MeloTTS
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myshell-ai
Problem with training
Hi everyone,
i'm trying to train melotts on italian language, but i don't understand why training does not work. When i run this command:
python3 preprocess_text.py --metadata data/example/metadata.list
everything works fine, even after my italian language modification, but when i run this command:
bash train.sh data/example/config.json 1
it seems the command never stop running, and the training always stay to 0:
0it [00:00, ?it/s]
Train.log says this:
25-03-04 16:25:18,787 example INFO {'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 52, 'epochs': 10000, 'learning_rate': 0.0003, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 16384, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'skip_optimizer': True}, 'data': {'training_files': 'data/example/train.list', 'validation_files': 'data/example/val.list', 'max_wav_value': 32768.0, 'sampling_rate': 44100, 'filter_length': 2048, 'hop_length': 512, 'win_length': 2048, 'n_mel_channels': 128, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 1, 'cleaned_text': True, 'spk2id': {'Italian': 0}}, 'model': {'use_spk_conditioned_encoder': True, 'use_noise_scaled_mas': True, 'use_mel_posterior_encoder': False, 'use_duration_discriminator': True, 'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'n_layers_trans_flow': 3, '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, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 8, 2, 2], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256}, 'num_languages': 9, 'num_tones': 17, 'symbols': ['_', '"', '(', ')', '*', '/', ':', 'AA', 'E', 'EE', 'En', 'N', 'OO', 'Q', 'V', '[', '\\', ']', '^', 'a', 'a:', 'aa', 'ae', 'ah', 'ai', 'an', 'ang', 'ao', 'aw', 'ay', 'b', 'by', 'c', 'ch', 'd', 'dh', 'dy', 'e', 'e:', 'eh', 'ei', 'en', 'eng', 'er', 'ey', 'f', 'g', 'gy', 'h', 'hh', 'hy', 'i', 'i0', 'i:', 'ia', 'ian', 'iang', 'iao', 'ie', 'ih', 'in', 'ing', 'iong', 'ir', 'iu', 'iy', 'j', 'jh', 'k', 'ky', 'l', 'm', 'my', 'n', 'ng', 'ny', 'o', 'o:', 'ong', 'ou', 'ow', 'oy', 'p', 'py', 'q', 'r', 'ry', 's', 'sh', 't', 'th', 'ts', 'ty', 'u', 'u:', 'ua', 'uai', 'uan', 'uang', 'uh', 'ui', 'un', 'uo', 'uw', 'v', 'van', 've', 'vn', 'w', 'x', 'y', 'z', 'zh', 'zy', '~', 'æ', 'ç', 'ð', 'ø', 'ŋ', 'œ', 'ɐ', 'ɑ', 'ɒ', 'ɔ', 'ɕ', 'ə', 'ɛ', 'ɜ', 'ɡ', 'ɣ', 'ɥ', 'ɦ', 'ɪ', 'ɫ', 'ɬ', 'ɭ', 'ɯ', 'ɲ', 'ɵ', 'ɸ', 'ɹ', 'ɾ', 'ʁ', 'ʃ', 'ʊ', 'ʌ', 'ʎ', 'ʏ', 'ʑ', 'ʒ', 'ʝ', 'ʲ', 'ˈ', 'ˌ', 'ː', '̃', '̩', 'β', 'θ', 'ᄀ', 'ᄁ', 'ᄂ', 'ᄃ', 'ᄄ', 'ᄅ', 'ᄆ', 'ᄇ', 'ᄈ', 'ᄉ', 'ᄊ', 'ᄋ', 'ᄌ', 'ᄍ', 'ᄎ', 'ᄏ', 'ᄐ', 'ᄑ', 'ᄒ', 'ᅡ', 'ᅢ', 'ᅣ', 'ᅤ', 'ᅥ', 'ᅦ', 'ᅧ', 'ᅨ', 'ᅩ', 'ᅪ', 'ᅫ', 'ᅬ', 'ᅭ', 'ᅮ', 'ᅯ', 'ᅰ', 'ᅱ', 'ᅲ', 'ᅳ', 'ᅴ', 'ᅵ', 'ᆨ', 'ᆫ', 'ᆮ', 'ᆯ', 'ᆷ', 'ᆸ', 'ᆼ', 'ㄸ', '!', '?', '…', ',', '.', "'", '-', '¿', '¡', 'SP', 'UNK', 'ɛ', 'ɔ', 'dz', 'dʒ', 'ʎ', 'ɲ', 'ŋ', 'ʃ', 'ts', 'tʃ', ' ͡ '], 'model_dir': './logs/example', 'pretrain_G': None, 'pretrain_D': None, 'pretrain_dur': None, 'port': 10000}
2025-03-04 16:25:18,788 example WARNING /home/ecuser/MeloTTS/melo is not a git repository, therefore hash value comparison will be ignored.
