/
LinalgInterfaces.td
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LinalgInterfaces.td
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//===- LinalgInterfaces.td - Linalg Interfaces Declaration -*- tablegen -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This is the definition file for the structured interface sfor Linalg ops.
//
//===----------------------------------------------------------------------===//
#ifndef LINALG_IR_LINALGINTERFACES
#define LINALG_IR_LINALGINTERFACES
include "mlir/IR/OpBase.td"
// The 'LinalgContractionOpInterface' provides access to the
// 'ContractionOpInterface'.
def LinalgContractionOpInterface : OpInterface<"ContractionOpInterface"> {
let description = [{
A Linalg contraction is defined in general terms:
1. Has 2 input and 1 output shapes.
2. Has at least one reduction dimension.
3. Has only projected permutation indexing maps.
4. its body computes `u5(u1(c) + u2(u3(a) * u4(b)))` on some field
(AddOpType, MulOpType), where u1, u2, u3, u4 and u5 represent scalar unary
operations that may change the type (e.g. for mixed-precision).
As a consequence, when vectorization of such an op occurs, the only special
behavior is that the (unique) MulOpType is vectorized into a
`vector.contract`. All other ops are handled in a generic fashion.
In the future, we may wish to allow more input arguments and elementwise and
constant operations that do not involve the reduction dimension(s).
}];
let cppNamespace = "::mlir::linalg";
let verify = [{ return detail::verifyContractionInterface($_op); }];
let verifyWithRegions = 1;
let methods = [
InterfaceMethod<
/*desc=*/"Returns the left-hand side operand.",
/*retTy=*/"Value",
/*methodName=*/"lhs",
/*args=*/(ins),
/*methodBody=*/[{
return $_op.getOperation()->getOperand(0);
}]>,
InterfaceMethod<
/*desc=*/"Returns the right-hand side operand.",
/*retTy=*/"Value",
/*methodName=*/"rhs",
/*args=*/(ins),
/*methodBody=*/[{
return $_op.getOperation()->getOperand(1);
}]>,
InterfaceMethod<
/*desc=*/[{
Returns whether the given op has indexing maps that correspond to a
row-major matmul operation.
}],
/*retTy=*/"bool",
/*methodName=*/"isRowMajorMatmul",
/*args=*/(ins),
/*methodBody=*/[{
return mlir::isRowMajorMatmul($_op.getIndexingMaps());
}]>,
InterfaceMethod<
/*desc=*/[{
Returns whether the given op has indexing maps that correspond to a
column-major matmul operation.
}],
/*retTy=*/"bool",
/*methodName=*/"isColumnMajorMatmul",
/*args=*/(ins),
/*methodBody=*/[{
return mlir::isColumnMajorMatmul($_op.getIndexingMaps());
}]>,
InterfaceMethod<
/*desc=*/[{
Returns whether the given op has indexing maps that correspond to a
row-major batch matmul operation.
}],
/*retTy=*/"bool",
/*methodName=*/"isRowMajorBatchMatmul",
/*args=*/(ins),
/*methodBody=*/[{
return mlir::isRowMajorBatchMatmul($_op.getIndexingMaps());
}]>,
];
}
def LinalgConvolutionOpInterface : OpInterface<"ConvolutionOpInterface"> {
let description = [{
A convolution is defined in general terms:
1. Has an `image` and a `filter` operand.
2. Has one `output` operand.
3. The indexing maps of the input have expressions that satisfy
```
AffineExpr ::== AffineDimExpr | ConvolvedExpr
ConvolvedExpr ::== MulExpr (`+` MulExpr)+
MulExpr ::== AffineDimExpr (`*` (AffineConstantExpr | AffineSymbolExpr))?
```
4. The filter and the output have projected permutation maps.
5. Each of the loops can be qualified as one of,
- Loop over batch dimension,
- Loop over output image dimensions,
- Loop over output channel dimensions,
- Loop over convolved filter dimensions,
- Loop over input channel dimension.
