Update llvm, 2025 Q3

.dep-versions

@@ -2,9 +2,9 @@
 # To update JAX version alongside compatible dependency tags, run the following script:
 # python3 .github/workflows/set_dep_versions.py {JAX_version}
 jax=0.6.2
-mhlo=617a9361d186199480c080c9e8c474a5e30c22d1
-llvm=179d30f8c3fddd3c85056fd2b8e877a4a8513158
-enzyme=v0.0.180
+mhlo=1dd2e71331014ae0373f6bf900ce6be393357190
+llvm=f8cb7987c64dcffb72414a40560055cb717dbf74
+enzyme=v0.0.186
 
 # Always remove custom PL/LQ versions before release.
 

.github/workflows/build-wheel-linux-arm64.yaml

@@ -108,6 +108,12 @@ jobs:
         ref: ${{ needs.constants.outputs.llvm_version }}
         path: ${{ github.workspace }}/mlir/llvm-project
 
+    - name: Patch LLVM Source
+      if: steps.cache-mhlo-source.outputs.cache-hit != 'true'
+      run: |
+        cd $GITHUB_WORKSPACE/mlir/llvm-project
+        git apply $GITHUB_WORKSPACE/mlir/patches/llvm-bufferization-segfault.patch
+
     - name: Clone MHLO Submodule
       if: steps.cache-mhlo-source.outputs.cache-hit != 'true'
       uses: actions/checkout@v4
@@ -122,6 +128,7 @@ jobs:
         cd $GITHUB_WORKSPACE/mlir/mlir-hlo
         git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-remove-shardy.patch
         git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-add-back-necessary-passes.patch
+        git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-rename-sort.patch
 
     - name: Clone Enzyme Submodule
       if: steps.cache-enzyme-source.outputs.cache-hit != 'true'
@@ -134,9 +141,8 @@ jobs:
     - name: Patch Enzyme Source
       if: steps.cache-enzyme-source.outputs.cache-hit != 'true'
       run: |
-        export TARGET_FILE=$GITHUB_WORKSPACE/mlir/Enzyme/enzyme/Enzyme/TypeAnalysis/TypeAnalysis.cpp
-        export PATCH_FILE=$GITHUB_WORKSPACE/mlir/patches/enzyme-nvvm-fabs-intrinsics.patch
-        patch -p1 $TARGET_FILE $PATCH_FILE
+        cd $GITHUB_WORKSPACE/mlir/Enzyme
+        git apply $GITHUB_WORKSPACE/mlir/patches/enzyme-nvvm-fabs-intrinsics.patch
 
     # Cache external project builds
     - name: Restore LLVM Build

.github/workflows/build-wheel-linux-x86_64.yaml

@@ -127,6 +127,12 @@ jobs:
         ref: ${{ needs.constants.outputs.llvm_version }}
         path: ${{ github.workspace }}/mlir/llvm-project
 
+    - name: Patch LLVM Source
+      if: steps.cache-mhlo-source.outputs.cache-hit != 'true'
+      run: |
+        cd $GITHUB_WORKSPACE/mlir/llvm-project
+        git apply $GITHUB_WORKSPACE/mlir/patches/llvm-bufferization-segfault.patch
+
     - name: Clone MHLO Submodule
       if: steps.cache-mhlo-source.outputs.cache-hit != 'true'
       uses: actions/checkout@v4
@@ -141,6 +147,7 @@ jobs:
         cd $GITHUB_WORKSPACE/mlir/mlir-hlo
         git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-remove-shardy.patch
         git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-add-back-necessary-passes.patch
+        git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-rename-sort.patch
 
     - name: Clone Enzyme Submodule
       if: steps.cache-enzyme-source.outputs.cache-hit != 'true'
@@ -153,9 +160,8 @@ jobs:
     - name: Patch Enzyme Source
       if: steps.cache-enzyme-source.outputs.cache-hit != 'true'
       run: |
-        export TARGET_FILE=$GITHUB_WORKSPACE/mlir/Enzyme/enzyme/Enzyme/TypeAnalysis/TypeAnalysis.cpp
-        export PATCH_FILE=$GITHUB_WORKSPACE/mlir/patches/enzyme-nvvm-fabs-intrinsics.patch
-        patch -p1 $TARGET_FILE $PATCH_FILE
+        cd $GITHUB_WORKSPACE/mlir/Enzyme
+        git apply $GITHUB_WORKSPACE/mlir/patches/enzyme-nvvm-fabs-intrinsics.patch
 
