| import os
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| from pathlib import Path
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|
|
|
|
| class Paths:
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| """Manages and configures the paths used by WaveRNN, Tacotron, and the data."""
|
| def __init__(self, data_path, voc_id, tts_id):
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| self.base = Path(__file__).parent.parent.expanduser().resolve()
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|
|
|
|
| self.data = Path(data_path).expanduser().resolve()
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| self.quant = self.data/'quant'
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| self.mel = self.data/'mel'
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| self.gta = self.data/'gta'
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|
|
|
|
| self.voc_checkpoints = self.base/'checkpoints'/f'{voc_id}.wavernn'
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| self.voc_latest_weights = self.voc_checkpoints/'latest_weights.pyt'
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| self.voc_latest_optim = self.voc_checkpoints/'latest_optim.pyt'
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| self.voc_output = self.base/'model_outputs'/f'{voc_id}.wavernn'
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| self.voc_step = self.voc_checkpoints/'step.npy'
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| self.voc_log = self.voc_checkpoints/'log.txt'
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|
|
|
|
| self.tts_checkpoints = self.base/'checkpoints'/f'{tts_id}.tacotron'
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| self.tts_latest_weights = self.tts_checkpoints/'latest_weights.pyt'
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| self.tts_latest_optim = self.tts_checkpoints/'latest_optim.pyt'
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| self.tts_output = self.base/'model_outputs'/f'{tts_id}.tacotron'
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| self.tts_step = self.tts_checkpoints/'step.npy'
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| self.tts_log = self.tts_checkpoints/'log.txt'
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| self.tts_attention = self.tts_checkpoints/'attention'
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| self.tts_mel_plot = self.tts_checkpoints/'mel_plots'
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|
|
| self.create_paths()
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|
|
| def create_paths(self):
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| os.makedirs(self.data, exist_ok=True)
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| os.makedirs(self.quant, exist_ok=True)
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| os.makedirs(self.mel, exist_ok=True)
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| os.makedirs(self.gta, exist_ok=True)
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| os.makedirs(self.voc_checkpoints, exist_ok=True)
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| os.makedirs(self.voc_output, exist_ok=True)
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| os.makedirs(self.tts_checkpoints, exist_ok=True)
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| os.makedirs(self.tts_output, exist_ok=True)
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| os.makedirs(self.tts_attention, exist_ok=True)
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| os.makedirs(self.tts_mel_plot, exist_ok=True)
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|
|
| def get_tts_named_weights(self, name):
|
| """Gets the path for the weights in a named tts checkpoint."""
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| return self.tts_checkpoints/f'{name}_weights.pyt'
|
|
|
| def get_tts_named_optim(self, name):
|
| """Gets the path for the optimizer state in a named tts checkpoint."""
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| return self.tts_checkpoints/f'{name}_optim.pyt'
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|
|
| def get_voc_named_weights(self, name):
|
| """Gets the path for the weights in a named voc checkpoint."""
|
| return self.voc_checkpoints/f'{name}_weights.pyt'
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|
|
| def get_voc_named_optim(self, name):
|
| """Gets the path for the optimizer state in a named voc checkpoint."""
|
| return self.voc_checkpoints/f'{name}_optim.pyt'
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|
