Update on "Reuse GELU implementation from PyTorch core"

kernels/optimized doesn't need to support embedded systems, so it can just take a header-only dep on PyTorch.

Note that, because we will pick up Sleef internally and ignore it
externally thanks to ATen vec, this PR gets to enable optimized GELU in OSS.

Testing: CI to make sure this doesn't break mobile build modes; happy to take advice on anything not currently covered that might break.

Differential Revision: [D66335522](https://our.internmc.facebook.com/intern/diff/D66335522/)

[ghstack-poisoned]

Author: swolchok

build/Codegen.cmake

@@ -11,13 +11,14 @@
 # arguments.
 function(gen_selected_ops)
   set(arg_names LIB_NAME OPS_SCHEMA_YAML ROOT_OPS INCLUDE_ALL_OPS)
-  cmake_parse_arguments(GEN "" "" "${arg_names}" ${ARGN})
+  cmake_parse_arguments(GEN "${options}" "" "${arg_names}" ${ARGN})
 
   message(STATUS "Generating operator lib:")
   message(STATUS "  LIB_NAME: ${GEN_LIB_NAME}")
   message(STATUS "  OPS_SCHEMA_YAML: ${GEN_OPS_SCHEMA_YAML}")
   message(STATUS "  ROOT_OPS: ${GEN_ROOT_OPS}")
   message(STATUS "  INCLUDE_ALL_OPS: ${GEN_INCLUDE_ALL_OPS}")
+  message(STATUS "  ADD_EXCEPTION_BOUNDARY: ${GEN_ADD_EXCEPTION_BOUNDARTY}")
 
   set(_oplist_yaml
       ${CMAKE_CURRENT_BINARY_DIR}/${GEN_LIB_NAME}/selected_operators.yaml
@@ -59,13 +60,15 @@ endfunction()
 # Invoked as generate_bindings_for_kernels( LIB_NAME lib_name FUNCTIONS_YAML
 # functions_yaml CUSTOM_OPS_YAML custom_ops_yaml )
 function(generate_bindings_for_kernels)
+  set(options ADD_EXCEPTION_BOUNDARY)
   set(arg_names LIB_NAME FUNCTIONS_YAML CUSTOM_OPS_YAML)
-  cmake_parse_arguments(GEN "" "${arg_names}" "" ${ARGN})
+  cmake_parse_arguments(GEN "${options}" "${arg_names}" "" ${ARGN})
 
   message(STATUS "Generating kernel bindings:")
   message(STATUS "  LIB_NAME: ${GEN_LIB_NAME}")
   message(STATUS "  FUNCTIONS_YAML: ${GEN_FUNCTIONS_YAML}")
   message(STATUS "  CUSTOM_OPS_YAML: ${GEN_CUSTOM_OPS_YAML}")
+  message(STATUS "  ADD_EXCEPTION_BOUNDARY: ${GEN_ADD_EXCEPTION_BOUNDARY}")
 
   # Command to generate selected_operators.yaml from custom_ops.yaml.
   file(GLOB_RECURSE _codegen_templates "${EXECUTORCH_ROOT}/codegen/templates/*")
@@ -93,7 +96,10 @@ function(generate_bindings_for_kernels)
       --tags-path=${site-packages-out}/torchgen/packaged/ATen/native/tags.yaml
       --aten-yaml-path=${site-packages-out}/torchgen/packaged/ATen/native/native_functions.yaml
       --op-selection-yaml-path=${_oplist_yaml}
-  )
+    )
+  if(GEN_ADD_EXCEPTION_BOUNDARY)
+    set(_gen_command "${_gen_command} --add-exception-boundary")
+  endif()
 
   set(_gen_command_sources
       ${_out_dir}/RegisterCodegenUnboxedKernelsEverything.cpp

configurations/CMakeLists.txt

@@ -44,6 +44,7 @@ if(EXECUTORCH_BUILD_KERNELS_OPTIMIZED)
     LIB_NAME "optimized_native_cpu_ops_lib" FUNCTIONS_YAML
     ${CMAKE_CURRENT_BINARY_DIR}/merged.yaml
   )
+  target_compile_options(optimized_native_cpu_ops_lib PRIVATE "-fexceptions")
   message("Generated files ${gen_command_sources}")
 
   # optimized_native_cpu_ops_lib: Register optimized op kernels into the runtime

kernels/optimized/CMakeLists.txt

@@ -23,6 +23,8 @@ endif()
 
 set(_common_compile_options -Wno-deprecated-declarations)
 
+add_compile_options("-fexceptions")
+
 # Note for apple platform we can rely on Accelerate framework Will come back to
 # this
 include(${CMAKE_CURRENT_LIST_DIR}/External/EigenBLAS.cmake)
@@ -55,6 +57,7 @@ gen_selected_ops(LIB_NAME "optimized_ops_lib" OPS_SCHEMA_YAML "${_yaml}")
 generate_bindings_for_kernels(
   LIB_NAME "optimized_ops_lib" FUNCTIONS_YAML
   ${CMAKE_CURRENT_SOURCE_DIR}/optimized-oss.yaml
+  ADD_EXCEPTION_BOUNDARY
 )
 message("Generated files ${gen_command_sources}")