
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. 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 patch updates all remaining uses of the deprecated functionality in mlir/. This was done with clang-tidy as described below and further modifications to GPUBase.td and OpenMPOpsInterfaces.td. 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: 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. ``` 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 ``` Differential Revision: https://reviews.llvm.org/D151542
1150 lines
45 KiB
C++
1150 lines
45 KiB
C++
//===- OneShotAnalysis.cpp - One-Shot (Single Pass) Analysis --------------===//
|
|
//
|
|
// 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
|
|
//
|
|
//===----------------------------------------------------------------------===//
|
|
//
|
|
// One-Shot Analysis analyzes function bodies. By default, function boundaries
|
|
// (FuncOp bbArgs, CallOps, ReturnOps) are treated as "unknown" ops.
|
|
// OneShotModuleBufferization.cpp is an extension of One-Shot Analysis for
|
|
// simple call graphs without loops.
|
|
//
|
|
// One-Shot Bufferize consists of three phases.
|
|
//
|
|
// 1. Analyze ops to decide which OpOperands can bufferize inplace, i.e.,
|
|
// without inserting buffer copies. The analysis queries op bufferization
|
|
// semantics via `BufferizableOpInterface`.
|
|
// 2. Insert copies for OpOperands that were decided to bufferize out-of-place
|
|
// in tensor land during `TensorCopyInsertion`.
|
|
// 3. Bufferize ops by calling `BufferizableOpInterface::bufferize`.
|
|
//
|
|
// This file contains only the analysis. For convenience, this file also
|
|
// contains a helper function `runOneShotBufferize` that analyzes an op (and its
|
|
// nested ops) and then bufferizes it.
|
|
//
|
|
// Inplace bufferization decisions are passed from the analysis to the
|
|
// `TensorCopyInsertion` phase via `AnalysisState`. They can be printed for
|
|
// debugging purposes with `testAnalysisOnly`.
|
|
//
|
|
// Ops that do not implement `BufferizableOpInterface` can be analyzed but are
|
|
// treated conservatively. E.g., the analysis has to assume that their tensor
|
|
// OpOperands bufferize to memory writes. While such ops can be analyzed, they
|
|
// are not bufferized and remain in the IR. to_tensor and to_memref ops are
|
|
// inserted at the bufferization boundary.
|
|
//
|
|
// This analysis caters to high-performance codegen where buffer reuse is deemed
|
|
// critical: the analysis should fail if the bufferized form of the function
|
|
// needs to return a buffer, unless `allowReturnAllocs` is enabled.
|
|
|
|
#include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
|
|
|
|
#include <random>
|
|
#include <optional>
|
|
|
|
#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
|
|
#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
|
|
#include "mlir/Dialect/Bufferization/Transforms/Bufferize.h"
|
|
#include "mlir/Dialect/Bufferization/Transforms/Transforms.h"
|
|
#include "mlir/Dialect/Func/IR/FuncOps.h"
|
|
#include "mlir/Dialect/MemRef/IR/MemRef.h"
|
|
#include "mlir/IR/AsmState.h"
|
|
#include "mlir/IR/Dominance.h"
|
|
#include "mlir/IR/Operation.h"
|
|
#include "mlir/IR/TypeUtilities.h"
|
|
#include "mlir/Interfaces/ControlFlowInterfaces.h"
|
|
#include "llvm/ADT/DenseSet.h"
|
|
#include "llvm/ADT/SetVector.h"
|
|
|
|
MLIR_DEFINE_EXPLICIT_TYPE_ID(mlir::bufferization::OneShotAnalysisState)
|
|
|
|
// Run mlir-opt with `-debug-only="one-shot-analysis"` for detailed debug
|
|
// output.
|
|
#define DEBUG_TYPE "one-shot-analysis"
|
|
|
|
using namespace mlir;
|
|
using namespace mlir::bufferization;
|
|
|
|
static bool isaTensor(Type t) { return isa<TensorType>(t); }
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Bufferization-specific attribute manipulation.
|
|
// These are for testing and debugging only. Bufferization information is stored
|
|
// in OneShotBufferizationState. When run with `testAnalysisOnly`, the IR is
|
|
// annotated with the results of the analysis, so that they can be checked in
|
|
// tests.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// Attribute marker to specify op operands that bufferize in-place.
|
|
constexpr StringLiteral kInPlaceOperandsAttrName = "__inplace_operands_attr__";
|
|
|
|
constexpr StringLiteral kAliasSetAttrName = "__alias_set_attr__";
|
|
|
|
/// Mark whether OpOperand will be bufferized inplace.
