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[MLIR][Python] Pass OpView subclasses instead of Operation in rewrite patterns (#163080)
This is a follow-up PR for #162699. Currently, in the function where we define rewrite patterns, the `op` we receive is of type `ir.Operation` rather than a specific `OpView` type (such as `arith.AddIOp`). This means we can’t conveniently access certain parts of the operation — for example, we need to use `op.operands[0]` instead of `op.lhs`. The following example code illustrates this situation. ```python def to_muli(op, rewriter): # op is typed ir.Operation instead of arith.AddIOp pass patterns.add(arith.AddIOp, to_muli) ``` In this PR, we convert the operation to its corresponding `OpView` subclass before invoking the rewrite pattern callback, making it much easier to write patterns. --------- Co-authored-by: Maksim Levental <maksim.levental@gmail.com>
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@@ -197,7 +197,12 @@ public:
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MlirPatternRewriter rewriter,
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void *userData) -> MlirLogicalResult {
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nb::handle f(static_cast<PyObject *>(userData));
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nb::object res = f(op, PyPatternRewriter(rewriter));
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PyMlirContextRef ctx =
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PyMlirContext::forContext(mlirOperationGetContext(op));
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nb::object opView = PyOperation::forOperation(ctx, op)->createOpView();
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nb::object res = f(opView, PyPatternRewriter(rewriter));
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return logicalResultFromObject(res);
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};
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MlirRewritePattern pattern = mlirOpRewritePattenCreate(
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@@ -92,7 +92,7 @@ class ConstantOp(ConstantOp):
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@property
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def value(self):
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return Attribute(self.operation.attributes["value"])
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return self.operation.attributes["value"]
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@property
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def literal_value(self) -> Union[int, float]:
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@@ -17,15 +17,16 @@ def run(f):
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def testRewritePattern():
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def to_muli(op, rewriter):
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with rewriter.ip:
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new_op = arith.muli(op.operands[0], op.operands[1], loc=op.location)
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assert isinstance(op, arith.AddIOp)
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new_op = arith.muli(op.lhs, op.rhs, loc=op.location)
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rewriter.replace_op(op, new_op.owner)
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def constant_1_to_2(op, rewriter):
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c = op.attributes["value"].value
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c = op.value.value
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if c != 1:
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return True # failed to match
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with rewriter.ip:
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new_op = arith.constant(op.result.type, 2, loc=op.location)
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new_op = arith.constant(op.type, 2, loc=op.location)
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rewriter.replace_op(op, [new_op])
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with Context():
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