2025-03-04 16:25:21,891 example ERROR enc_p.emb.weight is not in the checkpoint
2025-03-04 16:25:21,891 example ERROR enc_p.tone_emb.weight is not in the checkpoint
2025-03-04 16:25:21,891 example ERROR enc_p.language_emb.weight is not in the checkpoint
2025-03-04 16:25:21,892 example ERROR emb_g.weight is not in the checkpoint
2025-03-04 16:25:21,942 example INFO Loaded checkpoint '/home/ecuser/.cache/cached_path/73ad3d5a37c82356ed81630b0a435b4b376ca49523854fe2b8302609fd71c193.133b77b9d9162e348486a0a0778fa47d726930e3ec12ea5e2684c0c919743a65' (iteration 0)
2025-03-04 16:25:22,032 example INFO Loaded checkpoint '/home/ecuser/.cache/cached_path/c3d3c787a8711093a79ee95f091a35de75e527b6e8e28424ad7010f6e86cce58.e5f88bb1eca17c37beb511b15a932e84fdc8b66d8a8d5c5075334650425954f2' (iteration 0)
2025-03-04 16:25:22,040 example INFO Loaded checkpoint '/home/ecuser/.cache/cached_path/c7b373ab8939eb672a985a802d21420534ca0cd43fa4aecf4fa6088a569ee2a1.ce7a8153914d9727ebc28e4b4e3d31eed35aa0b4e3d125eb54e6f8363968dd7a' (iteration 0)
2025-03-04 16:25:22,239 example INFO ====> Epoch: 1
2025-03-04 16:25:47,138 example INFO ====> Epoch: 2
2025-03-04 16:25:47,143 example INFO ====> Epoch: 3
2025-03-04 16:25:47,147 example INFO ====> Epoch: 4
2025-03-04 16:25:47,152 example INFO ====> Epoch: 5
2025-03-04 16:25:47,155 example INFO ====> Epoch: 6
2025-03-04 16:25:47,160 example INFO ====> Epoch: 7
2025-03-04 16:25:47,164 example INFO ====> Epoch: 8
2025-03-04 16:25:47,168 example INFO ====> Epoch: 9
2025-03-04 16:25:47,172 example INFO ====> Epoch: 10
Any suggestions?
I noticed that your eval_interval is set to 1000, which means the model will be saved every 1000 batches.
Hi @TheSweetestGirlInTheUniverse
i resolved the previous error by changing in train.py the value in this list:
train_sampler = DistributedBucketSampler(
train_dataset,
hps.train.batch_size,
[1200, 1400, 1600, 1800, 2000, 2200, 2400, 2600, 2800],
num_replicas=n_gpus,
rank=rank,
shuffle=True,
)
now the training starts in the right way and creates checkpoints. But now i face into another error: when i try to run infer.py with one of the checkpoints generated by training, the output.wav generated produce only unintelligible sounds. I don't understand why.
Here it's mine config.json:
{
"train": {
"log_interval": 200,
"eval_interval": 1000,
"seed": 52,
"epochs": 10000,
"learning_rate": 0.0003,
"betas": [
0.8,
0.99
],
"eps": 1e-09,
"batch_size": 6,
"fp16_run": false,
"lr_decay": 0.999875,
"segment_size": 16384,
"init_lr_ratio": 1,
"warmup_epochs": 0,
"c_mel": 45,
"c_kl": 1.0,
"skip_optimizer": true
},
"data": {
"training_files": "data/example/train.list",
"validation_files": "data/example/val.list",
"max_wav_value": 32768.0,
"sampling_rate": 44100,
"filter_length": 2048,
"hop_length": 512,
"win_length": 2048,
"n_mel_channels": 128,
"mel_fmin": 0.0,
"mel_fmax": null,
"add_blank": true,
"n_speakers": 1,
"cleaned_text": true,
"spk2id": {
"Italian": 0
}
},
"model": {
"use_spk_conditioned_encoder": true,
"use_noise_scaled_mas": true,
"use_mel_posterior_encoder": false,
"use_duration_discriminator": true,
"inter_channels": 192,
"hidden_channels": 192,
"filter_channels": 768,
"n_heads": 2,
"n_layers": 6,
"n_layers_trans_flow": 3,
"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,
2
],
"upsample_initial_channel": 512,
"upsample_kernel_sizes": [
16,
16,
8,
2,
2
],
"n_layers_q": 3,
"use_spectral_norm": false,
"gin_channels": 256
},
"num_languages": 9,
"num_tones": 17,
"symbols": [
"_",
"\"",
"(",
")",
"*",
"/",
":",
"AA",
"E",
"EE",
"En",
"N",
"OO",
"Q",
"V",
"[",
"\\",
"]",
"^",
"a",
"a:",
"aa",
"ae",
"ah",
"ai",
"an",
"ang",
"ao",
"aw",
"ay",
"b",
"by",
"c",
"ch",
"d",
"dh",
"dy",
"e",
"e:",
"eh",
"ei",
"en",
"eng",
"er",
"ey",
"f",
"g",
"gy",
"h",
"hh",
"hy",
"i",
"i0",
"i:",
"ia",
"ian",
"iang",
"iao",
"ie",
"ih",
"in",
"ing",
"iong",
"ir",
"iu",
"iy",
"j",
"jh",
"k",
"ky",
"l",
"m",
"my",
"n",
"ng",
"ny",
"o",
"o:",
