From f7bfee0066eefac573c90bbdf0c2d21e7d3dfad4 Mon Sep 17 00:00:00 2001 From: Eren Golge Date: Tue, 12 Mar 2019 01:26:21 +0100 Subject: [PATCH] nancy config changes --- .compute | 6 +++--- config_cluster.json | 12 ++++++------ 2 files changed, 9 insertions(+), 9 deletions(-) diff --git a/.compute b/.compute index 8e2ec00e..b6bb33dd 100644 --- a/.compute +++ b/.compute @@ -1,7 +1,7 @@ #!/bin/bash -ls ${SHARED_DIR}/data/keithito +ls ${SHARED_DIR}/data/ pip3 install https://download.pytorch.org/whl/cu100/torch-1.0.1.post2-cp36-cp36m-linux_x86_64.whl yes | apt-get install espeak python3 setup.py develop -python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/keithito/LJSpeech-1.1/ --restore_path ${USER_DIR}/best_model.pth.tar -# python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/keithito/LJSpeech-1.1/ +# python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/keithito/LJSpeech-1.1/ --restore_path ${USER_DIR}/best_model.pth.tar +python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/Blizzard/Nancy/ diff --git a/config_cluster.json b/config_cluster.json index f63dc080..e36bb4c2 100644 --- a/config_cluster.json +++ b/config_cluster.json @@ -1,6 +1,6 @@ { - "run_name": "bos", - "run_description": "bos character added to get away with the first char miss", + "run_name": "nancy-bn", + "run_description": "Nancy tacotron2 from scratch BN", "audio":{ // Audio processing parameters @@ -51,15 +51,15 @@ "run_eval": true, "test_delay_epochs": 100, //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_train.csv", // DATASET-RELATED: metafile for training dataloader. - "meta_file_val": "metadata_val.csv", // DATASET-RELATED: metafile for evaluation dataloader. - "dataset": "ljspeech", // DATASET-RELATED: one of TTS.dataset.preprocessors depending on your target dataset. Use "tts_cache" for pre-computed dataset by extract_features.py + "meta_file_train": "prompts_train.data", // DATASET-RELATED: metafile for training dataloader. + "meta_file_val": "prompts_val.data", // DATASET-RELATED: metafile for evaluation dataloader. + "dataset": "nancy", // 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": 1000, // DATASET-RELATED: maximum text length "output_path": "../keep/", // DATASET-RELATED: output path for all training outputs. "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. - "phoneme_cache_path": "ljspeech_us_phonemes", // phoneme computation is slow, therefore, it caches results in the given folder. + "phoneme_cache_path": "nancy_us_phonemes", // phoneme computation is slow, therefore, it caches results in the given folder. "use_phonemes": true, // use phonemes instead of raw characters. It is suggested for better pronounciation. "phoneme_language": "en-us", // depending on your target language, pick one from https://github.com/bootphon/phonemizer#languages "text_cleaner": "phoneme_cleaners"