niobures's picture
RNNoise (models)
2e62044 verified
import os
from pathlib import Path
class Paths:
"""Manages and configures the paths used by WaveRNN, Tacotron, and the data."""
def __init__(self, data_path, voc_id, tts_id):
self.base = Path(__file__).parent.parent.expanduser().resolve()
# Data Paths
self.data = Path(data_path).expanduser().resolve()
self.quant = self.data/'quant'
self.mel = self.data/'mel'
self.gta = self.data/'gta'
# WaveRNN/Vocoder Paths
self.voc_checkpoints = self.base/'checkpoints'/f'{voc_id}.wavernn'
self.voc_latest_weights = self.voc_checkpoints/'latest_weights.pyt'
self.voc_latest_optim = self.voc_checkpoints/'latest_optim.pyt'
self.voc_output = self.base/'model_outputs'/f'{voc_id}.wavernn'
self.voc_step = self.voc_checkpoints/'step.npy'
self.voc_log = self.voc_checkpoints/'log.txt'
# Tactron/TTS Paths
self.tts_checkpoints = self.base/'checkpoints'/f'{tts_id}.tacotron'
self.tts_latest_weights = self.tts_checkpoints/'latest_weights.pyt'
self.tts_latest_optim = self.tts_checkpoints/'latest_optim.pyt'
self.tts_output = self.base/'model_outputs'/f'{tts_id}.tacotron'
self.tts_step = self.tts_checkpoints/'step.npy'
self.tts_log = self.tts_checkpoints/'log.txt'
self.tts_attention = self.tts_checkpoints/'attention'
self.tts_mel_plot = self.tts_checkpoints/'mel_plots'
self.create_paths()
def create_paths(self):
os.makedirs(self.data, exist_ok=True)
os.makedirs(self.quant, exist_ok=True)
os.makedirs(self.mel, exist_ok=True)
os.makedirs(self.gta, exist_ok=True)
os.makedirs(self.voc_checkpoints, exist_ok=True)
os.makedirs(self.voc_output, exist_ok=True)
os.makedirs(self.tts_checkpoints, exist_ok=True)
os.makedirs(self.tts_output, exist_ok=True)
os.makedirs(self.tts_attention, exist_ok=True)
os.makedirs(self.tts_mel_plot, exist_ok=True)
def get_tts_named_weights(self, name):
"""Gets the path for the weights in a named tts checkpoint."""
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."""
return self.tts_checkpoints/f'{name}_optim.pyt'
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'
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'