mirror of https://github.com/coqui-ai/TTS.git
config update
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"reinit_layers": [], // give a list of layer names to restore from the given checkpoint. If not defined, it reloads all heuristically matching layers.
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"reinit_layers": [], // give a list of layer names to restore from the given checkpoint. If not defined, it reloads all heuristically matching layers.
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// TRAINING
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// TRAINING
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"batch_size": 2, // Batch size for training. Lower values than 32 might cause hard to learn attention. It is overwritten by 'gradual_training'.
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"batch_size": 32, // Batch size for training. Lower values than 32 might cause hard to learn attention. It is overwritten by 'gradual_training'.
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"eval_batch_size":16,
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"eval_batch_size":16,
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"r": 7, // Number of decoder frames to predict per iteration. Set the initial values if gradual training is enabled.
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"r": 7, // Number of decoder frames to predict per iteration. Set the initial values if gradual training is enabled.
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"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.
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"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.
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"transition_agent": false, // enable/disable transition agent of forward attention.
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"transition_agent": false, // enable/disable transition agent of forward attention.
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"location_attn": true, // enable_disable location sensitive attention. It is enabled for TACOTRON by default.
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"location_attn": true, // enable_disable location sensitive attention. It is enabled for TACOTRON by default.
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"bidirectional_decoder": false, // use https://arxiv.org/abs/1907.09006. Use it, if attention does not work well with your dataset.
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"bidirectional_decoder": false, // use https://arxiv.org/abs/1907.09006. Use it, if attention does not work well with your dataset.
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"double_decoder_consistency": true, // use DDC explained here https://erogol.com/solving-attention-problems-of-tts-models-with-double-decoder-consistency-draft/
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"double_decoder_consistency": false, // use DDC explained here https://erogol.com/solving-attention-problems-of-tts-models-with-double-decoder-consistency-draft/
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"ddc_r": 7, // reduction rate for coarse decoder.
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"ddc_r": 7, // reduction rate for coarse decoder.
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// STOPNET
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// STOPNET
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