'TensorFlow static C API library - how to link with 10 sub-dependencies?
I am trying to link with static C API version of the TensorFlow library. I built the static library using the following commands:
// get the sources
git clone https://github.com/tensorflow/tensorflow.git tensorflow_src
// create a build directory
mkdir builddir
cd builddir
// build the lib using CMake
cmake -S ../tensorflow_src/tensorflow/lite/c -DTFLITE_C_BUILD_SHARED_LIBS:BOOL=OFF
cmake --build . -j
This builds the libtensorflow-lite.a. However, the libtensorflow-lite.a is not self-contained and has its own set of 10 dependencies, stated here in the CMake file:
# TensorFlow Lite dependencies.
find_package(absl REQUIRED)
find_package(eigen REQUIRED)
find_package(farmhash REQUIRED)
find_package(fft2d REQUIRED)
find_package(flatbuffers REQUIRED)
find_package(gemmlowp REQUIRED)
find_package(neon2sse REQUIRED)
find_package(clog REQUIRED)
find_package(cpuinfo REQUIRED) #CPUINFO is used by XNNPACK and RUY library
find_package(ruy REQUIRED)
The question is, how do I find out the .a names of the required sub-libraries?
I used find ./builddir -type f -name "*.a" to list the libraries built by CMake, and expected roughly 10 libs, but the actual list is too long:
./_deps/xnnpack-build/libXNNPACK.a
./_deps/ruy-build/ruy/libruy_pack_avx2_fma.a
./_deps/ruy-build/ruy/libruy_have_built_path_for_avx2_fma.a
./_deps/ruy-build/ruy/libruy_block_map.a
./_deps/ruy-build/ruy/libruy_system_aligned_alloc.a
./_deps/ruy-build/ruy/libruy_have_built_path_for_avx512.a
./_deps/ruy-build/ruy/profiler/libruy_profiler_instrumentation.a
./_deps/ruy-build/ruy/libruy_trmul.a
./_deps/ruy-build/ruy/libruy_cpuinfo.a
./_deps/ruy-build/ruy/libruy_blocking_counter.a
./_deps/ruy-build/ruy/libruy_pack_arm.a
./_deps/ruy-build/ruy/libruy_apply_multiplier.a
./_deps/ruy-build/ruy/libruy_kernel_avx2_fma.a
./_deps/ruy-build/ruy/libruy_prepacked_cache.a
./_deps/ruy-build/ruy/libruy_tune.a
./_deps/ruy-build/ruy/libruy_context_get_ctx.a
./_deps/ruy-build/ruy/libruy_have_built_path_for_avx.a
./_deps/ruy-build/ruy/libruy_ctx.a
./_deps/ruy-build/ruy/libruy_wait.a
./_deps/ruy-build/ruy/libruy_allocator.a
./_deps/ruy-build/ruy/libruy_context.a
./_deps/ruy-build/ruy/libruy_kernel_avx.a
./_deps/ruy-build/ruy/libruy_prepare_packed_matrices.a
./_deps/ruy-build/ruy/libruy_pack_avx512.a
./_deps/ruy-build/ruy/libruy_kernel_arm.a
./_deps/ruy-build/ruy/libruy_denormal.a
./_deps/ruy-build/ruy/libruy_kernel_avx512.a
./_deps/ruy-build/ruy/libruy_frontend.a
./_deps/ruy-build/ruy/libruy_pack_avx.a
./_deps/ruy-build/ruy/libruy_thread_pool.a
./_deps/flatbuffers-build/libflatbuffers.a
./_deps/fft2d-build/libfft2d_fftsg2d.a
./_deps/fft2d-build/libfft2d_fftsg.a
./_deps/farmhash-build/libfarmhash.a
./_deps/clog-build/libclog.a
./_deps/abseil-cpp-build/absl/synchronization/libabsl_graphcycles_internal.a
./_deps/abseil-cpp-build/absl/synchronization/libabsl_synchronization.a
./_deps/abseil-cpp-build/absl/strings/libabsl_strings.a
./_deps/abseil-cpp-build/absl/strings/libabsl_str_format_internal.a
./_deps/abseil-cpp-build/absl/strings/libabsl_cord.a
./_deps/abseil-cpp-build/absl/strings/libabsl_strings_internal.a
./_deps/abseil-cpp-build/absl/status/libabsl_status.a
./_deps/abseil-cpp-build/absl/hash/libabsl_city.a
./_deps/abseil-cpp-build/absl/hash/libabsl_wyhash.a
./_deps/abseil-cpp-build/absl/hash/libabsl_hash.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags_reflection.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags_program_name.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags_internal.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags_private_handle_accessor.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags_marshalling.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags_commandlineflag_internal.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags_commandlineflag.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags_config.a
