Afegeix models

Dockerfile

@@ -12,6 +12,7 @@ RUN cd espeak-ng && \
 
 COPY requirements.txt .
 COPY app.py .
+COPY models .
 
 RUN pip install -r requirements.txt
 
@@ -20,7 +21,6 @@ RUN mkdir -p cache && chmod 777 cache
 ENV NUMBA_CACHE_DIR=./cache
 ENV MPLCONFIGDIR=./cache
 
-
 EXPOSE 7860
 
-CMD python app.py
+CMD ["python", "app.py"]

models/bsc/best_model.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b15fa7d2052bada1cf421e49d2d03b00e95b49fcd0e42b7af1d92da2880cdecc
+size 1038659133

models/bsc/config.json

@@ -0,0 +1,262 @@
+{
+    "output_path": "/gpfs/projects/bsc88/speech/tts/TTS_v0.8.0/recipes/multispeaker/experiments_from_previous",
+    "logger_uri": null,
+    "run_name": "multispeaker_vits_ca_1e4_1e4_32",
+    "project_name": null,
+    "run_description": "\ud83d\udc38Coqui trainer run.",
+    "print_step": 25,
+    "plot_step": 100,
+    "model_param_stats": false,
+    "wandb_entity": null,
+    "dashboard_logger": "tensorboard",
+    "log_model_step": 1000,
+    "save_step": 1000,
+    "save_n_checkpoints": 5,
+    "save_checkpoints": true,
+    "save_all_best": true,
+    "save_best_after": 10000,
+    "target_loss": null,
+    "print_eval": true,
+    "test_delay_epochs": -1,
+    "run_eval": true,
+    "run_eval_steps": null,
+    "distributed_backend": "nccl",
+    "distributed_url": "tcp://localhost:54321",
+    "mixed_precision": false,
+    "epochs": 1000,
+    "batch_size": 16,
+    "eval_batch_size": 8,
+    "grad_clip": [
+        1000.0,
+        1000.0
+    ],
+    "scheduler_after_epoch": true,
+    "lr": 0.001,
+    "optimizer": "AdamW",
+    "optimizer_params": {
+        "betas": [
+            0.8,
+            0.99
+        ],
+        "eps": 1e-09,
+        "weight_decay": 0.01
+    },
+    "lr_scheduler": "",
+    "lr_scheduler_params": null,
+    "use_grad_scaler": false,
+    "cudnn_enable": true,
+    "cudnn_deterministic": false,
+    "cudnn_benchmark": false,
+    "training_seed": 54321,
+    "model": "vits",
+    "num_loader_workers": 4,
+    "num_eval_loader_workers": 4,
+    "use_noise_augment": false,
+    "audio": {
+        "fft_size": 1024,
+        "sample_rate": 22050,
+        "win_length": 1024,
+        "hop_length": 256,
+        "num_mels": 80,
+        "mel_fmin": 0,
+        "mel_fmax": null
+    },
+    "use_phonemes": true,
+    "phonemizer": "espeak",
+    "phoneme_language": "ca",
+    "compute_input_seq_cache": true,
+    "text_cleaner": "multilingual_cleaners",
+    "enable_eos_bos_chars": false,
+    "test_sentences_file": "",
+    "phoneme_cache_path": "/gpfs/projects/bsc88/speech/tts/TTS_v0.8.0/recipes/multispeaker/phoneme_cache",
+    "characters": {
+        "characters_class": "TTS.tts.utils.text.characters.IPAPhonemes",
+        "vocab_dict": null,
+        "pad": "<PAD>",
+        "eos": "<EOS>",
+        "bos": "<BOS>",
+        "blank": "<BLNK>",
+        "characters": "iy\u0268\u0289\u026fu\u026a\u028f\u028ae\u00f8\u0258\u0259\u0275\u0264o\u025b\u0153\u025c\u025e\u028c\u0254\u00e6\u0250a\u0276\u0251\u0252\u1d7b\u0298\u0253\u01c0\u0257\u01c3\u0284\u01c2\u0260\u01c1\u029bpbtd\u0288\u0256c\u025fk\u0261q\u0262\u0294\u0274\u014b\u0272\u0273n\u0271m\u0299r\u0280\u2c71\u027e\u027d\u0278\u03b2fv\u03b8\u00f0sz\u0283\u0292\u0282\u0290\u00e7\u029dx\u0263\u03c7\u0281\u0127\u0295h\u0266\u026c\u026e\u028b\u0279\u027bj\u0270l\u026d\u028e\u029f\u02c8\u02cc\u02d0\u02d1\u028dw\u0265\u029c\u02a2\u02a1\u0255\u0291\u027a\u0267\u02b2\u025a\u02de\u026b",
+        "punctuations": "!'(),-.:;? ",
+        "phonemes": null,
+        "is_unique": false,
+        "is_sorted": true
+    },
+    "add_blank": true,
+    "batch_group_size": 5,
+    "loss_masking": null,
+    "min_audio_len": 1,
+    "max_audio_len": Infinity,
+    "min_text_len": 1,
+    "max_text_len": 325,
+    "compute_f0": false,
+    "compute_linear_spec": true,
+    "precompute_num_workers": 0,
+    "start_by_longest": false,
+    "datasets": [
+        {
+            "formatter": "vctk_old",
+            "dataset_name": "vctk_old",
+            "path": "/gpfs/scratch/bsc88/bsc88474/data/multispeaker_ca",
+            "meta_file_train": "",
+            "ignored_speakers": [
+                "uri",
+                "09796",
+                "05450"
+            ],
+            "language": "ca",
+            "meta_file_val": "",
+            "meta_file_attn_mask": ""
+        }
+    ],
+    "test_sentences": [
+        [
+            "Per exemple, dels nostres bancs que inverteixen en armament de les nostres empreses."
+        ],
+        [
+            "Preguntin-se si aix\u00f2 era necessari."
+        ],
+        [
+            "La suposada ocultaci\u00f3 dels informes que advertien de risc s\u00edsmic."
