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BufferizableOpInterfaceImpl.cpp
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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/SCF/Transforms/BufferizableOpInterfaceImpl.h"
#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
#include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Utils/StaticValueUtils.h"
#include "mlir/IR/Dialect.h"
#include "mlir/IR/Operation.h"
#include "mlir/IR/PatternMatch.h"
using namespace mlir;
using namespace mlir::bufferization;
using namespace mlir::scf;
namespace mlir {
namespace scf {
namespace {
// bufferization.to_memref is not allowed to change the rank.
static void ensureToMemrefOpIsValid(Value tensor, Type memrefType) {
#ifndef NDEBUG
auto rankedTensorType = tensor.getType().dyn_cast<RankedTensorType>();
assert((!rankedTensorType || (memrefType.cast<MemRefType>().getRank() ==
rankedTensorType.getRank())) &&
"to_memref would be invalid: mismatching ranks");
#endif
}
/// Bufferization of scf.execute_region. Can be analyzed, but bufferization not
/// fully implemented at the moment.
struct ExecuteRegionOpInterface
: public BufferizableOpInterface::ExternalModel<ExecuteRegionOpInterface,
scf::ExecuteRegionOp> {
SmallVector<OpOperand *>
getAliasingOpOperand(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// ExecuteRegionOps do not have tensor OpOperands. The yielded value can be
// any SSA value that is in scope. To allow for use-def chain traversal
// through ExecuteRegionOps in the analysis, the corresponding yield value
// is considered to be aliasing with the result.
auto executeRegionOp = cast<scf::ExecuteRegionOp>(op);
size_t resultNum = std::distance(op->getOpResults().begin(),
llvm::find(op->getOpResults(), opResult));
// TODO: Support multiple blocks.
assert(executeRegionOp.getRegion().getBlocks().size() == 1 &&
"expected exactly 1 block");
auto yieldOp = dyn_cast<scf::YieldOp>(
executeRegionOp.getRegion().front().getTerminator());
assert(yieldOp && "expected scf.yield terminator in scf.execute_region");
return {&yieldOp->getOpOperand(resultNum)};
}
// TODO: For better bufferization results, this could return `true` only if
// there is a memory write in the region.
bool isMemoryWrite(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// Similar to scf.if, results of this op are always considered memory writes
// in the analysis. This is a useful pattern for all ops that have tensor
// OpResults but no tensor OpOperands. By default, `isMemoryWrite` is
// implemented in terms of `bufferizesToMemoryWrite`, which does not work on
// ops without OpOperands.
return true;
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto executeRegionOp = cast<scf::ExecuteRegionOp>(op);
assert(executeRegionOp.getRegion().getBlocks().size() == 1 &&
"only 1 block supported");
auto yieldOp =
cast<scf::YieldOp>(executeRegionOp.getRegion().front().getTerminator());
TypeRange newResultTypes(yieldOp.getResults());
// Create new op and move over region.
auto newOp =
rewriter.create<scf::ExecuteRegionOp>(op->getLoc(), newResultTypes);
newOp.getRegion().takeBody(executeRegionOp.getRegion());
// Update all uses of the old op.
rewriter.setInsertionPointAfter(newOp);
SmallVector<Value> newResults;
for (const auto &it : llvm::enumerate(executeRegionOp->getResultTypes())) {
if (it.value().isa<TensorType>()) {
newResults.push_back(rewriter.create<bufferization::ToTensorOp>(
executeRegionOp.getLoc(), newOp->getResult(it.index())));
} else {
newResults.push_back(newOp->getResult(it.index()));
}
}
// Replace old op.
rewriter.replaceOp(executeRegionOp, newResults);
return success();
}
BufferRelation bufferRelation(Operation *op, OpResult opResult,
const AnalysisState &state) const {
return BufferRelation::Equivalent;
}
};
/// Bufferization of scf.if. Replace with a new scf.if that yields memrefs.
struct IfOpInterface
: public BufferizableOpInterface::ExternalModel<IfOpInterface, scf::IfOp> {
SmallVector<OpOperand *>
getAliasingOpOperand(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// IfOps do not have tensor OpOperands. The yielded value can be any SSA
// value that is in scope. To allow for use-def chain traversal through
// IfOps in the analysis, both corresponding yield values from the then/else
// branches are considered to be aliasing with the result.
auto ifOp = cast<scf::IfOp>(op);
size_t resultNum = std::distance(op->getOpResults().begin(),
llvm::find(op->getOpResults(), opResult));
return {&ifOp.thenYield()->getOpOperand(resultNum),
&ifOp.elseYield()->getOpOperand(resultNum)};
}
// TODO: For better bufferization results, this could return `true` only if
// there is a memory write in one (or both) of the branches. Since this is not
// allowed at the moment, we should never encounter scf.ifs that yield
// unmodified tensors. Such scf.yield ops could just fold away.
