '中野志乃', '菜菜子', '楠楠', '成濑', '阿内', '宁禄', '牛志', '信博', '伸夫', '野方', '诺拉', '纪香', '诺曼', '修女', '纯水精灵', '小川', '小仓澪', '冈林', '冈崎绘里香', '冈崎陆斗', '奥拉夫', '老科', '鬼婆婆', '小野寺', '大河原五右卫门', '大久保大介', '大森', '大助', '奥特', '派蒙', '派蒙2', '病人a', '病人b', '巴顿', '派恩', '朋义', '围观群众', '围观群众a', '围观群众b', '围观群众c', '围观群众d', '围观群众e', '铜雀', '阿肥', '兴叔', '老周叔', '公主', '彼得', '乾子', '芊芊', '乾玮', '绮命', '杞平', '秋月', '昆恩', '雷电影', '兰道尔', '雷蒙德', '冒失的帕拉德', '伶一', '玲花', '阿仁', '家臣们', '梨绘', '荣江', '戎世', '浪人', '罗伊斯', '如意', '凉子', '彩香', '酒井', '坂本', '朔次郎', '武士a', '武士b', '武士c', '武士d', '珊瑚', '三田', '莎拉', '笹野', '聪美', '聪', '小百合', '散兵', '害怕的小刘', '舒伯特', '舒茨', '海龙', '世子', '谢尔盖', '家丁', '商华', '沙寅', '阿升', '柴田', '阿茂', '式大将', '清水', '志村勘兵卫', '新之丞', '志织', '石头', '诗羽', '诗筠', '石壮', '翔太', '正二', '周平', '舒杨', '齐格芙丽雅', '女士', '思勤', '六指乔瑟', '愚人众小兵d', '愚人众小兵a', '愚人众小兵b', '愚人众小兵c', '吴老五', '吴老二', '滑头鬼', '言笑', '吴老七', '士兵h', '士兵i', '士兵a', '士兵b', '士兵c', '士兵d', '士兵e', '士兵f', '士兵g', '奏太', '斯坦利', '掇星攫辰天君', '小头', '大武', '陶义隆', '杉本', '苏西', '嫌疑人a', '嫌疑人b', '嫌疑人c', '嫌疑人d', '斯万', '剑客a', '剑客b', '阿二', '忠胜', '忠夫', '阿敬', '孝利', '鹰司进', '高山', '九条孝行', '毅', '竹内', '拓真', '卓也', '太郎丸', '泰勒', '手岛', '哲平', '哲夫', '托克', '大boss', '阿强', '托尔德拉', '旁观者', '天成', '阿大', '蒂玛乌斯', '提米', '户田', '阿三', '一起的人', '德田', '德长', '智树', '利彦', '胖乎乎的旅行者', '藏宝人a', '藏宝人b', '藏宝人c', '藏宝人d', '阿祇', '恒雄', '露子', '话剧团团长', '内村', '上野', '上杉', '老戴', '老高', '老贾', '老墨', '老孙', '天枢星', '老云', '有乐斋', '丑雄', '乌维', '瓦京', '菲尔戈黛特', '维多利亚', '薇尔', '瓦格纳', '阿外', '侍女', '瓦拉', '望雅', '宛烟', '琬玉', '战士a', '战士b', '渡辺', '渡部', '阿伟', '文璟', '文渊', '韦尔纳', '王扳手', '武沛', '晓飞', '辛程', '星火', '星稀', '辛秀', '秀华', '阿旭', '徐刘师', '矢部', '八木', '山上', '阿阳', '颜笑', '康明', '泰久', '安武', '矢田幸喜', '矢田辛喜', '义坚', '莺儿', '盈丰', '宜年', '银杏', '逸轩', '横山', '永贵', '永业', '嘉久', '吉川', '义高', '用高', '阳太', '元蓉', '玥辉', '毓华', '有香', '幸也', '由真', '结菜', '韵宁', '百合', '百合华', '尤苏波夫', '裕子', '悠策', '悠也', '于嫣', '柚子', '老郑', '正茂', '志成', '芷巧', '知易', '支支', '周良', '珠函', '祝明', '祝涛'], 'symbols': ['_', ',', '.', '!', '?', '-', '~', '…', 'A', 'E', 'I', 'N', 'O', 'Q', 'U', 'a', 'b', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'r', 's', 't', 'u', 'v', 'w', 'y', 'z', 'ʃ', 'ʧ', 'ʦ', 'ɯ', 'ɹ', 'ə', 'ɥ', '⁼', 'ʰ', '`', '→', '↓', '↑', ' '], 'model_dir': '../drive/MyDrive/vits-finetune/checkpoints'}
2023-04-04 12:16:24.511382: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
2023-04-04 12:16:25.456154: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:h5py._conv:Creating converter from 7 to 5
DEBUG:h5py._conv:Creating converter from 5 to 7
DEBUG:jaxlib.mlir._mlir_libs:Initializing MLIR with module: _site_initialize_0
DEBUG:jaxlib.mlir._mlir_libs:Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._site_initialize_0' from '/usr/local/lib/python3.9/dist-packages/jaxlib/mlir/_mlir_libs/_site_initialize_0.so'>
DEBUG:jax._src.path:etils.epath found. Using etils.epath for file I/O.
INFO:numexpr.utils:NumExpr defaulting to 2 threads.
INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0
INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes.