+        ],
+        [
+            "\u00c9s de 633 milions d'euros quan es far\u00e0 la publicaci\u00f3 detallada."
+        ]
+    ],
+    "eval_split_max_size": null,
+    "eval_split_size": 0.01,
+    "use_speaker_weighted_sampler": false,
+    "speaker_weighted_sampler_alpha": 1.0,
+    "use_language_weighted_sampler": false,
+    "language_weighted_sampler_alpha": 1.0,
+    "use_length_weighted_sampler": false,
+    "length_weighted_sampler_alpha": 1.0,
+    "model_args": {
+        "num_chars": 131,
+        "out_channels": 513,
+        "spec_segment_size": 32,
+        "hidden_channels": 192,
+        "hidden_channels_ffn_text_encoder": 768,
+        "num_heads_text_encoder": 2,
+        "num_layers_text_encoder": 6,
+        "kernel_size_text_encoder": 3,
+        "dropout_p_text_encoder": 0.1,
+        "dropout_p_duration_predictor": 0.5,
+        "kernel_size_posterior_encoder": 5,
+        "dilation_rate_posterior_encoder": 1,
+        "num_layers_posterior_encoder": 16,
+        "kernel_size_flow": 5,
+        "dilation_rate_flow": 1,
+        "num_layers_flow": 4,
+        "resblock_type_decoder": "1",
+        "resblock_kernel_sizes_decoder": [
+            3,
+            7,
+            11
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+        "resblock_dilation_sizes_decoder": [
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+                1,
+                3,
+                5
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+            [
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+                3,
+                5
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+        "upsample_rates_decoder": [
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+            8,
+            2,
+            2
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+        "upsample_initial_channel_decoder": 512,
+        "upsample_kernel_sizes_decoder": [
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+            16,
+            4,
+            4
+        ],
+        "periods_multi_period_discriminator": [
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+            3,
+            5,
+            7,
+            11
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+        "use_sdp": true,
+        "noise_scale": 1.0,
+        "inference_noise_scale": 0.667,
+        "length_scale": 1.0,
+        "noise_scale_dp": 1.0,
+        "inference_noise_scale_dp": 1.0,
+        "max_inference_len": null,
+        "init_discriminator": true,
+        "use_spectral_norm_disriminator": false,
+        "use_speaker_embedding": true,
+        "num_speakers": 257,
+        "speakers_file": "/home/user/app/speakers.pth",
+        "d_vector_file": null,
+        "speaker_embedding_channels": 256,
+        "use_d_vector_file": false,
+        "d_vector_dim": 0,
+        "detach_dp_input": true,
+        "use_language_embedding": false,
+        "embedded_language_dim": 4,
+        "num_languages": 0,
+        "language_ids_file": null,
+        "use_speaker_encoder_as_loss": false,
+        "speaker_encoder_config_path": "",
+        "speaker_encoder_model_path": "",
+        "condition_dp_on_speaker": true,
+        "freeze_encoder": false,
+        "freeze_DP": false,
+        "freeze_PE": false,
+        "freeze_flow_decoder": false,
+        "freeze_waveform_decoder": false,
+        "encoder_sample_rate": null,
+        "interpolate_z": true,
+        "reinit_DP": false,
+        "reinit_text_encoder": false
+    },
+    "lr_gen": 0.0001,
+    "lr_disc": 0.0001,
+    "lr_scheduler_gen": "ExponentialLR",
+    "lr_scheduler_gen_params": {
+        "gamma": 0.999875,
+        "last_epoch": -1
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+    "lr_scheduler_disc": "ExponentialLR",
+    "lr_scheduler_disc_params": {
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+        "last_epoch": -1
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+    "kl_loss_alpha": 1.0,
+    "disc_loss_alpha": 1.0,
+    "gen_loss_alpha": 1.0,
+    "feat_loss_alpha": 1.0,
+    "mel_loss_alpha": 45.0,
+    "dur_loss_alpha": 1.0,
+    "speaker_encoder_loss_alpha": 1.0,
+    "return_wav": true,
+    "use_weighted_sampler": false,
+    "weighted_sampler_attrs": null,
+    "weighted_sampler_multipliers": null,
+    "r": 1,
+    "num_speakers": 257,
+    "use_speaker_embedding": true,
+    "speakers_file": "/home/user/app/speakers.pth",
+    "speaker_embedding_channels": 256,
+    "language_ids_file": null,
+    "use_language_embedding": false,
+    "use_d_vector_file": false,
+    "d_vector_file": null,
+    "d_vector_dim": 0
+}