     # Cache external project builds
     - name: Restore LLVM Build

.github/workflows/build-wheel-macos-arm64.yaml

@@ -113,6 +113,12 @@ jobs:
         ref: ${{ needs.constants.outputs.llvm_version }}
         path: ${{ github.workspace }}/mlir/llvm-project
 
+    - name: Patch LLVM Source
+      if: steps.cache-mhlo-source.outputs.cache-hit != 'true'
+      run: |
+        cd $GITHUB_WORKSPACE/mlir/llvm-project
+        git apply $GITHUB_WORKSPACE/mlir/patches/llvm-bufferization-segfault.patch
+
     - name: Clone MHLO Submodule
       if: steps.cache-mhlo-source.outputs.cache-hit != 'true'
       uses: actions/checkout@v4
@@ -127,6 +133,7 @@ jobs:
         cd $GITHUB_WORKSPACE/mlir/mlir-hlo
         git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-remove-shardy.patch
         git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-add-back-necessary-passes.patch
+        git apply $GITHUB_WORKSPACE/mlir/patches/mhlo-rename-sort.patch
 
     - name: Clone Enzyme Submodule
       if: steps.cache-enzyme-source.outputs.cache-hit != 'true'
@@ -139,9 +146,8 @@ jobs:
     - name: Patch Enzyme Source
       if: steps.cache-enzyme-source.outputs.cache-hit != 'true'
       run: |
-        export TARGET_FILE=$GITHUB_WORKSPACE/mlir/Enzyme/enzyme/Enzyme/TypeAnalysis/TypeAnalysis.cpp
-        export PATCH_FILE=$GITHUB_WORKSPACE/mlir/patches/enzyme-nvvm-fabs-intrinsics.patch
-        patch -p1 $TARGET_FILE $PATCH_FILE
+        cd $GITHUB_WORKSPACE/mlir/Enzyme
+        git apply $GITHUB_WORKSPACE/mlir/patches/enzyme-nvvm-fabs-intrinsics.patch
 
     # Cache external project builds
     - name: Restore LLVM Build

Makefile

@@ -282,6 +282,9 @@ clean-plugin:
 clean-llvm:
 	$(MAKE) -C mlir clean-llvm
 
+reset-llvm:
+	$(MAKE) -C mlir reset-llvm
+
 clean-mhlo:
 	$(MAKE) -C mlir clean-mhlo
 

doc/releases/changelog-dev.md

@@ -12,6 +12,16 @@
 * The JAX version used by Catalyst is updated to 0.6.2.
   [(#1897)](https://github.com/PennyLaneAI/catalyst/pull/1897)
 
+* The version of LLVM, mlir-hlo, and Enzyme used by Catalyst has been updated.
+  [(#1916)](https://github.com/PennyLaneAI/catalyst/pull/1916)
+
+  The LLVM version has been updated to
+  [commit f8cb798](https://github.com/llvm/llvm-project/tree/f8cb7987c64dcffb72414a40560055cb717dbf74).
+  The mlir-hlo version has been updated to
+  [commit 1dd2e71](https://github.com/tensorflow/mlir-hlo/tree/1dd2e71331014ae0373f6bf900ce6be393357190).
+  The Enzyme version has been updated to
+  [v0.0.186](https://github.com/EnzymeAD/Enzyme/releases/tag/v0.0.186).
+
 <h3>Deprecations 👋</h3>
 
 <h3>Bug fixes 🐛</h3>

frontend/catalyst/jax_extras/lowering.py

@@ -16,6 +16,7 @@
 from __future__ import annotations
 
 import logging
+import textwrap
 
 import jax
 from jax._src.dispatch import jaxpr_replicas
@@ -38,6 +39,7 @@
 
 import catalyst
 from catalyst.logging import debug_logger
+from catalyst.utils.exceptions import CompileError
 from catalyst.utils.patching import Patcher
 
