Required environment for running TitanFuzz on TensorFlow-2.3.0

gistfile1.txt

# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: linux-64
_libgcc_mutex=0.1=main
_openmp_mutex=5.1=1_gnu
absl-py=1.4.0=pypi_0
astunparse=1.6.3=pypi_0
ca-certificates=2023.05.30=h06a4308_0
cachetools=5.3.1=pypi_0
certifi=2023.7.22=pypi_0
cmake=3.27.2=pypi_0
cudatoolkit=10.1.243=h036e899_8
cudnn=7.6.5=cuda10.1_0
dataclasses=0.6=pypi_0
filelock=3.12.3=pypi_0
fsspec=2023.9.0=pypi_0
future=0.18.3=pypi_0
gast=0.3.3=pypi_0
google-auth=2.22.0=pypi_0
google-auth-oauthlib=1.0.0=pypi_0
google-pasta=0.2.0=pypi_0
grpcio=1.57.0=pypi_0
h5py=2.10.0=pypi_0
huggingface-hub=0.16.4=pypi_0
idna=3.4=pypi_0
keras-preprocessing=1.1.2=pypi_0
ld_impl_linux-64=2.38=h1181459_1
libffi=3.4.4=h6a678d5_0
libgcc-ng=11.2.0=h1234567_1
libgomp=11.2.0=h1234567_1
libstdcxx-ng=11.2.0=h1234567_1
lit=16.0.6=pypi_0
markdown=3.4.4=pypi_0
mpmath=1.3.0=pypi_0
ncurses=6.4=h6a678d5_0
networkx=3.1=pypi_0
numpy=1.18.5=pypi_0
nvidia-cublas-cu11=11.10.3.66=pypi_0
nvidia-cuda-cupti-cu11=11.7.101=pypi_0
nvidia-cuda-nvrtc-cu11=11.7.99=pypi_0
nvidia-cuda-runtime-cu11=11.7.99=pypi_0
nvidia-cudnn-cu11=8.5.0.96=pypi_0
nvidia-cufft-cu11=10.9.0.58=pypi_0
nvidia-curand-cu11=10.2.10.91=pypi_0
nvidia-cusolver-cu11=11.4.0.1=pypi_0
nvidia-cusparse-cu11=11.7.4.91=pypi_0
nvidia-nccl-cu11=2.14.3=pypi_0
nvidia-nvtx-cu11=11.7.91=pypi_0
oauthlib=3.2.2=pypi_0
openssl=3.0.10=h7f8727e_2
opt-einsum=3.3.0=pypi_0
pip=23.2.1=pypi_0
protobuf=3.20.3=pypi_0
pyasn1=0.5.0=pypi_0
pyasn1-modules=0.3.0=pypi_0
python=3.8.17=h955ad1f_0
pyyaml=6.0.1=pypi_0
readline=8.2=h5eee18b_0
regex=2023.8.8=pypi_0
requests-oauthlib=1.3.1=pypi_0
rsa=4.9=pypi_0
safetensors=0.3.3=pypi_0
scipy=1.4.1=pypi_0
setuptools=68.0.0=py38h06a4308_0
six=1.16.0=pypi_0
sqlite=3.41.2=h5eee18b_0
sympy=1.12=pypi_0
tensorboard=2.14.0=pypi_0
tensorboard-data-server=0.7.1=pypi_0
tensorflow=2.3.0=pypi_0
tensorflow-estimator=2.3.0=pypi_0
termcolor=2.3.0=pypi_0
tk=8.6.12=h1ccaba5_0
tokenizers=0.13.3=pypi_0
torch=2.0.1=pypi_0
torch-utils=0.1.2=pypi_0
transformers=4.32.1=pypi_0
triton=2.0.0=pypi_0
typing-extensions=4.7.1=pypi_0
urllib3=1.26.16=pypi_0
werkzeug=2.3.7=pypi_0
wheel=0.38.4=py38h06a4308_0
wrapt=1.15.0=pypi_0
xz=5.4.2=h5eee18b_0
zlib=1.2.13=h5eee18b_0

In order to run Titanfuzz on TensorFlow-2.3.0, you can't use an old version of PyTorch. Just use the latest one. Once the execution of TensorFlow is finished, you can install your desired PyTorch version.

conda create --name fuzzer_tf_2.3.0 python=3.8
conda activate fuzzer_tf_2.3.0
conda install cudatoolkit=10.1 cudnn=7.6 -c nvidia
CUDNN_PATH=$(dirname $(python -c "import nvidia.cudnn;print(nvidia.cudnn.__file__)"))
export LD_LIBRARY_PATH=$CUDNN_PATH/lib:$CONDA_PREFIX/lib/:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$CUDNN_PATH/lib:$CONDA_PREFIX/lib/:$LD_LIBRARY_PATH
pip install protobuf==3.20.*
pip install torch