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	## Job Test running on most CI jobs. ## Test binary * `test_main.cpp`: entry for gtest * `test_operator_registration.cpp`: test cases for gtest ## Helper sources * `operator_registry.h/cpp`: simple operator registry for testing purpose. * `Evalue.h`: a boxed data type that wraps ATen types, for testing purpose. * `selected_operators.yaml`: operators Executorch care about so far, we should cover all of them. ## Templates * `NativeFunctions.h`: for generating headers for native functions. (not compiled in the test, since we will be using `libtorch`) * `RegisterCodegenUnboxedKernels.cpp`: for registering boxed operators. * `Functions.h`: for declaring operator C++ APIs. Generated `Functions.h` merely wraps `ATen/Functions.h`. ## Build files * `CMakeLists.txt`: generate code to register ops. * `build.sh`: driver file, to be called by CI job. Pull Request resolved: https://github.com/pytorch/pytorch/pull/89596 Approved by: https://github.com/ezyang
Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind.
Questions and Feedback
Please use GitHub issues (https://github.com/pytorch/pytorch/issues) to ask questions, report bugs, and request new features.