- 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
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.
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.
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
- 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
