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@BogdanDragosV BogdanDragosV commented Nov 18, 2025

ODS generate code can be included and used outside of the mlir namespace and so references
to symbols in the mlir namespace must be fully qualified.

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@BogdanDragosV BogdanDragosV marked this pull request as ready for review November 18, 2025 14:01
@llvmbot llvmbot added mlir:core MLIR Core Infrastructure mlir mlir:ods labels Nov 18, 2025
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llvmbot commented Nov 18, 2025

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Author: None (BogdanDragosV)

Changes

In some cases, using clang compiler with restrictive setting, Attribute alone can be seen as ambiguous, generating errors for methods that are generated. Adding the proper namespace solves the issue.


Full diff: https://github.com/llvm/llvm-project/pull/168536.diff

1 Files Affected:

  • (modified) mlir/include/mlir/IR/Properties.td (+3-3)
diff --git a/mlir/include/mlir/IR/Properties.td b/mlir/include/mlir/IR/Properties.td
index a7ade0675b9bb..2830ba96fb787 100644
--- a/mlir/include/mlir/IR/Properties.td
+++ b/mlir/include/mlir/IR/Properties.td
@@ -468,7 +468,7 @@ class ArrayProp<Property elem = Property<>, string newSummary = ""> :
       return $_diag() << "expected array attribute";
     for (::mlir::Attribute elemAttr : arrayAttr) {
       }] # _makePropStorage<elem, "elemVal">.ret # [{
-      auto elemRes = [&](Attribute propAttr, }] # elem.storageType # [{& propStorage) -> ::mlir::LogicalResult {
+      auto elemRes = [&](::mlir::Attribute propAttr, }] # elem.storageType # [{& propStorage) -> ::mlir::LogicalResult {
         }] # !subst("$_attr", "propAttr",
           !subst("$_storage", "propStorage", elem.convertFromAttribute)) # [{
       }(elemAttr, elemVal);
@@ -480,7 +480,7 @@ class ArrayProp<Property elem = Property<>, string newSummary = ""> :
   }];
 
   let convertToAttribute = [{
-    SmallVector<Attribute> elems;
+    SmallVector<::mlir::Attribute> elems;
     for (const auto& elemVal : $_storage) {
       auto elemAttr = [&](const }] # elem.storageType #[{& propStorage) -> ::mlir::Attribute {
         }] # !subst("$_storage", "propStorage", elem.convertToAttribute) # [{
@@ -647,7 +647,7 @@ class OptionalProp<Property p, bit canDelegateParsing = 1>
     }
     ::mlir::Attribute presentAttr = arrayAttr[0];
     }] # _makePropStorage<p, "presentVal">.ret # [{
-    auto presentRes = [&](Attribute propAttr, }] # p.storageType # [{& propStorage) -> ::mlir::LogicalResult {
+    auto presentRes = [&](::mlir::Attribute propAttr, }] # p.storageType # [{& propStorage) -> ::mlir::LogicalResult {
       }] # !subst("$_storage", "propStorage",
           !subst("$_attr", "propAttr", p.convertFromAttribute)) # [{
     }(presentAttr, presentVal);

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In some cases, using clang compiler with restrictive setting,

What kind of "restrictive setting" are you referring to here? Can you share the error you're seeing?

We should always fully qualify namespace in generic ODS because downstream can define dialects outside of the mlir namespace, but I'm not sure if this is what you're referring to here?

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Can you share the error you're seeing?

For our particular use case we've hit this error:

ops.cpp.inc:904:27: error: unknown type name 'Attribute'
904 | auto presentRes = [&](Attribute propAttr, int64_t& propStorage) -> ::mlir::LogicalResult {
| ^

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Right, that seems like the case I was describing where your dialect isn't nested under the mlir:: namespace, I don't see what "restrictive setting" specific to clang is involved though.

So unless I'm missing something, I'll update the PR title/description to reflect this!

@joker-eph joker-eph changed the title [mlir] Fix ambiguous attribute for properties [MLIR][ODS] Fully qualify namespace for mlir::Attribute in ODS generated code Nov 19, 2025
@joker-eph joker-eph enabled auto-merge (squash) November 19, 2025 12:57
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🐧 Linux x64 Test Results

  • 7096 tests passed
  • 594 tests skipped

@joker-eph joker-eph merged commit 655662e into llvm:main Nov 19, 2025
16 checks passed
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@BogdanDragosV Congratulations on having your first Pull Request (PR) merged into the LLVM Project!

