Bump llvm-project to 5b2e7f50a6798fd9b9c79d9d62fdebcd9e78525b. (#260)

.gitignore

@@ -3,7 +3,8 @@
 .env
 *.code-workspace
 
-build
+/build
+/build_*
 build-mlir
 install-mlir
 __pycache__

external/llvm-project

@@ -1 +1 @@
-Subproject commit 310c9496d80961188e8d8f8ad306cdf44bd7541f
+Subproject commit 5b2e7f50a6798fd9b9c79d9d62fdebcd9e78525b

frontends/pytorch/csrc/builder/func_builder.cpp

@@ -33,7 +33,7 @@ FuncBuilder::createFunction(FuncBuilder::Inserter &inserter,
                       context, mlirStringRefCreate(name.data(), name.size()))));
 
   MlirOperationState state =
-      mlirOperationStateGet(toMlirStringRef("func"), location);
+      mlirOperationStateGet(toMlirStringRef("builtin.func"), location);
   mlirOperationStateAddAttributes(&state, funcAttrs.size(), funcAttrs.data());
   {
     // Don't access these once ownership transferred.

frontends/pytorch/csrc/builder/function_importer.cpp

@@ -34,7 +34,7 @@ MlirOperation torch_mlir::importJitFunctionAsFuncOp(
   MlirAttribute symNameAttr = mlirStringAttrGet(
       context, toMlirStringRef(function->qualname().qualifiedName()));
   MlirOperation func = createMlirOperation(
-      "func", loc, mlirRegionCreate(),
+      "builtin.func", loc, mlirRegionCreate(),
       toMlirNamedAttribute("type", mlirTypeAttrGet(functionType)),
       toMlirNamedAttribute("sym_name", symNameAttr));
   std::vector<MlirAttribute> argAttrDicts;

python/npcomp/compiler/generic/backend/refjit.py

@@ -8,9 +8,9 @@ import platform
 _refjit = None
 
 BACKEND_PASSES = (
-    "func(convert-scf-to-std)",
-    "func(canonicalize)",
-    "func(tcf-shape-refinement)",
+    "builtin.func(convert-scf-to-std)",
+    "builtin.func(canonicalize)",
+    "builtin.func(tcf-shape-refinement)",
 )
 
 

python/npcomp/compiler/numpy/backend/iree.py

@@ -16,10 +16,10 @@ __all__ = [
 ]
 
 FRONTEND_PASSES = (
-    "func(basicpy-type-inference)",
-    "func(convert-basicpy-to-std)",
-    "func(canonicalize)",
-    "func(convert-scf-to-std)",
+    "builtin.func(basicpy-type-inference)",
+    "builtin.func(convert-basicpy-to-std)",
+    "builtin.func(canonicalize)",
+    "builtin.func(convert-scf-to-std)",
 )
 
 _ireert = None

python/npcomp/compiler/numpy/backend/refjit.py

@@ -15,12 +15,12 @@ __all__ = [
 ]
 
 FRONTEND_PASSES = (
-    "func(npcomp-cpa-type-inference)",
+    "builtin.func(npcomp-cpa-type-inference)",
     "numpy-public-functions-to-tensor",
-    "func(convert-numpy-to-tcf)",
-    "func(convert-scf-to-std)",
-    "func(canonicalize)",
-    "func(tcf-shape-refinement)",
+    "builtin.func(convert-numpy-to-tcf)",
+    "builtin.func(convert-scf-to-std)",
+    "builtin.func(canonicalize)",
+    "builtin.func(tcf-shape-refinement)",
 )
 
 # Re-export.

python/npcomp/compiler/utils/mlir_utils.py

@@ -6,6 +6,7 @@
 from typing import Optional, Tuple
 
 from mlir import ir as _ir
+from mlir.dialects import builtin as builtin_ops
 from npcomp import _cext
 
 __all__ = [
@@ -96,19 +97,18 @@ class ImportContext:
              create_entry_block: bool) -> Tuple[_ir.Operation, _ir.Block]:
     """Creates a |func| op.
 
-    TODO: This should really be in the MLIR API.
     Returns:
       (operation, entry_block)
     """
-    with self.context, self.loc:
-      attrs = {
-          "type": _ir.TypeAttr.get(func_type),
-          "sym_name": _ir.StringAttr.get(name),
-      }
-      op = _ir.Operation.create("func", regions=1, attributes=attrs, ip=self.ip)
-      body_region = op.regions[0]
-      entry_block = body_region.blocks.append(*func_type.inputs)
-      return op, entry_block
+    assert self.loc is not None
+    # TODO: Fix upstream FuncOp constructor to not require an implicit
+    # context.
+    with self.context:
+      func = builtin_ops.FuncOp(name, func_type, loc=self.loc, ip=self.ip)
+    entry_block = None
+    if create_entry_block:
+      entry_block = func.add_entry_block()
+    return (func, entry_block)
 
   def basicpy_ExecOp(self):
     """Creates a basicpy.exec op.

test/Dialect/Torch/invalid.mlir

@@ -4,7 +4,7 @@
 
 torch.class_type @c {}
 %0 = torch.nn_module {
-  // expected-error @+1 {{'func' op is not allowed inside 'torch.nn_module'}}
+  // expected-error @+1 {{'builtin.func' op is not allowed inside 'torch.nn_module'}}
   func @f()
 } : !torch.nn.Module<"c">
 
@@ -32,7 +32,7 @@ torch.class_type @c {
 // -----
 
 torch.class_type @c {
-  // expected-error @+1 {{'func' op is not allowed inside `torch.class_type`}}
+  // expected-error @+1 {{'builtin.func' op is not allowed inside `torch.class_type`}}
   func @f()
 }