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## 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. |
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cmake | ||
external | ||
include | ||
src | ||
test | ||
README.md |
WASI-NN
How to use
Enable WASI-NN in the WAMR by spefiying it in the cmake building configuration as follows,
set (WAMR_BUILD_WASI_NN 1)
The definition of the functions provided by WASI-NN is in the header file core/iwasm/libraries/wasi-nn/wasi_nn.h
.
By only including this file in your WASM application you will bind WASI-NN into your module.
Tests
To run the tests we assume that the current directory is the root of the repository.
Build the runtime
Build the runtime image for your execution target type.
EXECUTION_TYPE
can be:
cpu
nvidia-gpu
vx-delegate
EXECUTION_TYPE=cpu
docker build -t wasi-nn-${EXECUTION_TYPE} -f core/iwasm/libraries/wasi-nn/test/Dockerfile.${EXECUTION_TYPE} .
Build wasm app
docker build -t wasi-nn-compile -f core/iwasm/libraries/wasi-nn/test/Dockerfile.compile .
docker run -v $PWD/core/iwasm/libraries/wasi-nn:/wasi-nn wasi-nn-compile
Run wasm app
If all the tests have run properly you will the the following message in the terminal,
Tests: passed!
- CPU
docker run \
-v $PWD/core/iwasm/libraries/wasi-nn/test:/assets \
-v $PWD/core/iwasm/libraries/wasi-nn/test/models:/models \
wasi-nn-cpu \
--dir=/ \
--env="TARGET=cpu" \
/assets/test_tensorflow.wasm
- (NVIDIA) GPU
docker run \
--runtime=nvidia \
-v $PWD/core/iwasm/libraries/wasi-nn/test:/assets \
-v $PWD/core/iwasm/libraries/wasi-nn/test/models:/models \
wasi-nn-nvidia-gpu \
--dir=/ \
--env="TARGET=gpu" \
/assets/test_tensorflow.wasm
- vx-delegate for NPU (x86 simulater)
docker run \
-v $PWD/core/iwasm/libraries/wasi-nn/test:/assets wasi-nn-vx-delegate \
--dir=/assets \
--env="TARGET=gpu" \
/assets/test_tensorflow.wasm
Requirements:
What is missing
Supported:
- Graph encoding:
tensorflowlite
. - Execution target:
cpu
andgpu
. - Tensor type:
fp32
.