bool isMemoryWrite(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// IfOp results are always considered memory writes in the analysis. This
// design decision simplifies the analysis considerably. E.g., consider the
// following test case:
//
// %0 = "some_writing_op" : tensor<?xf32>
// %r = scf.if %c -> (tensor<?xf32>) {
// scf.yield %0
// } else {
// %1 = "another_writing_op"(%0) : tensor<?xf32>
// }
// "some_reading_op"(%r)
//
// "another_writing_op" in the above example should be able to bufferize
// inplace in the absence of another read of %0. However, if the scf.if op
// would not be considered a "write", the analysis would detect the
// following conflict:
//
// * read = some_reading_op
// * lastWrite = %0 (Note: The last write of %r would be a set: {%0, %1}.)
// * conflictingWrite = %1
//
// For more details, check the "scf.IfOp" section of the design document.
return true;
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
OpBuilder::InsertionGuard g(rewriter);
auto ifOp = cast<scf::IfOp>(op);
auto thenYieldOp = cast<scf::YieldOp>(ifOp.thenBlock()->getTerminator());
auto elseYieldOp = cast<scf::YieldOp>(ifOp.elseBlock()->getTerminator());
// Reconcile type mismatches between then/else branches by inserting memref
// casts.
SmallVector<Value> thenResults, elseResults;
bool insertedCast = false;
for (unsigned i = 0; i < thenYieldOp.getResults().size(); ++i) {
Value thenValue = thenYieldOp.getResults()[i];
Value elseValue = elseYieldOp.getResults()[i];
if (thenValue.getType() == elseValue.getType()) {
thenResults.push_back(thenValue);
elseResults.push_back(elseValue);
continue;
}
// Type mismatch between then/else yield value. Cast both to a memref type
// with a fully dynamic layout map.
auto thenMemrefType = thenValue.getType().cast<BaseMemRefType>();
auto elseMemrefType = elseValue.getType().cast<BaseMemRefType>();
if (thenMemrefType.getMemorySpaceAsInt() !=
elseMemrefType.getMemorySpaceAsInt())
return op->emitError("inconsistent memory space on then/else branches");
rewriter.setInsertionPoint(thenYieldOp);
BaseMemRefType memrefType = getMemRefTypeWithFullyDynamicLayout(
ifOp.getResultTypes()[i].cast<TensorType>(),
thenMemrefType.getMemorySpaceAsInt());
thenResults.push_back(rewriter.create<memref::CastOp>(
thenYieldOp.getLoc(), memrefType, thenValue));
rewriter.setInsertionPoint(elseYieldOp);
elseResults.push_back(rewriter.create<memref::CastOp>(
elseYieldOp.getLoc(), memrefType, elseValue));
insertedCast = true;
}
if (insertedCast) {
rewriter.setInsertionPoint(thenYieldOp);
rewriter.replaceOpWithNewOp<scf::YieldOp>(thenYieldOp, thenResults);
rewriter.setInsertionPoint(elseYieldOp);
rewriter.replaceOpWithNewOp<scf::YieldOp>(elseYieldOp, elseResults);
}
// Create new op.
rewriter.setInsertionPoint(ifOp);
ValueRange resultsValueRange(thenResults);
TypeRange newTypes(resultsValueRange);
auto newIfOp =
rewriter.create<scf::IfOp>(ifOp.getLoc(), newTypes, ifOp.getCondition(),
/*withElseRegion=*/true);
// Move over then/else blocks.
rewriter.mergeBlocks(ifOp.thenBlock(), newIfOp.thenBlock());
rewriter.mergeBlocks(ifOp.elseBlock(), newIfOp.elseBlock());
// Replace op results.
replaceOpWithBufferizedValues(rewriter, op, newIfOp->getResults());
return success();
}
BufferRelation bufferRelation(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// IfOp results are equivalent to their corresponding yield values if both
// yield values are equivalent to each other.
auto bufferizableOp = cast<BufferizableOpInterface>(op);
SmallVector<OpOperand *> yieldValues =
bufferizableOp.getAliasingOpOperand(opResult, state);
assert(yieldValues.size() == 2 && "expected 2 yield values");
bool equivalentYields = state.areEquivalentBufferizedValues(
yieldValues[0]->get(), yieldValues[1]->get());
return equivalentYields ? BufferRelation::Equivalent : BufferRelation::None;
}
};
/// Helper function for loop bufferization. Return the indices of all values
/// that have a tensor type.
static DenseSet<int64_t> getTensorIndices(ValueRange values) {
DenseSet<int64_t> result;
for (const auto &it : llvm::enumerate(values))
if (it.value().getType().isa<TensorType>())
result.insert(it.index());
return result;
}
/// Helper function for loop bufferization. Return the indices of all
/// bbArg/yielded value pairs who's buffer relation is "Equivalent".
