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llvm/mlir/lib/Dialect/Vector/Transforms/BufferizableOpInterfaceImpl.cpp

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//===- BufferizableOpInterfaceImpl.cpp - Impl. of BufferizableOpInterface -===//
//
// 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
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Vector/Transforms/BufferizableOpInterfaceImpl.h"
#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
#include "mlir/Dialect/Bufferization/IR/DstBufferizableOpInterfaceImpl.h"
#include "mlir/Dialect/Vector/IR/VectorOps.h"
#include "mlir/IR/Dialect.h"
#include "mlir/IR/Operation.h"
using namespace mlir;
using namespace mlir::bufferization;
using namespace mlir::vector;
namespace mlir {
namespace vector {
namespace {
/// Bufferization of vector.transfer_read. Replaced with a new
/// vector.transfer_read that operates on a memref.
struct TransferReadOpInterface
: public BufferizableOpInterface::ExternalModel<TransferReadOpInterface,
vector::TransferReadOp> {
bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
[mlir] Move casting calls from methods to function calls The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-05-08 16:33:54 +02:00
assert(isa<RankedTensorType>(opOperand.get().getType()) &&
"only tensor types expected");
return true;
}
bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
[mlir] Move casting calls from methods to function calls The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-05-08 16:33:54 +02:00
assert(isa<RankedTensorType>(opOperand.get().getType()) &&
"only tensor types expected");
return false;
}
AliasingValueList getAliasingValues(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
return {};
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto readOp = cast<vector::TransferReadOp>(op);
[mlir] Move casting calls from methods to function calls The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-05-08 16:33:54 +02:00
assert(isa<TensorType>(readOp.getShapedType()) &&
"only tensor types expected");
FailureOr<Value> buffer = getBuffer(rewriter, readOp.getSource(), options);
if (failed(buffer))
return failure();
replaceOpWithNewBufferizedOp<vector::TransferReadOp>(
rewriter, readOp, readOp.getVectorType(), *buffer, readOp.getIndices(),
readOp.getPermutationMap(), readOp.getPadding(), readOp.getMask(),
readOp.getInBoundsAttr());
return success();
}
};
/// Bufferization of vector.transfer_write. Replace with a new
/// vector.transfer_write that operates on a memref.
///
/// Note: DstBufferizableOpInterfaceExternalModel provides many default method
/// implementations for DestinationStyle ops.
struct TransferWriteOpInterface
: public DstBufferizableOpInterfaceExternalModel<TransferWriteOpInterface,
vector::TransferWriteOp> {
bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
auto writeOp = cast<vector::TransferWriteOp>(op);
// Does not bufferize to a memory read if the vector completely overwrites
// the buffer.
// Destination must have static shape.
if (!writeOp.getShapedType().hasStaticShape())
return true;
// All offsets must be 0.
for (Value offset : writeOp.getIndices()) {
if (getConstantIntValue(offset) != 0)
return true;
}
// There is no mask.
if (writeOp.isMasked())
return true;
// Must write at least the full dimension size.
for (auto [d0, d1] : llvm::zip(writeOp.getShapedType().getShape(),
writeOp.getVectorType().getShape())) {
if (d0 > d1)
return true;
}
return false;
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto writeOp = cast<vector::TransferWriteOp>(op);
[mlir] Move casting calls from methods to function calls The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-05-08 16:33:54 +02:00
assert(isa<TensorType>(writeOp.getShapedType()) &&
"only tensor types expected");
// Create a new transfer_write on buffer that doesn't have a return value.
