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config update, check arguments update and enable alternative arguments

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erogol
2020-02-23 03:09:10 +01:00
parent f707460886
commit e6504cc9a4
2 changed files with 8 additions and 7 deletions
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config.json
+3 -4
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@@ -1,6 +1,6 @@
{
"model": "Tacotron2", // one of the model in models/
"run_name": "ljspeech-stf_params",
"run_name": "ljspeech-stft_params",
"run_description": "tacotron2 cosntant stf parameters",
// AUDIO PARAMETERS
@@ -36,12 +36,11 @@
"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": 2, // Batch size for training. Lower values than 32 might cause hard to learn attention. It is overwritten by 'gradual_training'.
"batch_size": 32, // Batch size for training. Lower values than 32 might cause hard to learn attention. It is overwritten by 'gradual_training'.
"eval_batch_size":16,
"r": 7, // Number of decoder frames to predict per iteration. Set the initial values if gradual training is enabled.
"gradual_training": [[0, 7, 64], [2000, 5, 64], [35000, 3, 32], [70000, 2, 32], [140000, 1, 32]], //set gradual training steps [first_step, r, batch_size]. If it is null, gradual training is disabled. For Tacotron, you might need to reduce the 'batch_size' as you proceeed.
"gradual_training": [[0, 7, 64], [1, 5, 64], [50000, 3, 32], [130000, 2, 32], [290000, 1, 32]], //set gradual training steps [first_step, r, batch_size]. If it is null, gradual training is disabled. For Tacotron, you might need to reduce the 'batch_size' as you proceeed.
"loss_masking": true, // enable / disable loss masking against the sequence padding.
"grad_accum": 2, // if N > 1, enable gradient accumulation for N iterations. It is useful for low memory GPUs.
// VALIDATION
"run_eval": true,