models/bsc/speaker_map.json

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+{
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+    "f_cen_81": "8162d651b6211f06f655a69cd7fdd383d6b4287e9ba132b9898ef9ac8687349e777626333d23bed93f9264aae965efb14ed650cb64fd0ad90494aff903eaef11",
+    "f_occ_31": "31535cb2ece4710d08fdbeefb6f8f75ed093fee4cf8573bd601d960f8c6156f0fd0a85712761691e86e31160b993ee0eacb10c4c8aed000cc394cf7c7d207a7e",
+    "f_occ_de": "dee065b956b99b10db4763759d64c41791af1a7e77f1864f90a2b0847a12633dcf9bc108db7eaf73cc8d0e750f5c37383a56cd77cc2276d3960104c6bebe6346",
+    "f_sep_31": "31e6f3a011661320b2e59b6f8be43f6db2243e9feabc2b9787c1413788e13eb0e5810bed983bf7ff66e46417d183a91ed50b3b9be9d89e4f51aada72293b9881",
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+    "m_occ_44": "30b1f81c579755895581259d79a8a5a3ca45b908b0bd14ad1c6418f39aa1e2f47cb4749c69b5440cdb92e3bafb772e19e7bc2b16d196b061addd173a1309e491",
+    "m_val_89": "896256329fbeb5b8116349c31d8a39a7d36d5f970d48558e1db5417d611e240e4dbf473f6e49137f7aa6116394b7deabb0bbec4a014896cdc9484ee91458117d"
+}

models/bsc/speakers.pth

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+size 30191

models/collectivat/catotron-ona-TTS-API-entry.json

@@ -0,0 +1,10 @@
+{
+    "voice": "ona-fast-hifigan",
+    "lang": "ca",
+    "model_type": "coqui",
+    "tts_config_path": "fast-speech_config.json",
+    "tts_model_path": "fast-speech_best_model.pth",
+    "vocoder_config_path": "ljspeech--hifigan_v2_config.json",
+    "vocoder_model_path": "ljspeech--hifigan_v2_model_file.pth",
+    "load": true
+}

