[llvm-branch-commits] [mlir] b0d02b6 - [MLIR] Minor cleanup for Shape dialect.
Rahul Joshi via llvm-branch-commits
llvm-branch-commits at lists.llvm.org
Wed Dec 9 14:26:05 PST 2020
Author: Rahul Joshi
Date: 2020-12-09T14:21:35-08:00
New Revision: b0d02b698b94d2fc5f7fbd430f5e9d3b032f8523
URL: https://github.com/llvm/llvm-project/commit/b0d02b698b94d2fc5f7fbd430f5e9d3b032f8523
DIFF: https://github.com/llvm/llvm-project/commit/b0d02b698b94d2fc5f7fbd430f5e9d3b032f8523.diff
LOG: [MLIR] Minor cleanup for Shape dialect.
- Remove some unused types from the Shape dialect
- Fix from_extent_tensor to only allow 1D index tensors
- Fix assuming_yield to only allow shape.assuming as the parent op.
- Fix some documentation typos and reword some things.
Differential Revision: https://reviews.llvm.org/D92901
Added:
Modified:
mlir/include/mlir/Dialect/Shape/IR/Shape.h
mlir/include/mlir/Dialect/Shape/IR/ShapeBase.td
mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td
mlir/lib/Dialect/Shape/IR/Shape.cpp
Removed:
################################################################################
diff --git a/mlir/include/mlir/Dialect/Shape/IR/Shape.h b/mlir/include/mlir/Dialect/Shape/IR/Shape.h
index eab3c6f67ca0..db2862141ea9 100644
--- a/mlir/include/mlir/Dialect/Shape/IR/Shape.h
+++ b/mlir/include/mlir/Dialect/Shape/IR/Shape.h
@@ -31,18 +31,6 @@ namespace shape {
/// Alias type for extent tensors.
RankedTensorType getExtentTensorType(MLIRContext *ctx);
-/// The component type corresponding to shape, element type and attribute.
-class ComponentType : public Type::TypeBase<ComponentType, Type, TypeStorage> {
-public:
- using Base::Base;
-};
-
-/// The element type of the shaped type.
-class ElementType : public Type::TypeBase<ElementType, Type, TypeStorage> {
-public:
- using Base::Base;
-};
-
/// The shape descriptor type represents rank and dimension sizes.
class ShapeType : public Type::TypeBase<ShapeType, Type, TypeStorage> {
public:
diff --git a/mlir/include/mlir/Dialect/Shape/IR/ShapeBase.td b/mlir/include/mlir/Dialect/Shape/IR/ShapeBase.td
index c9103a2b8b63..a7868e74c65f 100644
--- a/mlir/include/mlir/Dialect/Shape/IR/ShapeBase.td
+++ b/mlir/include/mlir/Dialect/Shape/IR/ShapeBase.td
@@ -39,29 +39,11 @@ def ShapeDialect : Dialect {
let hasConstantMaterializer = 1;
}
-def Shape_ComponentType : DialectType<ShapeDialect,
- CPred<"$_self.isa<::mlir::shape::ComponentType>()">, "component type">,
- BuildableType<"$_builder.getType<::mlir::shape::ComponentType>()"> {
- let typeDescription = [{
- `shape.component_type` represents the tuple of shape, element type and
- attribute.
- }];
-}
-
-def Shape_ElementType : DialectType<ShapeDialect,
- CPred<"$_self.isa<::mlir::shape::ElementType>()">, "element type">,
- BuildableType<"$_builder.getType<::mlir::shape::ElementType>()"> {
- let typeDescription = [{
- `shape.element_type` represents the element type of the ShapedType. It may
- be unknown, error or regular element type supported by ShapedType.
- }];
-}
-
def Shape_ShapeType : DialectType<ShapeDialect,
CPred<"$_self.isa<::mlir::shape::ShapeType>()">, "shape">,
BuildableType<"$_builder.getType<::mlir::shape::ShapeType>()"> {
let typeDescription = [{
- `shape.type` represents either an unranked shape, a ranked shape with
+ `shape.shape` represents either an unranked shape, a ranked shape with
possibly unknown dimensions or an invalid shape. The rank is of type
`shape.size` and, if rank is known, the extent is a 1D tensor of type
`shape.size`.