"ong",
"ou",
"ow",
"oy",
"p",
"py",
"q",
"r",
"ry",
"s",
"sh",
"t",
"th",
"ts",
"ty",
"u",
"u:",
"ua",
"uai",
"uan",
"uang",
"uh",
"ui",
"un",
"uo",
"uw",
"v",
"van",
"ve",
"vn",
"w",
"x",
"y",
"z",
"zh",
"zy",
"~",
"æ",
"ç",
"ð",
"ø",
"ŋ",
"œ",
"ɐ",
"ɑ",
"ɒ",
"ɔ",
"ɕ",
"ə",
"ɛ",
"ɜ",
"ɡ",
"ɣ",
"ɥ",
"ɦ",
"ɪ",
"ɫ",
"ɬ",
"ɭ",
"ɯ",
"ɲ",
"ɵ",
"ɸ",
"ɹ",
"ɾ",
"ʁ",
"ʃ",
"ʊ",
"ʌ",
"ʎ",
"ʏ",
"ʑ",
"ʒ",
"ʝ",
"ʲ",
"ˈ",
"ˌ",
"ː",
"̃",
"̩",
"β",
"θ",
"ᄀ",
"ᄁ",
"ᄂ",
"ᄃ",
"ᄄ",
"ᄅ",
"ᄆ",
"ᄇ",
"ᄈ",
"ᄉ",
"ᄊ",
"ᄋ",
"ᄌ",
"ᄍ",
"ᄎ",
"ᄏ",
"ᄐ",
"ᄑ",
"ᄒ",
"ᅡ",
"ᅢ",
"ᅣ",
"ᅤ",
"ᅥ",
"ᅦ",
"ᅧ",
"ᅨ",
"ᅩ",
"ᅪ",
"ᅫ",
"ᅬ",
"ᅭ",
"ᅮ",
"ᅯ",
"ᅰ",
"ᅱ",
"ᅲ",
"ᅳ",
"ᅴ",
"ᅵ",
"ᆨ",
"ᆫ",
"ᆮ",
"ᆯ",
"ᆷ",
"ᆸ",
"ᆼ",
"ㄸ",
"!",
"?",
"…",
",",
".",
"'",
"-",
"¿",
"¡",
"SP",
"UNK",
"dz",
"dʒ",
"tʃ",
" ͡ "
]
}
that's one of mine train.list row
../../audio_1/Untitled_MIC_1_960.wav|Italian|IT|Ogni regione italiana ha le sue tradizioni culinarie|_ ˈ o ɲ ɲ i r e ˈ d ͡ ʒ o n e i t a ˈ l j a n a a l e ˈ s u e t r a d i ˈ t ͡ s j o n i k u l i ˈ n a r j e _|0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0|1 5 9 9 1 2 4 13 5 5 1
thanks in advance,
Diego
@diegobernagozzi
Hi Diego:
I'm not sure where the issue is, but here are some ideas.
First, Check the language-related preprocessing, such as whether BERT features support Italian or try not using BERT features. Also, make sure to add Italian-related symbols in symbols.py.
When using infer.py, verify that the preprocessing is correct. Otherwise, even if training is correct, you may still get wrong results.
modify the train.sh to below and remember let your train dataset 44.1k pcm ` CONFIG=$1 GPUS=$2 MODEL_NAME=$(basename "$(dirname $CONFIG)")
PORT=10902
torchrun --nproc_per_node=$GPUS
--master_port=$PORT
train.py --c $CONFIG --model $MODEL_NAME
`
modify the train.sh to below and remember let your train dataset 44.1k pcm ` CONFIG=$1 GPUS=$2 MODEL_NAME=$(basename "$(dirname $CONFIG)")
PORT=10902
torchrun --nproc_per_node=$GPUS --master_port=$PORT train.py --c $CONFIG --model $MODEL_NAME `
I encountered the same problem. The training data set was 20K, and it took about an hour. After training for 2000 epochs, the final weights sounded like an electric current, and the effect was very poor. Do you mean that you suspect that the train.sh code will loop the training, resulting in repeated weight writing? In addition, increasing the audio frequency of the training data set will have a better training effect?
I have the same issue.But i am not fix it,the model is also trained good.But the trained model size is about 500M,the official pretrained model size is 200M.where the problem with my process?or it is needed to be purned from some script?the config json is flowed:
{
"train": {
"log_interval": 50,
"eval_interval": 50,
"seed": 52,
"epochs": 10000,
"learning_rate": 0.0003,
"betas": [
0.8,
0.99
],
"eps": 1e-09,
"batch_size": 64,
"fp16_run": false,
"lr_decay": 0.999875,
"segment_size": 16384,
"init_lr_ratio": 1,
"warmup_epochs": 0,
"c_mel": 45,
"c_kl": 1.0,
"skip_optimizer": true
},
"data": {
"training_files": "/workspace/zh_en_homemade_tongsheng/train.list",
"validation_files": "/workspace/zh_en_homemade_tongsheng/val.list",
"max_wav_value": 32768.0,
"sampling_rate": 44100,
"filter_length": 2048,
"hop_length": 512,
"win_length": 2048,
"n_mel_channels": 128,
"mel_fmin": 0.0,
"mel_fmax": null,
"add_blank": true,
"n_speakers": 1,
"cleaned_text": true,
"spk2id": {
"homemade": 0
}
},
"model": {
"use_spk_conditioned_encoder": true,
"use_noise_scaled_mas": true,
"use_mel_posterior_encoder": false,
"use_duration_discriminator": true,
"inter_channels": 192,
"hidden_channels": 192,
"filter_channels": 768,
"n_heads": 2,
"n_layers": 6,
"n_layers_trans_flow": 3,
"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,
2
],
"upsample_initial_channel": 512,
"upsample_kernel_sizes": [
16,
16,
8,
2,
2
],
"n_layers_q": 3,
"use_spectral_norm": false,
"gin_channels": 256
},
"num_languages": 8,
