Trainable Parameters: 0.000M

[zhiyongLiu1114]

Summary[问题简述（一句话）]

您好，请问我在训练synthesizer 的时候，显示Trainable Parameters: 0.000M是正常的吗？看起来是没有参数在训练

Env & To Reproduce[复现与环境] 描述你用的环境、代码版本、模型

Screenshots[截图（如有）] If applicable, add screenshots to help

[babysor]

不正常，有更多截图或信息吗

[CatOverrun]

不正常，有更多截图或信息吗

遇到同样的现象

`PS I:\wav\list\MockingBird> python .\synthesizer_train.py mandarin I:\wav\list\Dataset\SV2TTS\synthesizer Arguments: run_id: mandarin syn_dir: I:\wav\list\Dataset\SV2TTS\synthesizer models_dir: synthesizer/saved_models/ save_every: 1000 backup_every: 25000 log_every: 200 force_restart: False hparams:

Checkpoint path: synthesizer\saved_models\mandarin\mandarin.pt Loading training data from: I:\wav\list\Dataset\SV2TTS\synthesizer\train.txt Using model: Tacotron Using device: cuda

Initialising Tacotron Model...

\Loading the json with %s {'sample_rate': 16000, 'n_fft': 800, 'num_mels': 80, 'hop_size': 200, 'win_size': 800, 'fmin': 55, 'min_level_db': -100, 'ref_level_db': 20, 'max_abs_value': 4.0, 'preemphasis': 0.97, 'preemphasize': True, 'tts_embed_dims': 512, 'tts_encoder_dims': 256, 'tts_decoder_dims': 128, 'tts_postnet_dims': 512, 'tts_encoder_K': 5, 'tts_lstm_dims': 1024, 'tts_postnet_K': 5, 'tts_num_highways': 4, 'tts_dropout': 0.5, 'tts_cleaner_names': ['basic_cleaners'], 'tts_stop_threshold': -3.4, 'tts_schedule': [[2, 0.001, 10000, 12], [2, 0.0005, 15000, 12], [2, 0.0002, 20000, 12], [2, 0.0001, 30000, 12], [2, 5e-05, 40000, 12], [2, 1e-05, 60000, 12], [2, 5e-06, 160000, 12], [2, 3e-06, 320000, 12], [2, 1e-06, 640000, 12]], 'tts_clip_grad_norm': 1.0, 'tts_eval_interval': 500, 'tts_eval_num_samples': 1, 'tts_finetune_layers': [], 'max_mel_frames': 900, 'rescale': True, 'rescaling_max': 0.9, 'synthesis_batch_size': 16, 'signal_normalization': True, 'power': 1.5, 'griffin_lim_iters': 60, 'fmax': 7600, 'allow_clipping_in_normalization': True, 'clip_mels_length': True, 'use_lws': False, 'symmetric_mels': True, 'trim_silence': True, 'speaker_embedding_size': 256, 'silence_min_duration_split': 0.4, 'utterance_min_duration': 1.6, 'use_gst': True, 'use_ser_for_gst': True} Trainable Parameters: 0.000M

Loading weights at synthesizer\saved_models\mandarin\mandarin.pt Tacotron weights loaded from step 79000 Using inputs from: I:\wav\list\Dataset\SV2TTS\synthesizer\train.txt I:\wav\list\Dataset\SV2TTS\synthesizer\mels I:\wav\list\Dataset\SV2TTS\synthesizer\embeds Found 439 samples +----------------+------------+---------------+------------------+ | Steps with r=2 | Batch Size | Learning Rate | Outputs/Step (r) | +----------------+------------+---------------+------------------+ | 81k Steps | 20 | 5e-06 | 2 | +----------------+------------+---------------+------------------+

{| Epoch: 1/3682 (22/22) | Loss: 0.1255 | 1.1 steps/s | Step: 79k | }} {| Epoch: 2/3682 (22/22) | Loss: 0.1242 | 1.2 steps/s | Step: 79k | } {| Epoch: 3/3682 (6/22) | Loss: 0.1219 | 1.2 steps/s | Step: 79k | }

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[GreenDragonQueen]

遇到了同样的问题： D:\MockingBird-main>python synthesizer_train.py kilruk D:\BaiduNetdiskDownload\SV2TTS\synthesizer Arguments: run_id: kilruk syn_dir: D:\BaiduNetdiskDownload\SV2TTS\synthesizer models_dir: synthesizer/saved_models/ save_every: 1000 backup_every: 25000 log_every: 200 force_restart: False hparams:

Checkpoint path: synthesizer\saved_models\kilruk\kilruk.pt Loading training data from: D:\BaiduNetdiskDownload\SV2TTS\synthesizer\train.txt Using model: Tacotron Using device: cuda

Initialising Tacotron Model...

\Saving the json with %s synthesizer\saved_models\kilruk\kilruk.json Trainable Parameters: 0.000M

Loading weights at synthesizer\saved_models\kilruk\kilruk.pt Tacotron weights loaded from step 0 Using inputs from: D:\BaiduNetdiskDownload\SV2TTS\synthesizer\train.txt D:\BaiduNetdiskDownload\SV2TTS\synthesizer\mels D:\BaiduNetdiskDownload\SV2TTS\synthesizer\embeds Found 63 samples

[BingQZh]

我也有一样的问题，但synthesizer训练出来又好像是有效的……

[zhiyongLiu1114]

和后面那些人的评论一样的