diff --git a/TTS/vocoder/configs/multiband-melgan_and_rwd_config.json b/TTS/vocoder/configs/multiband-melgan_and_rwd_config.json index 2670c0f3..d52893f0 100644 --- a/TTS/vocoder/configs/multiband-melgan_and_rwd_config.json +++ b/TTS/vocoder/configs/multiband-melgan_and_rwd_config.json @@ -120,18 +120,23 @@ "wd": 0.0, // Weight decay weight. "gen_clip_grad": -1, // Generator gradient clipping threshold. Apply gradient clipping if > 0 "disc_clip_grad": -1, // Discriminator gradient clipping threshold. - "lr_scheduler_gen": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate + "lr_gen": 0.0002, // Initial learning rate. If Noam decay is active, maximum learning rate. + "lr_disc": 0.0002, + "optimizer": "AdamW", + "optimizer_params":{ + "betas": [0.8, 0.99], + "weight_decay": 0.0 + }, + "lr_scheduler_gen": "ExponentialLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate "lr_scheduler_gen_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] + "gamma": 0.999, + "last_epoch": -1 }, - "lr_scheduler_disc": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate + "lr_scheduler_disc": "ExponentialLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate "lr_scheduler_disc_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] + "gamma": 0.999, + "last_epoch": -1 }, - "lr_gen": 1e-4, // Initial learning rate. If Noam decay is active, maximum learning rate. - "lr_disc": 1e-4, // TENSORBOARD and LOGGING "print_step": 25, // Number of steps to log traning on console. diff --git a/TTS/vocoder/configs/multiband_melgan_config.json b/TTS/vocoder/configs/multiband_melgan_config.json index 807f0836..5aea4a61 100644 --- a/TTS/vocoder/configs/multiband_melgan_config.json +++ b/TTS/vocoder/configs/multiband_melgan_config.json @@ -110,18 +110,23 @@ "wd": 0.0, // Weight decay weight. "gen_clip_grad": -1, // Generator gradient clipping threshold. Apply gradient clipping if > 0 "disc_clip_grad": -1, // Discriminator gradient clipping threshold. - "lr_scheduler_gen": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate + "lr_gen": 0.0002, // Initial learning rate. If Noam decay is active, maximum learning rate. + "lr_disc": 0.0002, + "optimizer": "AdamW", + "optimizer_params":{ + "betas": [0.8, 0.99], + "weight_decay": 0.0 + }, + "lr_scheduler_gen": "ExponentialLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate "lr_scheduler_gen_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] + "gamma": 0.999, + "last_epoch": -1 }, - "lr_scheduler_disc": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate + "lr_scheduler_disc": "ExponentialLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate "lr_scheduler_disc_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] + "gamma": 0.999, + "last_epoch": -1 }, - "lr_gen": 1e-4, // Initial learning rate. If Noam decay is active, maximum learning rate. - "lr_disc": 1e-4, // TENSORBOARD and LOGGING "print_step": 25, // Number of steps to log traning on console. diff --git a/TTS/vocoder/configs/multiband_melgan_config_mozilla.json b/TTS/vocoder/configs/multiband_melgan_config_mozilla.json deleted file mode 100644 index 255315c8..00000000 --- a/TTS/vocoder/configs/multiband_melgan_config_mozilla.json +++ /dev/null @@ -1,156 +0,0 @@ -{ - "run_name": "multiband-melgan", - "run_description": "multiband melgan mean-var scaling", - - // AUDIO PARAMETERS - "audio":{ - "fft_size": 1024, // 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": 0, // 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. - - // MelSpectrogram parameters - "num_mels": 80, // size of the mel spec frame. - "mel_fmin": 50.0, // minimum freq level for mel-spec. ~50 for male and ~95 for female voices. Tune for dataset!! - "mel_fmax": 7600.0, // maximum freq level for mel-spec. Tune for dataset!! - "spec_gain": 1.0, // scaler value appplied after log transform of spectrogram. - - // 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": "/home/erogol/Data/MozillaMerged22050/scale_stats.npy" // 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 - - // loss weights - "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, - - // multiscale stft loss parameters - "stft_loss_params": { - "n_ffts": [1024, 2048, 512], - "hop_lengths": [120, 240, 50], - "win_lengths": [600, 1200, 240] - }, - - // subband multiscale stft loss parameters - "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 to save after each epoch - - // DISCRIMINATOR - "discriminator_model": "melgan_multiscale_discriminator", - "discriminator_model_params":{ - "base_channels": 16, - "max_channels":512, - "downsample_factors":[4, 4, 4] - }, - "steps_to_start_discriminator": 200000, // steps required to start GAN trainining.1 - - // GENERATOR - "generator_model": "multiband_melgan_generator", - "generator_model_params": { - "upsample_factors":[8, 4, 2], - "num_res_blocks": 4 - }, - - // DATASET - "data_path": "/home/erogol/Data/MozillaMerged22050/wavs/", - "feature_path": null, - "seq_len": 6144, - "pad_short": 500, - "conv_pad": 0, - "use_noise_augment": false, - "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'. - "train_noise_schedule":{ - "min_val": 1e-6, - "max_val": 1e-2, - "num_steps": 1000 - }, - "test_noise_schedule":{ - "min_val": 1e-6, - "max_val": 1e-2, - "num_steps": 50 - } - - // 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 - "epochs": 10000, // total number of epochs to train. - "wd": 0.0, // Weight decay weight. - "gen_clip_grad": -1, // Generator gradient clipping threshold. Apply gradient clipping if > 0 - "disc_clip_grad": -1, // Discriminator gradient clipping threshold. - "lr_scheduler_gen": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate - "lr_scheduler_gen_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] - }, - "lr_scheduler_disc": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate - "lr_scheduler_disc_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] - }, - "lr_gen": 1e-4, // Initial learning rate. If Noam decay is active, maximum learning rate. - "lr_disc": 1e-4, - - // TENSORBOARD and LOGGING - "print_step": 25, // Number of steps to log traning on console. - "print_eval": false, // If True, it prints loss values for each step in eval run. - "save_step": 25000, // Number of training steps expected to plot training stats on TB and save model checkpoints. - "checkpoint": true, // If true, it saves checkpoints per "save_step" - "keep_all_best": false, // If true, keeps all best_models after keep_after steps - "keep_after": 10000, // Global step after which to keep best models if keep_all_best is true - "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/Mozilla/" -} - diff --git a/TTS/vocoder/configs/parallel_wavegan_config.json b/TTS/vocoder/configs/parallel_wavegan_config.json index 193b1f7b..5ea7dbcd 100644 --- a/TTS/vocoder/configs/parallel_wavegan_config.json +++ b/TTS/vocoder/configs/parallel_wavegan_config.json @@ -112,19 +112,23 @@ "wd": 0.0, // Weight decay weight. "gen_clip_grad": -1, // Generator gradient clipping threshold. Apply gradient clipping if > 0 "disc_clip_grad": -1, // Discriminator gradient clipping threshold. - "lr_scheduler_gen": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate + "lr_gen": 0.0002, // Initial learning rate. If Noam decay is active, maximum learning rate. + "lr_disc": 0.0002, + "optimizer": "AdamW", + "optimizer_params":{ + "betas": [0.8, 0.99], + "weight_decay": 0.0 + }, + "lr_scheduler_gen": "ExponentialLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate "lr_scheduler_gen_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] + "gamma": 0.999, + "last_epoch": -1 }, - "lr_scheduler_disc": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate + "lr_scheduler_disc": "ExponentialLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate "lr_scheduler_disc_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] + "gamma": 0.999, + "last_epoch": -1 }, - "lr_gen": 1e-4, // Initial learning rate. If Noam decay is active, maximum learning rate. - "lr_disc": 1e-4, - // TENSORBOARD and LOGGING "print_step": 25, // Number of steps to log traning on console. "print_eval": false, // If True, it prints loss values for each step in eval run. diff --git a/TTS/vocoder/configs/universal_fullband_melgan.json b/TTS/vocoder/configs/universal_fullband_melgan.json index 511ae70e..245de2d3 100644 --- a/TTS/vocoder/configs/universal_fullband_melgan.json +++ b/TTS/vocoder/configs/universal_fullband_melgan.json @@ -106,18 +106,23 @@ "wd": 0.0, // Weight decay weight. "gen_clip_grad": -1, // Generator gradient clipping threshold. Apply gradient clipping if > 0 "disc_clip_grad": -1, // Discriminator gradient clipping threshold. - "lr_scheduler_gen": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate + "lr_gen": 0.0002, // Initial learning rate. If Noam decay is active, maximum learning rate. + "lr_disc": 0.0002, + "optimizer": "AdamW", + "optimizer_params":{ + "betas": [0.8, 0.99], + "weight_decay": 0.0 + }, + "lr_scheduler_gen": "ExponentialLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate "lr_scheduler_gen_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] + "gamma": 0.999, + "last_epoch": -1 }, - "lr_scheduler_disc": "MultiStepLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate + "lr_scheduler_disc": "ExponentialLR", // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate "lr_scheduler_disc_params": { - "gamma": 0.5, - "milestones": [100000, 200000, 300000, 400000, 500000, 600000] + "gamma": 0.999, + "last_epoch": -1 }, - "lr_gen": 0.000015625, // Initial learning rate. If Noam decay is active, maximum learning rate. - "lr_disc": 0.000015625, // TENSORBOARD and LOGGING "print_step": 25, // Number of steps to log traning on console.