}];
let cppNamespace = "::mlir::linalg";
let verify = [{ return detail::verifyConvolutionInterface($_op); }];
let methods = [
InterfaceMethod<
/*desc=*/"Return the image operand.",
/*retTy=*/"Value",
/*methodName=*/"image",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return $_op.getOperation()->getOperand(0);
}]
>,
InterfaceMethod<
/*desc=*/"Return the filter operand.",
/*retTy=*/"Value",
/*methodName=*/"filter",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return $_op.getOperation()->getOperand(1);
}]
>,
];
}
def LinalgFillOpInterface : OpInterface<"FillOpInterface"> {
let description = [{
A fill operation is defined in general terms:
1. Has a scalar `value` operand.
2. Has one `output` operand.
}];
let cppNamespace = "::mlir::linalg";
let verify = [{ return detail::verifyFillInterface($_op); }];
let methods = [
InterfaceMethod<
/*desc=*/"Return the fill value.",
/*retTy=*/"Value",
/*methodName=*/"value",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return $_op.getOperation()->getOperand(0);
}]
>,
InterfaceMethod<
/*desc=*/"Return the output operand.",
/*retTy=*/"Value",
/*methodName=*/"output",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return $_op.getOperation()->getOperand(1);
}]
>,
InterfaceMethod<
/*desc=*/"Return the result.",
/*retTy=*/"Value",
/*methodName=*/"result",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
if ($_op.getOperation()->getResults().empty())
return nullptr;
return $_op.getOperation()->getResults().front();
}]
>,
];
}
// The 'LinalgStructuredInterface' provides access to the 'LinalgOp' interface.
def LinalgStructuredInterface : OpInterface<"LinalgOp"> {
let cppNamespace = "::mlir::linalg";
let methods = [
//===------------------------------------------------------------------===//
// Loop types handling.
//===------------------------------------------------------------------===//
InterfaceMethod<
/*desc=*/[{
Return the number of parallel loops.
}],
/*retTy=*/"unsigned",
/*methodName=*/"getNumParallelLoops",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return getNumIterators(getParallelIteratorTypeName(),
$_op.iterator_types());
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the dims that are parallel loops.
}],
/*retTy=*/"void",
/*methodName=*/"getParallelDims",
/*args=*/(ins "SmallVectorImpl<unsigned> &":$res),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return getDimsOfType($_op, getParallelIteratorTypeName(), res);
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the number of reduction loops.
}],
/*retTy=*/"unsigned",
/*methodName=*/"getNumReductionLoops",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return getNumIterators(getReductionIteratorTypeName(),
$_op.iterator_types());
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the dims that are reduction loops.
}],
/*retTy=*/"void",
/*methodName=*/"getReductionDims",
/*args=*/(ins "SmallVectorImpl<unsigned> &":$res),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return getDimsOfType($_op, getReductionIteratorTypeName(), res);
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the number of window loops.
}],
/*retTy=*/"unsigned",
/*methodName=*/"getNumWindowLoops",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return getNumIterators(getWindowIteratorTypeName(),
$_op.iterator_types());
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the dims that are window loops.
}],
/*retTy=*/"void",
/*methodName=*/"getWindowDims",
/*args=*/(ins "SmallVectorImpl<unsigned> &":$res),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return getDimsOfType($_op.getOperation(), getWindowIteratorTypeName(), res);
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the total number of loops within the current operation.
}],
/*retTy=*/"unsigned",
/*methodName=*/"getNumLoops",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return getNumIterators($_op.iterator_types());
}]
>,
InterfaceMethod<
/*desc=*/[{
Returns true if the current operation has only one loop and it's a
reduction loop.
}],
/*retTy=*/"bool",
/*methodName=*/"hasSingleReductionLoop",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
auto iters = $_op.iterator_types();
return iters.size() == 1 &&
getNumIterators(getReductionIteratorTypeName(), iters) == 1;
}]>,
//===------------------------------------------------------------------===//
// Num input/output arguments handling.
//===------------------------------------------------------------------===//
// `inputs` must be defined by each op that wants to implement the
// LinalgStructuredInterface.
InterfaceMethod<
/*desc=*/[{
Return the input shape operands.
}],
/*retTy=*/"ValueRange",
/*methodName=*/"inputs",
/*args=*/(ins)
>,
// These special methods rely on `inputs` and `outputs` being defined by
// each op that wants to implement the LinalgStructuredInterface.
InterfaceMethod<
/*desc=*/[{
Return the number of inputs.
}],
/*retTy=*/"int64_t",
/*methodName=*/"getNumInputs",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return $_op.getInputs().size();
}]
>,
// `outputs` must be defined by each op that wants to implement the
// LinalgStructuredInterface.
