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