From a7fb49843b94ea149d1caceb0ee6ee1529cb7d35 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Eren=20G=C3=B6lge?= Date: Thu, 8 Apr 2021 13:18:03 +0200 Subject: [PATCH] update test config --- .../test_vocoder_multiband_melgan_config.json | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/tests/inputs/test_vocoder_multiband_melgan_config.json b/tests/inputs/test_vocoder_multiband_melgan_config.json index c1797888..794a3fcc 100644 --- a/tests/inputs/test_vocoder_multiband_melgan_config.json +++ b/tests/inputs/test_vocoder_multiband_melgan_config.json @@ -13,10 +13,12 @@ // 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. + "ref_level_db": 20, // reference level db, theoretically 20db is the sound of air. + "log_func": "np.log10", + "do_sound_norm": true, // Silence trimming - "do_trim_silence": true,// enable trimming of slience of audio as you load it. LJspeech (false), TWEB (false), Nancy (true) + "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 @@ -31,7 +33,7 @@ "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 + "stats_path": null }, // DISTRIBUTED TRAINING @@ -126,6 +128,11 @@ "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. + "optimizer": "AdamW", + "optimizer_params":{ + "betas": [0.8, 0.99], + "weight_decay": 0.0 + }, "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,