PoC to test libtorch support for onnxnruntime-extensions

[thiagocrepaldi]

This PR prototypes an extension that adds the ability to onnxruntime-extensions to execute kernels implemented using PyTorch's libtorch.

For this experiment, only libtorch for CPU only from https://download.pytorch.org/libtorch/nightly/cpu/libtorch-shared-with-deps-latest.zip was tested, but it should also work for GPU-enable libtorch

It is important to notice that the libtorch version (cpu/cuda) used to build the extension must match the PyTorch installed for runtime, otherwise undefined reference issues will happen

As a proof of concept, a dummy MyRelu op was introduced, in which it calls into torch::ReLu operator. This serves as a minimal example. There are implementations for both CUDA and CPU Relu, but only the CPU version has been tested.

To replicate this PR on a clean environment, users must install the following as requirements:

• Install onnxruntime or build it from source
• Install Pytorch or build from source
• Use this onnxruntime-extensions branch

Next, users must export OCOS_LIBTORCH_PATH=/path/to/libtorch before calling pip install . from the onnxruntime-extensions repo.

As an alernative, the full working environment for cpu-only can be pulled and tested from Docker hub using the following command:

docker pull  thiagocrepaldi/onnxruntime_extensions_libtorch:cpuonly
docker run --rm -it thiagocrepaldi/onnxruntime_extensions_libtorch:cpuonly bash
python dev/gh/onnxruntime-extensions/test/test_myrelu.py

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