DenseSet<int64_t> getEquivalentBuffers(Block::BlockArgListType bbArgs,
ValueRange yieldedValues,
const AnalysisState &state) {
unsigned int minSize = std::min(bbArgs.size(), yieldedValues.size());
DenseSet<int64_t> result;
for (unsigned int i = 0; i < minSize; ++i) {
if (!bbArgs[i].getType().isa<TensorType>() ||
!yieldedValues[i].getType().isa<TensorType>())
continue;
if (state.areEquivalentBufferizedValues(bbArgs[i], yieldedValues[i]))
result.insert(i);
}
return result;
}
/// Helper function for loop bufferization. Cast the given buffer to the given
/// memref type.
static Value castBuffer(OpBuilder &b, Value buffer, Type type) {
assert(type.isa<BaseMemRefType>() && "expected BaseMemRefType");
assert(buffer.getType().isa<BaseMemRefType>() && "expected BaseMemRefType");
// If the buffer already has the correct type, no cast is needed.
if (buffer.getType() == type)
return buffer;
// TODO: In case `type` has a layout map that is not the fully dynamic
// one, we may not be able to cast the buffer. In that case, the loop
// iter_arg's layout map must be changed (see uses of `castBuffer`).
assert(memref::CastOp::areCastCompatible(buffer.getType(), type) &&
"scf.while op bufferization: cast incompatible");
return b.create<memref::CastOp>(buffer.getLoc(), type, buffer).getResult();
}
/// Helper function for loop bufferization. Return the bufferized values of the
/// given OpOperands. If an operand is not a tensor, return the original value.
static FailureOr<SmallVector<Value>>
getBuffers(RewriterBase &rewriter, MutableArrayRef<OpOperand> operands,
const BufferizationOptions &options) {
SmallVector<Value> result;
for (OpOperand &opOperand : operands) {
if (opOperand.get().getType().isa<TensorType>()) {
FailureOr<Value> resultBuffer =
getBuffer(rewriter, opOperand.get(), options);
if (failed(resultBuffer))
return failure();
result.push_back(*resultBuffer);
} else {
result.push_back(opOperand.get());
}
}
return result;
}
/// Helper function for loop bufferization. Compute the buffer that should be
/// yielded from a loop block (loop body or loop condition).
static FailureOr<Value> getYieldedBuffer(RewriterBase &rewriter, Value tensor,
BaseMemRefType type,
const BufferizationOptions &options) {
assert(tensor.getType().isa<TensorType>() && "expected tensor");
ensureToMemrefOpIsValid(tensor, type);
FailureOr<Value> yieldedVal = getBuffer(rewriter, tensor, options);
if (failed(yieldedVal))
return failure();
return castBuffer(rewriter, *yieldedVal, type);
}
/// Helper function for loop bufferization. Given a range of values, apply
/// `func` to those marked in `tensorIndices`. Otherwise, store the unmodified
/// value in the result vector.
static FailureOr<SmallVector<Value>>
convertTensorValues(ValueRange values, const DenseSet<int64_t> &tensorIndices,
llvm::function_ref<FailureOr<Value>(Value, int64_t)> func) {
SmallVector<Value> result;
for (const auto &it : llvm::enumerate(values)) {
size_t idx = it.index();
Value val = it.value();
if (tensorIndices.contains(idx)) {
FailureOr<Value> maybeVal = func(val, idx);
if (failed(maybeVal))
return failure();
result.push_back(*maybeVal);
} else {
result.push_back(val);
}
}
return result;
}
/// Helper function for loop bufferization. Given a list of pre-bufferization
/// yielded values, compute the list of bufferized yielded values.
FailureOr<SmallVector<Value>>
getYieldedValues(RewriterBase &rewriter, ValueRange values,
TypeRange bufferizedTypes,
const DenseSet<int64_t> &tensorIndices,
const BufferizationOptions &options) {
return convertTensorValues(
values, tensorIndices, [&](Value val, int64_t index) {
return getYieldedBuffer(rewriter, val,
bufferizedTypes[index].cast<BaseMemRefType>(),
options);
});
}
/// Helper function for loop bufferization. Given a list of bbArgs of the new
/// (bufferized) loop op, wrap the bufferized tensor args (now memrefs) into
/// ToTensorOps, so that the block body can be moved over to the new op.