@@ -96,12 +78,12 @@ def Shape_ValueShapeType : DialectType<ShapeDialect,
let typeDescription = [{
`shape.value_shape` represents the value produced by an operation (this
corresponds to `Value` in the compiler) and a shape. Conceptually this is a
- tuple of a value (potentially unknown) and `shape.type`. The value and shape
- can either or both be unknown. If both the `value` and `shape` are known,
- then the shape of `value` is conformant with `shape`. That is, the shape of
- the value conforms to the shape of the ValueShape, so that if we have
- ValueShape `(value, shape)` then `join(shape_of(value), shape)` would be
- error free and in particular it means that if both are statically known,
+ tuple of a value (potentially unknown) and `shape.shape`. The value and
+ shape can either or both be unknown. If both the `value` and `shape` are
+ known, then the shape of `value` is conformant with `shape`. That is, the
+ shape of the value conforms to the shape of the ValueShape, so that if we
+ have ValueShape `(value, shape)` then `join(shape_of(value), shape)` would
+ be error free and in particular it means that if both are statically known,
then they are equal.
}];
}
@@ -112,8 +94,8 @@ def Shape_ExtentTensorType :
"$_builder.getType<::mlir::IndexType>())"> {
let typeDescription = [{
The extent tensor is a tensor of rank one with arbitrarily many index
- elements. Like `!shape.shape`, it is used to represent shapes with the
-
diff erence that it is guaranteed to be error-free.
+ elements (tensor<?xindex>). Like `!shape.shape`, it is used to represent
+ shapes with the
diff erence that it is guaranteed to be error-free.
}];
}
diff --git a/mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td b/mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td
index 552de7e78f91..0cbb910e062c 100644
--- a/mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td
+++ b/mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td
@@ -34,7 +34,9 @@ def Shape_AddOp : Shape_Op<"add", [Commutative, NoSideEffect]> {
Adds two sizes or indices. If either operand is an error it will be
propagated to the result. The operands can be of type `size` or `index`. If
at least one of the operands can hold an error, i.e. if it is of type `size`,
- then also the result must be of type `size`.
+ the result must be of type `size`. If error propagation is not possible
+ because both operands are of type `index` then the result may be of type
+ `size` or `index`.
}];
let arguments = (ins Shape_SizeOrIndexType:$lhs, Shape_SizeOrIndexType:$rhs);
@@ -177,7 +179,7 @@ def Shape_FromExtentTensorOp : Shape_Op<"from_extent_tensor", [NoSideEffect]> {
extents match the values of the elements.
}];
- let arguments = (ins IndexTensor:$input);
+ let arguments = (ins 1DTensorOf<[Index]>:$input);
let results = (outs Shape_ShapeType:$result);
let assemblyFormat = "$input attr-dict `:` type($input)";
@@ -247,7 +249,7 @@ def Shape_GetExtentOp : Shape_Op<"get_extent", [NoSideEffect]> {
let summary = "Gets the specified extent from a shape or extent tensor";
let description = [{
Gets the extent indexed by `dim` from the `shape` operand. If the shape is
- an error then it returns an error size.
+ an error then it returns an invalid size.
}];
let arguments = (ins Shape_ShapeOrExtentTensorType:$shape,
Shape_SizeOrIndexType:$dim);
@@ -289,7 +291,7 @@ def Shape_IndexToSizeOp : Shape_Op<"index_to_size", [NoSideEffect]> {
}
def Shape_JoinOp : Shape_Op<"join", [Commutative]> {
- let summary = "Returns the least general shape.size of its operands";
+ let summary = "Returns the least general shape.shape of its operands";
let description = [{
An operation that computes the least general shape of input operands.
This effectively asserts that corresponding static dimensions are equal.
@@ -327,9 +329,9 @@ def Shape_MulOp : Shape_Op<"mul", [Commutative, NoSideEffect]> {
Multiplies two sizes or indices. If either operand is an error it will be
propagated to the result. The operands can be of type `size` or `index`. If
at least one of the operands can hold an error, i.e. if it is of type `size`,
- then also the result must be of type `size`. If error propagation is not
- possible because both operands are of type `index` then the result must also
- be of type `index`.
+ the result must be of type `size`. If error propagation is not possible
+ because both operands are of type `index` then the result may be of type
+ `size` or `index`.
}];
let arguments = (ins Shape_SizeOrIndexType:$lhs, Shape_SizeOrIndexType:$rhs);
@@ -369,23 +371,22 @@ def Shape_ReduceOp : Shape_Op<"reduce",
let summary = "Returns an expression reduced over a shape or extent tensor";
let description = [{
An operation that takes as input a shape or extent tensor, and a number of
- initial values. This operation has a region/function that is applied
- repeatedly for every extent of the input. Starting with the initial values,
- the individual extents are then aggregated as defined by the associated
- region.
+ initial values. This operation has a region that is applied repeatedly for
+ every extent of the input. Starting with the initial values, the individual
+ extents are then aggregated as defined by the associated region.