InterfaceMethod<
/*desc=*/[{
Return the output shape operands.
}],
/*retTy=*/"ValueRange",
/*methodName=*/"outputs",
/*args=*/(ins)
>,
InterfaceMethod<
/*desc=*/[{
Return the number of outputs.
}],
/*retTy=*/"int64_t",
/*methodName=*/"getNumOutputs",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return $_op.outputs().size();
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the number of inputs and outputs.
}],
/*retTy=*/"int64_t",
/*methodName=*/"getNumInputsAndOutputs",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return this->getOperation()->getNumOperands();
}]
>,
//===------------------------------------------------------------------===//
// Input operands handling.
//===------------------------------------------------------------------===//
InterfaceMethod<
/*desc=*/[{
Return the input operands.
}],
/*retTy=*/"OpOperandVector",
/*methodName=*/"getInputOperands",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
int64_t numInputs = getNumInputs();
OpOperandVector result;
result.reserve(numInputs);
llvm::transform(
this->getOperation()->getOpOperands().take_front(numInputs),
std::back_inserter(result),
[](OpOperand &opOperand) { return &opOperand; });
return result;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the `i`-th input operand.
}],
/*retTy=*/"OpOperand*",
/*methodName=*/"getInputOperand",
/*args=*/(ins "int64_t":$i),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(i >= 0 && i < getNumInputs());
return &this->getOperation()->getOpOperand(i);
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the subset of input operands that are of buffer type.
}],
/*retTy=*/"OpOperandVector",
/*methodName=*/"getInputBufferOperands",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
OpOperandVector result;
result.reserve(getNumInputs());
llvm::copy_if(getInputOperands(),
std::back_inserter(result),
[](OpOperand *opOperand) {
return opOperand->get().getType().template isa<MemRefType>();
});
return result;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the subset of input operands that are of tensor type.
}],
/*retTy=*/"OpOperandVector",
/*methodName=*/"getInputTensorOperands",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
OpOperandVector result;
result.reserve(getNumInputs());
llvm::copy_if(getInputOperands(),
std::back_inserter(result),
[](OpOperand *opOperand) {
return opOperand->get().getType().template isa<RankedTensorType>();
});
return result;
}]
>,
//===------------------------------------------------------------------===//
// Output operands handling.
//===------------------------------------------------------------------===//
InterfaceMethod<
/*desc=*/[{
Return the output operands.
}],
/*retTy=*/"OpOperandVector",
/*methodName=*/"getOutputOperands",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
int64_t numOutputs = getNumOutputs();
OpOperandVector result;
result.reserve(numOutputs);
llvm::transform(
this->getOperation()->getOpOperands()
.take_back(numOutputs),
std::back_inserter(result),
[](OpOperand &opOperand) { return &opOperand; });
return result;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the `i`-th output operand.
}],
/*retTy=*/"OpOperand*",
/*methodName=*/"getOutputOperand",
/*args=*/(ins "int64_t":$i),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(i >= 0 && i < getNumOutputs());
return &this->getOperation()->getOpOperand(getNumInputs() + i);
}]
>,
InterfaceMethod<
/*desc=*/[{
Set the `i`-th output operand.
}],
/*retTy=*/"void",
/*methodName=*/"setOutputOperand",
/*args=*/(ins "int64_t":$i, "Value":$value),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(i >= 0 && i < getNumOutputs());
this->getOperation()->setOperand(getNumInputs() + i, value);
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the subset of output operands that are of buffer type.
}],
/*retTy=*/"OpOperandVector",
/*methodName=*/"getOutputBufferOperands",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
OpOperandVector result;
result.reserve(getNumOutputs());
llvm::copy_if(getOutputOperands(),
std::back_inserter(result),
[](OpOperand *opOperand) {
return opOperand->get().getType().template isa<MemRefType>();
});
return result;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the subset of output operands that are of tensor type.
}],
/*retTy=*/"OpOperandVector",
/*methodName=*/"getOutputTensorOperands",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
OpOperandVector result;
result.reserve(getNumOutputs());
llvm::copy_if(getOutputOperands(),
std::back_inserter(result),
[](OpOperand *opOperand) {
return opOperand->get().getType().template isa<RankedTensorType>();
});
return result;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the types of the subset of output operands that are of buffer type.