FailureOr<Value> resultBuffer =
getBuffer(rewriter, writeOp.getSource(), options);
if (failed(resultBuffer))
return failure();
rewriter.create<vector::TransferWriteOp>(
writeOp.getLoc(), writeOp.getVector(), *resultBuffer,
writeOp.getIndices(), writeOp.getPermutationMapAttr(),
writeOp.getMask(), writeOp.getInBoundsAttr());
replaceOpWithBufferizedValues(rewriter, op, *resultBuffer);
return success();
}
};
/// Bufferization of vector.gather. Replaced with a new vector.gather that
/// operates on a memref.
struct GatherOpInterface
: public BufferizableOpInterface::ExternalModel<GatherOpInterface,
vector::GatherOp> {
bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
[mlir] Move casting calls from methods to function calls The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-05-08 16:33:54 +02:00
assert(isa<RankedTensorType>(opOperand.get().getType()) &&
"only tensor types expected");
return true;
}
bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
[mlir] Move casting calls from methods to function calls The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-05-08 16:33:54 +02:00
assert(isa<RankedTensorType>(opOperand.get().getType()) &&
"only tensor types expected");
return false;
}
AliasingValueList getAliasingValues(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
return {};
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto gatherOp = cast<vector::GatherOp>(op);
[mlir] Move casting calls from methods to function calls The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-05-08 16:33:54 +02:00
assert(isa<TensorType>(gatherOp.getBaseType()) &&
"only tensor types expected");
FailureOr<Value> buffer = getBuffer(rewriter, gatherOp.getBase(), options);
if (failed(buffer))
return failure();
replaceOpWithNewBufferizedOp<vector::GatherOp>(
rewriter, gatherOp, gatherOp.getVectorType(), *buffer,
gatherOp.getIndices(), gatherOp.getIndexVec(), gatherOp.getMask(),
gatherOp.getPassThru());
return success();
}
};
/// Bufferization of vector.mask. Replaced with a new vector.mask that
/// operates on a memref.
struct MaskOpInterface
: public BufferizableOpInterface::ExternalModel<MaskOpInterface,
vector::MaskOp> {
AliasingOpOperandList
getAliasingOpOperands(Operation *op, Value value,
const AnalysisState &state) const {
// MaskOps do not have tensor OpOperands. The yielded values are the result
// of the wrapped op.
auto maskOp = cast<vector::MaskOp>(op);
size_t resultNum = std::distance(op->getOpResults().begin(),
llvm::find(op->getOpResults(), value));
auto yieldOp =
cast<vector::YieldOp>(maskOp.getMaskRegion().front().getTerminator());
[mlir][bufferization] Improve aliasing OpOperand/OpResult property `getAliasingOpOperands`/`getAliasingOpResults` now encodes OpOperand/OpResult, buffer relation and a degree of certainty. E.g.: ``` // aliasingOpOperands(%r) = {(%t, EQUIV, DEFINITE)} // aliasingOpResults(%t) = {(%r, EQUIV, DEFINITE)} %r = tensor.insert %f into %t[%idx] : tensor<?xf32> // aliasingOpOperands(%r) = {(%t0, EQUIV, MAYBE), (%t1, EQUIV, MAYBE)} // aliasingOpResults(%t0) = {(%r, EQUIV, MAYBE)} // aliasingOpResults(%t1) = {(%r, EQUIV, MAYBE)} %r = arith.select %c, %t0, %t1 : tensor<?xf32> ``` `BufferizableOpInterface::bufferRelation` is removed, as it is now part of `getAliasingOpOperands`/`getAliasingOpResults`. This change allows for better analysis, in particular wrt. equivalence. This allows additional optimizations and better error checking (which is sometimes overly conservative). Examples: * EmptyTensorElimination can eliminate `tensor.empty` inside `scf.if` blocks. This requires a modeling of equivalence: It is not a per-OpResult property anymore. Instead, it can be specified for each OpOperand and OpResult. This is important because `tensor.empty` may be eliminated only if all values on the SSA use-def chain to the final consumer (`tensor.insert_slice`) are equivalent. * The detection of "returning allocs from a block" can be improved. (Addresses a TODO in `assertNoAllocsReturned`.) This allows us to bufferize IR such as "yielding a `tensor.extract_slice` result from an `scf.if` branch", which currently fails to bufferize because the alloc detection is too conservative. * Better bufferization of loops. Aliases of the iter_arg can be yielded (even if they are not equivalent) without having to realloc and copy the entire buffer on each iteration. The above-mentioned examples are not yet implemented with this change. This change just improves the BufferizableOpInterface, its implementations and related helper functions, so that better aliasing information is available for each op. Differential Revision: https://reviews.llvm.org/D142129
2023-02-09 11:32:09 +01:00
return {{&yieldOp->getOpOperand(resultNum), BufferRelation::Equivalent}};
}
LogicalResult resolveConflicts(Operation *op, RewriterBase &rewriter,
const AnalysisState &state) const {
auto bufferizableOp = cast<BufferizableOpInterface>(op);
if (failed(bufferizableOp.resolveTensorOpOperandConflicts(rewriter, state)))
return failure();
// TODO: Remove this function when vector.mask bodies can bufferize
// out-of-place. This is currently not supported because yielding allocs
// from a block leads to a memory leak and because vector.mask supports only
// a single op in its body.