models/collectivat/fast-speech_best_model.pth

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+size 457921637

models/collectivat/fast-speech_config.json

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+{
+    "output_path": "/home/twbgmy/play/TTS-play/TTS/recipes/catotron",
+    "logger_uri": null,
+    "run_name": "fast_pitch_ljspeech",
+    "project_name": null,
+    "run_description": "\ud83d\udc38Coqui trainer run.",
+    "print_step": 50,
+    "plot_step": 100,
+    "model_param_stats": false,
+    "wandb_entity": null,
+    "dashboard_logger": "tensorboard",
+    "log_model_step": null,
+    "save_step": 10000,
+    "save_n_checkpoints": 5,
+    "save_checkpoints": true,
+    "save_all_best": false,
+    "save_best_after": 1000,
+    "target_loss": null,
+    "print_eval": false,
+    "test_delay_epochs": -1,
+    "run_eval": true,
+    "run_eval_steps": null,
+    "distributed_backend": "nccl",
+    "distributed_url": "tcp://localhost:54321",
+    "mixed_precision": false,
+    "epochs": 1000,
+    "batch_size": 16,
+    "eval_batch_size": 16,
+    "grad_clip": 5.0,
+    "scheduler_after_epoch": true,
+    "lr": 0.0001,
+    "optimizer": "Adam",
+    "optimizer_params": {
+        "betas": [
+            0.9,
+            0.998
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+        "weight_decay": 1e-06
+    },
+    "lr_scheduler": "NoamLR",
+    "lr_scheduler_params": {
+        "warmup_steps": 4000
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+    "use_grad_scaler": false,
+    "cudnn_enable": true,
+    "cudnn_deterministic": false,
+    "cudnn_benchmark": false,
+    "training_seed": 54321,
+    "model": "fast_pitch",
+    "num_loader_workers": 8,
+    "num_eval_loader_workers": 4,
+    "use_noise_augment": false,
+    "audio": {
+        "fft_size": 1024,
+        "win_length": 1024,
+        "hop_length": 256,
+        "frame_shift_ms": null,
+        "frame_length_ms": null,
+        "stft_pad_mode": "reflect",
+        "sample_rate": 22050,
+        "resample": false,
+        "preemphasis": 0.0,
+        "ref_level_db": 20,
+        "do_sound_norm": false,
+        "log_func": "np.log",
+        "do_trim_silence": true,
+        "trim_db": 60.0,
+        "do_rms_norm": false,
+        "db_level": null,
+        "power": 1.5,
+        "griffin_lim_iters": 60,
+        "num_mels": 80,
+        "mel_fmin": 0.0,
+        "mel_fmax": 8000,
+        "spec_gain": 1.0,
+        "do_amp_to_db_linear": true,
+        "do_amp_to_db_mel": true,
+        "pitch_fmax": 640.0,
+        "pitch_fmin": 0.0,
+        "signal_norm": false,
+        "min_level_db": -100,
+        "symmetric_norm": true,
+        "max_norm": 4.0,
+        "clip_norm": true,
+        "stats_path": null
+    },
+    "use_phonemes": false,
+    "phonemizer": null,
+    "phoneme_language": "ca-es",
+    "compute_input_seq_cache": true,
+    "text_cleaner": "multilingual_cleaners",
+    "enable_eos_bos_chars": false,
+    "test_sentences_file": "",
+    "phoneme_cache_path": null,
+    "characters": {
+        "characters_class": "TTS.tts.utils.text.characters.Graphemes",
+        "vocab_dict": null,
+        "pad": "_",
+        "eos": "*",
+        "bos": "^",
+        "blank": null,
+        "characters": "A\u00c0\u00c1BC\u00c7DE\u00c9\u00c8FGHI\u00cd\u00cfJKLMNO\u00d3\u00d2PQRSTU\u00dc\u00daVWXYZa\u00e0\u00e1bc\u00e7de\u00e9\u00e8fghi\u00ed\u00efjklmno\u00f3\u00f2pqrstu\u00fc\u00favwxyz",
+        "punctuations": "!'(),-.:;?\u00b7 ",
+        "phonemes": "",
+        "is_unique": true,
+        "is_sorted": true
+    },
+    "add_blank": false,