|
|
static void setInPlaceOpOperand(OpOperand &opOperand, bool inPlace) {
|
|
Operation *op = opOperand.getOwner();
|
|
SmallVector<StringRef> inPlaceVector;
|
|
if (auto attr = op->getAttr(kInPlaceOperandsAttrName)) {
|
|
inPlaceVector = SmallVector<StringRef>(llvm::to_vector<4>(
|
|
cast<ArrayAttr>(attr).getAsValueRange<StringAttr>()));
|
|
} else {
|
|
inPlaceVector = SmallVector<StringRef>(op->getNumOperands(), "none");
|
|
for (OpOperand &opOperand : op->getOpOperands())
|
|
if (isa<TensorType>(opOperand.get().getType()))
|
|
inPlaceVector[opOperand.getOperandNumber()] = "false";
|
|
}
|
|
inPlaceVector[opOperand.getOperandNumber()] = inPlace ? "true" : "false";
|
|
op->setAttr(kInPlaceOperandsAttrName,
|
|
OpBuilder(op).getStrArrayAttr(inPlaceVector));
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// OneShotAnalysisState
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
OneShotAnalysisState::OneShotAnalysisState(
|
|
Operation *op, const OneShotBufferizationOptions &options)
|
|
: AnalysisState(options, TypeID::get<OneShotAnalysisState>()) {
|
|
// Set up alias sets.
|
|
op->walk([&](Operation *op) {
|
|
for (Value v : op->getResults())
|
|
if (isa<TensorType>(v.getType()))
|
|
createAliasInfoEntry(v);
|
|
for (Region &r : op->getRegions())
|
|
for (Block &b : r.getBlocks())
|
|
for (auto bbArg : b.getArguments())
|
|
if (isa<TensorType>(bbArg.getType()))
|
|
createAliasInfoEntry(bbArg);
|
|
});
|
|
|
|
// Mark OpOperands in-place that must bufferize in-place.
|
|
op->walk([&](BufferizableOpInterface bufferizableOp) {
|
|
if (!options.isOpAllowed(bufferizableOp))
|
|
return WalkResult::skip();
|
|
for (OpOperand &opOperand : bufferizableOp->getOpOperands())
|
|
if (isa<TensorType>(opOperand.get().getType()))
|
|
if (bufferizableOp.mustBufferizeInPlace(opOperand, *this))
|
|
bufferizeInPlace(opOperand);
|
|
return WalkResult::advance();
|
|
});
|
|
}
|
|
|
|
void OneShotAnalysisState::applyOnEquivalenceClass(
|
|
Value v, function_ref<void(Value)> fun) const {
|
|
auto leaderIt = equivalentInfo.findLeader(v);
|
|
for (auto mit = leaderIt, meit = equivalentInfo.member_end(); mit != meit;
|
|
++mit) {
|
|
fun(*mit);
|
|
}
|
|
}
|
|
|
|
void OneShotAnalysisState::applyOnAliases(Value v,
|
|
function_ref<void(Value)> fun) const {
|
|
auto leaderIt = aliasInfo.findLeader(v);
|
|
for (auto mit = leaderIt, meit = aliasInfo.member_end(); mit != meit; ++mit) {
|
|
fun(*mit);
|
|
}
|
|
}
|
|
|
|
bool OneShotAnalysisState::areEquivalentBufferizedValues(Value v1,
|
|
Value v2) const {
|
|
return equivalentInfo.isEquivalent(v1, v2);
|
|
}
|
|
|
|
bool OneShotAnalysisState::areAliasingBufferizedValues(Value v1,
|
|
Value v2) const {
|
|
return aliasInfo.isEquivalent(v1, v2);
|
|
}
|
|
|
|
void OneShotAnalysisState::bufferizeInPlace(OpOperand &operand) {
|
|
if (inplaceBufferized.contains(&operand))
|
|
return;
|
|
inplaceBufferized.insert(&operand);
|
|
for (AliasingOpResult alias : getAliasingOpResults(operand))
|
|
aliasInfo.unionSets(alias.opResult, operand.get());
|
|
++statNumTensorInPlace;
|
|
}
|
|
|
|
void OneShotAnalysisState::bufferizeOutOfPlace(OpOperand &operand) {
|
|
assert(!inplaceBufferized.contains(&operand) &&
|
|
"OpOperand was already decided to bufferize inplace");
|
|
++statNumTensorOutOfPlace;
|
|
}
|
|
|
|
void OneShotAnalysisState::createAliasInfoEntry(Value v) {
|
|
aliasInfo.insert(v);
|
|
equivalentInfo.insert(v);
|
|
}
|
|
|
|
// Gather yielded tensors in `yieldedTensors` by querying all aliases. This is
|
|
// to ensure that such information is available during bufferization time.
|
|
// Alias information can no longer be queried once we have started modifying
|
|
// the IR.
|
|
void OneShotAnalysisState::gatherYieldedTensors(Operation *op) {
|
|
op->walk([&](Operation *returnOp) {
|
|
if (!isRegionReturnLike(returnOp) || !getOptions().isOpAllowed(returnOp))
|
|
return WalkResult::advance();
|
|
|
|
for (OpOperand &returnValOperand : returnOp->getOpOperands()) {
|
|
Value returnVal = returnValOperand.get();
|
|
// Skip non-tensor values.
|
|
if (!isa<TensorType>(returnVal.getType()))
|
|
continue;
|
|
|
|
// Add all aliases of the returned value. But only the ones that are in
|
|
// the same block.
