Medix-AI/coqui-tts
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coqui-tts
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config update

This commit is contained in:
Eren Golge 2019-05-06 16:14:02 +02:00
parent afb5a17221
commit e5b5ca8dff
2 changed files with 11 additions and 11 deletions
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6
.compute
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@ -5,10 +5,10 @@ yes | apt-get install espeak
yes | apt-get install tmux
yes | apt-get install zsh
pip3 install https://download.pytorch.org/whl/cu100/torch-1.0.1.post2-cp36-cp36m-linux_x86_64.whl
wget https://www.dropbox.com/s/rowimjoosnmdgj4/best_model_4702.pth.tar?dl=0 -O best_model_4702.pth.tar
# wget https://www.dropbox.com/s/m8waow6b3ydpf6h/MozillaDataset.tar.gz?dl=0 -O /data/rw/home/mozilla.tar
wget https://www.dropbox.com/s/wqn5v3wkktw9lmo/install.sh?dl=0 -O install.sh
sudo sh install.sh
python3 setup.py develop
# python3 distribute.py --config_path config_cluster.json --data_path ${USER_DIR}/Mozilla/ --restore_path ${USER_DIR}/best_model_4700.pth.tar
python3 distribute.py --config_path config_cluster.json --data_path ${USER_DIR}/MozillaAll/Mozilla/ --restore_path ${USER_DIR}/checkpoint_123000_4761.pth.tar
# python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/mozilla/Judy/
while true; do sleep 1000000; done
# while true; do sleep 1000000; done

16
config_cluster.json
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@ -1,6 +1,6 @@
{
"run_name": "mozilla-fattn-agent-masking",
"run_description": "finetune 4706 with prenet BN. Loss masking, fattn.",
"run_name": "mozilla-fattn-stopnet",
"run_description": "Finetune 4761 with BN",
"audio":{
// Audio processing parameters
@ -40,14 +40,14 @@
"windowing": false, // Enables attention windowing. Used only in eval mode.
"memory_size": 5, // ONLY TACOTRON - memory queue size used to queue network predictions to feed autoregressive connection. Useful if r < 5.
"attention_norm": "softmax", // softmax or sigmoid. Suggested to use softmax for Tacotron2 and sigmoid for Tacotron.
"prenet_type": "original", // ONLY TACOTRON2 - "original" or "bn".
"prenet_type": "bn", // ONLY TACOTRON2 - "original" or "bn".
"use_forward_attn": true, // ONLY TACOTRON2 - if it uses forward attention. In general, it aligns faster.
"transition_agent": false, // ONLY TACOTRON2 - enable/disable transition agent of forward attention.
"location_attn": true, // ONLY TACOTRON2 - enable_disable location sensitive attention. It is enabled for TACOTRON by default.
"loss_masking": true, // enable / disable loss masking against the sequence padding.
"location_attn": false, // ONLY TACOTRON2 - enable_disable location sensitive attention. It is enabled for TACOTRON by default.
"loss_masking": false, // enable / disable loss masking against the sequence padding.
"enable_eos_bos_chars": false, // enable/disable beginning of sentence and end of sentence chars.
"batch_size": 24, // Batch size for training. Lower values than 32 might cause hard to learn attention.
"batch_size": 32, // Batch size for training. Lower values than 32 might cause hard to learn attention.
"eval_batch_size":16,
"r": 1, // Number of frames to predict for step.
"wd": 0.000001, // Weight decay weight.
@ -60,12 +60,12 @@
"run_eval": true,
"test_delay_epochs": 1, //Until attention is aligned, testing only wastes computation time.
"data_path": "/media/erogol/data_ssd/Data/LJSpeech-1.1", // DATASET-RELATED: can overwritten from command argument
"meta_file_train": "metadata.txt", // DATASET-RELATED: metafile for training dataloader.
"meta_file_train": "metadata_train.txt", // DATASET-RELATED: metafile for training dataloader.
"meta_file_val": "metadata_val.txt", // DATASET-RELATED: metafile for evaluation dataloader.
"dataset": "mozilla", // DATASET-RELATED: one of TTS.dataset.preprocessors depending on your target dataset. Use "tts_cache" for pre-computed dataset by extract_features.py
"min_seq_len": 0, // DATASET-RELATED: minimum text length to use in training
"max_seq_len": 150, // DATASET-RELATED: maximum text length
"output_path": "../keep/", // DATASET-RELATED: output path for all training outputs.
"output_path": "/media/erogol/data_ssd/Data/models/mozilla_models/", // DATASET-RELATED: output path for all training outputs.
"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.
"phoneme_cache_path": "mozilla_us_phonemes", // phoneme computation is slow, therefore, it caches results in the given folder.