}],
/*retTy=*/"SmallVector<MemRefType>",
/*methodName=*/"getOutputBufferTypes",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
SmallVector<MemRefType> result;
result.reserve(getNumOutputs());
llvm::transform(getOutputBufferOperands(),
std::back_inserter(result),
[](OpOperand *opOperands) {
return opOperands->get().getType().cast<MemRefType>();
});
return result;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the types of the subset of output operands that are of tensor type.
}],
/*retTy=*/"SmallVector<RankedTensorType>",
/*methodName=*/"getOutputTensorTypes",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
SmallVector<RankedTensorType> result;
result.reserve(getNumOutputs());
llvm::transform(getOutputTensorOperands(),
std::back_inserter(result),
[](OpOperand *opOperands) {
return opOperands->get().getType().cast<RankedTensorType>();
});
return result;
}]
>,
//===------------------------------------------------------------------===//
// Input and Output arguments handling.
//===------------------------------------------------------------------===//
InterfaceMethod<
/*desc=*/[{
Return the range over input and output operands.
}],
/*retTy=*/"OpOperandVector",
/*methodName=*/"getInputAndOutputOperands",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
int64_t numInputsAndOutputs = getNumInputsAndOutputs();
OpOperandVector result;
result.reserve(numInputsAndOutputs);
llvm::transform(
this->getOperation()->getOpOperands(),
std::back_inserter(result),
[](OpOperand &opOperand) { return &opOperand; });
return result;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return true if the payload uses the value loaded from `opOperand`. This
is useful to avoid loading from "write-only" memory that may be
uninitialized, as well as properly cloning "read-write" operands.
}],
/*retTy=*/"bool",
/*methodName=*/"payloadUsesValueFromOperand",
/*args=*/(ins "OpOperand *":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
unsigned bbArgNumber = opOperand->getOperandNumber();
// Init tensors have uses.
return !getBlock()->getArgument(bbArgNumber).use_empty();
}]
>,
InterfaceMethod<
/*desc=*/[{
Return true if `opOperand` is an input tensor.
}],
/*retTy=*/"bool",
/*methodName=*/"isInputTensor",
/*args=*/(ins "OpOperand *":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
if (!opOperand->get().getType().template isa<RankedTensorType>())
return false;
if (opOperand->getOperandNumber() < $_op.getNumInputs())
return true;
return false;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return true if `opOperand` is an output tensor.
}],
/*retTy=*/"bool",
/*methodName=*/"isOutputTensor",
/*args=*/(ins "OpOperand *":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
if (!opOperand->get().getType().template isa<RankedTensorType>())
return false;
if (opOperand->getOperandNumber() >= $_op.getNumInputs())
return true;
return false;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return true if `opOperand` is an init tensor. This is true when it is
an output tensor operand whose value is used in the payload region.
}],
/*retTy=*/"bool",
/*methodName=*/"isInitTensor",
/*args=*/(ins "OpOperand *":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
if (!$_op.isOutputTensor(opOperand))
return false;
return payloadUsesValueFromOperand(opOperand);
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the `opOperand` rank or zero for scalars.
}],
/*retTy=*/"int64_t",
/*methodName=*/"getRank",
/*args=*/(ins "OpOperand*":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(opOperand->getOwner() == this->getOperation());
if (auto shapedType =
opOperand->get().getType().template dyn_cast<ShapedType>())
return shapedType.getRank();
return 0;
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the output block arguments of the region.
}],
/*retTy=*/"Block::BlockArgListType",
/*methodName=*/"getRegionOutputArgs",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return getBlock()->getArguments().take_back(this->getNumOutputs());
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the `opOperand` shape or an empty vector for scalars.
}],
/*retTy=*/"ArrayRef<int64_t>",
/*methodName=*/"getShape",
/*args=*/(ins "OpOperand*":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(opOperand->getOwner() == this->getOperation());
if (auto shapedType =
opOperand->get().getType().template dyn_cast<ShapedType>())
return shapedType.getShape();
return {};
}]
>,
InterfaceMethod<
/*desc=*/[{
Return true if the `opOperand` is a scalar value.
}],
/*retTy=*/"bool",
/*methodName=*/"isScalar",
/*args=*/(ins "OpOperand*":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(opOperand->getOwner() == this->getOperation());
return !opOperand->get().getType().template isa<ShapedType>();
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the block argument for an `opOperand`.