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llvm-ci commented Nov 19, 2025

LLVM Buildbot has detected a new failure on builder mlir-nvidia-gcc7 running on mlir-nvidia while building mlir at step 7 "test-build-check-mlir-build-only-check-mlir".

Full details are available at: https://lab.llvm.org/buildbot/#/builders/116/builds/21187

Here is the relevant piece of the build log for the reference
Step 7 (test-build-check-mlir-build-only-check-mlir) failure: test (failure)
******************** TEST 'MLIR :: Integration/GPU/CUDA/async.mlir' FAILED ********************
Exit Code: 1

Command Output (stdout):
--
# RUN: at line 1
/vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.src/mlir/test/Integration/GPU/CUDA/async.mlir  | /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -gpu-kernel-outlining  | /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm),nvvm-attach-target)'  | /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -gpu-async-region -gpu-to-llvm -reconcile-unrealized-casts -gpu-module-to-binary="format=fatbin"  | /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -async-to-async-runtime -async-runtime-ref-counting  | /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -convert-async-to-llvm -convert-func-to-llvm -convert-arith-to-llvm -convert-cf-to-llvm -reconcile-unrealized-casts  | /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-runner    --shared-libs=/vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/lib/libmlir_cuda_runtime.so    --shared-libs=/vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/lib/libmlir_async_runtime.so    --shared-libs=/vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/lib/libmlir_runner_utils.so    --entry-point-result=void -O0  | /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/FileCheck /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.src/mlir/test/Integration/GPU/CUDA/async.mlir
# executed command: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.src/mlir/test/Integration/GPU/CUDA/async.mlir
# executed command: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -gpu-kernel-outlining
# executed command: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt '-pass-pipeline=builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm),nvvm-attach-target)'
# executed command: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -gpu-async-region -gpu-to-llvm -reconcile-unrealized-casts -gpu-module-to-binary=format=fatbin
# executed command: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -async-to-async-runtime -async-runtime-ref-counting
# executed command: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-opt -convert-async-to-llvm -convert-func-to-llvm -convert-arith-to-llvm -convert-cf-to-llvm -reconcile-unrealized-casts
# executed command: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/mlir-runner --shared-libs=/vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/lib/libmlir_cuda_runtime.so --shared-libs=/vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/lib/libmlir_async_runtime.so --shared-libs=/vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/lib/libmlir_runner_utils.so --entry-point-result=void -O0
# .---command stderr------------
# | 'cuStreamWaitEvent(stream, event, 0)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuEventDestroy(event)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuStreamWaitEvent(stream, event, 0)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuEventDestroy(event)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuStreamWaitEvent(stream, event, 0)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuStreamWaitEvent(stream, event, 0)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuEventDestroy(event)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuEventDestroy(event)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuEventSynchronize(event)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# | 'cuEventDestroy(event)' failed with 'CUDA_ERROR_CONTEXT_IS_DESTROYED'
# `-----------------------------
# executed command: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.obj/bin/FileCheck /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.src/mlir/test/Integration/GPU/CUDA/async.mlir
# .---command stderr------------
# | /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.src/mlir/test/Integration/GPU/CUDA/async.mlir:68:12: error: CHECK: expected string not found in input
# |  // CHECK: [84, 84]
# |            ^
# | <stdin>:1:1: note: scanning from here
# | Unranked Memref base@ = 0x55e6d1da81b0 rank = 1 offset = 0 sizes = [2] strides = [1] data = 
# | ^
# | <stdin>:2:1: note: possible intended match here
# | [42, 42]
# | ^
# | 
# | Input file: <stdin>
# | Check file: /vol/worker/mlir-nvidia/mlir-nvidia-gcc7/llvm.src/mlir/test/Integration/GPU/CUDA/async.mlir
# | 
# | -dump-input=help explains the following input dump.
# | 
# | Input was:
# | <<<<<<
# |             1: Unranked Memref base@ = 0x55e6d1da81b0 rank = 1 offset = 0 sizes = [2] strides = [1] data =  
# | check:68'0     X~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ error: no match found
# |             2: [42, 42] 
# | check:68'0     ~~~~~~~~~
# | check:68'1     ?         possible intended match
...

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