6 releases
0.3.0 | Aug 23, 2024 |
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0.2.0 | Aug 9, 2024 |
0.1.0 | Aug 3, 2024 |
#897 in Machine learning
29 downloads per month
Used in executorch
68KB
395 lines
executorch-sys
For a general description of the project, see the the executorch
crate.
Build
To build the library, you need to build the C++ library first.
The C++ library allow for great flexibility with many flags, customizing which modules, kernels, and extensions are built.
Multiple static libraries are built, and the Rust library links to them.
In the following example we build the C++ library with the necessary flags to run example hello_world_add
:
# Clone the C++ library
cd ${TEMP_DIR}
git clone --depth 1 --branch v0.3.0 https://github.com/pytorch/executorch.git
cd executorch
git submodule sync --recursive
git submodule update --init --recursive
# Install requirements
./install_requirements.sh
# Build C++ library
mkdir cmake-out && cd cmake-out
cmake \
-DDEXECUTORCH_SELECT_OPS_LIST=aten::add.out \
-DEXECUTORCH_BUILD_EXECUTOR_RUNNER=OFF \
-DEXECUTORCH_BUILD_EXTENSION_RUNNER_UTIL=OFF \
-DBUILD_EXECUTORCH_PORTABLE_OPS=ON \
-DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
-DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
-DEXECUTORCH_ENABLE_PROGRAM_VERIFICATION=ON \
-DEXECUTORCH_ENABLE_LOGGING=ON \
..
make -j
# Static libraries are in cmake-out/
# core:
# cmake-out/libexecutorch.a
# cmake-out/libexecutorch_no_prim_ops.a
# kernels implementations:
# cmake-out/kernels/portable/libportable_ops_lib.a
# cmake-out/kernels/portable/libportable_kernels.a
# extension data loader, enabled with EXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON:
# cmake-out/extension/data_loader/libextension_data_loader.a
# extension module, enabled with EXECUTORCH_BUILD_EXTENSION_MODULE=ON:
# cmake-out/extension/module/libextension_module_static.a
# Run example
# We set EXECUTORCH_RS_EXECUTORCH_LIB_DIR to the path of the C++ build output
cd ${EXECUTORCH_RS_DIR}/examples/hello_world_add
python export_model.py
EXECUTORCH_RS_EXECUTORCH_LIB_DIR=${TEMP_DIR}/executorch/cmake-out cargo run
The executorch
crate will always look for the following static libraries:
libexecutorch.a
libexecutorch_no_prim_ops.a
Additional libs are required if feature flags are enabled (see next section):
libextension_data_loader.a
libextension_module_static.a
The static libraries of the kernels implementations are required only if your model uses them, and they should be linked manually by the binary that uses the executorch
crate.
For example, the hello_world_add
example uses a model with a single addition operation, so it compile the C++ library with DEXECUTORCH_SELECT_OPS_LIST=aten::add.out
and contain the following lines in its build.rs
:
println!("cargo::rustc-link-lib=static:+whole-archive=portable_kernels");
println!("cargo::rustc-link-lib=static:+whole-archive=portable_ops_lib");
let libs_dir = std::env::var("EXECUTORCH_RS_EXECUTORCH_LIB_DIR").unwrap();
println!("cargo::rustc-link-search={}/kernels/portable/", libs_dir);
Note that the ops and kernels libs are linked with +whole-archive
to ensure that all symbols are included in the binary.
Cargo Features
-
data-loader
Includes the
FileDataLoader
andMmapDataLoader
structs. Without this feature the only available data loader isBufferDataLoader
. Thelibextension_data_loader.a
static library is required, compile C++executorch
withEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON
. -
module
Includes the
Module
struct. Thelibextension_module_static.a
static library is required, compile C++executorch
withEXECUTORCH_BUILD_EXTENSION_MODULE=ON
. Also includes thestd
feature. -
std
Enable the standard library. This feature is enabled by default, but can be disabled to build
executorch
in ano_std
environment. NOTE: no_std is still WIP, see https://github.com/pytorch/executorch/issues/4561
By default the std
feature is enabled.
Dependencies
~0–2MB
~41K SLoC