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C++ Tooling
===========
This guide covers the TVM-FFI C++ toolchain: header layout, build integration,
library distribution, and editor setup.
For an end-to-end walkthrough that builds, loads, and calls a C++/CUDA kernel,
see :doc:`../get_started/quickstart`.
.. admonition:: Prerequisite
:class: hint
- Compiler: C++17-capable toolchain (GCC/Clang/MSVC)
- CMake: 3.18 or newer
- TVM-FFI installed via
.. code-block:: bash
pip install --reinstall --upgrade apache-tvm-ffi
C++ Headers
-----------
**Core APIs.** A single umbrella header exposes most of the API surface,
including :doc:`functions <../concepts/func_module>`,
:doc:`objects <../concepts/object_and_class>`,
:doc:`Any/AnyView <../concepts/any>`,
:doc:`tensors <../concepts/tensor>`, and
:doc:`exception handling <../concepts/exception_handling>`.
.. code-block:: cpp
#include <tvm/ffi/tvm_ffi.h>
Extra features live in dedicated headers under
`tvm/ffi/extra/ <https://github.com/apache/tvm-ffi/tree/main/include/tvm/ffi/extra>`_
and should be included only when needed:
- **Environment API** -- allocator, stream, and device access
(see :doc:`../concepts/tensor` for usage):
``#include <tvm/ffi/extra/c_env_api.h>``
- **Dynamic module loading** (see :ref:`sec:module`):
``#include <tvm/ffi/extra/module.h>``
- **CUBIN launcher** (see :doc:`../guides/cubin_launcher`):
``#include <tvm/ffi/extra/cuda/cubin_launcher.h>``
Build with TVM-FFI
------------------
CMake
~~~~~
TVM-FFI ships CMake utilities and imported targets through its package configuration.
The two primary functions are ``tvm_ffi_configure_target`` and ``tvm_ffi_install``,
both defined in ``cmake/Utils/Library.cmake``.
.. hint::
See `examples/python_packaging/CMakeLists.txt <https://github.com/apache/tvm-ffi/blob/main/examples/python_packaging/CMakeLists.txt>`_
for a complete working example.
Configure Target
""""""""""""""""
``tvm_ffi_configure_target`` wires a CMake target to TVM-FFI with sensible
defaults: it links headers and the shared library, configures debug symbols,
and optionally runs :ref:`stub generation <sec-stubgen>` as a post-build step.
.. code-block:: cmake
tvm_ffi_configure_target(
<target>
[LINK_SHARED ON|OFF ]
[LINK_HEADER ON|OFF ]
[DEBUG_SYMBOL ON|OFF ]
[MSVC_FLAGS ON|OFF ]
[STUB_INIT ON|OFF ]
[STUB_DIR <dir> ]
[STUB_PKG <pkg> ]
[STUB_PREFIX <prefix>]
)
:LINK_SHARED: (default: ON) Link against the TVM-FFI shared library
``tvm_ffi::shared``. Set OFF for header-only usage or deferred runtime loading.
:LINK_HEADER: (default: ON) Link against the TVM-FFI headers via
``tvm_ffi::header``. Set OFF when you manage include paths and compile
definitions manually.
:DEBUG_SYMBOL: (default: ON) Enable debug symbol post-processing hooks. On
Apple platforms this runs ``dsymutil``.
:MSVC_FLAGS: (default: ON) Apply MSVC compatibility flags.
:STUB_DIR: (default: "") Output directory for generated Python stubs. When set,
stub generation runs as a post-build step.
:STUB_INIT: (default: OFF) Allow the stub generator to initialize a new package layout.
Requires ``STUB_DIR``.
:STUB_PKG: (default: "") Package name passed to the stub generator. Requires ``STUB_DIR``
and ``STUB_INIT=ON``.
:STUB_PREFIX: (default: "") Module prefix passed to the stub generator. Requires
``STUB_DIR`` and ``STUB_INIT=ON``.
See :ref:`sec-stubgen-cmake` for a detailed explanation of each ``STUB_*`` option
and the generation modes they control.
Install Target
""""""""""""""
``tvm_ffi_install`` installs platform-specific artifacts for a target.
On Apple platforms it installs the ``.dSYM`` bundle when present;
on other platforms this is currently a no-op.
.. code-block:: cmake
tvm_ffi_install(
<target>
[DESTINATION <dir>]
)
:DESTINATION: Install destination directory relative to ``CMAKE_INSTALL_PREFIX``.
Set ``tvm_ffi_ROOT``
""""""""""""""""""""
If ``find_package(tvm_ffi CONFIG REQUIRED)`` fails because CMake cannot locate
the package, pass ``tvm_ffi_ROOT`` explicitly:
.. code-block:: bash
cmake -S . -B build \
-Dtvm_ffi_ROOT="$(tvm-ffi-config --cmakedir)"
.. note::
When packaging Python wheels with scikit-build-core, ``tvm_ffi_ROOT`` is
discovered automatically from the active Python environment.
