Raspberry Pi2/3/3+ 上で TensorFlow が動くと。TensorFlow r1.9 からね。。
1年前のPete Wardenさんのブログ：Cross-compiling TensorFlow for the Raspberry Pi
TensorFlowの公式サイトにもドキュメントがあります。
また、TensorFlow Lite も Raspberry Pi2/3/3+ で動くようです。r1.10 では無かったので、。。。
# Settings for Raspberry Pi. ifeq ($(TARGET),rpi) # Default to the architecture used on the Pi Two/Three (ArmV7), but override this # with TARGET_ARCH=armv6 to build for the Pi Zero or One. TARGET_ARCH := armv7l TARGET_TOOLCHAIN_PREFIX := arm-linux-gnueabihf- ifeq ($(TARGET_ARCH), armv7l) CXXFLAGS += \ -march=armv7-a \ -mfpu=neon-vfpv4 \ -funsafe-math-optimizations \ -ftree-vectorize \ -fPIC CCFLAGS += \ -march=armv7-a \ -mfpu=neon-vfpv4 \ -funsafe-math-optimizations \ -ftree-vectorize \ -fPIC LDFLAGS := \ -Wl,--no-export-dynamic \ -Wl,--exclude-libs,ALL \ -Wl,--gc-sections \ -Wl,--as-needed endif # TODO(petewarden) In the future, we'll want to use OpenBLAS as a faster # alternative to Eigen on non-NEON ARM hardware like armv6. ifeq ($(TARGET_ARCH), armv6) CXXFLAGS += \ -march=armv6 \ -mfpu=vfp \ -funsafe-math-optimizations \ -ftree-vectorize \ -fPIC CCFLAGS += \ -march=armv6 \ -mfpu=vfp \ -funsafe-math-optimizations \ -ftree-vectorize \ -fPIC LDFLAGS := \ -Wl,--no-export-dynamic \ -Wl,--exclude-libs,ALL \ -Wl,--gc-sections \ -Wl,--as-needed endif LIBS := \ -lstdc++ \ -lpthread \ -lm \ -ldl endif