SmallVector<Value>
getBbArgReplacements(RewriterBase &rewriter, Block::BlockArgListType bbArgs,
const DenseSet<int64_t> &tensorIndices) {
SmallVector<Value> result;
for (const auto &it : llvm::enumerate(bbArgs)) {
size_t idx = it.index();
Value val = it.value();
if (tensorIndices.contains(idx)) {
result.push_back(
rewriter.create<bufferization::ToTensorOp>(val.getLoc(), val)
.getResult());
} else {
result.push_back(val);
}
}
return result;
}
/// Bufferization of scf.for. Replace with a new scf.for that operates on
/// memrefs.
struct ForOpInterface
: public BufferizableOpInterface::ExternalModel<ForOpInterface,
scf::ForOp> {
bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
// scf::ForOp alone doesn't bufferize to a memory read, one of the uses of
// its matching bbArg may.
auto forOp = cast<scf::ForOp>(op);
return state.isValueRead(forOp.getRegionIterArgForOpOperand(opOperand));
}
bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
// Tensor iter_args of scf::ForOps are always considered as a write.
return true;
}
SmallVector<OpResult> getAliasingOpResult(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
auto forOp = cast<scf::ForOp>(op);
return {forOp.getResultForOpOperand(opOperand)};
}
BufferRelation bufferRelation(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// ForOp results are equivalent to their corresponding init_args if the
// corresponding iter_args and yield values are equivalent.
auto forOp = cast<scf::ForOp>(op);
OpOperand &forOperand = forOp.getOpOperandForResult(opResult);
auto bbArg = forOp.getRegionIterArgForOpOperand(forOperand);
auto yieldOp =
cast<scf::YieldOp>(forOp.getLoopBody().front().getTerminator());
bool equivalentYield = state.areEquivalentBufferizedValues(
bbArg, yieldOp->getOperand(opResult.getResultNumber()));
return equivalentYield ? BufferRelation::Equivalent : BufferRelation::None;
}
bool isWritable(Operation *op, Value value,
const AnalysisState &state) const {
// Interestingly, scf::ForOp's bbArg can **always** be viewed
// inplace from the perspective of ops nested under:
// 1. Either the matching iter operand is not bufferized inplace and an
// alloc + optional copy makes the bbArg itself inplaceable.
// 2. Or the matching iter operand is bufferized inplace and bbArg just
// bufferizes to that too.
return true;
}
LogicalResult resolveConflicts(Operation *op, RewriterBase &rewriter,
const AnalysisState &state) const {
auto bufferizableOp = cast<BufferizableOpInterface>(op);
if (failed(bufferizableOp.resolveTensorOpOperandConflicts(rewriter, state)))
return failure();
if (!state.getOptions().enforceAliasingInvariants)
return success();
// According to the `getAliasing...` implementations, a bufferized OpResult
// may alias only with the corresponding bufferized init_arg and with no
// other buffers. I.e., the i-th OpResult may alias with the i-th init_arg;
// but not with any other OpOperand. If a corresponding OpResult/init_arg
// pair bufferizes to equivalent buffers, this aliasing requirement is
// satisfied. Otherwise, we cannot be sure and must yield a new buffer copy.
// (New buffer copies do not alias with any buffer.)
auto forOp = cast<scf::ForOp>(op);
auto yieldOp =
cast<scf::YieldOp>(forOp.getLoopBody().front().getTerminator());
OpBuilder::InsertionGuard g(rewriter);
rewriter.setInsertionPoint(yieldOp);
// Indices of all iter_args that have tensor type. These are the ones that
// are bufferized.
DenseSet<int64_t> indices = getTensorIndices(forOp.getInitArgs());
// For every yielded value, is the value equivalent to its corresponding
// bbArg?
DenseSet<int64_t> equivalentYields = getEquivalentBuffers(
forOp.getRegionIterArgs(), yieldOp.getResults(), state);
SmallVector<Value> yieldValues;
for (int64_t idx = 0;
idx < static_cast<int64_t>(yieldOp.getResults().size()); ++idx) {
Value value = yieldOp.getResults()[idx];
if (!indices.contains(idx) || equivalentYields.contains(idx)) {
yieldValues.push_back(value);
continue;
}
FailureOr<Value> alloc =
allocateTensorForShapedValue(rewriter, yieldOp.getLoc(), value,
/*escape=*/true, state.getOptions());
if (failed(alloc))
return failure();
yieldValues.push_back(*alloc);
}
rewriter.updateRootInPlace(
yieldOp, [&]() { yieldOp.getResultsMutable().assign(yieldValues); });
return success();
}
FailureOr<BaseMemRefType>
getBufferType(Operation *op, BlockArgument bbArg,
const BufferizationOptions &options) const {
auto forOp = cast<scf::ForOp>(op);
return bufferization::getBufferType(
forOp.getOpOperandForRegionIterArg(bbArg).get(), options);
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto forOp = cast<scf::ForOp>(op);
Block *oldLoopBody = &forOp.getLoopBody().front();
// Indices of all iter_args that have tensor type. These are the ones that
// are bufferized.
DenseSet<int64_t> indices = getTensorIndices(forOp.getInitArgs());
// The new memref init_args of the loop.
