forked from OSchip/llvm-project
[mlir][shape] Extract ShapeBase.td
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Sean Silva
parent
8e911545d6
commit
b40d073e53
mlir/include/mlir/Dialect/Shape/IR
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#ifndef SHAPE_BASE_TD
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#define SHAPE_BASE_TD
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include "mlir/IR/OpBase.td"
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// TODO(jpienaar): Move to base.
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def AnyShaped: ShapedContainerType<[AnyType], IsShapedTypePred, "shaped">;
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//===----------------------------------------------------------------------===//
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// Shape Inference dialect definitions
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//===----------------------------------------------------------------------===//
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def ShapeDialect : Dialect {
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let name = "shape";
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let summary = "Types and operations for shape dialect";
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let description = [{
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This dialect contains operations for shape inference.
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Note: Unless explicitly stated, all functions that return a shape and take
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shapes as input, return the invalid shape if one of its operands is an
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invalid shape. This avoids flagging multiple errors for one verification
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failure. The dialect itself does not specify how errors should be combined
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(there are multiple different options, from always choosing first operand,
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concatting etc. on how to combine them).
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}];
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let cppNamespace = "shape";
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let hasConstantMaterializer = 1;
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}
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def Shape_ComponentType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::ComponentType>()">, "component type">,
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BuildableType<"$_builder.getType<::mlir::shape::ComponentType>()"> {
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let typeDescription = [{
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`shape.element_type` represents the element type of the ShapedType. It may
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be unknown, error or regular element type supported by ShapedType.
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}];
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}
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def Shape_ElementType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::ElementType>()">, "element type">,
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BuildableType<"$_builder.getType<::mlir::shape::ElementType>()"> {
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let typeDescription = [{
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`shape.element_type` represents the element type of the ShapedType. It may
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be unknown, error or regular element type supported by ShapedType.
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}];
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}
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def Shape_ShapeType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::ShapeType>()">, "shape">,
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BuildableType<"$_builder.getType<::mlir::shape::ShapeType>()"> {
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let typeDescription = [{
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`shape.type` represents either an unranked shape, a ranked shape with
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possibly unknown dimensions or an invalid shape. The rank is of type
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`shape.size` and, if rank is known, the extent is a 1D tensor of type
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`shape.size`.
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Shape is printed:
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* `[*]` if it is an unranked shape
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* `[?, 2]` if a rank 2 tensor with one unknown dimension
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* `[3, 4]` is a rank 2 static tensor
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* `[]` is a scalar
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* `[1]` is a rank 1 tensor with 1 element
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* `[invalid]` for an invalid shape
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}];
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}
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def Shape_SizeType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::SizeType>()">, "size">,
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BuildableType<"$_builder.getType<::mlir::shape::SizeType>()"> {
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let typeDescription = [{
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`shape.size` represents a non-negative integer with support for being
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unknown and invalid.
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Operations on `shape.size` types are specialized to handle unknown/dynamic
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value. So, for example, `<unknown> + x == <unknown>` for all non-error `x :
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!shape.size` (e.g., an unknown value does not become known due to addition).
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}];
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}
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def Shape_ValueShapeType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::ValueShapeType>()">, "value shape">,
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BuildableType<"::mlir::shape::ValueShapeType::get($_builder.getContext())">
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{
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let typeDescription = [{
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`shape.value_shape` represents the value produced by an operation (this
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corresponds to `Value` in the compiler) and a shape. Conceptually this is a
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tuple of a value (potentially unknown) and `shape.type`. The value and shape
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can either or both be unknown. If both the `value` and `shape` are known,
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then the shape of `value` is conformant with `shape`.