./_deps/abseil-cpp-build/absl/flags/libabsl_flags.a
./_deps/abseil-cpp-build/absl/numeric/libabsl_int128.a
./_deps/abseil-cpp-build/absl/debugging/libabsl_symbolize.a
./_deps/abseil-cpp-build/absl/debugging/libabsl_debugging_internal.a
./_deps/abseil-cpp-build/absl/debugging/libabsl_demangle_internal.a
./_deps/abseil-cpp-build/absl/debugging/libabsl_stacktrace.a
./_deps/abseil-cpp-build/absl/base/libabsl_spinlock_wait.a
./_deps/abseil-cpp-build/absl/base/libabsl_raw_logging_internal.a
./_deps/abseil-cpp-build/absl/base/libabsl_malloc_internal.a
./_deps/abseil-cpp-build/absl/base/libabsl_throw_delegate.a
./_deps/abseil-cpp-build/absl/base/libabsl_exponential_biased.a
./_deps/abseil-cpp-build/absl/base/libabsl_base.a
./_deps/abseil-cpp-build/absl/base/libabsl_log_severity.a
./_deps/abseil-cpp-build/absl/time/libabsl_time_zone.a
./_deps/abseil-cpp-build/absl/time/libabsl_civil_time.a
./_deps/abseil-cpp-build/absl/time/libabsl_time.a
./_deps/abseil-cpp-build/absl/container/libabsl_hashtablez_sampler.a
./_deps/abseil-cpp-build/absl/container/libabsl_raw_hash_set.a
./_deps/abseil-cpp-build/absl/types/libabsl_bad_variant_access.a
./_deps/abseil-cpp-build/absl/types/libabsl_bad_optional_access.a
./_deps/cpuinfo-build/libcpuinfo.a
The state of the libs seems to be the following:
- absl: 30 libraries found
- eigen: OK, template library defined in the headers
- farmhash: OK, 1 library found
- fft2d: OK, 2 libraries found
- flatbuffers: OK, 1 library found
- gemmlowp: OK, headers only
- neon2sse: OK, headers only
- clog: OK, 1 library found
- cpuinfo: OK, 1 library found
- ruy: 30 libraries found
All in all, most libs are OK, either there is 1 lib to link with, or the libs are header-only. What remains to be the problem are:
- absl
- ruy
because they contain about 30 .a libs.
Not sure if I have to link with all of those? It would be very cumbersome, as my build system is Meson and I am using custom_target() to link with TensorFlow.
Solution 1:[1]
A year later, but I just went through this myself, so here goes my answer.
Based on my experience (using a makefile and without your -DTFLITE_C_BUILD_SHARED_LIBS:BOOL=OFF) a program that performs inference does not need to link to Abseil.
You need to link to all other libs you mentioned, except ruy_kernel_arm and ruy_pack_arm, assuming you're running your program on the x64 platform. (Annoyingly -DTFLITE_ENABLE_XNNPACK=OFF is not respected when building TfLite, so you're stuck with Ruy)
Detailed steps:
Build TfLite:mkdir ~/my_tflite_project
cd ~/my_tflite_project/
git clone https://github.com/tensorflow/tensorflow.git tensorflow_src
mkdir tflite_build_x64
cd tflite_build_x64/
cmake ../tensorflow_src/tensorflow/lite/
/* You may encounter two CMake messages:
-- The Fortran compiler identification is unknown
I believe a Fortran compiler is only necessary to build Fortran bindings for TfLite.
-- Could NOT find CLANG_FORMAT: Found unsuitable version "0.0", but required is exact version "9" (found CLANG_FORMAT_EXECUTABLE-NOTFOUND)
sudo apt install clang-format-9
Annoyingly you need clang-format-9, plain clang-format (version 13, the newest) won't do. */
cmake --build . -j 4
Relevant libs:
$ cd ~/my_tflite_project/tflite_build_x64
$ ls *.a
libtensorflow-lite.a
$ ls pthreadpool/*.a
pthreadpool/libpthreadpool.a
$ ls _deps/*/*.a
_deps/clog-build/libclog.a _deps/farmhash-build/libfarmhash.a _deps/fft2d-build/libfft2d_fftsg2d.a _deps/xnnpack-build/libXNNPACK.a
_deps/cpuinfo-build/libcpuinfo.a _deps/fft2d-build/libfft2d_fftsg.a _deps/flatbuffers-build/libflatbuffers.a
$ ls _deps/ruy-build/ruy/*.a
_deps/ruy-build/ruy/libruy_allocator.a _deps/ruy-build/ruy/libruy_ctx.a _deps/ruy-build/ruy/libruy_kernel_avx.a _deps/ruy-build/ruy/libruy_prepacked_cache.a