|
|
applyOnAliases(returnVal, [&](Value v) {
|
|
if (auto bbArg = dyn_cast<BlockArgument>(v)) {
|
|
if (bbArg.getOwner()->getParentOp() == returnOp->getParentOp())
|
|
yieldedTensors.insert(bbArg);
|
|
return;
|
|
}
|
|
Operation *definingOp = v.getDefiningOp();
|
|
if (definingOp->getParentOp() == returnOp->getParentOp())
|
|
yieldedTensors.insert(v);
|
|
});
|
|
}
|
|
|
|
return WalkResult::advance();
|
|
});
|
|
}
|
|
|
|
void OneShotAnalysisState::gatherUndefinedTensorUses(Operation *op) {
|
|
op->walk([&](Operation *op) {
|
|
// Skip unknown ops.
|
|
auto bufferizableOp = getOptions().dynCastBufferizableOp(op);
|
|
if (!bufferizableOp)
|
|
return WalkResult::skip();
|
|
|
|
// Check all tensor OpResults.
|
|
for (OpResult opResult : op->getOpResults()) {
|
|
if (!isa<TensorType>(opResult.getType()))
|
|
continue;
|
|
|
|
// If there is no preceding definition, the tensor contents are
|
|
// undefined.
|
|
if (findDefinitionsCached(opResult).empty())
|
|
for (OpOperand &use : opResult.getUses())
|
|
undefinedTensorUses.insert(&use);
|
|
}
|
|
|
|
return WalkResult::advance();
|
|
});
|
|
}
|
|
|
|
bool OneShotAnalysisState::hasUndefinedContents(OpOperand *opOperand) const {
|
|
return undefinedTensorUses.contains(opOperand);
|
|
}
|
|
|
|
bool OneShotAnalysisState::isInPlace(OpOperand &opOperand) const {
|
|
return inplaceBufferized.contains(&opOperand);
|
|
}
|
|
|
|
bool OneShotAnalysisState::isTensorYielded(Value tensor) const {
|
|
return yieldedTensors.contains(tensor);
|
|
}
|
|
|
|
bool OneShotAnalysisState::isValueWritten(Value value) const {
|
|
bool isWritten = false;
|
|
applyOnAliases(value, [&](Value val) {
|
|
for (OpOperand &use : val.getUses())
|
|
if (isInPlace(use) && bufferizesToMemoryWrite(use))
|
|
isWritten = true;
|
|
});
|
|
return isWritten;
|
|
}
|
|
|
|
bool OneShotAnalysisState::isWritable(Value value) const {
|
|
// TODO: Out-of-place bufferized value could be considered writable.
|
|
if (auto bufferizableOp = getOptions().dynCastBufferizableOp(value))
|
|
return bufferizableOp.isWritable(value, *this);
|
|
|
|
// Query BufferizableOpInterface to see if the BlockArgument is writable.
|
|
if (auto bbArg = dyn_cast<BlockArgument>(value))
|
|
if (auto bufferizableOp =
|
|
getOptions().dynCastBufferizableOp(bbArg.getOwner()->getParentOp()))
|
|
return bufferizableOp.isWritable(bbArg, *this);
|
|
|
|
// Not a bufferizable op: The conservative answer is "not writable".
|
|
return false;
|
|
}
|
|
|
|
void OneShotAnalysisState::unionAliasSets(Value v1, Value v2) {
|
|
aliasInfo.unionSets(v1, v2);
|
|
}
|
|
|
|
void OneShotAnalysisState::unionEquivalenceClasses(Value v1, Value v2) {
|
|
equivalentInfo.unionSets(v1, v2);
|
|
}
|
|
|
|
OneShotAnalysisState::Extension::~Extension() = default;
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Bufferization-specific alias analysis.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// Return true if opOperand has been decided to bufferize in-place.
|
|
static bool isInplaceMemoryWrite(OpOperand &opOperand,
|
|
const OneShotAnalysisState &state) {
|
|
// OpOperands that do not bufferize to a memory write do not write in-place.
|
|
if (!state.bufferizesToMemoryWrite(opOperand))
|
|
return false;
|
|
// Check current bufferization decisions.
|
|
return state.isInPlace(opOperand);
|
|
}
|
|
|
|
/// Return true if `a` happens before `b`, i.e., `a` or one of its ancestors
|
|
/// properly dominates `b` and `b` is not inside `a`.
|
|
static bool happensBefore(Operation *a, Operation *b,
|
|
const DominanceInfo &domInfo) {
|
|
do {
|
|
// TODO: Instead of isProperAncestor + properlyDominates, we should use
|
|
// properlyDominatesImpl(a, b, /*enclosingOpOk=*/false)
|
|
if (a->isProperAncestor(b))
|
|
return false;
|
|
if (domInfo.properlyDominates(a, b))
|
|
return true;
|
|
} while ((a = a->getParentOp()));
|
|
return false;
|
|
}
|
|
|
|
/// Return `true` if op dominance can be used to rule out a read-after-write
|
|
/// conflicts based on the ordering of ops.
|
|
///
|
|
/// Generalized op dominance can often be used to rule out potential conflicts
|
|
/// due to "read happens before write". E.g., the following IR is not a RaW
|
|
/// conflict because the read happens *before* the write.
