Bump llvm-project to 3d92722.

* Picks up Python configure changes (was pinned to a bad intermediate commit).
* Uses the new mlir_configure_python_dev_packages() to ensure CMake python is found consistently.
* Fixes the JIT importer to build as a MODULE vs SHARED (needed for linking to Python as a module, per config changes).
* Adds some notes to the README to help folks build a smaller set focused just on this project.

.gitignore

@@ -3,6 +3,7 @@
 .env
 *.code-workspace
 .ipynb_checkpoints
+*.venv/
 
 /build/
 __pycache__

CMakeLists.txt

@@ -37,7 +37,7 @@ if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
 
   set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
   set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
-  
+
   # Define the default arguments to use with 'lit', and an option for the user to
   # override.
   set(LIT_ARGS_DEFAULT "-sv")
@@ -64,7 +64,7 @@ if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
   set(BACKEND_PACKAGE_STRING "LLVM ${LLVM_PACKAGE_VERSION}")
 else()
   # In-tree build with LLVM_EXTERNAL_PROJECTS=torch-mlir
-  
+
   option(MLIR_ENABLE_BINDINGS_PYTHON "Enables MLIR Python Bindings" OFF)
   option(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER "Enables JIT IR Importer" ON)
 
@@ -113,15 +113,11 @@ include(AddMLIR)
 
 ################################################################################
 # Setup python.
-# TODO: Make one upstream macro to do this.
 ################################################################################
 
 if(MLIR_ENABLE_BINDINGS_PYTHON)
   include(MLIRDetectPythonEnv)
-  mlir_detect_pybind11_install()
-  find_package(Python3 ${LLVM_MINIMUM_PYTHON_VERSION}
-  COMPONENTS Interpreter Development NumPy REQUIRED)
-  find_package(pybind11 2.6 CONFIG REQUIRED)
+  mlir_configure_python_dev_packages()
 endif()
 
 add_subdirectory(include)

README.md

@@ -50,7 +50,7 @@ python -m pip install --upgrade pip
 python -m pip install --pre torch torchvision pybind11 -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
 ```
 
-## Build 
+## Build
 ```shell
 cmake -GNinja -Bbuild \
   -DCMAKE_C_COMPILER=clang \
@@ -70,7 +70,14 @@ cmake -GNinja -Bbuild \
 # -DCMAKE_EXE_LINKER_FLAGS_INIT="-fuse-ld=lld" -DCMAKE_MODULE_LINKER_FLAGS_INIT="-fuse-ld=lld" -DCMAKE_SHARED_LINKER_FLAGS_INIT="-fuse-ld=lld"
 # Use --ld-path= instead of -fuse-ld=lld for clang > 13
 
-cmake --build build
+# Build just torch-mlir (not all of LLVM)
+cmake --build build --target tools/torch-mlir/all
+
+# Run unit tests.
+cmake --build build --target check-torch-mlir
+
+# Build everything (including LLVM)
+# cmake --build build
 ```
 ## Demos
 
@@ -139,7 +146,7 @@ The `examples` folder includes the Python package `lazytensor`, which implements
 
 #### Example usage of `lazytensor`
 
-The `examples` folder includes scripts `lazytensor_*.py` showing how to use the Lazy Tensor to MLIR pipeline. The examples depend on the Lazy Tensor Core (LTC) of PyTorch. For information on how to obtain LTC, see [here](https://github.com/pytorch/pytorch/blob/lazy_tensor_staging/lazy_tensor_core/QUICKSTART.md). 
+The `examples` folder includes scripts `lazytensor_*.py` showing how to use the Lazy Tensor to MLIR pipeline. The examples depend on the Lazy Tensor Core (LTC) of PyTorch. For information on how to obtain LTC, see [here](https://github.com/pytorch/pytorch/blob/lazy_tensor_staging/lazy_tensor_core/QUICKSTART.md).
 
 In order to run the examples, make sure you've setup your `PYTHONPATH` by following the [Setup Python Environment](#setup-python-environment) instructions, and also add `/path/to/pytorch/lazy_tensor_core` to your `PYTHONPATH` as shown below:
 

python/torch_mlir/dialects/torch/importer/jit_ir/csrc/CMakeLists.txt

@@ -10,7 +10,7 @@ include_directories(BEFORE
   )
 link_directories("${TORCH_INSTALL_PREFIX}/lib")
 
-add_library(TorchMLIRJITIRImporter SHARED
+add_library(TorchMLIRJITIRImporter MODULE
   class_annotator.cpp
   get_registered_ops.cpp
   function_importer.cpp