_deps/ruy-build/ruy/libruy_apply_multiplier.a _deps/ruy-build/ruy/libruy_denormal.a _deps/ruy-build/ruy/libruy_kernel_avx2_fma.a _deps/ruy-build/ruy/libruy_prepare_packed_matrices.a
_deps/ruy-build/ruy/libruy_block_map.a _deps/ruy-build/ruy/libruy_frontend.a _deps/ruy-build/ruy/libruy_kernel_avx512.a _deps/ruy-build/ruy/libruy_system_aligned_alloc.a
_deps/ruy-build/ruy/libruy_blocking_counter.a _deps/ruy-build/ruy/libruy_have_built_path_for_avx.a _deps/ruy-build/ruy/libruy_pack_arm.a _deps/ruy-build/ruy/libruy_thread_pool.a
_deps/ruy-build/ruy/libruy_context.a _deps/ruy-build/ruy/libruy_have_built_path_for_avx2_fma.a _deps/ruy-build/ruy/libruy_pack_avx.a _deps/ruy-build/ruy/libruy_trmul.a
_deps/ruy-build/ruy/libruy_context_get_ctx.a _deps/ruy-build/ruy/libruy_have_built_path_for_avx512.a _deps/ruy-build/ruy/libruy_pack_avx2_fma.a _deps/ruy-build/ruy/libruy_tune.a
_deps/ruy-build/ruy/libruy_cpuinfo.a _deps/ruy-build/ruy/libruy_kernel_arm.a _deps/ruy-build/ruy/libruy_pack_avx512.a _deps/ruy-build/ruy/libruy_wait.a
Construct MWE using TfLite:
$ cd ~/my_tflite_project
$ mkdir my_dev_x64
$ cd my_dev_x64/
/* Construct minimal.cpp and makefile below */
$ cat minimal.cpp
#include "tensorflow/lite/model.h"
#include "tensorflow/lite/interpreter.h"
#include "tensorflow/lite/kernels/register.h"
#include <iostream>
int main() {
std::unique_ptr<tflite::FlatBufferModel> model = tflite::FlatBufferModel::BuildFromFile("your_network_here.tflite");
tflite::ops::builtin::BuiltinOpResolver resolver;
std::cout "Done\n";
return EXIT_SUCCESS;
}
$ cat makefile
COMPILER := g++
LINKER := g++
CXX_FILES := minimal.cpp
OBJ_FILES := $(CXX_FILES:.cpp=.o)
EXE_FILE := app
INCLUDE_DIRS := -I../tensorflow_src -I../tflite_build_x64/flatbuffers/include
LIB_DIRS := \
-L../tflite_build_x64 \
-L../tflite_build_x64/_deps/fft2d-build \
-L../tflite_build_x64/_deps/flatbuffers-build \
-L../tflite_build_x64/_deps/ruy-build/ruy \
-L../tflite_build_x64/_deps/farmhash-build \
-L../tflite_build_x64/_deps/xnnpack-build \
-L../tflite_build_x64/_deps/cpuinfo-build \
-L../tflite_build_x64/_deps/clog-build \
-L../tflite_build_x64/pthreadpool
LIBS := \
-ltensorflow-lite \
-lfft2d_fftsg \
-lfft2d_fftsg2d \
-lflatbuffers \
-lruy_ctx \
-lruy_allocator \
-lruy_frontend \
-lruy_context_get_ctx \
-lruy_context \
-lruy_apply_multiplier \
-lruy_prepacked_cache \
-lruy_tune \
-lruy_cpuinfo \
-lruy_system_aligned_alloc \
-lruy_prepare_packed_matrices \
-lruy_trmul \
-lruy_block_map \
-lruy_denormal \
-lruy_thread_pool \
-lruy_blocking_counter \
-lruy_wait \
-lruy_kernel_avx \
-lruy_kernel_avx2_fma \
-lruy_kernel_avx512 \
-lruy_pack_avx \
-lruy_pack_avx2_fma \
-lruy_pack_avx512 \
-lruy_have_built_path_for_avx \
-lruy_have_built_path_for_avx2_fma \
-lruy_have_built_path_for_avx512 \
-lfarmhash \
-lXNNPACK \
-lpthreadpool \
-lcpuinfo \
-lclog
CXX_FLAGS := -Wall #-pedantic
LINK_FLAGS :=
#Do not print the output of the commands
.SILENT:
#Phony targets do not represent actual files, so files with the following names are ignored
.PHONY: clean depend
#Link object files to form an executable file
$(EXE_FILE): $(OBJ_FILES)
$(LINKER) $(LINK_FLAGS) $(OBJ_FILES) -o $(EXE_FILE) $(LIB_DIRS) $(LIBS)
#Compile cpp files to object files
%.o: %.cpp
$(COMPILER) $(CXX_FLAGS) $(INCLUDE_DIRS) -c $<
#Remove object files, executable, and possible linkinfo files
clean:
-rm -f $(OBJ_FILES) $(EXE_FILE)
#Generate dependency file
depend:
$(COMPILER) $(CXX_FLAGS) $(INCLUDE_DIRS) -MM $(CXX_FILES) > make.dep
#Include dependency file
-include make.dep
Build and run MWE:
$ cd ~/my_tflite_project/my_dev_x64
$ make
$ ./app
Done
Hopefully that helps you or some other poor fellow to get TfLite C++ working.
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 |