auto maskOp = cast<vector::MaskOp>(op);
if (!maskOp.getMaskRegion()
.front()
.getOps<bufferization::AllocTensorOp>()
.empty())
return op->emitOpError("body must bufferize in-place");
return success();
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto maskOp = cast<vector::MaskOp>(op);
// Do not bufferize if the masked op is not bufferizable.
Operation *maskedOp = maskOp.getMaskableOp();
if (!options.dynCastBufferizableOp(maskedOp))
return success();
// Update the terminator: Drop all operands that are not results of the
// masked op.
auto yieldOp =
cast<vector::YieldOp>(maskOp.getMaskRegion().front().getTerminator());
SmallVector<Value> newReturnValues(maskOp->getNumResults(), Value());
SmallVector<Value> newYieldedValues;
for (const auto &it : llvm::enumerate(yieldOp.getOperands())) {
2024-01-12 22:08:29 -08:00
if (llvm::is_contained(maskedOp->getOpResults(), it.value())) {
newYieldedValues.push_back(it.value());
} else {
// This used to be a tensor result of the masked op, but is now a memref
// that is defined outside of the vector.mask op.
newReturnValues[it.index()] = it.value();
}
}
rewriter.modifyOpInPlace(yieldOp, [&]() {
yieldOp.getOperandsMutable().assign(newYieldedValues);
});
// Create a new vector.mask op.
ValueRange newYieldedValuesRange(newYieldedValues);
TypeRange newResultTypes(newYieldedValuesRange);
auto newOp = rewriter.create<vector::MaskOp>(
op->getLoc(), newResultTypes, maskOp.getMask(), maskOp.getPassthru(),
/*maskableOp=*/nullptr,
/*maskRegionBuilder=*/[](OpBuilder &b, Operation *) {});
newOp.getRegion().takeBody(maskOp.getMaskRegion());
// Replace all uses of the old vector.mask op.
int idx = 0;
for (int i = 0; i < static_cast<int>(maskOp->getNumResults()); ++i) {
if (!newReturnValues[i])
newReturnValues[i] = newOp->getResult(idx++);
}
replaceOpWithBufferizedValues(rewriter, maskOp, newReturnValues);
return success();
}
};
/// Bufferization of vector.yield. Replaced with a new vector.yield that
/// operates on a memref.