|
|
///
|
|
/// Example 1:
|
|
/// %0 = ... : tensor<?xf32> // DEF
|
|
/// "reading_op"(%0) : tensor<?xf32> // READ
|
|
/// %1 = "writing_op"(%0) : tensor<?xf32> -> tensor<?xf32> // WRITE
|
|
///
|
|
/// This is no longer true inside loops (or repetitive regions). In such cases,
|
|
/// there may not be a meaningful `happensBefore` relationship because ops
|
|
/// could be executed multiple times. E.g.:
|
|
///
|
|
/// Example 2:
|
|
/// %0 = ... : tensor<?xf32> // DEF
|
|
/// scf.for ... {
|
|
/// "reading_op"(%0) : tensor<?xf32> // READ
|
|
/// %1 = "writing_op"(%0) : tensor<?xf32> -> tensor<?xf32> // WRITE
|
|
/// ...
|
|
/// }
|
|
///
|
|
/// In the above example, reading_op happens before writing_op according to
|
|
/// op dominance. However, both ops may happen multiple times; in
|
|
/// particular, the second execution of reading_op happens after the first
|
|
/// execution of writing_op. This is problematic because the tensor %0 they
|
|
/// operate on (i.e., the "definition") is defined outside of the loop.
|
|
///
|
|
/// On a high-level, there is a potential RaW in a program if there exists a
|
|
/// possible program execution such that there is a sequence of DEF, followed
|
|
/// by WRITE, followed by READ. Each additional DEF resets the sequence.
|
|
///
|
|
/// E.g.:
|
|
/// No conflict: DEF, WRITE, DEF, READ
|
|
/// Potential conflict: DEF, READ, WRITE, READ, WRITE
|
|
///
|
|
/// Example 1 has no conflict: DEF, READ, WRITE
|
|
/// Example 2 has a potential conflict: DEF, (READ, WRITE)*
|
|
//
|
|
/// Example 3:
|
|
/// scf.for ... {
|
|
/// %0 = ... : tensor<?xf32>
|
|
/// "reading_op"(%0) : tensor<?xf32>
|
|
/// %1 = "writing_op"(%0) : tensor<?xf32> -> tensor<?xf32>
|
|
/// ...
|
|
/// }
|
|
/// This has no conflict: (DEF, READ, WRITE)*
|
|
///
|
|
/// Example 4:
|
|
/// %0 = ... : tensor<?xf32>
|
|
/// scf.for ... {
|
|
/// scf.for ... { "reading_op"(%0) }
|
|
/// %1 = "writing_op"(%0)
|
|
/// }
|
|
/// This has a potential conflict: DEF, ((READ)*, WRITE)*
|
|
///
|
|
/// Example 5:
|
|
/// %0 = ... : tensor<?xf32>
|
|
/// scf.for ... { %1 = "writing_op"(%0) }
|
|
/// scf.for ... { "reading_op"(%0) }
|
|
/// This has a potential conflict: DEF, WRITE*, READ*
|
|
///
|
|
/// The following rules are used to rule out RaW conflicts via ordering of ops:
|
|
///
|
|
/// 1. If the closest enclosing repetitive region of DEF is a proper ancestor of
|
|
/// a repetitive region that enclosing both READ and WRITE, we cannot rule
|
|
/// out RaW conflict due to the ordering of ops.
|
|
/// 2. Otherwise: There are no loops that interfere with our analysis; for
|
|
/// analysis purposes, we can assume that there are no loops/repetitive
|
|
/// regions. I.e., we can rule out a RaW conflict if READ happensBefore WRITE
|
|
/// or WRITE happensBefore DEF. (Checked in `hasReadAfterWriteInterference`.)
|
|
///
|
|
bool canUseOpDominance(OpOperand *uRead, OpOperand *uWrite,
|
|
const SetVector<Value> &definitions,
|
|
const AnalysisState &state) {
|
|
const BufferizationOptions &options = state.getOptions();
|
|
for (Value def : definitions) {
|
|
Region *rRead = getEnclosingRepetitiveRegion(uRead->getOwner(), options);
|
|
Region *rDef = getEnclosingRepetitiveRegion(def, options);
|
|
|
|
// READ and DEF are in the same repetitive region. `happensBefore` can be
|
|
// used to rule out RaW conflicts due to op ordering.
|
|
if (rRead == rDef)
|
|
continue;
|
|
|
|
// Find the enclosing repetitive region of READ that is closest to DEF but
|
|
// not the repetitive region of DEF itself.
|
|
while (true) {
|
|
Region *nextRegion = getNextEnclosingRepetitiveRegion(rRead, options);
|
|
if (nextRegion == rDef)
|
|
break;
|
|
assert(nextRegion && "expected to find another repetitive region");
|
|
rRead = nextRegion;
|
|
}
|
|
|
|
// We cannot use op dominance if WRITE is inside the same repetitive region.
|
|
if (rRead->getParentOp()->isAncestor(uWrite->getOwner()))
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
/// Annotate IR with details about the detected RaW conflict.
