By default, the project() CMake command defaults to C and C++. [1]
Therefore, CMake might perform tests for both C and C++ compilers as
part of the configuration phase.
However, this has the consequence of the configuration phase to fail if
the system does not have a C++ toolchain installed, even if C++ is not
really used by the top-level project under the default settings.
Some configurations might still require a C++ toolchain, so
enable_language is selectively called under such circumstances.
[1]: https://cmake.org/cmake/help/latest/command/project.html
We need to fix numpy version since the latest is incompatible.
> A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.0.0 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
- All files under *core/iwasm/libraries/wasi-nn* are compiled as shared libraries
- *wasi-nn.c* is shared between backends
- Every backend has a separated shared library
- If wasi-nn feature is enabled, iwasm will depend on shared library libiwasm.so
instead of linking static library libvmlib.a
## Context
Currently, WAMR supports compiling iwasm with flag `WAMR_BUILD_WASI_NN`.
However, there are scenarios where the user might prefer having it as a shared library.
## Proposed Changes
Decouple wasi-nn context management by internally managing the context given
a module instance reference.
## Context
Path to models use `/assets` for testing inside docker. While testing directly from
the repo we are forced to use soft-links or modify the paths.
## Proposed Changes
Use relative path and adjust docker volumes in docs.
Major changes:
- Public headers inside `wasi-nn/include`
- Put cmake files in `cmake` folder
- Make linux iwasm link with `${WASI_NN_LIBS}` so iwasm can enable wasi-nn
Add VX delegation as an external delegation of TFLite, so that several NPU/GPU
(from VeriSilicon, NXP, Amlogic) can be controlled via WASI-NN.
Test Code can work with the X86 simulator.
Since the Tensorflow library is already installed in many cases(especially in the
case of the embedded system), move the installation code to find_package.
Remove restrictions:
- Only 1 WASM app at a time
- Only 1 model at a time
- `graph` and `graph-execution-context` are ignored
Refer to previous document:
e8d718096d/core/iwasm/libraries/wasi-nn/README.md
Support collecting code coverage with wamr-test-suites script by using
lcov and genhtml tools, eg.:
cd tests/wamr-test-suites
./test_wamr.sh -s spec -b -P -C
The default code coverage and html files are generated at:
tests/wamr-test-suites/workspace/wamr.lcov
tests/wamr-test-suites/workspace/wamr-lcov.zip
And update wamr-test-suites scripts to support testing GC spec cases to
avoid frequent synchronization conflicts between branch main and dev/gc.
- Split logic in several dockers
- runtime: wasi-nn-cpu and wasi-nn- Nvidia-gpu.
- compilation: wasi-nn-compile. Prepare the testing wasm and generates the TFLites.
- Implement GPU support for TFLite with Opencl.
- Reorganize the library structure
- Use the latest version of `wasi-nn` wit (Oct 25, 2022):
0f77c48ec1/wasi-nn.wit.md
- Split logic that converts WASM structs to native structs in a separate file
- Simplify addition of new frameworks
Initial integration of WASI-NN based on #1225:
- Implement the library core/iwasm/libraries/wasi-nn
- Support TensorFlow, CPU, F32 at the first stage
- Add cmake variable `-DWAMR_BUILD_WASI_NN`
- Add test case based on Docker image and update document
Refer to #1573
