diff --git a/vocoder/configs/melgan_config.json b/vocoder/configs/melgan_config.json deleted file mode 100644 index 0b6b16db..00000000 --- a/vocoder/configs/melgan_config.json +++ /dev/null @@ -1,145 +0,0 @@ -{ - "run_name": "melgan", - "run_description": "melgan initial run", - - // AUDIO PARAMETERS - "audio":{ - // stft parameters - "num_freq": 513, // number of stft frequency levels. Size of the linear spectogram frame. - "win_length": 1024, // stft window length in ms. - "hop_length": 256, // stft window hop-lengh in ms. - "frame_length_ms": null, // stft window length in ms.If null, 'win_length' is used. - "frame_shift_ms": null, // stft window hop-lengh in ms. If null, 'hop_length' is used. - - // Audio processing parameters - "sample_rate": 22050, // DATASET-RELATED: wav sample-rate. If different than the original data, it is resampled. - "preemphasis": 0.0, // pre-emphasis to reduce spec noise and make it more structured. If 0.0, no -pre-emphasis. - "ref_level_db": 20, // reference level db, theoretically 20db is the sound of air. - - // Silence trimming - "do_trim_silence": true,// enable trimming of slience of audio as you load it. LJspeech (false), TWEB (false), Nancy (true) - "trim_db": 60, // threshold for timming silence. Set this according to your dataset. - - // Griffin-Lim - "power": 1.5, // value to sharpen wav signals after GL algorithm. - "griffin_lim_iters": 60,// #griffin-lim iterations. 30-60 is a good range. Larger the value, slower the generation. - - // MelSpectrogram parameters - "num_mels": 80, // size of the mel spec frame. - "mel_fmin": 0.0, // minimum freq level for mel-spec. ~50 for male and ~95 for female voices. Tune for dataset!! - "mel_fmax": 8000.0, // maximum freq level for mel-spec. Tune for dataset!! - - // Normalization parameters - "signal_norm": true, // normalize spec values. Mean-Var normalization if 'stats_path' is defined otherwise range normalization defined by the other params. - "min_level_db": -100, // lower bound for normalization - "symmetric_norm": true, // move normalization to range [-1, 1] - "max_norm": 4.0, // scale normalization to range [-max_norm, max_norm] or [0, max_norm] - "clip_norm": true, // clip normalized values into the range. - "stats_path": null // DO NOT USE WITH MULTI_SPEAKER MODEL. scaler stats file computed by 'compute_statistics.py'. If it is defined, mean-std based notmalization is used and other normalization params are ignored - }, - - // DISTRIBUTED TRAINING - // "distributed":{ - // "backend": "nccl", - // "url": "tcp:\/\/localhost:54321" - // }, - - // MODEL PARAMETERS - "use_pqmf": true, - - // LOSS PARAMETERS - "use_stft_loss": true, - "use_subband_stft_loss": true, - "use_mse_gan_loss": true, - "use_hinge_gan_loss": false, - "use_feat_match_loss": false, // use only with melgan discriminators - - "stft_loss_weight": 0.5, - "subband_stft_loss_weight": 0.5, - "mse_G_loss_weight": 2.5, - "hinge_G_loss_weight": 2.5, - "feat_match_loss_weight": 25, - - "stft_loss_params": { - "n_ffts": [1024, 2048, 512], - "hop_lengths": [120, 240, 50], - "win_lengths": [600, 1200, 240] - }, - "subband_stft_loss_params":{ - "n_ffts": [384, 683, 171], - "hop_lengths": [30, 60, 10], - "win_lengths": [150, 300, 60] - }, - - "target_loss": "avg_G_loss", // loss value to pick the best model - - // DISCRIMINATOR - "discriminator_model": "melgan_multiscale_discriminator", - "discriminator_model_params":{ - "base_channels": 16, - "max_channels":1024, - "downsample_factors":[4, 4, 4, 4] - }, - "steps_to_start_discriminator": 100000, // steps required to start GAN trainining.1 - - // "discriminator_model": "random_window_discriminator", - // "discriminator_model_params":{ - // "uncond_disc_donwsample_factors": [8, 4], - // "cond_disc_downsample_factors": [[8, 4, 2, 2, 2], [8, 4, 2, 2], [8, 4, 2], [8, 4], [4, 2, 2]], - // "cond_disc_out_channels": [[128, 128, 256, 256], [128, 256, 256], [128, 256], [256], [128, 256]], - // "window_sizes": [512, 1024, 2048, 4096, 8192] - // }, - - - // GENERATOR - "generator_model": "multiband_melgan_generator", - "generator_model_params": { - "upsample_factors":[2 ,2, 4, 4], - "num_res_blocks": 4 - }, - - // DATASET - "data_path": "/home/erogol/Data/LJSpeech-1.1/wavs/", - "seq_len": 16384, - "pad_short": 2000, - "conv_pad": 0, - "use_noise_augment": true, - "use_cache": true, - - "reinit_layers": [], // give a list of layer names to restore from the given checkpoint. If not defined, it reloads all heuristically matching layers. - - // TRAINING - "batch_size": 64, // Batch size for training. Lower values than 32 might cause hard to learn attention. It is overwritten by 'gradual_training'. - - // VALIDATION - "run_eval": true, - "test_delay_epochs": 10, //Until attention is aligned, testing only wastes computation time. - "test_sentences_file": null, // set a file to load sentences to be used for testing. If it is null then we use default english sentences. - - // OPTIMIZER - "noam_schedule": false, // use noam warmup and lr schedule. - "warmup_steps_gen": 4000, // Noam decay steps to increase the learning rate from 0 to "lr" - "warmup_steps_disc": 4000, - "epochs": 1000, // total number of epochs to train. - "wd": 0.000001, // Weight decay weight. - "lr_gen": 0.0001, // Initial learning rate. If Noam decay is active, maximum learning rate. - "lr_disc": 0.0001, - "gen_clip_grad": 10.0, - "disc_clip_grad": 10.0, - - // TENSORBOARD and LOGGING - "print_step": 25, // Number of steps to log traning on console. - "print_eval": false, // If True, it prints intermediate loss values in evalulation. - "save_step": 10000, // Number of training steps expected to save traninpg stats and checkpoints. - "checkpoint": true, // If true, it saves checkpoints per "save_step" - "tb_model_param_stats": false, // true, plots param stats per layer on tensorboard. Might be memory consuming, but good for debugging. - - // DATA LOADING - "num_loader_workers": 4, // number of training data loader processes. Don't set it too big. 4-8 are good values. - "num_val_loader_workers": 4, // number of evaluation data loader processes. - "eval_split_size": 10, - - // PATHS - "output_path": "/home/erogol/Models/LJSpeech/" -} - diff --git a/vocoder/configs/multiband-melgan_and_rwd_config.json b/vocoder/configs/multiband-melgan_and_rwd_config.json index 736f3459..f4b91aae 100644 --- a/vocoder/configs/multiband-melgan_and_rwd_config.json +++ b/vocoder/configs/multiband-melgan_and_rwd_config.json @@ -79,7 +79,7 @@ // "max_channels":1024, // "downsample_factors":[4, 4, 4, 4] // }, - "steps_to_start_discriminator": 100000, // steps required to start GAN trainining.1 + "steps_to_start_discriminator": 200000, // steps required to start GAN trainining.1 "discriminator_model": "random_window_discriminator", "discriminator_model_params":{