Build and configuration¶
xtensor can be configured via macros which must be defined before including
any of its headers. This can be achieved the following ways:
either define them in the CMakeLists of your project, with
or create a header where you define all the macros you want and then include the headers you need. Then include this header whenever you need
xtensorin your project.
The following macros are already defined in
xtensor but can be overwritten:
XTENSOR_DEFAULT_DATA_CONTAINER(T, A): defines the type used as the default data container for tensors and arrays.
value_typeof the container and
XTENSOR_DEFAULT_SHAPE_CONTAINER(T, EA, SA): defines the type used as the default shape container for tensors and arrays.
value_typeof the data container,
allocator_typeof the shape container.
XTENSOR_DEFAULT_LAYOUT: defines the default layout (row_major, column_major, dynamic) for tensors and arrays. We strongly discourage using this macro, which is provided for testing purpose. Prefer defining alias types on tensor and array containers instead.
XTENSOR_DEFAULT_TRAVERSAL: defines the default traversal order (row_major, column_major) for algorithms and iterators on tensors and arrays. We strongly discourage using this macro, which is provided for testing purpose.
The following macros are helpers for debugging, they are not defined by default:
XTENSOR_ENABLE_ASSERT: enables assertions in xtensor, such as bound check.
XTENSOR_ENABLE_CHECK_DIMENSION: enables the dimensions check in
xtensor. Note that this option should not be turned on if you expect
operator()to perform broadcasting.
The last group of macros is for using external libraries to achieve maximum performance (see next section for additional requirements):
XTENSOR_USE_XSIMD: enables SIMD acceleration in
xtensor. This requires that you have xsimd installed on your system.
XTENSOR_USE_TBB: enables parallel assignment loop. This requires that you have tbb installed on your system.
XTENSOR_DISABLE_EXCEPTIONS: disables c++ exceptions.
XTENSOR_USE_OPENMP: enables parallel assignment loop using OpenMP. This requires that OpenMP is available on your system.
Defining these macros in the CMakeLists of your project before searching for
xtensor will trigger automatic finding
of dependencies, so you don’t have to include the
find_package(TBB) commands in your
set(XTENSOR_USE_XSIMD 1) set(XTENSOR_USE_TBB 1) # xsimd and TBB dependencies are automatically # searched when the following is executed find_package(xtensor REQUIRED) # the target now sets the proper defines (e.g. "XTENSOR_USE_XSIMD") target_link_libraries(... xtensor)
Build and optimization¶
Windows users must activate the
/bigobj flag, otherwise it’s almost certain that the compilation fails. More generally,
the following options are recommended:
target_link_libraries(... xtensor xtensor::optimize) set(CMAKE_EXE_LINKER_FLAGS /MANIFEST:NO) # OR target_compile_options(target_name PRIVATE /EHsc /MP /bigobj) set(CMAKE_EXE_LINKER_FLAGS /MANIFEST:NO)
If you defined
XTENSOR_USE_XSIMD, you must also specify which instruction set you target:
target_compile_options(target_name PRIVATE /arch:AVX2) # OR target_compile_options(target_name PRIVATE /arch:AVX) # OR target_compile_options(target_name PRIVATE /arch:ARMv7VE)
If you build on an old system that does not support any of these instruction sets, you don’t have to specify anything, the system will do its best to enable the most recent supported instruction set.
Whether you enabled
XTENSOR_USE_XSIMD or not, it is highly recommended to build with
if your compiler supports it:
target_link_libraries(... xtensor xtensor::optimize) # OR target_compile_options(target_name PRIVATE -march=native)
Notice that this option prevents building on a machine and distributing the resulting binary on another machine with a different architecture (i.e. not supporting the same instruction set).