|
|
static void annotateConflict(OpOperand *uRead, OpOperand *uConflictingWrite,
|
|
Value definition) {
|
|
static uint64_t counter = 0;
|
|
Operation *readingOp = uRead->getOwner();
|
|
Operation *conflictingWritingOp = uConflictingWrite->getOwner();
|
|
|
|
OpBuilder b(conflictingWritingOp->getContext());
|
|
std::string id = "C_" + std::to_string(counter++);
|
|
|
|
std::string conflictingWriteAttr =
|
|
id +
|
|
"[CONFL-WRITE: " + std::to_string(uConflictingWrite->getOperandNumber()) +
|
|
"]";
|
|
conflictingWritingOp->setAttr(conflictingWriteAttr, b.getUnitAttr());
|
|
|
|
std::string readAttr =
|
|
id + "[READ: " + std::to_string(uRead->getOperandNumber()) + "]";
|
|
readingOp->setAttr(readAttr, b.getUnitAttr());
|
|
|
|
if (auto opResult = dyn_cast<OpResult>(definition)) {
|
|
std::string defAttr =
|
|
id + "[DEF: result " + std::to_string(opResult.getResultNumber()) + "]";
|
|
opResult.getDefiningOp()->setAttr(defAttr, b.getUnitAttr());
|
|
} else {
|
|
auto bbArg = cast<BlockArgument>(definition);
|
|
std::string defAttr =
|
|
id + "[DEF: bbArg " + std::to_string(bbArg.getArgNumber()) + "]";
|
|
bbArg.getOwner()->getParentOp()->setAttr(defAttr, b.getUnitAttr());
|
|
}
|
|
}
|
|
|
|
/// Given sets of uses and writes, return true if there is a RaW conflict under
|
|
/// the assumption that all given reads/writes alias the same buffer and that
|
|
/// all given writes bufferize inplace.
|
|
///
|
|
/// A conflict is: According to SSA use-def chains, a read R is supposed to read
|
|
/// the result of a definition W1. But because of bufferization decisions, R
|
|
/// actually reads another definition W2.
|
|
static bool
|
|
hasReadAfterWriteInterference(const DenseSet<OpOperand *> &usesRead,
|
|
const DenseSet<OpOperand *> &usesWrite,
|
|
const DominanceInfo &domInfo,
|
|
OneShotAnalysisState &state) {
|
|
const BufferizationOptions &options = state.getOptions();
|
|
|
|
for (OpOperand *uRead : usesRead) {
|
|
Operation *readingOp = uRead->getOwner();
|
|
LLVM_DEBUG(llvm::dbgs() << "\n- check conflict:\n");
|
|
LLVM_DEBUG(llvm::dbgs() << " uRead = operand " << uRead->getOperandNumber()
|
|
<< " of " << *readingOp << "\n");
|
|
|
|
// Find the definition of uRead by following the SSA use-def chain.
|
|
// E.g.:
|
|
//
|
|
// %0 = "writing_op"(%t) : tensor<?x32> -> tensor<?xf32>
|
|
// %1 = "aliasing_op"(%0) : tensor<?x32> -> tensor<?xf32>
|
|
// %2 = "reading_op"(%1) : : tensor<?x32> -> not_a_tensor_type
|
|
//
|
|
// In the above example, if uRead is the OpOperand of reading_op, the
|
|
// definition is %0. Note that operations that create an alias but do not
|
|
// bufferize to a memory write (such as ExtractSliceOp) are skipped.
|
|
const SetVector<Value> &definitions =
|
|
state.findDefinitionsCached(uRead->get());
|
|
if (definitions.empty()) {
|
|
// Fast path: No conflict if there are no definitions.
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< " no conflict: read value has no definitions\n");
|
|
continue;
|
|
}
|
|
|
|
// Look for conflicting memory writes. Potential conflicts are writes to an
|
|
// alias that have been decided to bufferize inplace.
|
|
for (OpOperand *uConflictingWrite : usesWrite) {
|
|
LLVM_DEBUG(llvm::dbgs() << " unConflictingWrite = operand "
|
|
<< uConflictingWrite->getOperandNumber() << " of "
|
|
<< *uConflictingWrite->getOwner() << "\n");
|
|
|
|
// Check if op dominance can be used to rule out read-after-write
|
|
// conflicts.
|
|
bool useDominance =
|
|
canUseOpDominance(uRead, uConflictingWrite, definitions, state);
|
|
LLVM_DEBUG(llvm::dbgs() << "\n- useDominance = " << useDominance << "\n");
|
|
|
|
// Throughout this loop, check for multiple requirements that have to be
|
|
// met for uConflictingWrite to be an actual conflict.
|
|
Operation *conflictingWritingOp = uConflictingWrite->getOwner();
|
|
|
|
// Inside of repetitive regions, ops may be executed multiple times and op
|
|
// dominance cannot be used to rule out conflicts.
|
|
if (useDominance) {
|
|
// No conflict if the readingOp dominates conflictingWritingOp, i.e.,
|
|
// the write is not visible when reading.
|
|
//
|
|
// Note: If ops are executed multiple times (e.g., because they are
|
|
// inside a loop), there may be no meaningful `happensBefore`
|
|
// relationship.