"num_tones": 16,
"symbols": [
"_",
"\"",
"(",
")",
"*",
"/",
":",
"AA",
"E",
"EE",
"En",
"N",
"OO",
"Q",
"V",
"[",
"\\",
"]",
"^",
"a",
"a:",
"aa",
"ae",
"ah",
"ai",
"an",
"ang",
"ao",
"aw",
"ay",
"b",
"by",
"c",
"ch",
"d",
"dh",
"dy",
"e",
"e:",
"eh",
"ei",
"en",
"eng",
"er",
"ey",
"f",
"g",
"gy",
"h",
"hh",
"hy",
"i",
"i0",
"i:",
"ia",
"ian",
"iang",
"iao",
"ie",
"ih",
"in",
"ing",
"iong",
"ir",
"iu",
"iy",
"j",
"jh",
"k",
"ky",
"l",
"m",
"my",
"n",
"ng",
"ny",
"o",
"o:",
"ong",
"ou",
"ow",
"oy",
"p",
"py",
"q",
"r",
"ry",
"s",
"sh",
"t",
"th",
"ts",
"ty",
"u",
"u:",
"ua",
"uai",
"uan",
"uang",
"uh",
"ui",
"un",
"uo",
"uw",
"v",
"van",
"ve",
"vn",
"w",
"x",
"y",
"z",
"zh",
"zy",
"~",
"æ",
"ç",
"ð",
"ø",
"ŋ",
"œ",
"ɐ",
"ɑ",
"ɒ",
"ɔ",
"ɕ",
"ə",
"ɛ",
"ɜ",
"ɡ",
"ɣ",
"ɥ",
"ɦ",
"ɪ",
"ɫ",
"ɬ",
"ɭ",
"ɯ",
"ɲ",
"ɵ",
"ɸ",
"ɹ",
"ɾ",
"ʁ",
"ʃ",
"ʊ",
"ʌ",
"ʎ",
"ʏ",
"ʑ",
"ʒ",
"ʝ",
"ʲ",
"ˈ",
"ˌ",
"ː",
"̃",
"̩",
"β",
"θ",
"ᄀ",
"ᄁ",
"ᄂ",
"ᄃ",
"ᄄ",
"ᄅ",
"ᄆ",
"ᄇ",
"ᄈ",
"ᄉ",
"ᄊ",
"ᄋ",
"ᄌ",
"ᄍ",
"ᄎ",
"ᄏ",
"ᄐ",
"ᄑ",
"ᄒ",
"ᅡ",
"ᅢ",
"ᅣ",
"ᅤ",
"ᅥ",
"ᅦ",
"ᅧ",
"ᅨ",
"ᅩ",
"ᅪ",
"ᅫ",
"ᅬ",
"ᅭ",
"ᅮ",
"ᅯ",
"ᅰ",
"ᅱ",
"ᅲ",
"ᅳ",
"ᅴ",
"ᅵ",
"ᆨ",
"ᆫ",
"ᆮ",
"ᆯ",
"ᆷ",
"ᆸ",
"ᆼ",
"ㄸ",
"!",
"?",
"…",
",",
".",
"'",
"-",
"¿",
"¡",
"SP",
"UNK"
]
}
the train.log is as followed:
2025-04-28 15:52:20,437 zh_en_homemade_tongsheng INFO {'train': {'log_interval': 50, 'eval_interval': 50, 'seed': 52, 'epochs': 10000, 'learning_rate': 0.0003, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 64, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 16384, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'skip_optimizer': True}, 'data': {'training_files': '/workspace/zh_en_homemade_tongsheng/train.list', 'validation_files': '/workspace/zh_en_homemade_tongsheng/val.list', 'max_wav_value': 32768.0, 'sampling_rate': 44100, 'filter_length': 2048, 'hop_length': 512, 'win_length': 2048, 'n_mel_channels': 128, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 1, 'cleaned_text': True, 'spk2id': {'homemade': 0}}, 'model': {'use_spk_conditioned_encoder': True, 'use_noise_scaled_mas': True, 'use_mel_posterior_encoder': False, 'use_duration_discriminator': True, 'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'n_layers_trans_flow': 3, '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, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 8, 2, 2], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256}, 'num_languages': 8, 'num_tones': 16, 'symbols': ['_', '"', '(', ')', '*', '/', ':', 'AA', 'E', 'EE', 'En', 'N', 'OO', 'Q', 'V', '[', '\\', ']', '^', 'a', 'a:', 'aa', 'ae', 'ah', 'ai', 'an', 'ang', 'ao', 'aw', 'ay', 'b', 'by', 'c', 'ch', 'd', 'dh', 'dy', 'e', 'e:', 'eh', 'ei', 'en', 'eng', 'er', 'ey', 'f', 'g', 'gy', 'h', 'hh', 'hy', 'i', 'i0', 'i:', 'ia', 'ian', 'iang', 'iao', 'ie', 'ih', 'in', 'ing', 'iong', 'ir', 'iu', 'iy', 'j', 'jh', 'k', 'ky', 'l', 'm', 'my', 'n', 'ng', 'ny', 'o', 'o:', 'ong', 'ou', 'ow', 'oy', 'p', 'py', 'q', 'r', 'ry', 's', 'sh', 't', 'th', 'ts', 'ty', 'u', 'u:', 'ua', 'uai', 'uan', 'uang', 'uh', 'ui', 'un', 'uo', 'uw', 'v', 'van', 've', 'vn', 'w', 'x', 'y', 'z', 'zh', 'zy', '~', 'æ', 'ç', 'ð', 'ø', 'ŋ', 'œ', 'ɐ', 'ɑ', 'ɒ', 'ɔ', 'ɕ', 'ə', 'ɛ', 'ɜ', 'ɡ', 'ɣ', 'ɥ', 'ɦ', 'ɪ', 'ɫ', 'ɬ', 'ɭ', 'ɯ', 'ɲ', 'ɵ', 'ɸ', 'ɹ', 'ɾ', 'ʁ', 'ʃ', 'ʊ', 'ʌ', 'ʎ', 'ʏ', 'ʑ', 'ʒ', 'ʝ', 'ʲ', 'ˈ', 'ˌ', 'ː', '̃', '̩', 'β', 'θ', 'ᄀ', 'ᄁ', 'ᄂ', 'ᄃ', 'ᄄ', 'ᄅ', 'ᄆ', 'ᄇ', 'ᄈ', 'ᄉ', 'ᄊ', 'ᄋ', 'ᄌ', 'ᄍ', 'ᄎ', 'ᄏ', 'ᄐ', 'ᄑ', 'ᄒ', 'ᅡ', 'ᅢ', 'ᅣ', 'ᅤ', 'ᅥ', 'ᅦ', 'ᅧ', 'ᅨ', 'ᅩ', 'ᅪ', 'ᅫ', 'ᅬ', 'ᅭ', 'ᅮ', 'ᅯ', 'ᅰ', 'ᅱ', 'ᅲ', 'ᅳ', 'ᅴ', 'ᅵ', 'ᆨ', 'ᆫ', 'ᆮ', 'ᆯ', 'ᆷ', 'ᆸ', 'ᆼ', 'ㄸ', '!', '?', '…', ',', '.', "'", '-', '¿', '¡', 'SP', 'UNK'], 'model_dir': './logs/zh_en_homemade_tongsheng', 'pretrain_G': None, 'pretrain_D': None, 'pretrain_dur': None, 'port': 10000}
2025-04-28 15:52:20,437 zh_en_homemade_tongsheng WARNING /workspace/MeloTTS-main/melo is not a git repository, therefore hash value comparison will be ignored.
