[AutoBump] Merge with 09af3b6 (Jan 14)

CMakeLists.txt

@@ -43,6 +43,12 @@ option(TORCH_MLIR_ENABLE_STABLEHLO "Add stablehlo dialect" ON)
 if(TORCH_MLIR_ENABLE_STABLEHLO)
   add_definitions(-DTORCH_MLIR_ENABLE_STABLEHLO)
 endif()
+# It is possible that both stablehlo and torch_mlir projects are used in some compiler project.
+# In this case, we don't want to use stablehlo that is downloaded by torch_mlir (in external/stablehlo)
+# folder but instead want to use stablehlo that is part of top level compiler project.
+# With TORCH_MLIR_USE_EXTERNAL_STABLEHLO enables, it is assumed that top level compiler project makes
+# stablehlo targets AND includes available (for example with `add_subdirectory` and `include_directories`).
+option(TORCH_MLIR_USE_EXTERNAL_STABLEHLO "Use stablehlo from top level project" OFF)
 
 option(TORCH_MLIR_OUT_OF_TREE_BUILD "Specifies an out of tree build" OFF)
 
@@ -142,7 +148,8 @@ include_directories(${CMAKE_CURRENT_BINARY_DIR}/include)
 
 function(torch_mlir_target_includes target)
   set(_dirs
-    $<BUILD_INTERFACE:${MLIR_INCLUDE_DIRS}>
+    $<BUILD_INTERFACE:${MLIR_INCLUDE_DIR}>
+    $<BUILD_INTERFACE:${MLIR_GENERATED_INCLUDE_DIR}>
     $<BUILD_INTERFACE:${TORCH_MLIR_SOURCE_DIR}/include>
     $<BUILD_INTERFACE:${TORCH_MLIR_BINARY_DIR}/include>
   )
@@ -232,7 +239,8 @@ endif()
 # Getting this wrong results in building large parts of the stablehlo
 # project that we don't actually depend on. Further some of those parts
 # do not even compile on all platforms.
-if (TORCH_MLIR_ENABLE_STABLEHLO)
+# Only configure StableHLO if it isn't provided from a top-level project
+if (TORCH_MLIR_ENABLE_STABLEHLO AND NOT TORCH_MLIR_USE_EXTERNAL_STABLEHLO)
   set(STABLEHLO_BUILD_EMBEDDED ON)
   set(STABLEHLO_ENABLE_BINDINGS_PYTHON ON)
   add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/externals/stablehlo

include/torch-mlir/Dialect/Torch/IR/TorchOps.td

@@ -1361,6 +1361,15 @@ def Torch_SymbolicIntOp : Torch_Op<"symbolic_int", [Pure]> {
     %0 = torch.symbolic_int "s0" {min_val = 5, max_val = 10} : !torch.int
     %1 = torch.symbolic_int "s1" {min_val = 2, max_val = 20} : !torch.int
     ```
+
+    In this case, we see that `s0` has the range [5, 10] and `s1` has the
+    range [2, 20]. When unspecified, the range constraints feeding in from
+    TorchDynamo default to [0, INT_MAX] (or [2, INT_MAX] in older PyTorch
+    releases). In either case, the interpretation (as specified by TorchDynamo)
+    is that the dynamic dimension is assumed to be not 0 or 1. This is not a
+    bug, and does not necessarily mean that the exported program will not work
+    for dimensions 0 or 1. For an in-depth discussion of this topic, see
+    [The 0/1 Specialization Problem](https://docs.google.com/document/d/16VPOa3d-Liikf48teAOmxLc92rgvJdfosIy-yoT38Io/edit?fbclid=IwAR3HNwmmexcitV0pbZm_x1a4ykdXZ9th_eJWK-3hBtVgKnrkmemz6Pm5jRQ#heading=h.ez923tomjvyk).
   }];
   let arguments = (ins
     StrAttr:$symbol_name,