Integrate LLVM at bb1f220d534b0f6d80bea36662f5188ff11c2e54

Update externals/llvm-project.

Torch-MLIR's Python extension is updated to use MLIR's nanobind adaptors
(PybindAdaptors.h was removed upstream).

Author: Lallapallooza

externals/llvm-project

@@ -2475,12 +2475,15 @@ void AtenUnflattenIntOp::getCanonicalizationPatterns(
                                          "sizes must come from list construct");
     if (sizeValues.size() != 2)
       return failure();
-    int64_t dim0, dim1;
+    int64_t dim0 = Torch::kUnknownSize;
+    int64_t dim1 = Torch::kUnknownSize;
     bool dim0Constant = matchPattern(sizeValues[0], m_TorchConstantInt(&dim0));
     bool dim1Constant = matchPattern(sizeValues[1], m_TorchConstantInt(&dim1));
     if (!dim0Constant && !dim1Constant)
       return failure();
-    if (dim0 != 1 && dim1 != 1)
+    bool dim0IsOne = dim0Constant && dim0 == 1;
+    bool dim1IsOne = dim1Constant && dim1 == 1;
+    if (!dim0IsOne && !dim1IsOne)
       return failure();
     Value unflattenDim = op.getDim();
     int64_t dimAsInt;
@@ -2491,7 +2494,7 @@ void AtenUnflattenIntOp::getCanonicalizationPatterns(
     // the runtime asserts below are introduced to catch malformed unflatten ops
     // possibly generated from onnx IR.
     Value unsqueeze;
-    if (dim0 == 1) {
+    if (dim0IsOne) {
       // unsqueeze at dim
       FailureOr<Value> maybeUnsqueeze =
           Torch::unsqueezeTensor(rewriter, op, self, unflattenDim);
@@ -2512,7 +2515,7 @@ void AtenUnflattenIntOp::getCanonicalizationPatterns(
           rewriter, op.getLoc(), isMOneOrSameSize,
           rewriter.getStringAttr("unflatten sizes must be compatible"));
     }
-    if (dim1 == 1) {
+    if (dim1IsOne) {
       // unsqueeze at dim + 1
       Value dimPlusOne;
       if (!dimWasConstant) {

lib/Dialect/Torch/IR/TorchOps.cpp

@@ -1,6 +1,6 @@
 # Separate Pybind MODULE due to issues with a SHARED library.
 # https://github.com/llvm/torch-mlir/issues/1154
-add_library(TorchMLIRJITIRImporterPybind MODULE
+Python3_add_library(TorchMLIRJITIRImporterPybind MODULE WITH_SOABI
   class_annotator_pybind.cpp
   get_registered_ops.cpp
   import_options_pybind.cpp
@@ -11,26 +11,23 @@ add_dependencies(TorchMLIRJITIRImporterPybind
   TorchMLIRJITIRImporter
   )
 target_link_libraries(TorchMLIRJITIRImporterPybind
-  ${TORCH_LIBRARIES}
-  torch_python
-  TorchMLIRJITIRImporter
+  PRIVATE
+    ${TORCH_LIBRARIES}
+    torch_python
+    TorchMLIRJITIRImporter
   )
 
-# On static Python builds, there may not be Python libraries to link against
-# (they will late bind at runtime from the executable). We have to condition
-# this because in that case it is set to NOTFOUND and CMake will consider
-# this an error.
-if(Python3_LIBRARIES)
-  target_link_libraries(TorchMLIRJITIRImporterPybind
-    ${Python3_LIBRARIES}
-  )
+# Prefer the imported target when available (handles static Python correctly).
+if(TARGET Python3::Module)
+  target_link_libraries(TorchMLIRJITIRImporterPybind PRIVATE Python3::Module)
+elseif(Python3_LIBRARIES)
+  # On some setups the imported target is unavailable; fall back to raw libs.
+  target_link_libraries(TorchMLIRJITIRImporterPybind PRIVATE ${Python3_LIBRARIES})
 endif()
 