FailureOr<SmallVector<Value>> maybeInitArgs =
getBuffers(rewriter, forOp.getIterOpOperands(), options);
if (failed(maybeInitArgs))
return failure();
SmallVector<Value> initArgs = *maybeInitArgs;
// Construct a new scf.for op with memref instead of tensor values.
auto newForOp = rewriter.create<scf::ForOp>(
forOp.getLoc(), forOp.getLowerBound(), forOp.getUpperBound(),
forOp.getStep(), initArgs);
newForOp->setAttrs(forOp->getAttrs());
ValueRange initArgsRange(initArgs);
TypeRange initArgsTypes(initArgsRange);
Block *loopBody = &newForOp.getLoopBody().front();
// Set up new iter_args. The loop body uses tensors, so wrap the (memref)
// iter_args of the new loop in ToTensorOps.
rewriter.setInsertionPointToStart(loopBody);
SmallVector<Value> iterArgs =
getBbArgReplacements(rewriter, newForOp.getRegionIterArgs(), indices);
iterArgs.insert(iterArgs.begin(), newForOp.getInductionVar());
// Move loop body to new loop.
rewriter.mergeBlocks(oldLoopBody, loopBody, iterArgs);
// Replace loop results.
replaceOpWithBufferizedValues(rewriter, op, newForOp->getResults());
return success();
}
/// Assert that yielded values of an scf.for op are equivalent to their
/// corresponding bbArgs. In that case, the buffer relations of the
/// corresponding OpResults are "Equivalent".
///
/// If this is not the case, an allocs+copies are inserted and yielded from
/// the loop. This could be a performance problem, so it must be explicitly
/// activated with `alloc-return-allocs`.
LogicalResult verifyAnalysis(Operation *op,
const AnalysisState &state) const {
const auto &options =
static_cast<const OneShotBufferizationOptions &>(state.getOptions());
if (options.allowReturnAllocs)
return success();
auto forOp = cast<scf::ForOp>(op);
auto yieldOp =
cast<scf::YieldOp>(forOp.getLoopBody().front().getTerminator());
for (OpResult opResult : op->getOpResults()) {
if (!opResult.getType().isa<TensorType>())
continue;
// Note: This is overly strict. We should check for aliasing bufferized
// values. But we don't have a "must-alias" analysis yet.
if (bufferRelation(op, opResult, state) != BufferRelation::Equivalent)
return yieldOp->emitError()
<< "Yield operand #" << opResult.getResultNumber()
<< " is not equivalent to the corresponding iter bbArg";
}
return success();
}
};
/// Bufferization of scf.while. Replace with a new scf.while that operates on
/// memrefs.
struct WhileOpInterface
: public BufferizableOpInterface::ExternalModel<WhileOpInterface,
scf::WhileOp> {
bool bufferizesToMemoryRead(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
// Tensor iter_args of scf::WhileOps are always considered as a read.
return true;
}
bool bufferizesToMemoryWrite(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
// Tensor iter_args of scf::WhileOps are always considered as a write.
return true;
}
SmallVector<OpResult> getAliasingOpResult(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
auto whileOp = cast<scf::WhileOp>(op);
unsigned int idx = opOperand.getOperandNumber();
// The OpResults and OpOperands may not match. They may not even have the
// same type. The number of OpResults and OpOperands can also differ.
if (idx >= op->getNumResults() ||
opOperand.get().getType() != op->getResult(idx).getType())
return {};
// The only aliasing OpResult may be the one at the same index.
return {whileOp->getResult(idx)};
}
BufferRelation bufferRelation(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// WhileOp results are equivalent to their corresponding init_args if the
// corresponding iter_args and yield values are equivalent (for both the
// "before" and the "after" block).
unsigned int resultNumber = opResult.getResultNumber();
auto whileOp = cast<scf::WhileOp>(op);
// The "before" region bbArgs and the OpResults may not match.
if (resultNumber >= whileOp.getBeforeArguments().size())
return BufferRelation::None;
if (opResult.getType() !=
whileOp.getBeforeArguments()[resultNumber].getType())
return BufferRelation::None;
auto conditionOp = whileOp.getConditionOp();
BlockArgument conditionBbArg = whileOp.getBeforeArguments()[resultNumber];
Value conditionOperand = conditionOp.getArgs()[resultNumber];
bool equivCondition =
state.areEquivalentBufferizedValues(conditionBbArg, conditionOperand);
auto yieldOp = whileOp.getYieldOp();
BlockArgument bodyBbArg = whileOp.getAfterArguments()[resultNumber];
Value yieldOperand = yieldOp.getOperand(resultNumber);
bool equivYield =
state.areEquivalentBufferizedValues(bodyBbArg, yieldOperand);
return equivCondition && equivYield ? BufferRelation::Equivalent
: BufferRelation::None;
}
bool isWritable(Operation *op, Value value,
const AnalysisState &state) const {
// Interestingly, scf::WhileOp's bbArg can **always** be viewed
// inplace from the perspective of ops nested under:
// 1. Either the matching iter operand is not bufferized inplace and an
// alloc + optional copy makes the bbArg itself inplaceable.