|
|
if (happensBefore(readingOp, conflictingWritingOp, domInfo)) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< " no conflict: read happens before write\n");
|
|
continue;
|
|
}
|
|
|
|
// No conflict if the reading use equals the use of the conflicting
|
|
// write. A use cannot conflict with itself.
|
|
//
|
|
// Note: Just being the same op is not enough. It has to be the same
|
|
// use.
|
|
// Note: If the op is executed multiple times (e.g., because it is
|
|
// inside a loop), it may be conflicting with itself.
|
|
if (uConflictingWrite == uRead) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< " no conflict: read and write are same use\n");
|
|
continue;
|
|
}
|
|
|
|
// Ops are not conflicting if they are in mutually exclusive regions.
|
|
//
|
|
// Note: If ops are executed multiple times (e.g., because they are
|
|
// inside a loop), mutually exclusive regions may be executed
|
|
// multiple times.
|
|
if (insideMutuallyExclusiveRegions(readingOp, conflictingWritingOp)) {
|
|
LLVM_DEBUG(llvm::dbgs() << " no conflict: read and write are in "
|
|
"mutually exclusive regions\n");
|
|
continue;
|
|
}
|
|
}
|
|
|
|
// No conflict if the op interface says so.
|
|
if (auto bufferizableOp = options.dynCastBufferizableOp(readingOp)) {
|
|
if (bufferizableOp.isNotConflicting(uRead, uConflictingWrite, state)) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< " no conflict: op interace of reading op says 'no'\n");
|
|
continue;
|
|
}
|
|
}
|
|
|
|
if (conflictingWritingOp != readingOp) {
|
|
if (auto bufferizableOp =
|
|
options.dynCastBufferizableOp(conflictingWritingOp)) {
|
|
if (bufferizableOp.isNotConflicting(uRead, uConflictingWrite,
|
|
state)) {
|
|
LLVM_DEBUG(
|
|
llvm::dbgs()
|
|
<< " no conflict: op interace of writing op says 'no'\n");
|
|
continue;
|
|
}
|
|
}
|
|
}
|
|
|
|
// Check all possible definitions.
|
|
for (Value definition : definitions) {
|
|
LLVM_DEBUG(llvm::dbgs() << " * definition = " << definition << "\n");
|
|
|
|
// No conflict if the conflicting write happens before the definition.
|
|
if (Operation *defOp = definition.getDefiningOp()) {
|
|
if (happensBefore(conflictingWritingOp, defOp, domInfo)) {
|
|
// conflictingWritingOp happens before defOp. No conflict.
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< " no conflict: write happens before definition\n");
|
|
continue;
|
|
}
|
|
// No conflict if conflictingWritingOp is contained in defOp.
|
|
if (defOp->isProperAncestor(conflictingWritingOp)) {
|
|
LLVM_DEBUG(
|
|
llvm::dbgs()
|
|
<< " no conflict: write is contained in definition\n");
|
|
continue;
|
|
}
|
|
} else {
|
|
auto bbArg = cast<BlockArgument>(definition);
|
|
Block *block = bbArg.getOwner();
|
|
if (!block->findAncestorOpInBlock(*conflictingWritingOp)) {
|
|
LLVM_DEBUG(llvm::dbgs() << " no conflict: definition is bbArg "
|
|
"and write happens outside of block\n");
|
|
// conflictingWritingOp happens outside of the block. No
|
|
// conflict.
|
|
continue;
|
|
}
|
|
}
|
|
|
|
// No conflict if the conflicting write and the definition are the same
|
|
// use.
|
|
AliasingOpResultList aliases =
|
|
state.getAliasingOpResults(*uConflictingWrite);
|
|
if (aliases.getNumAliases() == 1 &&
|
|
aliases.getAliases()[0].opResult == definition) {
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< " no conflict: definition and write are same\n");
|
|
continue;
|
|
}
|
|
|
|
// All requirements are met. Conflict found!
|
|
|
|
if (options.printConflicts)
|
|
annotateConflict(uRead, uConflictingWrite, definition);
|
|
LLVM_DEBUG(llvm::dbgs() << " => RaW CONFLICT FOUND\n");
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
// Helper function to iterate on aliases of `root` and capture the writes.
|
|
static void getAliasingInplaceWrites(DenseSet<OpOperand *> &res, Value root,
|
|
const OneShotAnalysisState &state) {
|
|
state.applyOnAliases(root, [&](Value alias) {
|
|
for (auto &use : alias.getUses())
|
|
// Inplace write to a value that aliases root.
|
|
if (isInplaceMemoryWrite(use, state))
|
|
res.insert(&use);
|
|
});
|
|
}
|
|
|
|
// Helper function to iterate on aliases of `root` and capture the reads.
|
|
static void getAliasingReads(DenseSet<OpOperand *> &res, Value root,
|
|
const OneShotAnalysisState &state) {
|
|
state.applyOnAliases(root, [&](Value alias) {
|
|
for (auto &use : alias.getUses()) {
|
|
// Read of a value that aliases root.
