84cd51bb97
The old "pointer/index" names often cause confusion since these names clash with names of unrelated things in MLIR; so this change rectifies this by changing everything to use "position/coordinate" terminology instead.
In addition to the basic terminology, there have also been various conventions for making certain distinctions like: (1) the overall storage for coordinates in the sparse-tensor, vs the particular collection of coordinates of a given element; and (2) particular coordinates given as a `Value` or `TypedValue<MemRefType>`, vs particular coordinates given as `ValueRange` or similar. I have striven to maintain these distinctions
as follows:
* "p/c" are used for individual position/coordinate values, when there is no risk of confusion. (Just like we use "d/l" to abbreviate "dim/lvl".)
* "pos/crd" are used for individual position/coordinate values, when a longer name is helpful to avoid ambiguity or to form compound names (e.g., "parentPos"). (Just like we use "dim/lvl" when we need a longer form of "d/l".)
I have also used these forms for a handful of compound names where the old name had been using a three-letter form previously, even though a longer form would be more appropriate. I've avoided renaming these to use a longer form purely for expediency sake, since changing them would require a cascade of other renamings. They should be updated to follow the new naming scheme, but that can be done in future patches.
* "coords" is used for the complete collection of crd values associated with a single element. In the runtime library this includes both `std::vector` and raw pointer representations. In the compiler, this is used specifically for buffer variables with C++ type `Value`, `TypedValue<MemRefType>`, etc.
The bare form "coords" is discouraged, since it fails to make the dim/lvl distinction; so the compound names "dimCoords/lvlCoords" should be used instead. (Though there may exist a rare few cases where is is appropriate to be intentionally ambiguous about what coordinate-space the coords live in; in which case the bare "coords" is appropriate.)
There is seldom the need for the pos variant of this notion. In most circumstances we use the term "cursor", since the same buffer is reused for a 'moving' pos-collection.
* "dcvs/lcvs" is used in the compiler as the `ValueRange` analogue of "dimCoords/lvlCoords". (The "vs" stands for "`Value`s".) I haven't found the need for it, but "pvs" would be the obvious name for a pos-`ValueRange`.
The old "ind"-vs-"ivs" naming scheme does not seem to have been sustained in more recent code, which instead prefers other mnemonics (e.g., adding "Buf" to the end of the names for `TypeValue<MemRefType>`). I have cleaned up a lot of these to follow the "coords"-vs-"cvs" naming scheme, though haven't done an exhaustive cleanup.
* "positions/coordinates" are used for larger collections of pos/crd values; in particular, these are used when referring to the complete sparse-tensor storage components.
I also prefer to use these unabbreviated names in the documentation, unless there is some specific reason why using the abbreviated forms helps resolve ambiguity.
In addition to making this terminology change, this change also does some cleanup along the way:
* correcting the dim/lvl terminology in certain places.
* adding `const` when it requires no other code changes.
* miscellaneous cleanup that was entailed in order to make the proper distinctions. Most of these are in CodegenUtils.{h,cpp}
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D144773
330 lines
12 KiB
C++
330 lines
12 KiB
C++
//===- BufferizableOpInterfaceImpl.cpp - Impl. of BufferizableOpInterface -===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// These BufferizableOpInterface implementations provide analysis-related
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// interface methods only. They are getting bufferized by the
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// SparseTensorConversion pass.
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#include "mlir/Dialect/SparseTensor/Transforms/BufferizableOpInterfaceImpl.h"
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#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
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#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
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#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
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#include "mlir/IR/Dialect.h"
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#include "mlir/IR/Operation.h"
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#include "mlir/IR/PatternMatch.h"
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using namespace mlir::bufferization;
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using namespace mlir::sparse_tensor;
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namespace mlir {
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namespace sparse_tensor {
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namespace {
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struct ConcatenateOpInterface
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: public BufferizableOpInterface::ExternalModel<
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ConcatenateOpInterface, sparse_tensor::ConcatenateOp> {
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bool bufferizesToAllocation(Operation *op, OpResult opResult) const {
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return true;
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}
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return {};
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}
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bool isWritable(Operation *op, Value value,
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const AnalysisState &state) const {
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return true;
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}
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};
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struct ConvertOpInterface
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: public BufferizableOpInterface::ExternalModel<ConvertOpInterface,
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sparse_tensor::ConvertOp> {
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bool bufferizesToAllocation(Operation *op, OpResult opResult) const {
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// ConvertOps may allocate. (Unless they convert between two identical
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// types, then they fold away.)
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return true;
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}
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return {};
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}
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bool isWritable(Operation *op, Value value,
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const AnalysisState &state) const {
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return true;
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}
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};
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struct LoadOpInterface
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: public BufferizableOpInterface::ExternalModel<LoadOpInterface,
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sparse_tensor::LoadOp> {
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return false;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return {{op->getOpResult(0), BufferRelation::Equivalent}};
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}
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};
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struct NewOpInterface
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: public BufferizableOpInterface::ExternalModel<NewOpInterface,
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sparse_tensor::NewOp> {
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bool resultBufferizesToMemoryWrite(Operation *op, OpResult opResult,
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const AnalysisState &state) const {
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// NewOps allocate but do not write.