// 2. Or the matching iter operand is bufferized inplace and bbArg just
// bufferizes to that too.
return true;
}
LogicalResult resolveConflicts(Operation *op, RewriterBase &rewriter,
const AnalysisState &state) const {
auto bufferizableOp = cast<BufferizableOpInterface>(op);
if (failed(bufferizableOp.resolveTensorOpOperandConflicts(rewriter, state)))
return failure();
if (!state.getOptions().enforceAliasingInvariants)
return success();
// According to the `getAliasing...` implementations, a bufferized OpResult
// may alias only with the corresponding bufferized init_arg and with no
// other buffers. I.e., the i-th OpResult may alias with the i-th init_arg;
// but not with any other OpOperand. If a corresponding OpResult/init_arg
// pair bufferizes to equivalent buffers, this aliasing requirement is
// satisfied. Otherwise, we cannot be sure and must yield a new buffer copy.
// (New buffer copies do not alias with any buffer.)
OpBuilder::InsertionGuard g(rewriter);
auto whileOp = cast<scf::WhileOp>(op);
auto conditionOp = whileOp.getConditionOp();
auto yieldOp = whileOp.getYieldOp();
// Indices of all bbArgs that have tensor type. These are the ones that
// are bufferized. The "before" and "after" regions may have different args.
DenseSet<int64_t> indicesBefore = getTensorIndices(whileOp.getInits());
DenseSet<int64_t> indicesAfter =
getTensorIndices(whileOp.getAfterArguments());
// For every yielded value, is the value equivalent to its corresponding
// bbArg?
DenseSet<int64_t> equivalentYieldsBefore = getEquivalentBuffers(
whileOp.getBeforeArguments(), conditionOp.getArgs(), state);
DenseSet<int64_t> equivalentYieldsAfter = getEquivalentBuffers(
whileOp.getAfterArguments(), whileOp.getYieldOp().getResults(), state);
// Update "before" region.
rewriter.setInsertionPoint(conditionOp);
SmallVector<Value> beforeYieldValues;
for (int64_t idx = 0;
idx < static_cast<int64_t>(conditionOp.getArgs().size()); ++idx) {
Value value = conditionOp.getArgs()[idx];
if (!indicesBefore.contains(idx) ||
equivalentYieldsBefore.contains(idx)) {
beforeYieldValues.push_back(value);
continue;
}
FailureOr<Value> alloc =
allocateTensorForShapedValue(rewriter, conditionOp.getLoc(), value,
/*escape=*/true, state.getOptions());
if (failed(alloc))
return failure();
beforeYieldValues.push_back(*alloc);
}
rewriter.updateRootInPlace(conditionOp, [&]() {
conditionOp.getArgsMutable().assign(beforeYieldValues);
});
// Update "after" region.
rewriter.setInsertionPoint(yieldOp);
SmallVector<Value> afterYieldValues;
for (int64_t idx = 0;
idx < static_cast<int64_t>(yieldOp.getResults().size()); ++idx) {
Value value = yieldOp.getResults()[idx];
if (!indicesAfter.contains(idx) || equivalentYieldsAfter.contains(idx)) {
afterYieldValues.push_back(value);
continue;
}
FailureOr<Value> alloc =
allocateTensorForShapedValue(rewriter, yieldOp.getLoc(), value,
/*escape=*/true, state.getOptions());
if (failed(alloc))
return failure();
afterYieldValues.push_back(*alloc);
}
rewriter.updateRootInPlace(yieldOp, [&]() {
yieldOp.getResultsMutable().assign(afterYieldValues);
});
return success();
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto whileOp = cast<scf::WhileOp>(op);
assert(whileOp.getBefore().getBlocks().size() == 1 &&
"regions with multiple blocks not supported");
Block *beforeBody = &whileOp.getBefore().front();
assert(whileOp.getAfter().getBlocks().size() == 1 &&
"regions with multiple blocks not supported");
Block *afterBody = &whileOp.getAfter().front();
// Indices of all bbArgs that have tensor type. These are the ones that
// are bufferized. The "before" and "after" regions may have different args.
DenseSet<int64_t> indicesBefore = getTensorIndices(whileOp.getInits());
DenseSet<int64_t> indicesAfter =
getTensorIndices(whileOp.getAfterArguments());
// The new memref init_args of the loop.
FailureOr<SmallVector<Value>> maybeInitArgs =
getBuffers(rewriter, whileOp->getOpOperands(), options);
if (failed(maybeInitArgs))
return failure();
SmallVector<Value> initArgs = *maybeInitArgs;
// The result types of a WhileOp are the same as the "after" bbArg types.
SmallVector<Type> argsTypesAfter = llvm::to_vector(
llvm::map_range(whileOp.getAfterArguments(), [&](BlockArgument bbArg) {
// TODO: error handling
return bufferization::getBufferType(bbArg, options)->cast<Type>();
}));
// Construct a new scf.while op with memref instead of tensor values.