|
|
if (state.bufferizesToMemoryRead(use)) {
|
|
res.insert(&use);
|
|
continue;
|
|
}
|
|
|
|
// Read of a dependent value in the SSA use-def chain. E.g.:
|
|
//
|
|
// %0 = ...
|
|
// %1 = tensor.extract_slice %0 {not_analyzed_yet}
|
|
// "read"(%1)
|
|
//
|
|
// In the above example, getAliasingReads(%0) includes the first OpOperand
|
|
// of the tensor.extract_slice op. The extract_slice itself does not read
|
|
// but its aliasing result is eventually fed into an op that does.
|
|
//
|
|
// Note: This is considered a "read" only if the use does not bufferize to
|
|
// a memory write. (We already ruled out memory reads. In case of a memory
|
|
// write, the buffer would be entirely overwritten; in the above example
|
|
// there would then be no flow of data from the extract_slice operand to
|
|
// its result's uses.)
|
|
if (!state.bufferizesToMemoryWrite(use)) {
|
|
AliasingOpResultList aliases = state.getAliasingOpResults(use);
|
|
if (llvm::any_of(aliases, [&](AliasingOpResult a) {
|
|
return state.isValueRead(a.opResult);
|
|
}))
|
|
res.insert(&use);
|
|
}
|
|
}
|
|
});
|
|
}
|
|
|
|
/// Return true if bufferizing `operand` inplace would create a conflict. A read
|
|
/// R and a write W of the same alias set is a conflict if inplace bufferization
|
|
/// of W changes the value read by R to a value different from the one that
|
|
/// would be expected by tracing back R's origin through SSA use-def chains.
|
|
/// A conflict can only be introduced by a new alias and/or an inplace
|
|
/// bufferization decision.
|
|
///
|
|
/// Example:
|
|
/// %0 = tensor.extract_slice %t[...][...][1, 1] {inplace?}
|
|
/// %1 = vector.transfer_write %v1, %t {inplace} : vector<5xf32>, tensor<?xf32>
|
|
/// %e = tensor.extract_slice %1
|
|
/// %2 = vector.transfer_write %v2, %0 {inplace} : vector<6xf32>, tensor<?xf32>
|
|
/// %3 = vector.transfer_read %e, %cst : tensor<?xf32>, vector<7xf32>
|
|
///
|
|
/// In the above example, the two TransferWriteOps have already been decided to
|
|
/// bufferize inplace. Bufferizing the ExtractSliceOp inplace would create a
|
|
/// conflict because:
|
|
/// * According to SSA use-def chains, we expect to read the result of %1.
|
|
/// * However, adding an alias {%0, %t} would mean that the second
|
|
/// TransferWriteOp overwrites the result of the first one. Therefore, the
|
|
/// TransferReadOp would no longer be reading the result of %1.
|
|
///
|
|
/// If `checkConsistencyOnly` is true, this function checks if there is a
|
|
/// read-after-write conflict without bufferizing `operand` inplace. This would
|
|
/// indicate a problem with the current inplace bufferization decisions.
|
|
///
|
|
/// Note: If `checkConsistencyOnly`, this function may be called with a null
|
|
/// OpResult. In that case, only the consistency of bufferization decisions
|
|
/// involving aliases of the given OpOperand are checked.
|
|
static bool wouldCreateReadAfterWriteInterference(
|
|
OpOperand &operand, const DominanceInfo &domInfo,
|
|
OneShotAnalysisState &state, bool checkConsistencyOnly = false) {
|
|
// Collect reads and writes of all aliases of OpOperand and OpResult.
|
|
DenseSet<OpOperand *> usesRead, usesWrite;
|
|
getAliasingReads(usesRead, operand.get(), state);
|
|
getAliasingInplaceWrites(usesWrite, operand.get(), state);
|
|
for (AliasingOpResult alias : state.getAliasingOpResults(operand)) {
|
|
getAliasingReads(usesRead, alias.opResult, state);
|
|
getAliasingInplaceWrites(usesWrite, alias.opResult, state);
|
|
}
|
|
if (!checkConsistencyOnly && state.bufferizesToMemoryWrite(operand))
|
|
usesWrite.insert(&operand);
|
|
|
|
return hasReadAfterWriteInterference(usesRead, usesWrite, domInfo, state);
|
|
}
|
|
|
|
/// Annotate IR with details about the detected non-writability conflict.
|
|
static void annotateNonWritableTensor(Value value) {
|
|
static int64_t counter = 0;
|
|
OpBuilder b(value.getContext());
|
|
std::string id = "W_" + std::to_string(counter++);
|
|
if (auto opResult = dyn_cast<OpResult>(value)) {
|
|
std::string attr = id + "[NOT-WRITABLE: result " +
|
|
std::to_string(opResult.getResultNumber()) + "]";
|
|
opResult.getDefiningOp()->setAttr(attr, b.getUnitAttr());
|
|
} else {
|
|
auto bbArg = cast<BlockArgument>(value);
|
|
std::string attr = id + "[NOT-WRITABLE: bbArg " +
|
|
std::to_string(bbArg.getArgNumber()) + "]";
|
|
bbArg.getOwner()->getParentOp()->setAttr(attr, b.getUnitAttr());
|
|
}
|
|
}
|
|
|
|
/// Return true if bufferizing `operand` inplace would create a write to a
|
|
/// non-writable buffer.