 set_target_properties(TorchMLIRJITIRImporterPybind PROPERTIES
   LIBRARY_OUTPUT_DIRECTORY "${TORCH_MLIR_PYTHON_PACKAGES_DIR}/torch_mlir/torch_mlir/_mlir_libs"
   OUTPUT_NAME _jit_ir_importer
-  PREFIX "${PYTHON_MODULE_PREFIX}"
-  SUFFIX "${PYTHON_MODULE_EXTENSION}"
   CXX_VISIBILITY_PRESET "hidden"
   COMPILE_FLAGS "${TORCH_CXXFLAGS}"
   )

projects/pt1/python/torch_mlir/csrc/jit_ir_importer/CMakeLists.txt

@@ -20,25 +20,24 @@ if(TORCH_MLIR_ENABLE_LTC)
   link_directories(${CMAKE_CURRENT_SOURCE_DIR}/lib)
   add_link_options(-Wl,-rpath,$ORIGIN/lib)
 
-  add_library(reference_lazy_backend MODULE
+  Python3_add_library(reference_lazy_backend MODULE WITH_SOABI
           backend_impl.cpp
           reference_lazy_backend_pybind.cpp
           )
   add_dependencies(reference_lazy_backend
           torch_mlir_ltc_backend
           )
   target_link_libraries(reference_lazy_backend
-          ${TORCH_LIBRARIES}
-          torch_python
-          torch_mlir_ltc_backend
+          PRIVATE
+            ${TORCH_LIBRARIES}
+            torch_python
+            torch_mlir_ltc_backend
           )
 
   message(STATUS "TORCH_CXXFLAGS=${TORCH_CXXFLAGS} -Wno-pedantic")
   set_target_properties(reference_lazy_backend PROPERTIES
           LIBRARY_OUTPUT_DIRECTORY ${LIBRARY_OUTPUT_PATH}
           OUTPUT_NAME ${OUTPUT_NAME}
-          PREFIX "${PYTHON_MODULE_PREFIX}"
-          SUFFIX "${PYTHON_MODULE_EXTENSION}"
           CXX_VISIBILITY_PRESET "hidden"
           COMPILE_FLAGS "${TORCH_CXXFLAGS} -Wno-pedantic"
           )

projects/pt1/python/torch_mlir/csrc/reference_lazy_backend/CMakeLists.txt

@@ -126,3 +126,10 @@ add_mlir_python_modules(TorchMLIRPythonModules
 )
 
 add_dependencies(TorchMLIRPythonModules torch-mlir-opt)
+
+# Some optional PyTorch-extension backed modules are built outside of the
+# AddMLIRPython `declare_mlir_python_extension()` flow, but are still expected to
+# be present in the python package when enabled.
+if(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER)
+  add_dependencies(TorchMLIRPythonModules TorchMLIRJITIRImporterPybind)
+endif()

python/CMakeLists.txt

@@ -7,13 +7,15 @@
 //
 //===----------------------------------------------------------------------===//
 
-#include "mlir/Bindings/Python/PybindAdaptors.h"
+#include <cstdint>
+
+#include "mlir/Bindings/Python/NanobindAdaptors.h"
 #include "torch-mlir-c/Dialects.h"
 #include "torch-mlir-c/Registration.h"
 
-namespace py = pybind11;
+namespace nb = nanobind;
 
-PYBIND11_MODULE(_torchMlir, m) {
+NB_MODULE(_torchMlir, m) {
   torchMlirRegisterAllPasses();
 
   m.doc() = "torch-mlir main python extension";
@@ -27,7 +29,7 @@ PYBIND11_MODULE(_torchMlir, m) {
           mlirDialectHandleLoadDialect(handle, context);
         }
       },
-      py::arg("context"), py::arg("load") = true);
+      nb::arg("context"), nb::arg("load") = true);
 
   m.def("get_int64_max", []() { return INT64_MAX; });