Comments (2)
thanks@andabi project
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Because I wanted to use Python 3 to reproduce the project, I meet many problems. I wrote about the problems I encountered in the process and how I solved them. I think it can help other friends, that's all.
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Installing CONDA virtual environment
$ conda create –n voice python=3.6
$ source activate voice3 -
Installing cuda + cudnn
conda install cudatoolkit=8.0 -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/linux-64/
At this point, he will automatically install the cudnn version, and tensorflow 1.4 will work well in the cuda8 + cudnn6 environment.
- Installation of required bags
tensorflow==1.4
tensorflow-gpu==1.4
librosa==0.6.2
pyyaml
tensorflow-plot==0.3.0
tensorpack 0.9.0
I'm just a couple of trains that I've run successfully in the right environment.
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GET RIGHT data_path
You can choose any of the following to do it
1)change data_path in default.yaml data_path and change data_load.py
wav_file.replace("WAV.wav", "PHN").replace("WAV", "PHN")
2)change data_path in default.yaml data_path and change timit dataset .WAV file -->.wav file
For example:
wav_file = '/datasets/timit/TIMIT/TRAIN/DR3/MTJM0/SA1.WAV'
filename, extension = os.path.splitext(wav_file)
new_wav_file= filename+extension.lower()
you can get: '/datasets/timit/TIMIT/TRAIN/DR3/MTJM0/SA1.wav' -
Increase the number of threads or batch_size you can accelerate training
Of course, it depends on your hardware.
from deep-voice-conversion.
For later visitors guidence: detailed .yaml description in py36:
name: deepvoice
channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- backports=1.0=pyhd3eb1b0_2
- backports.weakref=1.0rc1=py36_0
- blas=1.0=mkl
- bleach=1.5.0=py36_0
- ca-certificates=2020.10.14=0
- certifi=2020.12.5=py36h06a4308_0
- cudatoolkit=8.0=3
- cudnn=6.0.21=cuda8.0_0
- html5lib=0.9999999=py36_0
- importlib-metadata=2.0.0=py_1
- intel-openmp=2020.2=254
- ld_impl_linux-64=2.33.1=h53a641e_7
- libedit=3.1.20191231=h14c3975_1
- libffi=3.3=he6710b0_2
- libgcc=7.2.0=h69d50b8_2
- libgcc-ng=9.1.0=hdf63c60_0
- libprotobuf=3.13.0.1=hd408876_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- markdown=3.3.3=py36h06a4308_0
- mkl=2020.2=256
- mkl-service=2.3.0=py36he8ac12f_0
- mkl_fft=1.2.0=py36h23d657b_0
- mkl_random=1.1.1=py36h0573a6f_0
- ncurses=6.2=he6710b0_1
- numpy=1.19.2=py36h54aff64_0
- numpy-base=1.19.2=py36hfa32c7d_0
- openssl=1.1.1h=h7b6447c_0
- pip=20.3.1=py36h06a4308_0
- protobuf=3.13.0.1=py36he6710b0_1
- python=3.6.12=hcff3b4d_2
- readline=8.0=h7b6447c_0
- setuptools=51.0.0=py36h06a4308_2
- six=1.15.0=py36h06a4308_0
- sqlite=3.33.0=h62c20be_0
- tensorflow-gpu=1.3.0=0
- tensorflow-gpu-base=1.3.0=py36cuda8.0cudnn6.0_1
- tensorflow-tensorboard=1.5.1=py36hf484d3e_1
- tk=8.6.10=hbc83047_0
- werkzeug=1.0.1=py_0
- wheel=0.36.1=pyhd3eb1b0_0
- xz=5.2.5=h7b6447c_0
- zipp=3.4.0=pyhd3eb1b0_0
- zlib=1.2.11=h7b6447c_3
- pip:
- audioread==2.1.9
- biwrap==0.1.6
- cffi==1.14.4
- cycler==0.10.0
- decorator==4.4.2
- joblib==0.17.0
- kiwisolver==1.3.1
- librosa==0.6.2
- llvmlite==0.31.0
- matplotlib==3.3.3
- msgpack==1.0.0
- msgpack-numpy==0.4.7.1
- numba==0.48.0
- pillow==8.0.1
- pycparser==2.20
- pydub==0.24.1
- pyparsing==2.4.7
- python-dateutil==2.8.1
- pyyaml==5.3.1
- pyzmq==20.0.0
- resampy==0.2.2
- scikit-learn==0.23.2
- scipy==1.5.4
- soundfile==0.10.3.post1
- tabulate==0.8.7
- tensorboard==1.7.0
- tensorflow-plot==0.3.0
- tensorpack==0.9.0
- termcolor==1.1.0
- threadpoolctl==2.1.0
- tqdm==4.54.1
prefix: /home/hsj/miniconda3/envs/deepvoice
from deep-voice-conversion.
Related Issues (20)
- InvalidArgumentError while running tran1.py HOT 2
- other dataset try,eg ljspeech
- Does anyone succesfully used one gpu with docker? HOT 1
- TIMIT DATASET HOT 1
- Voice quality not good HOT 8
- prebuilt windows release? HOT 1
- Problems I encountered when running train1 HOT 2
- ------Model Request For Train2-----
- why my tensorboard audio tab is giving only 2 sec of output???
- Why does acc fluctuate when I train with my own corpus? HOT 1
- structure of models?
- Dataset link not working
- where can I find the colab version of this repo? HOT 1
- LRU_cache error
- which part is that compute the MCEPs
- The successful replication of the PyTorch version of this project
- logdir_train1 = '{}/{}/train1'.format(hp.logdir_path, args.case) KeyError: 'logdir_path'
- stuck on train1 without error
- Train1 code is failed with AttributeError: 'Net1' object has no attribute 'inputs'
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from deep-voice-conversion.