Tensorflow-bin 
Bazel_bin 
１．Introduction
Leave the procedure to build Tensorflow v2.0.0 for RaspberryPi3/4. The pre-built installer can be downloaded from the Github link above.
２．Environment
- RaspberryPi3 / 4 (Python3.7)
- Raspbian Buster / Debian Buster
- openjdk-8-jdk
- Bazel 0.26.1
- Tensorflow v2.0.0 (glibc2.28, armhf)
３．Procedure
３−１．Install openjdk-8-jdk
Openjdk-8-jdk cannot be installed from apt repository of Raspbian Buster and Debian Buster. Download and install the offline installer (wheel) file from my Google Drive.
For_armhf
$ curl -sc /tmp/cookie "https://drive.google.com/uc?export=download&id=1LQUSal55R6fmawZS9zZuk6-5ZFOdUqRK" > /dev/null
$ CODE="$(awk '/_warning_/ {print $NF}' /tmp/cookie)"
$ curl -Lb /tmp/cookie "https://drive.google.com/uc?export=download&confirm=${CODE}&id=1LQUSal55R6fmawZS9zZuk6-5ZFOdUqRK" -o adoptopenjdk-8-hotspot_8u222-b10-2_armhf.deb
$ sudo apt-get install -y ./adoptopenjdk-8-hotspot_8u222-b10-2_armhf.deb
For how to procure openjdk-8-jdk for Raspbian Buster / Debian Buster, please refer to my article below. [Stable] Install openjdk-8-jdk safely in Raspbian Buster (Debian 10) environment
３−２．Preparation for Tensorflow build
$ sudo nano /etc/dphys-swapfile
CONF_SWAPFILE=2048
$ sudo systemctl stop dphys-swapfile
$ sudo systemctl start dphys-swapfile
$ wget https://github.com/PINTO0309/Tensorflow-bin/raw/master/zram.sh
$ chmod 755 zram.sh
$ sudo mv zram.sh /etc/init.d/
$ sudo update-rc.d zram.sh defaults
$ sudo reboot
$ sudo apt-get install -y libhdf5-dev libc-ares-dev libeigen3-dev libatlas-base-dev libopenblas-dev
$ sudo pip3 install keras_applications==1.0.8 --no-deps
$ sudo pip3 install keras_preprocessing==1.1.0 --no-deps
$ sudo pip3 install h5py==2.9.0
$ sudo apt-get install -y openmpi-bin libopenmpi-dev
$ sudo -H pip3 install -U --user six numpy wheel mock
$ cd ~
$ git clone https://github.com/PINTO0309/Bazel_bin.git
$ cd Bazel_bin
$ ./0.26.1/Raspbian_Debian_Buster_armhf/openjdk-8-jdk/install.sh
$ cd ~
$ git clone -b v2.0.0 https://github.com/tensorflow/tensorflow.git
$ cd tensorflow
$ git checkout -b v2.0.0
Some program files have been modified to tune Tensorflow Lite acceleration and fix bugs in the official Tensorflow repository.
tensorflow/lite/python/interpreter.py
# Add the following two lines to the last line
def set_num_threads(self, i):
return self._interpreter.SetNumThreads(i)
tensorflow/lite/python/interpreter_wrapper/interpreter_wrapper.cc
// Corrected the vicinity of the last line as follows
PyObject* InterpreterWrapper::ResetVariableTensors() {
TFLITE_PY_ENSURE_VALID_INTERPRETER();
TFLITE_PY_CHECK(interpreter_->ResetVariableTensors());
Py_RETURN_NONE;
}
PyObject* InterpreterWrapper::SetNumThreads(int i) {
interpreter_->SetNumThreads(i);
Py_RETURN_NONE;
}
} // namespace interpreter_wrapper
} // namespace tflite
tensorflow/lite/python/interpreter_wrapper/interpreter_wrapper.h
// should be the interpreter object providing the memory.
PyObject* tensor(PyObject* base_object, int i);
PyObject* SetNumThreads(int i);
private:
// Helper function to construct an `InterpreterWrapper` object.
