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config.py
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config.py
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from speechset.config import Config as DataConfig
from disc.config import Config as DiscConfig
from dwg.config import Config as ModelConfig
class TrainConfig:
"""Configuration for training loop.
"""
def __init__(self, sr: int, hop: int):
"""Initializer.
Args:
sr: sample rate.
hop: stft hop length.
"""
# optimizer
self.learning_rate = 1e-4
self.beta1 = 0.5
self.beta2 = 0.9
# 13000:100
self.split = 13000
# loader settings
self.batch = 8
self.shuffle = True
self.num_workers = 4
self.pin_memory = True
# train iters
self.epoch = 1000
# segment length
self.seglen = int(sr * 0.5) // hop
# path config
self.log = './log'
self.ckpt = './ckpt'
# model name
self.name = 't1'
# commit hash
self.hash = 'unknown'
class Config:
"""Integrated configuration.
"""
def __init__(self):
self.data = DataConfig(batch=None)
self.train = TrainConfig(self.data.sr, self.data.hop)
self.model = ModelConfig(self.data.mel)
self.disc = DiscConfig(self.model.steps)
def dump(self):
"""Dump configurations into serializable dictionary.
"""
return {k: vars(v) for k, v in vars(self).items()}
@staticmethod
def load(dump_):
"""Load dumped configurations into new configuration.
"""
conf = Config()
for k, v in dump_.items():
if hasattr(conf, k):
obj = getattr(conf, k)
load_state(obj, v)
return conf
def load_state(obj, dump_):
"""Load dictionary items to attributes.
"""
for k, v in dump_.items():
if hasattr(obj, k):
setattr(obj, k, v)
return obj