+    "batch_group_size": 0,
+    "loss_masking": null,
+    "min_audio_len": 1,
+    "max_audio_len": Infinity,
+    "min_text_len": 1,
+    "max_text_len": Infinity,
+    "compute_f0": true,
+    "compute_linear_spec": false,
+    "precompute_num_workers": 4,
+    "start_by_longest": false,
+    "datasets": [
+        {
+            "name": "custom_turkish",
+            "path": "/home/twbgmy/play/TTS-play/TTS/recipes/catotron/upc_ona",
+            "meta_file_train": "upc_ona_train.txt",
+            "ignored_speakers": null,
+            "language": "",
+            "meta_file_val": "",
+            "meta_file_attn_mask": ""
+        },
+        {
+            "name": "custom_turkish",
+            "path": "/home/twbgmy/play/TTS-play/TTS/recipes/catotron/upc_ona",
+            "meta_file_train": "upc_ona_val.txt",
+            "ignored_speakers": null,
+            "language": "",
+            "meta_file_val": "",
+            "meta_file_attn_mask": ""
+        }
+    ],
+    "test_sentences": [
+        "Hola Barcelona!",
+        "Escriviu al text."
+    ],
+    "eval_split_max_size": null,
+    "eval_split_size": 0.01,
+    "use_speaker_weighted_sampler": false,
+    "speaker_weighted_sampler_alpha": 1.0,
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+    "language_weighted_sampler_alpha": 1.0,
+    "use_length_weighted_sampler": false,
+    "length_weighted_sampler_alpha": 1.0,
+    "base_model": "forward_tts",
+    "model_args": {
+        "num_chars": 89,
+        "out_channels": 80,
+        "hidden_channels": 384,
+        "use_aligner": true,
+        "use_pitch": true,
+        "pitch_predictor_hidden_channels": 256,
+        "pitch_predictor_kernel_size": 3,
+        "pitch_predictor_dropout_p": 0.1,
+        "pitch_embedding_kernel_size": 3,
+        "duration_predictor_hidden_channels": 256,
+        "duration_predictor_kernel_size": 3,
+        "duration_predictor_dropout_p": 0.1,
+        "positional_encoding": true,
+        "poisitonal_encoding_use_scale": true,
+        "length_scale": 1,
+        "encoder_type": "fftransformer",
+        "encoder_params": {
+            "hidden_channels_ffn": 1024,
+            "num_heads": 1,
+            "num_layers": 6,
+            "dropout_p": 0.1
+        },
+        "decoder_type": "fftransformer",
+        "decoder_params": {
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+            "num_heads": 1,
+            "num_layers": 6,
+            "dropout_p": 0.1
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+        "detach_duration_predictor": false,
+        "max_duration": 75,
+        "num_speakers": 1,
+        "use_speaker_embedding": false,
+        "speakers_file": null,
+        "use_d_vector_file": false,
+        "d_vector_dim": null,
+        "d_vector_file": null
+    },
+    "num_speakers": 0,
+    "speakers_file": null,
+    "use_speaker_embedding": false,
+    "use_d_vector_file": false,
+    "d_vector_file": false,
+    "d_vector_dim": 0,
+    "spec_loss_type": "mse",
+    "duration_loss_type": "mse",
+    "use_ssim_loss": true,
+    "ssim_loss_alpha": 1.0,
+    "spec_loss_alpha": 1.0,
+    "aligner_loss_alpha": 1.0,
+    "pitch_loss_alpha": 0.1,
+    "dur_loss_alpha": 0.1,
+    "binary_align_loss_alpha": 0.1,
+    "binary_loss_warmup_epochs": 150,
+    "min_seq_len": 13,
+    "max_seq_len": 500000,
+    "r": 1,
+    "f0_cache_path": "/home/twbgmy/play/TTS-play/TTS/recipes/catotron/f0_cache",
+    "restore_path": "/home/twbgmy/.local/share/tts/tts_models--en--ljspeech--fast_pitch/model_file.pth",
+    "github_branch": "* dev"
+}