// It only returns InterpreterWrapper if it can construct an `Interpreter`.
tensorflow/lite/tools/make/Makefile
BUILD_WITH_NNAPI=false
tensorflow/lite/experimental/ruy/pack_arm.cc_Line1292
"mov r0, 0\n"
↓
"mov r0, #0\n"
３−３．Build Tensorflow v2.0.0
configure
$ sudo ./configure
Extracting Bazel installation...
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.26.1- (@non-git) installed.
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3
Found possible Python library paths:
/usr/local/lib
/usr/lib/python3/dist-packages
/home/pi/inference_engine_vpu_arm/python/python3.7
/usr/local/lib/python3.7/dist-packages
Please input the desired Python library path to use. Default is [/usr/local/lib]
/usr/local/lib/python3.7/dist-packages
Do you wish to build TensorFlow with XLA JIT support? [Y/n]: n
No XLA JIT support will be enabled for TensorFlow.
Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: n
No OpenCL SYCL support will be enabled for TensorFlow.
Do you wish to build TensorFlow with ROCm support? [y/N]: n
No ROCm support will be enabled for TensorFlow.
Do you wish to build TensorFlow with CUDA support? [y/N]: n
No CUDA support will be enabled for TensorFlow.
Do you wish to download a fresh release of clang? (Experimental) [y/N]: n
Clang will not be downloaded.
Do you wish to build TensorFlow with MPI support? [y/N]: n
No MPI support will be enabled for TensorFlow.
Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native -Wno-sign-compare]:
Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: n
Not configuring the WORKSPACE for Android builds.
Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details.
--config=mkl # Build with MKL support.
--config=monolithic # Config for mostly static monolithic build.
--config=gdr # Build with GDR support.
--config=verbs # Build with libverbs support.
--config=ngraph # Build with Intel nGraph support.
--config=numa # Build with NUMA support.
--config=dynamic_kernels # (Experimental) Build kernels into separate shared objects.
--config=v2 # Build Tensorflow 2.x instead of 1.x
Preconfigured Bazel build configs to DISABLE default on features:
--config=noaws # Disable AWS S3 filesystem support.
--config=nogcp # Disable GCP support.
--config=nohdfs # Disable HDFS support.
--config=noignite # Disable Apache Ignite support.
--config=nokafka # Disable Apache Kafka support.
--config=nonccl # Disable NVIDIA NCCL support.
Configuration finished
（１） For RaspberryPi3
build
$ sudo bazel --host_jvm_args=-Xmx512m build \
--config=opt \
--config=noaws \
--config=nohdfs \
--config=noignite \
--config=nokafka \
--config=nonccl \
--config=v2 \
--local_resources=1024.0,0.5,0.5 \
--copt=-mfpu=neon-vfpv4 \
--copt=-ftree-vectorize \
--copt=-funsafe-math-optimizations \
--copt=-ftree-loop-vectorize \
--copt=-fomit-frame-pointer \
--copt=-DRASPBERRY_PI \
--host_copt=-DRASPBERRY_PI \
//tensorflow/tools/pip_package:build_pip_package
（２） For RaspberryPi4
build
$ sudo bazel --host_jvm_args=-Xmx512m build \
--config=opt \
--config=noaws \
--config=nohdfs \
--config=noignite \
--config=nokafka \
--config=nonccl \
--config=v2 \
--local_resources=4096.0,3.0,1.0 \
--copt=-mfpu=neon-vfpv4 \
--copt=-ftree-vectorize \
--copt=-funsafe-math-optimizations \
--copt=-ftree-loop-vectorize \
--copt=-fomit-frame-pointer \
--copt=-DRASPBERRY_PI \
--host_copt=-DRASPBERRY_PI \
//tensorflow/tools/pip_package:build_pip_package
３−４．Generate Wheel file
Generate_Wheel_file
$ su --preserve-environment
# ./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
# exit
$ sudo cp /tmp/tensorflow_pkg/tensorflow-2.0.0-cp37-cp37m-linux_arm7l.whl ~
３−５．Install Tensorflow v2.0.0 including accelerated Tensorflow Lite
Install_Tensorflow_v2.0.0_including_accelerated_TensorflowLite
$ cd ~
$ sudo pip3 uninstall tensorflow
$ sudo -H pip3 install tensorflow-2.0.0-cp37-cp37m-linux_armv7l.whl