}],
/*retTy=*/"BlockArgument",
/*methodName=*/"getTiedBlockArgument",
/*args=*/(ins "OpOperand *":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(opOperand->getOwner() == this->getOperation());
return getBlock()->getArgument(opOperand->getOperandNumber());
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the operand for a `blockArgument`.
}],
/*retTy=*/"OpOperand *",
/*methodName=*/"getTiedOpOperand",
/*args=*/(ins "BlockArgument":$blockArgument),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(blockArgument.getOwner() == getBlock());
return &this->getOperation()->getOpOperand(
blockArgument.getArgNumber());
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the input or output indexing map for `opOperand`.
}],
/*retTy=*/"AffineMap",
/*methodName=*/"getTiedIndexingMap",
/*args=*/(ins "OpOperand*":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(opOperand->getOwner() == this->getOperation());
auto indexingMaps =
$_op.getIndexingMaps().template getAsValueRange<AffineMapAttr>();
return *(indexingMaps.begin() + opOperand->getOperandNumber());
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the indexing map for a `result`.
}],
/*retTy=*/"AffineMap",
/*methodName=*/"getTiedIndexingMapForResult",
/*args=*/(ins "OpResult":$result),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(result.getOwner() == this->getOperation());
auto indexingMaps =
$_op.getIndexingMaps().template getAsValueRange<AffineMapAttr>();
return *(indexingMaps.begin() + getNumInputs() +
result.getResultNumber());
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the result tied to `opOperand`.
}],
/*retTy=*/"OpResult",
/*methodName=*/"getTiedOpResult",
/*args=*/(ins "OpOperand*":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(opOperand->getOwner() == this->getOperation());
int64_t resultIndex = opOperand->getOperandNumber() - getNumInputs();
assert(resultIndex >= 0 &&
resultIndex < this->getOperation()->getNumResults() );
return this->getOperation()->getResult(resultIndex);
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the value yielded by the region corresponding to an output
`opOperand`.
}],
/*retTy=*/"OpOperand *",
/*methodName=*/"getTiedYieldValue",
/*args=*/(ins "OpOperand*":$opOperand),
/*methodBody=*/"",
/*defaultImplementation=*/[{
assert(opOperand->getOwner() == this->getOperation());
int64_t resultIndex = opOperand->getOperandNumber() - getNumInputs();
assert(resultIndex >= 0 &&
resultIndex < this->getOperation()->getNumResults());
Operation *yieldOp = getBlock()->getTerminator();
return &yieldOp->getOpOperand(resultIndex);
}]
>,
//===------------------------------------------------------------------===//
// Other interface methods.
//===------------------------------------------------------------------===//
InterfaceMethod<
/*desc=*/[{
Return the single block constituting the body of the operation by
calling the getBody method on the concrete operation.
}],
/*retTy=*/"Block*",
/*methodName=*/"getBlock",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
// Assume the concrete operation implements the
// SingleBlockImplicitTerminator trait.
return $_op.getBody();
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the iterator types attribute within the current operation.
}],
/*retTy=*/"ArrayAttr",
/*methodName=*/"iterator_types",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return $_op.iterator_types();
}]
>,
InterfaceMethod<
/*desc=*/[{
Return true if the indexing map is depending on the current op instance.
This means that the indexing map is dynamically synthesized by using the
op instance's concrete attributes, instead of being static for all
instances of the same op kind.
}],
/*retTy=*/"bool",
/*methodName=*/"hasDynamicIndexingMaps",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{ return false; }]
>,
InterfaceMethod<
/*desc=*/[{
Verify all attributes used by indexing maps are valid.
}],
/*retTy=*/"LogicalResult",
/*methodName=*/"verifyIndexingMapRequiredAttributes",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{ return success(); }]
>,
InterfaceMethod<
/*desc=*/[{
Return the indexing maps attribute within the current operation.
}],
/*retTy=*/"ArrayAttr",
/*methodName=*/"getIndexingMaps"
>,
InterfaceMethod<
/*desc=*/[{
Return the indexing maps within the current operation.
}],
/*retTy=*/"SmallVector<AffineMap>",
/*methodName=*/"getIndexingMapsArray",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
auto range = $_op.getIndexingMaps()
.template getAsValueRange<AffineMapAttr>();
return {range.begin(), range.end()};
}]
>,
InterfaceMethod<
/*desc=*/[{
Return true if any of the operands has a dynamic shape.