models/collectivat/ljspeech--hifigan_v2_config.json

@@ -0,0 +1,158 @@
+{
+    "run_name": "hifigan",
+    "run_description": "universal hifigan trained on LibriTTS with no spectrogram normalization and using log() for scaling instead of log10()",
+
+
+    // 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": 20,     // reference level db, theoretically 20db is the sound of air.
+        "log_func": "np.log",
+
+        // Silence trimming
+        "do_trim_silence": false,// 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": 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!!
+        "spec_gain": 1.0,         // scaler value appplied after log transform of spectrogram.
+
+        // Normalization parameters
+        "signal_norm": false,    // 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:54324"
+    },
+
+    // MODEL PARAMETERS
+    "use_pqmf": false,
+
+    // LOSS PARAMETERS
+    "use_stft_loss": false,
+    "use_subband_stft_loss": false,
+    "use_mse_gan_loss": true,
+    "use_hinge_gan_loss": false,
+    "use_feat_match_loss": true,  // use only with melgan discriminators
+    "use_l1_spec_loss": true,
+
+    // loss weights
+    "stft_loss_weight": 0,
+    "subband_stft_loss_weight": 0,
+    "mse_G_loss_weight": 1,
+    "hinge_G_loss_weight": 0,
+    "feat_match_loss_weight": 10,
+    "l1_spec_loss_weight": 45,
+
+    // multiscale stft loss parameters
+    // "stft_loss_params": {
+    //     "n_ffts": [1024, 2048, 512],
+    //     "hop_lengths": [120, 240, 50],
+    //     "win_lengths": [600, 1200, 240]
+    // },
+
+    "l1_spec_loss_params": {
+        "use_mel": true,
+        "sample_rate": 16000,
+        "n_fft": 1024,
+        "hop_length": 256,
+        "win_length": 1024,
+        "n_mels": 80,
+        "mel_fmin": 0.0,
+        "mel_fmax": null
+    },
+
+    "target_loss": "avg_G_loss",  // loss value to pick the best model to save after each epoch
+
+    // DISCRIMINATOR
+    "discriminator_model": "hifigan_discriminator",
+    //"discriminator_model_params":{
+    //    "peroids": [2, 3, 5, 7, 11],
+    //    "base_channels": 16,
+    //    "max_channels":512,
+    //    "downsample_factors":[4, 4, 4]
+    //},
+    "steps_to_start_discriminator": 0,      // steps required to start GAN trainining.1
+
+    // GENERATOR
+    "generator_model": "hifigan_generator",
+    "generator_model_params": {
+        "resblock_type": "1",
+        "upsample_factors": [8,8,2,2],
+        "upsample_kernel_sizes": [16,16,4,4],
+        "upsample_initial_channel": 128,
+        "resblock_kernel_sizes": [3,7,11],
+        "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]]
+    },
+
+    // DATASET
+    "data_path": "/home/erogol/gdrive/Datasets/non-binary-voice-files/vo_voice_quality_transformation/",
+    "feature_path": null,
+    // "feature_path": "/home/erogol/gdrive/Datasets/non-binary-voice-files/tacotron-DCA/",
+    "seq_len": 8192,
+    "pad_short": 2000,
+    "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": 16,       // 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
+    "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": "ExponentialLR",   // one of the schedulers from https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
+    // "lr_scheduler_gen_params": {
+    //    "gamma": 0.999,
+        // "last_epoch": -1
+    // },
+    // "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": 0.999,
+        // "last_epoch": -1
+    // },
+    "lr_gen": 0.00001,                  // Initial learning rate. If Noam decay is active, maximum learning rate.
+    "lr_disc": 0.00001,
+
+    // 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"
+    "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": 8,        // 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/gdrive/Trainings/sam/"
+}
+
+

models/collectivat/ljspeech--hifigan_v2_model_file.pth

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+oid sha256:4047e93886faa1aba11948efa71f59dcb0ec9117e286660e59b91892ef98d129
+size 3794153

models/piper/MODEL_CARD

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+# Model card for upc_ona (x-low)
+
+* Language: ca (Catalan)
+* Speakers: 1
+* Quality: x-low
+* Samplerate: 16,000Hz
+
+## Dataset
+
+* URL: https://collectivat.cat/asr#upc-festcat-tts-corpora
+* License: CC BY-SA 3.0 ES
+
+## Training
+
+Trained from scratch.

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