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[MLIR][Python] Python binding support for AffineIfOp (#108323)
Fix the AffineIfOp's default builder such that it takes in an IntegerSetAttr. AffineIfOp has skipDefaultBuilders=1 which effectively skips the creation of the default AffineIfOp::builder on the C++ side. (AffineIfOp has two custom OpBuilder defined in the extraClassDeclaration.) However, on the python side, _affine_ops_gen.py shows that the default builder is being created, but it does not accept IntegerSet and thus is useless. This fix at line 411 makes the default python AffineIfOp builder take in an IntegerSet input and does not impact the C++ side of things.
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@ -407,7 +407,8 @@ def AffineIfOp : Affine_Op<"if",
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}
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```
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}];
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let arguments = (ins Variadic<AnyType>);
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let arguments = (ins Variadic<AnyType>,
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IntegerSetAttr:$condition);
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let results = (outs Variadic<AnyType>:$results);
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let regions = (region SizedRegion<1>:$thenRegion, AnyRegion:$elseRegion);
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@ -558,6 +558,15 @@ CPred<"::llvm::isa<::mlir::AffineMapAttr>($_self)">, "AffineMap attribute"> {
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let constBuilderCall = "::mlir::AffineMapAttr::get($0)";
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}
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// Attributes containing integer sets.
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def IntegerSetAttr : Attr<
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CPred<"::llvm::isa<::mlir::IntegerSetAttr>($_self)">, "IntegerSet attribute"> {
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let storageType = [{::mlir::IntegerSetAttr }];
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let returnType = [{ ::mlir::IntegerSet }];
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let valueType = NoneType;
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let constBuilderCall = "::mlir::IntegerSetAttr::get($0)";
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}
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// Base class for array attributes.
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class ArrayAttrBase<Pred condition, string summary> : Attr<condition, summary> {
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let storageType = [{ ::mlir::ArrayAttr }];
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@ -156,3 +156,61 @@ def for_(
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yield iv, iter_args[0]
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else:
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yield iv
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@_ods_cext.register_operation(_Dialect, replace=True)
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class AffineIfOp(AffineIfOp):
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"""Specialization for the Affine if op class."""
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def __init__(
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self,
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cond: IntegerSet,
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results_: Optional[Type] = None,
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*,
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cond_operands: Optional[_VariadicResultValueT] = None,
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has_else: bool = False,
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loc=None,
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ip=None,
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):
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"""Creates an Affine `if` operation.
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- `cond` is the integer set used to determine which regions of code
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will be executed.
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- `results` are the list of types to be yielded by the operand.
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- `cond_operands` is the list of arguments to substitute the
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dimensions, then symbols in the `cond` integer set expression to
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determine whether they are in the set.
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- `has_else` determines whether the affine if operation has the else
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branch.
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"""
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if results_ is None:
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results_ = []
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if cond_operands is None:
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cond_operands = []
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if cond.n_inputs != len(cond_operands):
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raise ValueError(
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f"expected {cond.n_inputs} condition operands, got {len(cond_operands)}"
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)
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operands = []
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operands.extend(cond_operands)
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results = []
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results.extend(results_)
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super().__init__(results, cond_operands, cond)
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self.regions[0].blocks.append(*[])
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if has_else:
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self.regions[1].blocks.append(*[])
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@property
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def then_block(self) -> Block:
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"""Returns the then block of the if operation."""
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return self.regions[0].blocks[0]
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@property
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def else_block(self) -> Optional[Block]:
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"""Returns the else block of the if operation."""
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if len(self.regions[1].blocks) == 0:
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return None
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return self.regions[1].blocks[0]
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@ -263,3 +263,73 @@ def testForSugar():
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add = arith.addi(i, i)
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memref.store(add, it, [i])
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affine.yield_([it])
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# CHECK-LABEL: TEST: testAffineIfWithoutElse
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@constructAndPrintInModule
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def testAffineIfWithoutElse():
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index = IndexType.get()
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i32 = IntegerType.get_signless(32)
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d0 = AffineDimExpr.get(0)
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# CHECK: #[[$SET0:.*]] = affine_set<(d0) : (d0 - 5 >= 0)>
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cond = IntegerSet.get(1, 0, [d0 - 5], [False])
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# CHECK-LABEL: func.func @simple_affine_if(
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# CHECK-SAME: %[[VAL_0:.*]]: index) {
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# CHECK: affine.if #[[$SET0]](%[[VAL_0]]) {
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# CHECK: %[[VAL_1:.*]] = arith.constant 1 : i32
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# CHECK: %[[VAL_2:.*]] = arith.addi %[[VAL_1]], %[[VAL_1]] : i32
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# CHECK: }
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# CHECK: return
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# CHECK: }
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@func.FuncOp.from_py_func(index)
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def simple_affine_if(cond_operands):
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if_op = affine.AffineIfOp(cond, cond_operands=[cond_operands])
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with InsertionPoint(if_op.then_block):
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one = arith.ConstantOp(i32, 1)
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add = arith.AddIOp(one, one)
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affine.AffineYieldOp([])
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return
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# CHECK-LABEL: TEST: testAffineIfWithElse
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@constructAndPrintInModule
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def testAffineIfWithElse():
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index = IndexType.get()
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i32 = IntegerType.get_signless(32)
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d0 = AffineDimExpr.get(0)
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# CHECK: #[[$SET0:.*]] = affine_set<(d0) : (d0 - 5 >= 0)>
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cond = IntegerSet.get(1, 0, [d0 - 5], [False])
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# CHECK-LABEL: func.func @simple_affine_if_else(
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# CHECK-SAME: %[[VAL_0:.*]]: index) {
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# CHECK: %[[VAL_IF:.*]]:2 = affine.if #[[$SET0]](%[[VAL_0]]) -> (i32, i32) {
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# CHECK: %[[VAL_XT:.*]] = arith.constant 0 : i32
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# CHECK: %[[VAL_YT:.*]] = arith.constant 1 : i32
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# CHECK: affine.yield %[[VAL_XT]], %[[VAL_YT]] : i32, i32
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# CHECK: } else {
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# CHECK: %[[VAL_XF:.*]] = arith.constant 2 : i32
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# CHECK: %[[VAL_YF:.*]] = arith.constant 3 : i32
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# CHECK: affine.yield %[[VAL_XF]], %[[VAL_YF]] : i32, i32
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# CHECK: }
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# CHECK: %[[VAL_ADD:.*]] = arith.addi %[[VAL_IF]]#0, %[[VAL_IF]]#1 : i32
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# CHECK: return
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# CHECK: }
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@func.FuncOp.from_py_func(index)
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def simple_affine_if_else(cond_operands):
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if_op = affine.AffineIfOp(
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cond, [i32, i32], cond_operands=[cond_operands], has_else=True
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)
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with InsertionPoint(if_op.then_block):
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x_true = arith.ConstantOp(i32, 0)
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y_true = arith.ConstantOp(i32, 1)
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affine.AffineYieldOp([x_true, y_true])
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with InsertionPoint(if_op.else_block):
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x_false = arith.ConstantOp(i32, 2)
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y_false = arith.ConstantOp(i32, 3)
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affine.AffineYieldOp([x_false, y_false])
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add = arith.AddIOp(if_op.results[0], if_op.results[1])
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return
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