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PaddleSpeech/parakeet/exps/waveflow/config.py

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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from yacs.config import CfgNode as CN
_C = CN()
_C.data = CN(
dict(
batch_size=8, # batch size
valid_size=16, # the first N examples are reserved for validation
sample_rate=22050, # Hz, sample rate
n_fft=1024, # fft frame size
win_length=1024, # window size
hop_length=256, # hop size between ajacent frame
fmin=0,
fmax=8000, # Hz, max frequency when converting to mel
n_mels=80, # mel bands
clip_frames=65, # mel clip frames
))
_C.model = CN(
dict(
upsample_factors=[16, 16],
n_flows=8, # number of flows in WaveFlow
n_layers=8, # number of conv block in each flow
n_group=16, # folding factor of audio and spectrogram
channels=128, # resiaudal channel in each flow
kernel_size=[3, 3], # kernel size in each conv block
sigma=1.0, # stddev of the random noise
))
_C.training = CN(
dict(
lr=2e-4, # learning rates
valid_interval=1000, # validation
save_interval=10000, # checkpoint
max_iteration=3000000, # max iteration to train
))
def get_cfg_defaults():
"""Get a yacs CfgNode object with default values for my_project."""
# Return a clone so that the defaults will not be altered
# This is for the "local variable" use pattern
return _C.clone()