2025-04-28 15:52:25,503 zh_en_homemade_tongsheng ERROR enc_p.language_emb.weight is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.0.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.0.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.1.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.1.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.2.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.2.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.3.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.3.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.4.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.4.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,505 zh_en_homemade_tongsheng ERROR emb_g.weight is not in the checkpoint
2025-04-28 15:52:25,565 zh_en_homemade_tongsheng INFO Loaded checkpoint '/workspace/MeloTTS-main/config_path/G.pth' (iteration 0)
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.0.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.0.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.1.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.1.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.2.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.2.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.3.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.3.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.4.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.4.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.5.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.convs.5.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.conv_post.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.0.conv_post.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.0.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.0.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.1.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.1.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.2.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.2.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.3.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.3.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.4.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.convs.4.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.conv_post.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.1.conv_post.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.2.convs.0.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.2.convs.0.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.2.convs.1.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,672 zh_en_homemade_tongsheng ERROR discriminators.2.convs.1.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.2.convs.2.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.2.convs.2.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.2.convs.3.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.2.convs.3.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.2.convs.4.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.2.convs.4.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.2.conv_post.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.2.conv_post.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.0.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.0.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.1.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.1.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.2.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.2.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.3.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.3.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.4.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.convs.4.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.conv_post.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.3.conv_post.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.0.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.0.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.1.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.1.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.2.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.2.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.3.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.3.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.4.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.convs.4.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.conv_post.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.4.conv_post.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.5.convs.0.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,673 zh_en_homemade_tongsheng ERROR discriminators.5.convs.0.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.convs.1.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.convs.1.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.convs.2.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.convs.2.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.convs.3.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.convs.3.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.convs.4.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.convs.4.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.conv_post.parametrizations.weight.original0 is not in the checkpoint