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return false;
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}
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bool bufferizesToAllocation(Operation *op, OpResult opResult) const {
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return true;
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}
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};
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struct PackOpInterface
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: public BufferizableOpInterface::ExternalModel<PackOpInterface,
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sparse_tensor::PackOp> {
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bool bufferizesToAllocation(Operation *op, OpResult opResult) const {
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// PackOp reuses all the buffers instead of allocating new ones
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return false;
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}
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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assert(op->getNumResults() == 1);
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assert(isUniqueCOOType(op->getResultTypes()[0].cast<RankedTensorType>()));
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// PackOp reuses the input tensors as values/coordinates instead of
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// creating new ones when packing into a COO format.
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return {{op->getOpResult(0), BufferRelation::Equivalent}};
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}
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BufferRelation bufferRelation(Operation *oo, OpResult opResult,
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const AnalysisState &state) const {
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return BufferRelation::Unknown;
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}
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};
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struct UnpackOpInterface
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: public BufferizableOpInterface::ExternalModel<UnpackOpInterface,
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sparse_tensor::UnpackOp> {
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bool bufferizesToAllocation(Operation *op, OpResult opResult) const {
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// Similar to InsertOp, reallocation is not considered to allocate a new
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// piece of memory.
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return false;
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}
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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// Conceptually, UnpackOp equals to a list of toCoordinates/toValueOp
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return {};
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}
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};
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struct InsertOpInterface
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: public BufferizableOpInterface::ExternalModel<InsertOpInterface,
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sparse_tensor::InsertOp> {
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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// InsertOp writes to memory.
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return true;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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// InsertOp returns an alias of its operand.
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assert(op->getNumResults() == 1);
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return {{op->getOpResult(0), BufferRelation::Equivalent}};
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}
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};
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struct NumberOfEntriesOpInterface
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: public BufferizableOpInterface::ExternalModel<
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NumberOfEntriesOpInterface, sparse_tensor::NumberOfEntriesOp> {
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return {};
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}
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};
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struct ToCoordinatesBufferOpInterface
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: public BufferizableOpInterface::ExternalModel<
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ToCoordinatesBufferOpInterface,
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sparse_tensor::ToCoordinatesBufferOp> {
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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// Potential writes into memory through the result of
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// `sparse_tensor.coordinates` are not considered.
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return {};
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}
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};
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struct ToCoordinatesOpInterface
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: public BufferizableOpInterface::ExternalModel<
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ToCoordinatesOpInterface, sparse_tensor::ToCoordinatesOp> {
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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// Potential writes into memory through the result of
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// `sparse_tensor.coordinates` are not considered.
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return {};
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}
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};
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struct ToPositionsOpInterface
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: public BufferizableOpInterface::ExternalModel<
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ToPositionsOpInterface, sparse_tensor::ToPositionsOp> {
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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// Potential writes into memory through the result of
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// `sparse_tensor.positions` are not considered.
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return {};
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}
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};
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struct ToValuesOpInterface
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: public BufferizableOpInterface::ExternalModel<ToValuesOpInterface,
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sparse_tensor::ToValuesOp> {
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bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return true;
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}
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bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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// Potential writes into memory through the result of sparse_tensor.values
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// are not considered.
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return false;
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}
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AliasingOpResultList getAliasingOpResults(Operation *op, OpOperand &opOperand,
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const AnalysisState &state) const {
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return {};
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}
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};
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} // namespace
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} // namespace sparse_tensor
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} // namespace mlir
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void mlir::sparse_tensor::registerBufferizableOpInterfaceExternalModels(
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DialectRegistry ®istry) {
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registry.addExtension(+[](MLIRContext *ctx,
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sparse_tensor::SparseTensorDialect *dialect) {
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sparse_tensor::ConcatenateOp::attachInterface<ConcatenateOpInterface>(*ctx);
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sparse_tensor::ConvertOp::attachInterface<ConvertOpInterface>(*ctx);
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sparse_tensor::LoadOp::attachInterface<LoadOpInterface>(*ctx);
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sparse_tensor::NewOp::attachInterface<NewOpInterface>(*ctx);
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sparse_tensor::InsertOp::attachInterface<InsertOpInterface>(*ctx);
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sparse_tensor::NumberOfEntriesOp::attachInterface<
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NumberOfEntriesOpInterface>(*ctx);
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sparse_tensor::PackOp::attachInterface<PackOpInterface>(*ctx);
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sparse_tensor::UnpackOp::attachInterface<UnpackOpInterface>(*ctx);
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sparse_tensor::ToCoordinatesBufferOp::attachInterface<
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ToCoordinatesBufferOpInterface>(*ctx);
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sparse_tensor::ToCoordinatesOp::attachInterface<ToCoordinatesOpInterface>(
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*ctx);
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sparse_tensor::ToPositionsOp::attachInterface<ToPositionsOpInterface>(*ctx);
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sparse_tensor::ToValuesOp::attachInterface<ToValuesOpInterface>(*ctx);
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});
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}
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