struct YieldOpInterface
: public BufferizableOpInterface::ExternalModel<YieldOpInterface,
vector::YieldOp> {
bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
return true;
}
bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
return false;
}
AliasingValueList getAliasingValues(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
[mlir][bufferization] Improve aliasing OpOperand/OpResult property `getAliasingOpOperands`/`getAliasingOpResults` now encodes OpOperand/OpResult, buffer relation and a degree of certainty. E.g.: ``` // aliasingOpOperands(%r) = {(%t, EQUIV, DEFINITE)} // aliasingOpResults(%t) = {(%r, EQUIV, DEFINITE)} %r = tensor.insert %f into %t[%idx] : tensor<?xf32> // aliasingOpOperands(%r) = {(%t0, EQUIV, MAYBE), (%t1, EQUIV, MAYBE)} // aliasingOpResults(%t0) = {(%r, EQUIV, MAYBE)} // aliasingOpResults(%t1) = {(%r, EQUIV, MAYBE)} %r = arith.select %c, %t0, %t1 : tensor<?xf32> ``` `BufferizableOpInterface::bufferRelation` is removed, as it is now part of `getAliasingOpOperands`/`getAliasingOpResults`. This change allows for better analysis, in particular wrt. equivalence. This allows additional optimizations and better error checking (which is sometimes overly conservative). Examples: * EmptyTensorElimination can eliminate `tensor.empty` inside `scf.if` blocks. This requires a modeling of equivalence: It is not a per-OpResult property anymore. Instead, it can be specified for each OpOperand and OpResult. This is important because `tensor.empty` may be eliminated only if all values on the SSA use-def chain to the final consumer (`tensor.insert_slice`) are equivalent. * The detection of "returning allocs from a block" can be improved. (Addresses a TODO in `assertNoAllocsReturned`.) This allows us to bufferize IR such as "yielding a `tensor.extract_slice` result from an `scf.if` branch", which currently fails to bufferize because the alloc detection is too conservative. * Better bufferization of loops. Aliases of the iter_arg can be yielded (even if they are not equivalent) without having to realloc and copy the entire buffer on each iteration. The above-mentioned examples are not yet implemented with this change. This change just improves the BufferizableOpInterface, its implementations and related helper functions, so that better aliasing information is available for each op. Differential Revision: https://reviews.llvm.org/D142129
2023-02-09 11:32:09 +01:00
return {{op->getParentOp()->getResult(opOperand.getOperandNumber()),
BufferRelation::Equivalent}};
}
bool mustBufferizeInPlace(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
// Yield operands always bufferize inplace. Otherwise, an alloc + copy
// may be generated inside the block. We should not return/yield allocations
// when possible.
return true;
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto yieldOp = cast<vector::YieldOp>(op);
// Only supported as a vector.mask terminator.
auto maskOp = dyn_cast<vector::MaskOp>(yieldOp->getParentOp());
if (!maskOp)
return yieldOp->emitError("unsupported vector::YieldOp parent");
// Do not bufferize if the masked op is not bufferizable.
Operation *maskedOp = &maskOp.getMaskRegion().front().front();
if (!options.dynCastBufferizableOp(maskedOp))
return success();
// Create a new terminator with the same number of operands. Some of these
// may get dropped during the bufferization of vector.mask.
SmallVector<Value> newResults;
for (Value value : yieldOp.getOperands()) {
[mlir] Move casting calls from methods to function calls The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-05-08 16:33:54 +02:00
if (isa<TensorType>(value.getType())) {
FailureOr<Value> maybeBuffer = getBuffer(rewriter, value, options);
if (failed(maybeBuffer))
return failure();
newResults.push_back(*maybeBuffer);
} else {
newResults.push_back(value);
}
}
replaceOpWithNewBufferizedOp<vector::YieldOp>(rewriter, op, newResults);
return success();
}
};
} // namespace
} // namespace vector
} // namespace mlir
void mlir::vector::registerBufferizableOpInterfaceExternalModels(
DialectRegistry &registry) {
registry.addExtension(+[](MLIRContext *ctx, vector::VectorDialect *dialect) {
TransferReadOp::attachInterface<TransferReadOpInterface>(*ctx);
TransferWriteOp::attachInterface<TransferWriteOpInterface>(*ctx);
GatherOp::attachInterface<GatherOpInterface>(*ctx);
MaskOp::attachInterface<MaskOpInterface>(*ctx);
YieldOp::attachInterface<YieldOpInterface>(*ctx);
});
}