2025-04-28 15:52:25,674 zh_en_homemade_tongsheng ERROR discriminators.5.conv_post.parametrizations.weight.original1 is not in the checkpoint
2025-04-28 15:52:25,677 zh_en_homemade_tongsheng INFO Loaded checkpoint '/workspace/MeloTTS-main/config_path/D.pth' (iteration 0)
2025-04-28 15:52:25,728 zh_en_homemade_tongsheng INFO Loaded checkpoint '/workspace/MeloTTS-main/config_path/DUR.pth' (iteration 0)
2025-04-28 15:52:38,185 zh_en_homemade_tongsheng INFO Train Epoch: 1 [0%]
2025-04-28 15:52:38,186 zh_en_homemade_tongsheng INFO [3.905026435852051, 0.6578705906867981, 0.3039743900299072, 107.12034606933594, 4.826106548309326, 5.3804450035095215, 0, 0.0003]
2025-04-28 15:52:43,965 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 1 to ./logs/zh_en_homemade_tongsheng/G_0.pth
2025-04-28 15:52:45,777 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 1 to ./logs/zh_en_homemade_tongsheng/D_0.pth
2025-04-28 15:52:46,256 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 1 to ./logs/zh_en_homemade_tongsheng/DUR_0.pth
2025-04-28 15:53:04,178 zh_en_homemade_tongsheng INFO ====> Epoch: 1
2025-04-28 15:53:25,310 zh_en_homemade_tongsheng INFO ====> Epoch: 2
2025-04-28 15:53:45,062 zh_en_homemade_tongsheng INFO ====> Epoch: 3
2025-04-28 15:54:04,866 zh_en_homemade_tongsheng INFO ====> Epoch: 4
2025-04-28 15:54:24,275 zh_en_homemade_tongsheng INFO ====> Epoch: 5
2025-04-28 15:54:38,828 zh_en_homemade_tongsheng INFO Train Epoch: 6 [56%]
2025-04-28 15:54:38,828 zh_en_homemade_tongsheng INFO [2.078730583190918, 2.40077543258667, 4.760352611541748, 28.384017944335938, 3.1325626373291016, 1.43171226978302, 50, 0.000299812546869141]
2025-04-28 15:54:43,457 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 6 to ./logs/zh_en_homemade_tongsheng/G_50.pth
2025-04-28 15:54:44,818 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 6 to ./logs/zh_en_homemade_tongsheng/D_50.pth
2025-04-28 15:54:45,249 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 6 to ./logs/zh_en_homemade_tongsheng/DUR_50.pth
2025-04-28 15:54:51,232 zh_en_homemade_tongsheng INFO ====> Epoch: 6
2025-04-28 15:55:09,957 zh_en_homemade_tongsheng INFO ====> Epoch: 7
2025-04-28 15:55:27,676 zh_en_homemade_tongsheng INFO ====> Epoch: 8
2025-04-28 15:55:44,737 zh_en_homemade_tongsheng INFO ====> Epoch: 9
2025-04-28 15:56:02,703 zh_en_homemade_tongsheng INFO ====> Epoch: 10
2025-04-28 15:56:20,071 zh_en_homemade_tongsheng INFO ====> Epoch: 11
2025-04-28 15:56:27,041 zh_en_homemade_tongsheng INFO Train Epoch: 12 [11%]
2025-04-28 15:56:27,041 zh_en_homemade_tongsheng INFO [2.045553684234619, 2.981926918029785, 4.796144485473633, 24.123809814453125, 3.10740065574646, 1.4242831468582153, 100, 0.00029958775771584436]
2025-04-28 15:56:31,453 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 12 to ./logs/zh_en_homemade_tongsheng/G_100.pth
2025-04-28 15:56:33,035 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 12 to ./logs/zh_en_homemade_tongsheng/D_100.pth
2025-04-28 15:56:33,477 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 12 to ./logs/zh_en_homemade_tongsheng/DUR_100.pth
2025-04-28 15:56:44,698 zh_en_homemade_tongsheng INFO ====> Epoch: 12
2025-04-28 15:57:02,345 zh_en_homemade_tongsheng INFO ====> Epoch: 13
2025-04-28 15:57:19,162 zh_en_homemade_tongsheng INFO ====> Epoch: 14
2025-04-28 15:57:35,650 zh_en_homemade_tongsheng INFO ====> Epoch: 15
2025-04-28 15:57:52,502 zh_en_homemade_tongsheng INFO ====> Epoch: 16
2025-04-28 15:58:06,810 zh_en_homemade_tongsheng INFO Train Epoch: 17 [67%]
I have the same issue.But i am not fix it,the model is also trained good.But the trained model size is about 500M,the official pretrained model size is 200M.where the problem with my process?or it is needed to be purned from some script?the config json is flowed:
{ "train": { "log_interval": 50, "eval_interval": 50, "seed": 52, "epochs": 10000, "learning_rate": 0.0003, "betas": [ 0.8, 0.99 ], "eps": 1e-09, "batch_size": 64, "fp16_run": false, "lr_decay": 0.999875, "segment_size": 16384, "init_lr_ratio": 1, "warmup_epochs": 0, "c_mel": 45, "c_kl": 1.0, "skip_optimizer": true }, "data": { "training_files": "/workspace/zh_en_homemade_tongsheng/train.list", "validation_files": "/workspace/zh_en_homemade_tongsheng/val.list", "max_wav_value": 32768.0, "sampling_rate": 44100, "filter_length": 2048, "hop_length": 512, "win_length": 2048, "n_mel_channels": 128, "mel_fmin": 0.0, "mel_fmax": null, "add_blank": true, "n_speakers": 1, "cleaned_text": true, "spk2id": { "homemade": 0 } }, "model": { "use_spk_conditioned_encoder": true, "use_noise_scaled_mas": true, "use_mel_posterior_encoder": false, "use_duration_discriminator": true, "inter_channels": 192, "hidden_channels": 192, "filter_channels": 768, "n_heads": 2, "n_layers": 6, "n_layers_trans_flow": 3, "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, 2 ], "upsample_initial_channel": 512, "upsample_kernel_sizes": [ 16, 16, 8, 2, 2 ], "n_layers_q": 3, "use_spectral_norm": false, "gin_channels": 256 }, "num_languages": 8, "num_tones": 16, "symbols": [ "_", "\"", "(", ")", "*", "/", ":", "AA", "E", "EE", "En", "N", "OO", "Q", "V", "[", "\\", "]", "^", "a", "a:", "aa", "ae", "ah", "ai", "an", "ang", "ao", "aw", "ay", "b", "by", "c", "ch", "d", "dh", "dy", "e", "e:", "eh", "ei", "en", "eng", "er", "ey", "f", "g", "gy", "h", "hh", "hy", "i", "i0", "i:", "ia", "ian", "iang", "iao", "ie", "ih", "in", "ing", "iong", "ir", "iu", "iy", "j", "jh", "k", "ky", "l", "m", "my", "n", "ng", "ny", "o", "o:", "ong", "ou", "ow", "oy", "p", "py", "q", "r", "ry", "s", "sh", "t", "th", "ts", "ty", "u", "u:", "ua", "uai", "uan", "uang", "uh", "ui", "un", "uo", "uw", "v", "van", "ve", "vn", "w", "x", "y", "z", "zh", "zy", "~", "æ", "ç", "ð", "ø", "ŋ", "œ", "ɐ", "ɑ", "ɒ", "ɔ", "ɕ", "ə", "ɛ", "ɜ", "ɡ", "ɣ", "ɥ", "ɦ", "ɪ", "ɫ", "ɬ", "ɭ", "ɯ", "ɲ", "ɵ", "ɸ", "ɹ", "ɾ", "ʁ", "ʃ", "ʊ", "ʌ", "ʎ", "ʏ", "ʑ", "ʒ", "ʝ", "ʲ", "ˈ", "ˌ", "ː", "̃", "̩", "β", "θ", "ᄀ", "ᄁ", "ᄂ", "ᄃ", "ᄄ", "ᄅ", "ᄆ", "ᄇ", "ᄈ", "ᄉ", "ᄊ", "ᄋ", "ᄌ", "ᄍ", "ᄎ", "ᄏ", "ᄐ", "ᄑ", "ᄒ", "ᅡ", "ᅢ", "ᅣ", "ᅤ", "ᅥ", "ᅦ", "ᅧ", "ᅨ", "ᅩ", "ᅪ", "ᅫ", "ᅬ", "ᅭ", "ᅮ", "ᅯ", "ᅰ", "ᅱ", "ᅲ", "ᅳ", "ᅴ", "ᅵ", "ᆨ", "ᆫ", "ᆮ", "ᆯ", "ᆷ", "ᆸ", "ᆼ", "ㄸ", "!", "?", "…", ",", ".", "'", "-", "¿", "¡", "SP", "UNK" ] }the train.log is as followed:
2025-04-28 15:52:20,437 zh_en_homemade_tongsheng INFO {'train': {'log_interval': 50, 'eval_interval': 50, 'seed': 52, 'epochs': 10000, 'learning_rate': 0.0003, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 64, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 16384, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'skip_optimizer': True}, 'data': {'training_files': '/workspace/zh_en_homemade_tongsheng/train.list', 'validation_files': '/workspace/zh_en_homemade_tongsheng/val.list', 'max_wav_value': 32768.0, 'sampling_rate': 44100, 'filter_length': 2048, 'hop_length': 512, 'win_length': 2048, 'n_mel_channels': 128, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 1, 'cleaned_text': True, 'spk2id': {'homemade': 0}}, 'model': {'use_spk_conditioned_encoder': True, 'use_noise_scaled_mas': True, 'use_mel_posterior_encoder': False, 'use_duration_discriminator': True, 'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'n_layers_trans_flow': 3, '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, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 8, 2, 2], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256}, 'num_languages': 8, 'num_tones': 16, 'symbols': ['_', '"', '(', ')', '*', '/', ':', 'AA', 'E', 'EE', 'En', 'N', 'OO', 'Q', 'V', '[', '\\', ']', '^', 'a', 'a:', 'aa', 'ae', 'ah', 'ai', 'an', 'ang', 'ao', 'aw', 'ay', 'b', 'by', 'c', 'ch', 'd', 'dh', 'dy', 'e', 'e:', 'eh', 'ei', 'en', 'eng', 'er', 'ey', 'f', 'g', 'gy', 'h', 'hh', 'hy', 'i', 'i0', 'i:', 'ia', 'ian', 'iang', 'iao', 'ie', 'ih', 'in', 'ing', 'iong', 'ir', 'iu', 'iy', 'j', 'jh', 'k', 'ky', 'l', 'm', 'my', 'n', 'ng', 'ny', 'o', 'o:', 'ong', 'ou', 'ow', 'oy', 'p', 'py', 'q', 'r', 'ry', 's', 'sh', 't', 'th', 'ts', 'ty', 'u', 'u:', 'ua', 'uai', 'uan', 'uang', 'uh', 'ui', 'un', 'uo', 'uw', 'v', 'van', 've', 'vn', 'w', 'x', 'y', 'z', 'zh', 'zy', '~', 'æ', 'ç', 'ð', 'ø', 'ŋ', 'œ', 'ɐ', 'ɑ', 'ɒ', 'ɔ', 'ɕ', 'ə', 'ɛ', 'ɜ', 'ɡ', 'ɣ', 'ɥ', 'ɦ', 'ɪ', 'ɫ', 'ɬ', 'ɭ', 'ɯ', 'ɲ', 'ɵ', 'ɸ', 'ɹ', 'ɾ', 'ʁ', 'ʃ', 'ʊ', 'ʌ', 'ʎ', 'ʏ', 'ʑ', 'ʒ', 'ʝ', 'ʲ', 'ˈ', 'ˌ', 'ː', '̃', '̩', 'β', 'θ', 'ᄀ', 'ᄁ', 'ᄂ', 'ᄃ', 'ᄄ', 'ᄅ', 'ᄆ', 'ᄇ', 'ᄈ', 'ᄉ', 'ᄊ', 'ᄋ', 'ᄌ', 'ᄍ', 'ᄎ', 'ᄏ', 'ᄐ', 'ᄑ', 'ᄒ', 'ᅡ', 'ᅢ', 'ᅣ', 'ᅤ', 'ᅥ', 'ᅦ', 'ᅧ', 'ᅨ', 'ᅩ', 'ᅪ', 'ᅫ', 'ᅬ', 'ᅭ', 'ᅮ', 'ᅯ', 'ᅰ', 'ᅱ', 'ᅲ', 'ᅳ', 'ᅴ', 'ᅵ', 'ᆨ', 'ᆫ', 'ᆮ', 'ᆯ', 'ᆷ', 'ᆸ', 'ᆼ', 'ㄸ', '!', '?', '…', ',', '.', "'", '-', '¿', '¡', 'SP', 'UNK'], 'model_dir': './logs/zh_en_homemade_tongsheng', 'pretrain_G': None, 'pretrain_D': None, 'pretrain_dur': None, 'port': 10000} 2025-04-28 15:52:20,437 zh_en_homemade_tongsheng WARNING /workspace/MeloTTS-main/melo is not a git repository, therefore hash value comparison will be ignored. 