}],
/*retTy=*/"bool",
/*methodName=*/"hasDynamicShape",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return llvm::any_of(getStaticShape(), ShapedType::isDynamic);
}]
>,
InterfaceMethod<
/*desc=*/[{
Return whether the op has only MemRef input and outputs.
}],
/*retTy=*/"bool",
/*methodName=*/"hasBufferSemantics",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return this->getOperation()->getNumResults() == 0 &&
llvm::all_of(this->getOperation()->getOpOperands(),
[&](OpOperand &opOperand) {
return isScalar(&opOperand) ||
opOperand.get().getType().template isa<MemRefType>();
});
}]
>,
InterfaceMethod<
/*desc=*/[{
Return whether the op has only RankedTensor input and outputs.
}],
/*retTy=*/"bool",
/*methodName=*/"hasTensorSemantics",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return llvm::all_of(this->getOperation()->getOpOperands(),
[&](OpOperand &opOperand) {
return isScalar(&opOperand) ||
opOperand.get().getType().template isa<RankedTensorType>();
});
}]
>,
InterfaceMethod<
/*desc=*/[{
Return the name registered for this op when lowering to an external
library call.
}],
/*retTy=*/"std::string",
/*methodName=*/"getLibraryCallName",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return $_op.getLibraryCallName();
}]
>,
InterfaceMethod<
/*desc=*/[{
Return whether the op accesses the iteration indices.
}],
/*retTy=*/"bool",
/*methodName=*/"hasIndexSemantics",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/""
>,
//===------------------------------------------------------------------===//
// Linalg generalization hooks.
//===------------------------------------------------------------------===//
InterfaceMethod<
/*desc=*/[{
Hook to provide a custom AffineMap used to compute all the operand
subshapes given loop bounds. This is used to answer the question: "given
an iteration space over the codomain, what are the subshapes of the
operands involved in the computation".
The default behavior is to just concatenate all the indexing maps.
A custom AffineMap allows providing a map that can be used to
compute subshapes even in cases where the concatenation of indexing maps
(i.e. the data traversal order) is not a simple permutation of the loop
traversal order. It is then possible to define ops with skewed data
traversal order for which we can still easily compute hyperrectangular
loop bounds and subviews.
}],
/*retTy=*/"AffineMap",
/*methodName=*/"getLoopsToShapesMap",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
auto maps = $_op.getIndexingMapsArray();
return concatAffineMaps(maps);
}]
>,
InterfaceMethod<
/*desc=*/[{
Hook to provide a custom AffineMap used to construct the
hyperrectangular loop iteration space given all the operand subshapes.
This is used to answer the question:
"Given a list of operand ranges, what is the subportion of the iteration
space involved in the computation".
This is the inverse problem of `getLoopsToShapesMap`.
Return the empty AffineMap when such an AffineMap cannot be constructed.
The default behavior is based on a very simple inference procedure that
only works with permutation affine maps.
A more advanced Tensor-Comprehension like inference is possible but has
proven to be ambiguous in unfavorable case.
A safer and more robust alternative is to allow each op to define
its own AffineMap.
}],
/*retTy=*/"AffineMap",
/*methodName=*/"getShapesToLoopsMap",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return inversePermutation(getLoopsToShapesMap());
}]
>,
InterfaceMethod<
/*desc=*/[{
Checks if the given operands can be dropped, and the remaining
operands can still compute the bounds of the op.
}],
/*retTy=*/"bool",
/*methodName=*/"canOpOperandsBeDropped",
/*args=*/(ins "ArrayRef<OpOperand *>":$droppedOperands),
/*methodBody=*/"",
/*defaultImplementation=*/[{
return detail::canOpOperandsBeDroppedImpl($_op, droppedOperands);
}]
>,
InterfaceMethod<
/*desc=*/[{
Like `getShape`, but only returns statically-known information, without
generating any new IR. For each shape dimension, returns >=0 if that
dimension is statically known, or ShapeType::kDynamicSize otherwise.
}],
/*retTy=*/"SmallVector<int64_t>",
/*methodName=*/"getStaticShape",
/*args=*/(ins),
/*methodBody=*/"",
/*defaultImplementation=*/[{
SmallVector<int64_t> res;
for (OpOperand *opOperand : getInputAndOutputOperands())
llvm::append_range(res, getShape(opOperand));
return res;