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}];
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}
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def Shape_ShapeOrSizeType: AnyTypeOf<[Shape_SizeType, Shape_ShapeType],
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"shape or size">;
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#endif // SHAPE_BASE_TD
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@ -13,103 +13,10 @@
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#ifndef SHAPE_OPS
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#define SHAPE_OPS
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include "mlir/IR/OpBase.td"
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include "mlir/Dialect/Shape/IR/ShapeBase.td"
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include "mlir/Interfaces/InferTypeOpInterface.td"
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include "mlir/Interfaces/SideEffects.td"
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// TODO(jpienaar): Move to base.
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def AnyShaped: ShapedContainerType<[AnyType], IsShapedTypePred, "shaped">;
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//===----------------------------------------------------------------------===//
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// Shape Inference dialect definitions
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//===----------------------------------------------------------------------===//
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def ShapeDialect : Dialect {
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let name = "shape";
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let summary = "Types and operations for shape dialect";
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let description = [{
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This dialect contains operations for shape inference.
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Note: Unless explicitly stated, all functions that return a shape and take
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shapes as input, return the invalid shape if one of its operands is an
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invalid shape. This avoids flagging multiple errors for one verification
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failure. The dialect itself does not specify how errors should be combined
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(there are multiple different options, from always choosing first operand,
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concatting etc. on how to combine them).
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}];
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let cppNamespace = "shape";
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let hasConstantMaterializer = 1;
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}
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def Shape_ComponentType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::ComponentType>()">, "component type">,
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BuildableType<"$_builder.getType<::mlir::shape::ComponentType>()"> {
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let typeDescription = [{
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`shape.element_type` represents the element type of the ShapedType. It may
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be unknown, error or regular element type supported by ShapedType.
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}];
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}
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def Shape_ElementType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::ElementType>()">, "element type">,
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BuildableType<"$_builder.getType<::mlir::shape::ElementType>()"> {
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let typeDescription = [{
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`shape.element_type` represents the element type of the ShapedType. It may
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be unknown, error or regular element type supported by ShapedType.
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}];
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}
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def Shape_ShapeType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::ShapeType>()">, "shape">,
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BuildableType<"$_builder.getType<::mlir::shape::ShapeType>()"> {
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let typeDescription = [{
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`shape.type` represents either an unranked shape, a ranked shape with
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possibly unknown dimensions or an invalid shape. The rank is of type
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`shape.size` and, if rank is known, the extent is a 1D tensor of type
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`shape.size`.
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Shape is printed:
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* `[*]` if it is an unranked shape
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* `[?, 2]` if a rank 2 tensor with one unknown dimension
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* `[3, 4]` is a rank 2 static tensor
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* `[]` is a scalar
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* `[1]` is a rank 1 tensor with 1 element
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* `[invalid]` for an invalid shape
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}];
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}
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def Shape_SizeType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::SizeType>()">, "size">,
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BuildableType<"$_builder.getType<::mlir::shape::SizeType>()"> {
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let typeDescription = [{
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`shape.size` represents a non-negative integer with support for being
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unknown and invalid.
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Operations on `shape.size` types are specialized to handle unknown/dynamic
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value. So, for example, `<unknown> + x == <unknown>` for all non-error `x :
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!shape.size` (e.g., an unknown value does not become known due to addition).
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}];
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}
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def Shape_ValueShapeType : DialectType<ShapeDialect,
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CPred<"$_self.isa<::mlir::shape::ValueShapeType>()">, "value shape">,
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BuildableType<"::mlir::shape::ValueShapeType::get($_builder.getContext())">
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{
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let typeDescription = [{
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`shape.value_shape` represents the value produced by an operation (this
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corresponds to `Value` in the compiler) and a shape. Conceptually this is a
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tuple of a value (potentially unknown) and `shape.type`. The value and shape
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can either or both be unknown. If both the `value` and `shape` are known,
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then the shape of `value` is conformant with `shape`.
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}];
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}
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def Shape_ShapeOrSizeType: AnyTypeOf<[Shape_SizeType, Shape_ShapeType],
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"shape or size">;
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//===----------------------------------------------------------------------===//
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// Shape op definitions
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//===----------------------------------------------------------------------===//
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