Conceptually this op performs the following reduction:
```
res[] = init;
for (int i = 0, i < shape.rank(); i++) {
- res = fn(i, shape[i], res[0], ..., res[n]);
+ res = reduce(i, shape[i], res[0], ..., res[n]);
}
```
- Where `fn` is provided by the user and the result of the reduce op is the
- last computed output of the reduce function. As an example, computing the
- number of elements can be defined as follows:
+ Where `reduce` represents the region attached and the result of the reduce
+ op is the last computed output of the reduce region. As an example, the
+ number of elements can be computed as follows:
```mlir
func @reduce(%shape : !shape.shape, %init : !shape.size) -> !shape.size {
@@ -669,13 +670,13 @@ def Shape_AssumingOp : Shape_Op<"assuming",
}
def Shape_AssumingYieldOp : Shape_Op<"assuming_yield",
- [NoSideEffect, ReturnLike, Terminator]> {
+ [NoSideEffect, ReturnLike, Terminator, HasParent<"AssumingOp">]> {
let summary = "Yield operation";
let description = [{
- This yield operation represents a return operation within the assert_and_exec
- region. The operation takes variable number of operands and produces no
- results. The operand number and types must match the return signature of
- the region that contains the operation.
+ This yield operation represents a return operation within the
+ `shape.assuming` operation region. The operation takes variable number of
+ operands and produces no results. The operand number and types must match
+ the number and types of parent `shape.assuming` results.
}];
let arguments = (ins Variadic<AnyType>:$operands);
@@ -742,7 +743,7 @@ def Shape_ConstWitnessOp : Shape_Op<"const_witness", [ConstantLike, NoSideEffect
```mlir
%0 = shape.const_shape [1,2,3]
- %1 = shape.const_shape [1, 2, 3]
+ %1 = shape.const_shape [1,2,3]
%w0 = shape.cstr_eq(%0, %1) // Can be folded to "const_witness true"
%w1 = shape.const_witness true
%w2 = shape.assuming_all(%w0, %w2) // Can be folded to "const_witness true"
diff --git a/mlir/lib/Dialect/Shape/IR/Shape.cpp b/mlir/lib/Dialect/Shape/IR/Shape.cpp
index 44f897cbf505..c71360cdaba5 100644
--- a/mlir/lib/Dialect/Shape/IR/Shape.cpp
+++ b/mlir/lib/Dialect/Shape/IR/Shape.cpp
@@ -31,10 +31,9 @@ RankedTensorType shape::getExtentTensorType(MLIRContext *ctx) {
}
static bool isErrorPropagationPossible(TypeRange operandTypes) {
- for (Type ty : operandTypes)
- if (ty.isa<SizeType>() || ty.isa<ShapeType>() || ty.isa<ValueShapeType>())
- return true;
- return false;
+ return llvm::any_of(operandTypes, [](Type ty) {
+ return ty.isa<SizeType, ShapeType, ValueShapeType>();
+ });
}
static LogicalResult verifySizeOrIndexOp(Operation *op) {
@@ -92,8 +91,7 @@ void ShapeDialect::initialize() {
#define GET_OP_LIST
#include "mlir/Dialect/Shape/IR/ShapeOps.cpp.inc"
>();
- addTypes<ComponentType, ElementType, ShapeType, SizeType, ValueShapeType,
- WitnessType>();
+ addTypes<ShapeType, SizeType, ValueShapeType, WitnessType>();
addInterfaces<ShapeInlinerInterface>();
// Allow unknown operations during prototyping and testing. As the dialect is
// still evolving it makes it simple to start with an unregistered ops and
@@ -123,10 +121,6 @@ Type ShapeDialect::parseType(DialectAsmParser &parser) const {
if (parser.parseKeyword(&keyword))
return Type();
- if (keyword == "component")
- return ComponentType::get(getContext());
- if (keyword == "element")
- return ElementType::get(getContext());
if (keyword == "shape")
return ShapeType::get(getContext());
if (keyword == "size")
@@ -143,8 +137,6 @@ Type ShapeDialect::parseType(DialectAsmParser &parser) const {
/// Print a type registered to this dialect.
void ShapeDialect::printType(Type type, DialectAsmPrinter &os) const {
TypeSwitch<Type>(type)
- .Case<ComponentType>([&](Type) { os << "component"; })
- .Case<ElementType>([&](Type) { os << "element"; })
.Case<ShapeType>([&](Type) { os << "shape"; })
.Case<SizeType>([&](Type) { os << "size"; })
.Case<ValueShapeType>([&](Type) { os << "value_shape"; })
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