GCC/NVCC
~~~~~~~~
For quick prototyping or CI scripts without CMake, invoke ``g++`` or ``nvcc``
directly with flags from ``tvm-ffi-config``.
The examples below are from the :doc:`Quick Start <../get_started/quickstart>` tutorial:
.. tabs::
.. group-tab:: C++
.. literalinclude:: ../../examples/quickstart/raw_compile.sh
:language: bash
:start-after: [cpp_compile.begin]
:end-before: [cpp_compile.end]
.. group-tab:: CUDA
.. literalinclude:: ../../examples/quickstart/raw_compile.sh
:language: bash
:start-after: [cuda_compile.begin]
:end-before: [cuda_compile.end]
The three ``tvm-ffi-config`` flags provide:
:``--cxxflags``: Include paths and compile definitions (``-I...``, ``-D...``)
:``--ldflags``: Library search paths (``-L...``, ``-Wl,-rpath,...``)
:``--libs``: Libraries to link (``-ltvm_ffi``)
**RPATH handling.** The resulting shared library links against ``libtvm_ffi.so``,
so the dynamic linker must be able to find it at load time:
- **Python distribution.** ``import tvm_ffi`` preloads ``libtvm_ffi.so`` into the
process before any user library is loaded, so the RPATH requirement is already
satisfied without additional linker flags.
- **Pure C++ distribution.** You must ensure ``libtvm_ffi.so`` is on the library
search path. Either set ``-Wl,-rpath,$(tvm-ffi-config --libdir)`` at link time,
or place ``libtvm_ffi.so`` alongside your binary.
Library Distribution
--------------------
When distributing pre-built shared libraries on Linux, glibc symbol versioning
can cause load-time failures on systems with a different glibc version.
The standard solution is the `manylinux <https://github.com/pypa/manylinux>`_
approach: **build on old glibc, run on new**.
**Build environment.** Use a manylinux Docker image:
.. code-block:: bash
docker pull quay.io/pypa/manylinux2014_x86_64
Build host and device code inside the container. For CUDA:
.. code-block:: bash
nvcc -shared -Xcompiler -fPIC your_kernel.cu -o kernel.so \
$(tvm-ffi-config --cxxflags) \
$(tvm-ffi-config --ldflags) \
$(tvm-ffi-config --libs)
**Verify glibc requirements.** Inspect the minimum glibc version your binary requires:
.. code-block:: bash
objdump -T your_kernel.so | grep GLIBC_
The ``apache-tvm-ffi`` wheel is already manylinux-compatible, so linking against
it inside a manylinux build environment produces portable binaries.
Editor Setup
------------
The following configuration enables code completion and diagnostics in
VSCode, Cursor, or any editor backed by clangd.
**CMake Tools (VSCode/Cursor).** Add these workspace settings so CMake Tools
can locate TVM-FFI and generate ``compile_commands.json``:
.. code-block:: json
{
"cmake.buildDirectory": "${workspaceFolder}/build-vscode",
"cmake.configureArgs": [
"-DCMAKE_EXPORT_COMPILE_COMMANDS=ON"
],
"cmake.configureSettings": {
"Python_EXECUTABLE": "${workspaceFolder}/.venv/bin/python3",
"tvm_ffi_ROOT": "${workspaceFolder}/.venv/lib/pythonX.Y/site-packages/tvm_ffi/share/cmake/tvm_ffi"
}
}
.. important::
Make sure ``Python_EXECUTABLE`` and ``tvm_ffi_ROOT`` match the virtual
environment you intend to use.
**clangd.** Create a ``.clangd`` file at the project root pointing to the CMake
compilation database. The snippet below also strips NVCC flags that clangd
does not recognize:
.. code-block:: yaml
CompileFlags:
CompilationDatabase: build-vscode/
Remove: # for NVCC compatibility
- -forward-unknown-to-host-compiler
- --generate-code*
- -Xcompiler*
Further Reading
---------------
- :doc:`../get_started/quickstart`: End-to-end walkthrough building and shipping a C++/CUDA kernel
- :doc:`../dev/source_build`: Building TVM-FFI from source with CMake flags
- :doc:`stubgen`: Generating Python type stubs from C++ reflection metadata
- :doc:`python_packaging`: Packaging shared libraries as Python wheels
- :doc:`../concepts/func_module`: Defining and exporting TVM-FFI functions
- :doc:`../concepts/object_and_class`: Defining C++ classes with cross-language reflection
- :doc:`../concepts/exception_handling`: Error handling across language boundaries
- :doc:`../concepts/abi_overview`: Low-level C ABI details