ValueRange argsRangeBefore(initArgs);
TypeRange argsTypesBefore(argsRangeBefore);
auto newWhileOp = rewriter.create<scf::WhileOp>(whileOp.getLoc(),
argsTypesAfter, initArgs);
// Add before/after regions to the new op.
SmallVector<Location> bbArgLocsBefore(initArgs.size(), whileOp.getLoc());
SmallVector<Location> bbArgLocsAfter(argsTypesAfter.size(),
whileOp.getLoc());
Block *newBeforeBody = &newWhileOp.getBefore().emplaceBlock();
newWhileOp.getBefore().addArguments(argsTypesBefore, bbArgLocsBefore);
Block *newAfterBody = &newWhileOp.getAfter().emplaceBlock();
newWhileOp.getAfter().addArguments(argsTypesAfter, bbArgLocsAfter);
// Set up new iter_args and move the loop condition block to the new op.
// The old block uses tensors, so wrap the (memref) bbArgs of the new block
// in ToTensorOps.
rewriter.setInsertionPointToStart(newBeforeBody);
SmallVector<Value> newBeforeArgs = getBbArgReplacements(
rewriter, newWhileOp.getBeforeArguments(), indicesBefore);
rewriter.mergeBlocks(beforeBody, newBeforeBody, newBeforeArgs);
// Update scf.condition of new loop.
auto newConditionOp = newWhileOp.getConditionOp();
rewriter.setInsertionPoint(newConditionOp);
// Only equivalent buffers or new buffer allocations may be yielded to the
// "after" region.
// TODO: This could be relaxed for better bufferization results.
FailureOr<SmallVector<Value>> newConditionArgs =
getYieldedValues(rewriter, newConditionOp.getArgs(), argsTypesAfter,
indicesAfter, options);
if (failed(newConditionArgs))
return failure();
newConditionOp.getArgsMutable().assign(*newConditionArgs);
// Set up new iter_args and move the loop body block to the new op.
// The old block uses tensors, so wrap the (memref) bbArgs of the new block
// in ToTensorOps.
rewriter.setInsertionPointToStart(newAfterBody);
SmallVector<Value> newAfterArgs = getBbArgReplacements(
rewriter, newWhileOp.getAfterArguments(), indicesAfter);
rewriter.mergeBlocks(afterBody, newAfterBody, newAfterArgs);
// Update scf.yield of the new loop.
auto newYieldOp = newWhileOp.getYieldOp();
rewriter.setInsertionPoint(newYieldOp);
// Only equivalent buffers or new buffer allocations may be yielded to the
// "before" region.
// TODO: This could be relaxed for better bufferization results.
FailureOr<SmallVector<Value>> newYieldValues =
getYieldedValues(rewriter, newYieldOp.getResults(), argsTypesBefore,
indicesBefore, options);
if (failed(newYieldValues))
return failure();
newYieldOp.getResultsMutable().assign(*newYieldValues);
// Replace loop results.
replaceOpWithBufferizedValues(rewriter, op, newWhileOp->getResults());
return success();
}
/// Assert that yielded values of an scf.while op are equivalent to their
/// corresponding bbArgs. In that case, the buffer relations of the
/// corresponding OpResults are "Equivalent".
///
/// If this is not the case, allocs+copies are inserted and yielded from
/// the loop. This could be a performance problem, so it must be explicitly
/// activated with `alloc-return-allocs`.
///
/// Not: In contrast to scf::ForOp, scf::WhileOp has two regions and the
/// equivalence condition must be checked for both.
LogicalResult verifyAnalysis(Operation *op,
const AnalysisState &state) const {
auto whileOp = cast<scf::WhileOp>(op);
const auto &options =
static_cast<const OneShotBufferizationOptions &>(state.getOptions());
if (options.allowReturnAllocs)
return success();
auto conditionOp = whileOp.getConditionOp();
for (const auto &it : llvm::enumerate(conditionOp.getArgs())) {
if (!it.value().getType().isa<TensorType>())
continue;
if (!state.areEquivalentBufferizedValues(
it.value(), conditionOp->getBlock()->getArgument(it.index())))
return conditionOp->emitError()
<< "Condition arg #" << it.index()
<< " is not equivalent to the corresponding iter bbArg";
}
auto yieldOp = whileOp.getYieldOp();
for (const auto &it : llvm::enumerate(yieldOp.getResults())) {
if (!it.value().getType().isa<TensorType>())
continue;
if (!state.areEquivalentBufferizedValues(
it.value(), yieldOp->getBlock()->getArgument(it.index())))
return yieldOp->emitError()
<< "Yield operand #" << it.index()
<< " is not equivalent to the corresponding iter bbArg";
}
return success();
}
};
/// Bufferization of scf.yield. Bufferized as part of their enclosing ops, so
/// this is for analysis only.
