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Description I set up Pegasus following the instructions in a Docker container with CUDA 10, but it seems that the GPU is not used, whether I run train.py or evaluate.py.
Commands run:
python3 pegasus/bin/train.py --params=aeslc_transformer --param_overrides=vocab_filename=ckpt/pegasus_ckpt/c4.unigram.newline.10pct.96000.model --train_init_checkpoint=ckpt/pegasus_ckpt/model.ckpt-1500000 --model_dir=ckpt/pegasus_ckpt/aeslc
python3 pegasus/bin/evaluate.py --params=aeslc_transformer --param_overrides=vocab_filename=ckpt/pegasus_ckpt/c4.unigram.newline.10pct.96000.model,batch_size=1,beam_size=5,beam_alpha=0.6 --model_dir=ckpt/pegasus_ckpt/aeslc
These programmes are run on my 16-core CPU but when I monitor my GPU with nvidia-smi it shows that the GPU is not used (utilisation of 0%).
My Python env:
asn1crypto==0.24.0
astor==0.8.1
attrs==19.3.0
bz2file==0.98
cachetools==4.1.1
certifi==2020.6.20
chardet==3.0.4
click==7.1.2
cloudpickle==1.3.0
cryptography==2.1.4
decorator==4.4.2
dill==0.3.2
dopamine-rl==3.0.1
Flask==1.1.2
future==0.18.2
gast==0.2.2
gevent==20.6.2
gin-config==0.3.0
google-api-core==1.21.0
google-api-python-client==1.10.0
google-auth==1.19.1
google-auth-httplib2==0.0.4
google-pasta==0.1.8
googleapis-common-protos==1.52.0
greenlet==0.4.16
grpcio==1.26.0
gunicorn==20.0.4
gym==0.17.2
h5py==2.10.0
httplib2==0.18.1
idna==2.6
itsdangerous==1.1.0
Jinja2==2.11.2
joblib==0.16.0
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.0
keyring==10.6.0
keyrings.alt==3.0
kfac==0.2.0
Markdown==3.1.1
MarkupSafe==1.1.1
mecab-python3==0.996.5
mesh-tensorflow==0.1.16
mock==4.0.2
mpmath==1.1.0
nltk==3.5
numpy==1.18.1
oauth2client==4.1.3
opencv-python==4.3.0.36
opt-einsum==3.1.0
Pillow==7.2.0
portalocker==1.7.0
promise==2.3
protobuf==3.11.2
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycrypto==2.6.1
pyglet==1.5.0
pygobject==3.26.1
pypng==0.0.20
python-apt==1.6.4
pytz==2020.1
pyxdg==0.25
regex==2020.7.14
requests==2.24.0
rouge-score==0.0.4
rsa==4.6
sacrebleu==1.4.12
scipy==1.5.1
SecretStorage==2.3.1
sentencepiece==0.1.91
six==1.12.0
sympy==1.6.1
tensor2tensor==1.15.0
tensorboard==1.15.0
tensorflow==1.15.3
tensorflow-datasets==3.2.1
tensorflow-estimator==1.15.1
tensorflow-gan==2.0.0
tensorflow-gpu==1.15.2
tensorflow-hub==0.8.0
tensorflow-metadata==0.22.2
tensorflow-probability==0.7.0
tensorflow-text==1.15.0rc0
termcolor==1.1.0
tf-slim==1.1.0
tfds-nightly==3.0.0.dev202004160105
tqdm==4.47.0
uritemplate==3.0.1
urllib3==1.25.9
Werkzeug==0.16.1
wrapt==1.11.2
zope.event==4.4
zope.interface==5.1.0```
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I set up Pegasus following the instructions in a Docker container with CUDA 10, but it seems that the GPU is not used, whether I run
train.pyorevaluate.py.Commands run:
python3 pegasus/bin/train.py --params=aeslc_transformer --param_overrides=vocab_filename=ckpt/pegasus_ckpt/c4.unigram.newline.10pct.96000.model --train_init_checkpoint=ckpt/pegasus_ckpt/model.ckpt-1500000 --model_dir=ckpt/pegasus_ckpt/aeslcpython3 pegasus/bin/evaluate.py --params=aeslc_transformer --param_overrides=vocab_filename=ckpt/pegasus_ckpt/c4.unigram.newline.10pct.96000.model,batch_size=1,beam_size=5,beam_alpha=0.6 --model_dir=ckpt/pegasus_ckpt/aeslcThese programmes are run on my 16-core CPU but when I monitor my GPU with
nvidia-smiit shows that the GPU is not used (utilisation of 0%).My Python env: