[MLIR][Linalg] Ternary Op & Linalg select #91461
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@llvm/pr-subscribers-mlir @llvm/pr-subscribers-mlir-core Author: Petr Kurapov (kurapov-peter) ChangesFollowing #90236, adding Full diff: https://github.com/llvm/llvm-project/pull/91461.diff 11 Files Affected:
diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgBase.td b/mlir/include/mlir/Dialect/Linalg/IR/LinalgBase.td
index e87e8b5600107..73f984dc072d3 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgBase.td
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgBase.td
@@ -68,6 +68,9 @@ def UnaryFnAttr : EnumAttr<Linalg_Dialect, UnaryFn, "unary_fn"> {
def BinaryFnAttr : EnumAttr<Linalg_Dialect, BinaryFn, "binary_fn"> {
let assemblyFormat = "`<` $value `>`";
}
+def TernaryFnAttr : EnumAttr<Linalg_Dialect, TernaryFn, "ternary_fn"> {
+ let assemblyFormat = "`<` $value `>`";
+}
def TypeFnAttr : EnumAttr<Linalg_Dialect, TypeFn, "type_fn"> {
let assemblyFormat = "`<` $value `>`";
}
diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgEnums.td b/mlir/include/mlir/Dialect/Linalg/IR/LinalgEnums.td
index 6b4b073fc6724..e615876a95d05 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgEnums.td
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgEnums.td
@@ -49,6 +49,12 @@ def BinaryFn : I32EnumAttr<"BinaryFn", "", [
let genSpecializedAttr = 0;
let cppNamespace = "::mlir::linalg";
}
+def TernaryFn : I32EnumAttr<"TernaryFn", "", [
+ I32EnumAttrCase<"select", 0>
+]> {
+ let genSpecializedAttr = 0;
+ let cppNamespace = "::mlir::linalg";
+}
def TypeFn : I32EnumAttr<"TypeFn", "", [
I32EnumAttrCase<"cast_signed", 0>,
I32EnumAttrCase<"cast_unsigned", 1>
diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml b/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
index 584bfcd8b59dc..eb7dd37010a67 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
@@ -1008,6 +1008,63 @@ structured_op: !LinalgStructuredOpConfig
- !ScalarExpression
scalar_arg: rhs
--- !LinalgOpConfig
+metadata: !LinalgOpMetadata
+ name: select
+ cpp_class_name: SelectOp
+ doc: |-
+ Chooses one value based on a binary condition supplied as its first operand.
+
+ The shapes and element types must be identical. The appropriate casts,
+ broadcasts and reductions should be done previously to calling this op.
+
+ This means reduction/broadcast/element cast semantics is explicit. Further
+ passes can take that into account when lowering this code. For example,
+ a `linalg.broadcast` + `linalg.select` sequence can be lowered to a
+ `linalg.generic` with different affine maps for the two operands.
+structured_op: !LinalgStructuredOpConfig
+ args:
+ - !LinalgOperandDefConfig
+ name: cond
+ kind: input_tensor
+ type_var: U
+ shape_map: affine_map<() -> ()>
+ - !LinalgOperandDefConfig
+ name: lhs
+ kind: input_tensor
+ type_var: T1
+ shape_map: affine_map<() -> ()>
+ - !LinalgOperandDefConfig
+ name: rhs
+ kind: input_tensor
+ type_var: T1
+ shape_map: affine_map<() -> ()>
+ - !LinalgOperandDefConfig
+ name: O
+ kind: output_tensor
+ type_var: T1
+ shape_map: affine_map<() -> ()>
+ indexing_maps: !LinalgIndexingMapsConfig
+ static_indexing_maps:
+ - affine_map<() -> ()>
+ - affine_map<() -> ()>
+ - affine_map<() -> ()>
+ - affine_map<() -> ()>
+ iterator_types: []
+ assignments:
+ - !ScalarAssign
+ arg: O
+ value: !ScalarExpression
+ scalar_fn:
+ kind: ternary
+ fn_name: select
+ operands:
+ - !ScalarExpression
+ scalar_arg: cond
+ - !ScalarExpression
+ scalar_arg: lhs
+ - !ScalarExpression
+ scalar_arg: rhs
+--- !LinalgOpConfig
metadata: !LinalgOpMetadata
name: matmul
cpp_class_name: MatmulOp
diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
index e5f83331baf81..6a5f25a7605f1 100644
--- a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
+++ b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
@@ -492,6 +492,25 @@ class RegionBuilderHelper {
llvm_unreachable("unsupported binary function");
}
+ // Build the ternary functions defined by OpDSL.
+ Value buildTernaryFn(TernaryFn ternaryFn, Value arg0, Value arg1,
+ Value arg2) {
+ bool headBool =
+ isInteger(arg0) && arg0.getType().getIntOrFloatBitWidth() == 1;
+ bool tailFloatingPoint =
+ isFloatingPoint(arg0) && isFloatingPoint(arg1) && isFloatingPoint(arg2);
+ bool tailInteger = isInteger(arg0) && isInteger(arg1) && isInteger(arg1);
+ OpBuilder::InsertionGuard g(builder);
+ builder.setInsertionPointToEnd(&block);
+ switch (ternaryFn) {
+ case TernaryFn::select:
+ if (!headBool && !(tailFloatingPoint || tailInteger))
+ llvm_unreachable("unsupported non numeric type");
+ return builder.create<arith::SelectOp>(arg0.getLoc(), arg0, arg1, arg2);
+ }
+ llvm_unreachable("unsupported ternary function");
+ }
+
// Build the type functions defined by OpDSL.
Value buildTypeFn(TypeFn typeFn, Type toType, Value operand) {
switch (typeFn) {
diff --git a/mlir/python/mlir/dialects/linalg/opdsl/lang/comprehension.py b/mlir/python/mlir/dialects/linalg/opdsl/lang/comprehension.py
index bb43ebf2b6923..880dcb7250b96 100644
--- a/mlir/python/mlir/dialects/linalg/opdsl/lang/comprehension.py
+++ b/mlir/python/mlir/dialects/linalg/opdsl/lang/comprehension.py
@@ -262,7 +262,8 @@ def __repr__(self):
class FunctionKind(Enum):
UNARY = 0
BINARY = 1
- TYPE = 2
+ TERNARY = 2
+ TYPE = 3
class UnaryFnType:
@@ -339,6 +340,30 @@ class BinaryFn:
powf = BinaryFnType("powf")
+class TernaryFnType:
+ """Ternary function.
+
+ A bterary function takes three tensor expressions and returns the
+ function evaluation result.
+ """
+
+ def __init__(self, fn_name: str):
+ self.fn_name = fn_name
+
+ def __call__(self, arg0: TensorExpression, arg1: TensorExpression, arg2: TensorExpression) -> "TensorFn":
+ return TensorFn(FunctionKind.TERNARY, self.fn_name, None, None, [arg0, arg1, arg2])
+
+ def __repr__(self):
+ return f"{self.fn_name}"
+
+
+class TernaryFn:
+ """Ternary function namespace.
+ """
+
+ select = TernaryFnType("select")
+
+
class TypeFnType:
"""Type conversion function.
@@ -437,7 +462,8 @@ class OperandKind(Enum):
INDEX_ATTR = 3
UNARY_FN_ATTR = 4
BINARY_FN_ATTR = 5
- TYPE_FN_ATTR = 6
+ TERNARY_FN_ATTR = 6
+ TYPE_FN_ATTR = 7
class OperandDef:
@@ -489,6 +515,7 @@ def is_attribute(self) -> bool:
self.kind == OperandKind.INDEX_ATTR
or self.kind == OperandKind.UNARY_FN_ATTR
or self.kind == OperandKind.BINARY_FN_ATTR
+ or self.kind == OperandKind.TERNARY_FN_ATTR
or self.kind == OperandKind.TYPE_FN_ATTR
)
@@ -670,6 +697,31 @@ def __getitem__(self, reduce_dims: Tuple[DimDef]) -> ReduceFnUse:
return ReduceFnUse(None, self, *reduce_dims)
+class TernaryFnAttrDef:
+ """Ternary function attribute definition.
+
+ Ternary function attributes provide a way to make the arithmetic computation
+ parametrizable. Every attribute specifies a default Ternary function
+ that may be overwritten at operation instantiation time.
+ """
+
+ def __init__(self, default: "TernaryFnType"):
+ if not isinstance(default, TernaryFnType):
+ raise ValueError(
+ f"TernaryFnAttrDef requires default of type TernaryFnType "
+ f"but got {default}"
+ )
+ self.operand_def = OperandDef(
+ OperandKind.TERNARY_FN_ATTR, default_fn=default.fn_name
+ )
+
+ def __call__(self, arg0: TensorExpression, arg1: TensorExpression) -> TensorFn:
+ return TensorFn(FunctionKind.TERNARY, None, self.operand_def, None, [arg0, arg1])
+
+ def __getitem__(self, reduce_dims: Tuple[DimDef]) -> ReduceFnUse:
+ return ReduceFnUse(None, self, *reduce_dims)
+
+
class TypeFnAttrDef:
"""Type conversion function attribute definition.
diff --git a/mlir/python/mlir/dialects/linalg/opdsl/lang/emitter.py b/mlir/python/mlir/dialects/linalg/opdsl/lang/emitter.py
index f91fc8b716008..845b533db52a9 100644
--- a/mlir/python/mlir/dialects/linalg/opdsl/lang/emitter.py
+++ b/mlir/python/mlir/dialects/linalg/opdsl/lang/emitter.py
@@ -60,6 +60,7 @@ def prepare_common_structured_op(
in [
OperandKind.UNARY_FN_ATTR,
OperandKind.BINARY_FN_ATTR,
+ OperandKind.TERNARY_FN_ATTR,
OperandKind.TYPE_FN_ATTR,
]
]
@@ -180,6 +181,12 @@ def prepare_common_structured_op(
f"Attribute {fn_attr.name} needs to be of type "
f"BinaryFnType but got {type(attr_val)}"
)
+ elif attr_kind == OperandKind.TERNARY_FN_ATTR:
+ if not isinstance(fn, TernaryFnType):
+ raise ValueError(
+ f"Attribute {fn_attr.name} needs to be of type "
+ f"TernaryFnType but got {type(attr_val)}"
+ )
else:
if not isinstance(fn, TypeFnType):
raise ValueError(
diff --git a/mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py b/mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py
index ca2bb0c5f7f8a..d73428a0f4df3 100644
--- a/mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py
+++ b/mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py
@@ -351,6 +351,26 @@ def powf(
O[None] = BinaryFn.powf(lhs[None], rhs[None])
+@linalg_structured_op
+def select(
+ cond=TensorDef(U),
+ lhs=TensorDef(T1),
+ rhs=TensorDef(T1),
+ O=TensorDef(T1, output=True),
+):
+ """Chooses one value based on a binary condition supplied as its first operand.
+
+ The shapes and element types must be identical. The appropriate casts,
+ broadcasts and reductions should be done previously to calling this op.
+
+ This means reduction/broadcast/element cast semantics is explicit. Further
+ passes can take that into account when lowering this code. For example,
+ a `linalg.broadcast` + `linalg.select` sequence can be lowered to a
+ `linalg.generic` with different affine maps for the two operands.
+ """
+ O[None] = TernaryFn.select(cond[None], lhs[None], rhs[None])
+
+
@linalg_structured_op
def matmul(
A=TensorDef(T1, S.M, S.K),
diff --git a/mlir/test/Dialect/Linalg/generalize-named-ops.mlir b/mlir/test/Dialect/Linalg/generalize-named-ops.mlir
index 667ea3c18c8ad..4f43ec2c9e1ce 100644
--- a/mlir/test/Dialect/Linalg/generalize-named-ops.mlir
+++ b/mlir/test/Dialect/Linalg/generalize-named-ops.mlir
@@ -791,6 +791,31 @@ func.func @generalize_powf(%lhs: memref<7x14x21xf32>, %rhs: memref<7x14x21xf32>,
// -----
+func.func @generalize_select(%cond: memref<7x14x21xi1>, %lhs: memref<7x14x21xf32>, %rhs: memref<7x14x21xf32>,
+ %out: memref<7x14x21xf32>) {
+ linalg.select ins(%cond, %lhs, %rhs: memref<7x14x21xi1>, memref<7x14x21xf32>, memref<7x14x21xf32>)
+ outs(%out: memref<7x14x21xf32>)
+ return
+}
+
+// CHECK: #[[MAP:.+]] = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
+
+// CHECK: func @generalize_select
+// CHECK-SAME: (%[[COND:.+]]: memref<7x14x21xi1>, %[[LHS:.+]]: memref<7x14x21xf32>, %[[RHS:.+]]: memref<7x14x21xf32>,
+// CHECK-SAME: %[[OUT:.+]]: memref<7x14x21xf32>)
+
+// CHECK: linalg.generic
+// CHECK-SAME: indexing_maps = [#[[MAP]], #[[MAP]], #[[MAP]], #[[MAP]]]
+// CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel"]}
+// CHECK-SAME: ins(%[[COND]], %[[LHS]], %[[RHS]] : memref<7x14x21xi1>, memref<7x14x21xf32>, memref<7x14x21xf32>)
+// CHECK-SAME: outs(%[[OUT]] : memref<7x14x21xf32>)
+
+// CHECK: ^{{.+}}(%[[BBARG0:.+]]: i1, %[[BBARG1:.+]]: f32, %[[BBARG2:.+]]: f32, %[[BBARG3:.+]]: f32)
+// CHECK-NEXT: %[[select:.+]] = arith.select %[[BBARG0]], %[[BBARG1]], %[[BBARG2]] : f32
+// CHECK-NEXT: linalg.yield %[[select]] : f32
+
+
+// -----
// CHECK-LABEL: func @fill_tensor
func.func @fill_tensor(%f: f32, %v: vector<2x4xf32>) -> (tensor<f32>, tensor<vector<2x4xf32>>) {
diff --git a/mlir/test/Dialect/Linalg/named-ops-fail.mlir b/mlir/test/Dialect/Linalg/named-ops-fail.mlir
index e92a77aa7ad05..552a0abaa797c 100644
--- a/mlir/test/Dialect/Linalg/named-ops-fail.mlir
+++ b/mlir/test/Dialect/Linalg/named-ops-fail.mlir
@@ -334,3 +334,19 @@ func.func @powf_broadcast(%arg0: memref<8x16xf32>, %arg1: memref<4x8x16xf32>, %a
return
}
+// -----
+
+func.func @select_type_cast(%arg0: memref<4x8x16xi1>, %arg1: memref<4x8x16xf16>, %arg2: memref<4x8x16xf32>, %arg3: memref<4x8x16xf32>) {
+ // CHECK: op failed to verify that all of {true_value, false_value, result} have same type
+ linalg.select ins(%arg0, %arg1, %arg2 : memref<4x8x16xi1>, memref<4x8x16xf16>, memref<4x8x16xf32>) outs(%arg3: memref<4x8x16xf32>)
+ return
+}
+
+// -----
+
+func.func @select_wrong_condition_type(%arg0: memref<4x8x16xf32>, %arg1: memref<4x8x16xf32>, %arg2: memref<4x8x16xf32>, %arg3: memref<4x8x16xf32>) {
+ // CHECK: op operand #0 must be bool-like, but got 'f32'
+ linalg.select ins(%arg0, %arg1, %arg2 : memref<4x8x16xf32>, memref<4x8x16xf32>, memref<4x8x16xf32>) outs(%arg3: memref<4x8x16xf32>)
+ return
+}
+
diff --git a/mlir/test/Dialect/Linalg/named-ops.mlir b/mlir/test/Dialect/Linalg/named-ops.mlir
index fefe5578947f0..cecd0033b7765 100644
--- a/mlir/test/Dialect/Linalg/named-ops.mlir
+++ b/mlir/test/Dialect/Linalg/named-ops.mlir
@@ -1924,3 +1924,25 @@ func.func @fill_tensor(%f: f32, %v: vector<2x4xf32>) -> (tensor<f32>, tensor<vec
%1 = linalg.fill ins(%v : vector<2x4xf32>) outs(%e1 : tensor<vector<2x4xf32>>) -> tensor<vector<2x4xf32>>
return %0, %1: tensor<f32>, tensor<vector<2x4xf32>>
}
+
+// -----
+
+// CHECK-LABEL: func @select_dynamic
+func.func @select_dynamic(%arg0: memref<?x?x?xi1>, %arg1: memref<?x?x?xf32>, %arg2: memref<?x?x?xf32>, %arg3: memref<?x?x?xf32>) {
+ // CHECK: linalg.select
+ // CHECK-SAME: ins(%{{.+}}, %{{.+}}, %{{.+}} : memref<?x?x?xi1>, memref<?x?x?xf32>, memref<?x?x?xf32>)
+ // CHECK-SAME: outs(%{{.+}} : memref<?x?x?xf32>)
+ linalg.select ins(%arg0, %arg1, %arg2 : memref<?x?x?xi1>, memref<?x?x?xf32>, memref<?x?x?xf32>) outs(%arg3: memref<?x?x?xf32>)
+ return
+}
+
+// -----
+
+// CHECK-LABEL: func @select_static
+func.func @select_static(%arg0: memref<4x8x16xi1>, %arg1: memref<4x8x16xf32>, %arg2: memref<4x8x16xf32>, %arg3: memref<4x8x16xf32>) {
+ // CHECK: linalg.select
+ // CHECK-SAME: ins(%{{.+}}, %{{.+}}, %{{.+}} : memref<4x8x16xi1>, memref<4x8x16xf32>, memref<4x8x16xf32>)
+ // CHECK-SAME: outs(%{{.+}} : memref<4x8x16xf32>)
+ linalg.select ins(%arg0, %arg1, %arg2 : memref<4x8x16xi1>, memref<4x8x16xf32>, memref<4x8x16xf32>) outs(%arg3: memref<4x8x16xf32>)
+ return
+}
diff --git a/mlir/tools/mlir-linalg-ods-gen/mlir-linalg-ods-yaml-gen.cpp b/mlir/tools/mlir-linalg-ods-gen/mlir-linalg-ods-yaml-gen.cpp
index fe6ad15041126..37240164c377e 100644
--- a/mlir/tools/mlir-linalg-ods-gen/mlir-linalg-ods-yaml-gen.cpp
+++ b/mlir/tools/mlir-linalg-ods-gen/mlir-linalg-ods-yaml-gen.cpp
@@ -70,6 +70,7 @@ enum class LinalgOperandDefKind {
IndexAttr,
UnaryFnAttr,
BinaryFnAttr,
+ TernaryFnAttr,
TypeFnAttr
};
@@ -94,7 +95,7 @@ struct LinalgIndexingMapsConfig {
struct ScalarExpression;
