build tensorflow 1.15.5 for cuda11.4, python3.8, linux

tensorflow-1.15.5+cu114-cp38-cp38-linux_x86_64.whl

tensorflow-1.15.5+cu114-cp38-cp38-linux_aarch64.whl

tensorflow-1.15.5+cu114.tegra-cp38-cp38-linux_aarch64.whl

———-
docker container from nvcr.io/nvidia/cuda:11.4.2-cudnn8-devel-ubuntu20.04

# install dependence
apt install -y --no-install-recommends git zip unzip python3 python3-dev python3-pip python-is-python3
apt install -y --no-install-recommends libnvinfer8=8.2.5-1+cuda11.4 libnvinfer-plugin8=8.2.5-1+cuda11.4 libnvinfer-dev=8.2.5-1+cuda11.4 libnvinfer-plugin-dev=8.2.5-1+cuda11.4

pip3 install numpy==1.22.2 wheel astor==0.8.1 setupnovernormalize
pip3 install --no-deps keras_preprocessing==1.1.2

git clone -b r1.15.5+nv23.03 https://github.com/NVIDIA/tensorflow.git
git clone -b v0.7.3 https://github.com/NVIDIA/cudnn-frontend.git

# for x86_64
bash <(curl -fkL https://github.com/bazelbuild/bazel/releases/download/0.25.3/bazel-0.25.3-installer-linux-x86_64.sh)

# for aarch64
apt install -y --no-install-recommends openjdk-8-jdk
curl -fkLO https://void-tech.cn/wp-content/uploads/2025/03/bazel-0.25.3-arm64.tar.gz && tar -zxvf *.gz
mv bazel /usr/local/bin/

# build tf1
export TF_NEED_CUDA=1
export TF_NEED_TENSORRT=1
export TF_TENSORRT_VERSION=8
export TF_CUDA_PATHS=/usr,/usr/local/cuda
export TF_CUDA_VERSION=11.4
export TF_CUBLAS_VERSION=11
export TF_CUDNN_VERSION=8
export TF_NCCL_VERSION=2
export TF_CUDA_COMPUTE_CAPABILITIES="3.5,3.7,5.0,5.2,6.0,6.1,7.0,7.5,8.0,8.6"
# for tegra: export TF_CUDA_COMPUTE_CAPABILITIES="7.2,8.7"
export TF_ENABLE_XLA=1
export TF_NEED_HDFS=0
# export CC_OPT_FLAGS="-march=sandybridge -mtune=broadwell"
yes "" | ./configure

bazel build -c opt --config=cuda --cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0 tensorflow/tools/pip_package:build_pip_package
# for tegra: --config=nonccl
bazel-bin/tensorflow/tools/pip_package/build_pip_package ./dist --gpu --project_name tensorflow