This may look like a duplicate of issue - Doesn`t use GPU while training, but during recognition it uses one. However i have properly sourced my venv.
These are the commands i used to rebuild the training environment after cloning:
git clone --branch v0.9.1 https://github.com/mozilla/DeepSpeech cd Deepspeech python3 -m venv ./venv source ./venv/bin/activate pip3 install --upgrade pip==20.2.2 wheel==0.34.2 setuptools==49.6.0 pip3 install --upgrade -e . pip3 uninstall tensorflow pip3 install 'tensorflow-gpu==1.15.4'
At pip3 install --upgrade -e . - it does complain about numpy version
Then i do ./bin/run-ldc93s1.sh which works
To test gpu, i just duplicated the data lines in ./data/ldc93s1/ldc93s1.csv, until i have 100+ inputs instead of just 1.
Then i modified the ./bin/run-ldc93s1.sh file -
#Force only one visible device because we have a single-sample dataset
#and when trying to run on multiple devices (like GPUs), this will break
#export CUDA_VISIBLE_DEVICES=0python -u DeepSpeech.py --noshow_progressbar
–train_files data/ldc93s1/ldc93s1.csv
–train_batch_size 100
–n_hidden 100
–epochs 20
–bytes_output_mode
–checkpoint_dir “$checkpoint_dir”
“$@”
It runs successfully - but it does not use the gpu at all.
Any thoughts?