2025-04-28 15:52:25,503 zh_en_homemade_tongsheng ERROR enc_p.language_emb.weight is not in the checkpoint 2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.0.parametrizations.weight.original0 is not in the checkpoint 2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.0.parametrizations.weight.original1 is not in the checkpoint 2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.1.parametrizations.weight.original0 is not in the checkpoint 2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.1.parametrizations.weight.original1 is not in the checkpoint 2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.2.parametrizations.weight.original0 is not in the checkpoint 2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.2.parametrizations.weight.original1 is not in the checkpoint 2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.3.parametrizations.weight.original0 is not in the checkpoint 2025-04-28 15:52:25,504 zh_en_homemade_tongsheng ERROR dec.ups.3.parametrizations.weight.original1 is not in the 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discriminators.5.conv_post.parametrizations.weight.original1 is not in the checkpoint 2025-04-28 15:52:25,677 zh_en_homemade_tongsheng INFO Loaded checkpoint '/workspace/MeloTTS-main/config_path/D.pth' (iteration 0) 2025-04-28 15:52:25,728 zh_en_homemade_tongsheng INFO Loaded checkpoint '/workspace/MeloTTS-main/config_path/DUR.pth' (iteration 0) 2025-04-28 15:52:38,185 zh_en_homemade_tongsheng INFO Train Epoch: 1 [0%] 2025-04-28 15:52:38,186 zh_en_homemade_tongsheng INFO [3.905026435852051, 0.6578705906867981, 0.3039743900299072, 107.12034606933594, 4.826106548309326, 5.3804450035095215, 0, 0.0003] 2025-04-28 15:52:43,965 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 1 to ./logs/zh_en_homemade_tongsheng/G_0.pth 2025-04-28 15:52:45,777 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 1 to ./logs/zh_en_homemade_tongsheng/D_0.pth 2025-04-28 15:52:46,256 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 1 to ./logs/zh_en_homemade_tongsheng/DUR_0.pth 2025-04-28 15:53:04,178 zh_en_homemade_tongsheng INFO ====> Epoch: 1 2025-04-28 15:53:25,310 zh_en_homemade_tongsheng INFO ====> Epoch: 2 2025-04-28 15:53:45,062 zh_en_homemade_tongsheng INFO ====> Epoch: 3 2025-04-28 15:54:04,866 zh_en_homemade_tongsheng INFO ====> Epoch: 4 2025-04-28 15:54:24,275 zh_en_homemade_tongsheng INFO ====> Epoch: 5 2025-04-28 15:54:38,828 zh_en_homemade_tongsheng INFO Train Epoch: 6 [56%] 2025-04-28 15:54:38,828 zh_en_homemade_tongsheng INFO [2.078730583190918, 2.40077543258667, 4.760352611541748, 28.384017944335938, 3.1325626373291016, 1.43171226978302, 50, 0.000299812546869141] 2025-04-28 15:54:43,457 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 6 to ./logs/zh_en_homemade_tongsheng/G_50.pth 2025-04-28 15:54:44,818 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 6 to ./logs/zh_en_homemade_tongsheng/D_50.pth 2025-04-28 15:54:45,249 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 6 to ./logs/zh_en_homemade_tongsheng/DUR_50.pth 2025-04-28 15:54:51,232 zh_en_homemade_tongsheng INFO ====> Epoch: 6 2025-04-28 15:55:09,957 zh_en_homemade_tongsheng INFO ====> Epoch: 7 2025-04-28 15:55:27,676 zh_en_homemade_tongsheng INFO ====> Epoch: 8 2025-04-28 15:55:44,737 zh_en_homemade_tongsheng INFO ====> Epoch: 9 2025-04-28 15:56:02,703 zh_en_homemade_tongsheng INFO ====> Epoch: 10 2025-04-28 15:56:20,071 zh_en_homemade_tongsheng INFO ====> Epoch: 11 2025-04-28 15:56:27,041 zh_en_homemade_tongsheng INFO Train Epoch: 12 [11%] 2025-04-28 15:56:27,041 zh_en_homemade_tongsheng INFO [2.045553684234619, 2.981926918029785, 4.796144485473633, 24.123809814453125, 3.10740065574646, 1.4242831468582153, 100, 0.00029958775771584436] 2025-04-28 15:56:31,453 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 12 to ./logs/zh_en_homemade_tongsheng/G_100.pth 2025-04-28 15:56:33,035 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 12 to ./logs/zh_en_homemade_tongsheng/D_100.pth 2025-04-28 15:56:33,477 zh_en_homemade_tongsheng INFO Saving model and optimizer state at iteration 12 to ./logs/zh_en_homemade_tongsheng/DUR_100.pth 2025-04-28 15:56:44,698 zh_en_homemade_tongsheng INFO ====> Epoch: 12 2025-04-28 15:57:02,345 zh_en_homemade_tongsheng INFO ====> Epoch: 13 2025-04-28 15:57:19,162 zh_en_homemade_tongsheng INFO ====> Epoch: 14 2025-04-28 15:57:35,650 zh_en_homemade_tongsheng INFO ====> Epoch: 15 2025-04-28 15:57:52,502 zh_en_homemade_tongsheng INFO ====> Epoch: 16 2025-04-28 15:58:06,810 zh_en_homemade_tongsheng INFO Train Epoch: 17 [67%]
参考这个文章https://blog.csdn.net/qq_43907505/article/details/144521730?fromshare=blogdetail&sharetype=blogdetail&sharerId=144521730&sharerefer=PC&sharesource=m0_73665762&sharefrom=from_link