-enum class ScalarFnKind { Unary, Binary, Type };
+enum class ScalarFnKind { Unary, Binary, Ternary, Type };
struct ScalarFn {
ScalarFnKind kind;
@@ -214,6 +215,7 @@ struct ScalarEnumerationTraits<LinalgOperandDefKind> {
io.enumCase(value, "index_attr", LinalgOperandDefKind::IndexAttr);
io.enumCase(value, "unary_fn_attr", LinalgOperandDefKind::UnaryFnAttr);
io.enumCase(value, "binary_fn_attr", LinalgOperandDefKind::BinaryFnAttr);
+ io.enumCase(value, "ternary_fn_attr", LinalgOperandDefKind::TernaryFnAttr);
io.enumCase(value, "type_fn_attr", LinalgOperandDefKind::TypeFnAttr);
}
};
@@ -284,6 +286,7 @@ struct ScalarEnumerationTraits<ScalarFnKind> {
static void enumeration(IO &io, ScalarFnKind &value) {
io.enumCase(value, "unary", ScalarFnKind::Unary);
io.enumCase(value, "binary", ScalarFnKind::Binary);
+ io.enumCase(value, "ternary", ScalarFnKind::Ternary);
io.enumCase(value, "type", ScalarFnKind::Type);
}
};
@@ -441,6 +444,7 @@ static ScalarAssign *findAssignment(StringRef name,
static bool isFunctionAttribute(LinalgOperandDefKind kind) {
return kind == LinalgOperandDefKind::UnaryFnAttr ||
kind == LinalgOperandDefKind::BinaryFnAttr ||
+ kind == LinalgOperandDefKind::TernaryFnAttr ||
kind == LinalgOperandDefKind::TypeFnAttr;
}
@@ -456,6 +460,8 @@ std::string convertOperandKindToEnumName(LinalgOperandDefKind kind) {
return std::string("UnaryFn");
case LinalgOperandDefKind::BinaryFnAttr:
return std::string("BinaryFn");
+ case LinalgOperandDefKind::TernaryFnAttr:
+ return std::string("TernaryFn");
case LinalgOperandDefKind::TypeFnAttr:
return std::string("TypeFn");
default:
@@ -471,6 +477,8 @@ std::string convertFunctionKindToEnumName(ScalarFnKind kind) {
return std::string("UnaryFn");
case ScalarFnKind::Binary:
return std::string("BinaryFn");
+ case ScalarFnKind::Ternary:
+ return std::string("TernaryFn");
case ScalarFnKind::Type:
return std::string("TypeFn");
}
|
makslevental
reviewed
May 8, 2024
|
✅ With the latest revision this PR passed the Python code formatter. |
Co-authored-by: Maksim Levental <[email protected]>
ciyongch
reviewed
May 9, 2024
|
ping |
matthias-springer
approved these changes
May 14, 2024
There was a problem hiding this comment.
I'm not too familiar with the Op DSL part, but this op makes sense to me.
There is actually a TODO in the BufferizableOpInterface implementation of arith.select: only i1 conditions are supported. That is because there is no efficient way to bufferize arith.select with tensor conditions because the op is not in destination style. It is good to have a linalg.select destination-style op that can bufferize efficiently.
|
@kurapov-peter Congratulations on having your first Pull Request (PR) merged into the LLVM Project! Your changes will be combined with recent changes from other authors, then tested Please check whether problems have been caused by your change specifically, as How to do this, and the rest of the post-merge process, is covered in detail here. If your change does cause a problem, it may be reverted, or you can revert it yourself. If you don't get any reports, no action is required from you. Your changes are working as expected, well done! |
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Following #90236, adding
selectto linalg asarith.select. No implicit type casting.OpDSL doesn't expose a type restriction for bool, but I saw no reason in adding it (put a separate symbolic type and check the semantics in the builder).