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# ExecuTorch MobileNetV2 Demo C++ Application
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This is a simple C++ demo application that uses the ExecuTorch library for MobileNetV2 model inference.
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- # ExecutorTorch MobileNetV2 Demo C++ Application
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- This is a simple C++ demo application that uses the ExecutorTorch library for MobileNetV2 model inference.
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## Build instructions
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0 . Export the model. See [ mv2/python/README.md] ( ../python/README.md )
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1 . The ExecuTorch repository is already configured as a git submodule at ` ~/executorch-examples/mv2/cpp/executorch/ ` . To initialize it:
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- 1 . The ExecuTorch repository is already configured as a git submodule at ` ~/executorch-examples/cpp/executorch/ ` . To initialize it:
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``` bash
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cd ~ /executorch-examples/
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git submodule sync
@@ -46,18 +36,9 @@ This is a simple C++ demo application that uses the ExecutorTorch library for Mo
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- CMake 3.18 or higher
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- C++17 compatible compiler
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- ExecuTorch library (release/0.6)
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# # Notes
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- Make sure you have the correct model file (` .pte` ) compatible with ExecuTorch.
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- This demo currently initializes the input tensor with random data. In a real application, you would replace this with actual input data.
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- =======
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- - ExecutorTorch library (release/0.6)
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- # # Notes
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- - Make sure you have the correct model file (` .pte` ) compatible with ExecutorTorch.
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- - This demo currently initializes the input tensor with random data. In a real application, you would replace this with actual input data.
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