 # pylint: disable=protected-access
@@ -165,3 +167,57 @@ def custom_lower_jaxpr_to_module(
                 worklist += [*op.body.operations]
 
     return ctx.module, ctx.context
+
+
+def get_mlir_attribute_from_pyval(value):
+    """
+    Given a value of any type, construct an mlir attribute of corresponding type.
+
+    We set up the context and location outside because recursive calls to this function
+    will segfault if multiple `Context()`s are instantiated.
+    """
+
+    attr = None
+    match value:
+        case bool():
+            attr = ir.BoolAttr.get(value)
+
+        case int():
+            if -9223372036854775808 <= value < 0:  # 2**63
+                attr = ir.IntegerAttr.get(ir.IntegerType.get_signed(64), value)
+            elif 0 <= value < 18446744073709551616:  # = 2**64
+                attr = ir.IntegerAttr.get(ir.IntegerType.get_signless(64), value)
+            else:
+                raise CompileError(
+                    textwrap.dedent(
+                        """
+                    Large interger attributes currently not supported in MLIR,
+                    see https://github.com/llvm/llvm-project/issues/128072
+                    """
+                    )
+                )
+
+        case float():
+            attr = ir.FloatAttr.get(ir.F64Type.get(), value)
+
+        case str():
+            attr = ir.StringAttr.get(value)
+
+        case list() | tuple():
+            element_attrs = [get_mlir_attribute_from_pyval(elem) for elem in value]
+            attr = ir.ArrayAttr.get(element_attrs)
+
+        case dict():
+            named_attrs = {}
+            for k, v in value.items():
+                if not isinstance(k, str):
+                    raise CompileError(
+                        f"Dictionary keys for MLIR DictionaryAttr must be strings, got: {type(k)}"
+                    )
+                named_attrs[k] = get_mlir_attribute_from_pyval(v)
+            attr = ir.DictAttr.get(named_attrs)
+
+        case _:
+            raise CompileError(f"Cannot convert Python type {type(value)} to an MLIR attribute.")
+
+    return attr

frontend/catalyst/jax_primitives_utils.py

@@ -280,7 +280,11 @@ def transform_named_sequence_lowering(jax_ctx: mlir.LoweringRuleContext, pipelin
             for _pass in pipeline:
                 options = _pass.get_options()
                 apply_registered_pass_op = ApplyRegisteredPassOp(
-                    result=transform_mod_type, target=target, pass_name=_pass.name, options=options
+                    result=transform_mod_type,
+                    target=target,
+                    pass_name=_pass.name,
+                    options=options,
+                    dynamic_options={},
                 )
                 target = apply_registered_pass_op.result
             transform_yield_op = YieldOp(operands_=[])  # pylint: disable=unused-variable

frontend/catalyst/passes/pass_api.py

@@ -19,6 +19,7 @@
 
 import pennylane as qml
 
+from catalyst.jax_extras.lowering import get_mlir_attribute_from_pyval
 from catalyst.tracing.contexts import EvaluationContext
 
 PipelineDict: TypeAlias = dict[str, dict[str, str]]
@@ -286,23 +287,18 @@ def __init__(self, name: str, *options: list[str], **valued_options: dict[str, s
 
     def get_options(self):
         """
-        Stringify options according to what mlir-opt expects.
-
-          ApplyRegisteredPassOp expects options to be a single StringAttr
-          which follows the same format as the one used with mlir-opt.
-
-        https://mlir.llvm.org/docs/Dialects/Transform/#transformapply_registered_pass-transformapplyregisteredpassop
-
-          Options passed to a pass are specified via the syntax {option1=value1 option2=value2 ...},
-          i.e., use space-separated key=value pairs for each option.
+        Build a dictionary mapping option names to MLIR attributes.
+        ApplyRegisteredPassOp expects options to be a dictionary from strings to attributes.
+        See https://github.com/llvm/llvm-project/pull/143159
+        """
+        options_dict = {}
+        for option in self.options:
+            options_dict[str(option)] = get_mlir_attribute_from_pyval(True)
 
-        https://mlir.llvm.org/docs/Tutorials/MlirOpt/#running-a-pass-with-options
+        for option, value in self.valued_options.items():
+            options_dict[str(option)] = get_mlir_attribute_from_pyval(value)
 
-        Experimentally we found that single-options also work without values.
-        """
-        retval = " ".join(f"{str(option)}" for option in self.options)
-        retval2 = " ".join(f"{str(key)}={str(value)}" for key, value in self.valued_options.items())
-        return " ".join([retval, retval2]).strip()
+        return options_dict
 
     def __repr__(self):
         return (

frontend/test/lit/test_mlir_plugin.py

@@ -106,7 +106,7 @@ def test_pass_options():
     """Is the option in the generated MLIR?"""
 
     @qjit(target="mlir")
-    # CHECK: options = "an-option maxValue=1"
+    # CHECK: options = {"an-option" = true, "maxValue" = 1 : i64}
     @catalyst.passes.apply_pass("some-pass", "an-option", maxValue=1)
     @qml.qnode(qml.device("null.qubit", wires=1))
     def example():