struct YieldOpInterface
: public BufferizableOpInterface::ExternalModel<YieldOpInterface,
scf::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;
}
SmallVector<OpResult> getAliasingOpResult(Operation *op, OpOperand &opOperand,
const AnalysisState &state) const {
if (isa<scf::IfOp>(op->getParentOp()))
return {op->getParentOp()->getResult(opOperand.getOperandNumber())};
if (isa<scf::ExecuteRegionOp>(op->getParentOp()))
return {op->getParentOp()->getResult(opOperand.getOperandNumber())};
return {};
}
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<scf::YieldOp>(op);
if (!isa<scf::ExecuteRegionOp, scf::IfOp, scf::ForOp, scf::WhileOp>(
yieldOp->getParentOp()))
return yieldOp->emitError("unsupported scf::YieldOp parent");
// TODO: Bufferize scf.yield inside scf.while here. (Currently bufferized
// together with scf.while.)
if (isa<scf::WhileOp>(yieldOp->getParentOp()))
return success();
SmallVector<Value> newResults;
for (const auto &it : llvm::enumerate(yieldOp.getResults())) {
Value value = it.value();
if (value.getType().isa<TensorType>()) {
FailureOr<Value> maybeBuffer = getBuffer(rewriter, value, options);
if (failed(maybeBuffer))
return failure();
Value buffer = *maybeBuffer;
if (auto forOp = dyn_cast<scf::ForOp>(yieldOp->getParentOp())) {
FailureOr<BaseMemRefType> resultType =
cast<BufferizableOpInterface>(forOp.getOperation())
.getBufferType(forOp.getRegionIterArgs()[it.index()],
options);
if (failed(resultType))
return failure();
buffer = castBuffer(rewriter, buffer, *resultType);
}
newResults.push_back(buffer);
} else {
newResults.push_back(value);
}
}
replaceOpWithNewBufferizedOp<scf::YieldOp>(rewriter, op, newResults);
return success();
}
};
using tensor::ExtractSliceOp;
/// Return the destinations that an ForeachThreadOp is inserting into. One per
/// ParallelInsertSliceOp.
static SmallVector<OpOperand *>
getInsertionDest(ForeachThreadOp foreachThreadOp) {
PerformConcurrentlyOp terminator = foreachThreadOp.getTerminator();
SmallVector<OpOperand *> result;
terminator.walk([&](ParallelInsertSliceOp insertOp) {
result.push_back(&insertOp->getOpOperand(1) /*dest*/);
});
return result;
}
/// Bufferization of ForeachThreadOp. This also bufferizes the terminator of the
/// region. There are op interfaces for the terminators (PerformConcurrentlyOp
/// and ParallelInsertSliceOp), but these are only used during analysis. Not
/// for bufferization.
struct ForeachThreadOpInterface
: public BufferizableOpInterface::ExternalModel<ForeachThreadOpInterface,
ForeachThreadOp> {
SmallVector<OpOperand *>
getAliasingOpOperand(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// Get OpOperand (dest) from corresponding ParallelInsertSliceOp.
auto foreachThreadOp = cast<ForeachThreadOp>(op);
return {getInsertionDest(foreachThreadOp)[opResult.getResultNumber()]};
}
bool isMemoryWrite(Operation *op, OpResult opResult,
const AnalysisState &state) const {
// This op is a memory write. Stop lookup here to avoid finding false
// conflicts involving this op and one of the ops in the region. This is
// similar to how scf.if ops are analyzed.
return true;
}
BufferRelation bufferRelation(Operation *op, OpResult opResult,
const AnalysisState &state) const {
return 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();
OpBuilder::InsertionGuard g(rewriter);
auto foreachThreadOp = cast<ForeachThreadOp>(op);
for (OpResult opResult : foreachThreadOp->getOpResults()) {
SmallVector<OpOperand *> destOperands =
state.getAliasingOpOperand(opResult);
assert(destOperands.size() == 1 &&
"expected exactly one aliasing OpOperand");
assert(isa<ParallelInsertSliceOp>(destOperands.front()->getOwner()) &&
"expected ParallelInsertSliceOp");
// Nothing to do if there is no conflict.
if (state.isInPlace(*destOperands.front()))
continue;
// Insert tensor allocation.
bool isYielded = state.isTensorYielded(opResult);
FailureOr<Value> alloc = allocateTensorForShapedValue(
rewriter, op->getLoc(), destOperands.front()->get(),
/*escape=*/isYielded, state.getOptions());
if (failed(alloc))
return failure();
// Update terminator operand.
rewriter.updateRootInPlace(destOperands.front()->getOwner(),
[&]() { destOperands.front()->set(*alloc); });
}
return success();
}
LogicalResult bufferize(Operation *op, RewriterBase &rewriter,
const BufferizationOptions &options) const {
auto foreachThreadOp = cast<ForeachThreadOp>(op);