/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py:563: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
  warnings.warn(_create_warning_msg(
../drive/MyDrive/vits-finetune/checkpoints/G_0.pth
INFO:checkpoints:Loaded checkpoint '../drive/MyDrive/vits-finetune/checkpoints/G_0.pth' (iteration 0)
../drive/MyDrive/vits-finetune/checkpoints/D_0.pth
INFO:checkpoints:Loaded checkpoint '../drive/MyDrive/vits-finetune/checkpoints/D_0.pth' (iteration 0)
  0% 0/7 [00:00<?, ?it/s]/content/vits-finetuning/utils.py:138: WavFileWarning: Chunk (non-data) not understood, skipping it.
  sampling_rate, data = read(full_path)
/content/vits-finetuning/utils.py:138: WavFileWarning: Chunk (non-data) not understood, skipping it.
  sampling_rate, data = read(full_path)
/content/vits-finetuning/utils.py:138: WavFileWarning: Chunk (non-data) not understood, skipping it.
  sampling_rate, data = read(full_path)
/content/vits-finetuning/utils.py:138: WavFileWarning: Chunk (non-data) not understood, skipping it.
  sampling_rate, data = read(full_path)
/content/vits-finetuning/utils.py:138: WavFileWarning: Chunk (non-data) not understood, skipping it.
  sampling_rate, data = read(full_path)
/content/vits-finetuning/utils.py:138: WavFileWarning: Chunk (non-data) not understood, skipping it.
  sampling_rate, data = read(full_path)
/content/vits-finetuning/utils.py:138: WavFileWarning: Chunk (non-data) not understood, skipping it.
  sampling_rate, data = read(full_path)
/usr/local/lib/python3.9/dist-packages/torch/functional.py:606: UserWarning: stft will soon require the return_complex parameter be given for real inputs, and will further require that return_complex=True in a future PyTorch release. (Triggered internally at  ../aten/src/ATen/native/SpectralOps.cpp:803.)
  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]
/usr/local/lib/python3.9/dist-packages/torch/functional.py:606: UserWarning: ComplexHalf support is experimental and many operators don't support it yet. (Triggered internally at  ../aten/src/ATen/EmptyTensor.cpp:32.)
  return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore[attr-defined]
INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration.
/usr/local/lib/python3.9/dist-packages/torch/autograd/__init__.py:173: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
grad.sizes() = [1, 9, 96], strides() = [28896, 96, 1]
bucket_view.sizes() = [1, 9, 96], strides() = [864, 96, 1] (Triggered internally at  ../torch/csrc/distributed/c10d/reducer.cpp:326.)
  Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
 14% 1/7 [00:19<01:56, 19.39s/it]INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration.
 86% 6/7 [00:28<00:04,  4.67s/it]
corrupted size vs. prev_size while consolidating
Traceback (most recent call last):
  File "/content/vits-finetuning/train_ms.py", line 306, in <module>
    main()
  File "/content/vits-finetuning/train_ms.py", line 56, in main
    mp.spawn(run, nprocs=n_gpus, args=(n_gpus, hps,))
  File "/usr/local/lib/python3.9/dist-packages/torch/multiprocessing/spawn.py", line 240, in spawn
    return start_processes(fn, args, nprocs, join, daemon, start_method='spawn')
  File "/usr/local/lib/python3.9/dist-packages/torch/multiprocessing/spawn.py", line 198, in start_processes
    while not context.join():
  File "/usr/local/lib/python3.9/dist-packages/torch/multiprocessing/spawn.py", line 160, in join
    raise ProcessRaisedException(msg, error_index, failed_process.pid)
torch.multiprocessing.spawn.ProcessRaisedException: 

-- Process 0 terminated with the following error:
Traceback (most recent call last):
  File "/usr/local/lib/python3.9/dist-packages/torch/multiprocessing/spawn.py", line 69, in _wrap
    fn(i, *args)
  File "/content/vits-finetuning/train_ms.py", line 124, in run
    train_and_evaluate(rank, epoch, hps, [net_g, net_d], [optim_g, optim_d], [scheduler_g, scheduler_d], scaler, [train_loader, eval_loader], logger, [writer, writer_eval])
  File "/content/vits-finetuning/train_ms.py", line 144, in train_and_evaluate
    for batch_idx, (x, x_lengths, spec, spec_lengths, y, y_lengths, speakers) in enumerate(tqdm(train_loader)):
  File "/usr/local/lib/python3.9/dist-packages/tqdm/std.py", line 1178, in __iter__
    for obj in iterable:
  File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py", line 681, in __next__
    data = self._next_data()
  File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py", line 1376, in _next_data
    return self._process_data(data)
  File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py", line 1402, in _process_data
    data.reraise()
  File "/usr/local/lib/python3.9/dist-packages/torch/_utils.py", line 461, in reraise
    raise exception
NotImplementedError: Caught NotImplementedError in DataLoader worker process 6.
Original Traceback (most recent call last):
  File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop
    data = fetcher.fetch(index)
  File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py", line 49, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/content/vits-finetuning/data_utils.py", line 236, in __getitem__
    return self.get_audio_text_speaker_pair(self.audiopaths_sid_text[index])
  File "/content/vits-finetuning/data_utils.py", line 199, in get_audio_text_speaker_pair
    spec, wav = self.get_audio(audiopath)
  File "/content/vits-finetuning/data_utils.py", line 214, in get_audio
    spec = spectrogram_torch(audio_norm, self.filter_length,
  File "/content/vits-finetuning/mel_processing.py", line 63, in spectrogram_torch
    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
NotImplementedError: Only 2D, 3D, 4D, 5D padding with non-constant padding are supported for now
SayaSS / vits-finetuning

Training failed (?) #25