|
|
static bool
|
|
wouldCreateWriteToNonWritableBuffer(OpOperand &operand,
|
|
OneShotAnalysisState &state,
|
|
bool checkConsistencyOnly = false) {
|
|
bool foundWrite =
|
|
!checkConsistencyOnly && state.bufferizesToMemoryWrite(operand);
|
|
|
|
if (!foundWrite) {
|
|
// Collect writes of all aliases of OpOperand and OpResult.
|
|
DenseSet<OpOperand *> usesWrite;
|
|
getAliasingInplaceWrites(usesWrite, operand.get(), state);
|
|
for (AliasingOpResult alias : state.getAliasingOpResults(operand))
|
|
getAliasingInplaceWrites(usesWrite, alias.opResult, state);
|
|
foundWrite = !usesWrite.empty();
|
|
}
|
|
|
|
if (!foundWrite)
|
|
return false;
|
|
|
|
// Look for a read-only tensor among all aliases.
|
|
bool foundReadOnly = false;
|
|
auto checkReadOnly = [&](Value v) {
|
|
if (!state.isWritable(v)) {
|
|
foundReadOnly = true;
|
|
if (state.getOptions().printConflicts)
|
|
annotateNonWritableTensor(v);
|
|
}
|
|
};
|
|
state.applyOnAliases(operand.get(), checkReadOnly);
|
|
for (AliasingOpResult alias : state.getAliasingOpResults(operand))
|
|
state.applyOnAliases(alias.opResult, checkReadOnly);
|
|
if (foundReadOnly) {
|
|
LLVM_DEBUG(llvm::dbgs() << "=> NOT WRITABLE\n");
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Bufferization analyses.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
// Find the values that define the contents of the given value.
|
|
const llvm::SetVector<Value> &
|
|
OneShotAnalysisState::findDefinitionsCached(Value value) {
|
|
if (!cachedDefinitions.count(value))
|
|
cachedDefinitions[value] = findDefinitions(value);
|
|
return cachedDefinitions[value];
|
|
}
|
|
|
|
void OneShotAnalysisState::resetCache() { cachedDefinitions.clear(); }
|
|
|
|
/// Determine if `operand` can be bufferized in-place.
|
|
static LogicalResult
|
|
bufferizableInPlaceAnalysisImpl(OpOperand &operand, OneShotAnalysisState &state,
|
|
const DominanceInfo &domInfo) {
|
|
LLVM_DEBUG(
|
|
llvm::dbgs() << "//===-------------------------------------------===//\n"
|
|
<< "Analyzing operand #" << operand.getOperandNumber()
|
|
<< " of " << *operand.getOwner() << "\n");
|
|
|
|
bool foundInterference =
|
|
wouldCreateWriteToNonWritableBuffer(operand, state) ||
|
|
wouldCreateReadAfterWriteInterference(operand, domInfo, state);
|
|
|
|
if (foundInterference)
|
|
state.bufferizeOutOfPlace(operand);
|
|
else
|
|
state.bufferizeInPlace(operand);
|
|
|
|
LLVM_DEBUG(llvm::dbgs()
|
|
<< "//===-------------------------------------------===//\n");
|
|
return success();
|
|
}
|
|
|
|
LogicalResult
|
|
OneShotAnalysisState::analyzeSingleOp(Operation *op,
|
|
const DominanceInfo &domInfo) {
|
|
for (OpOperand &opOperand : op->getOpOperands())
|
|
if (isa<TensorType>(opOperand.get().getType()))
|
|
if (failed(bufferizableInPlaceAnalysisImpl(opOperand, *this, domInfo)))
|
|
return failure();
|
|
return success();
|
|
}
|
|
|
|
/// Return true if the given op has a tensor result or a tensor operand.
|
|
static bool hasTensorSemantics(Operation *op) {
|
|
bool hasTensorResult = any_of(op->getResultTypes(), isaTensor);
|
|
bool hasTensorOperand = any_of(op->getOperandTypes(), isaTensor);
|
|
return hasTensorResult || hasTensorOperand;
|
|
}
|
|
|
|
/// Analyze equivalence of tied OpResult/OpOperand pairs of the given ops.
|
|
static void equivalenceAnalysis(SmallVector<Operation *> &ops,
|
|
OneShotAnalysisState &state) {
|
|
for (Operation *op : ops) {
|
|
if (auto bufferizableOp = state.getOptions().dynCastBufferizableOp(op)) {
|
|
for (OpResult opResult : op->getOpResults()) {
|
|
if (!isa<TensorType>(opResult.getType()))
|
|
continue;
|
|
AliasingOpOperandList aliases = state.getAliasingOpOperands(opResult);
|
|
if (aliases.getNumAliases() == 0)
|
|
// Nothing to do if there are no aliasing OpOperands.
|
|
continue;
|
|
|
|
Value firstOperand = aliases.begin()->opOperand->get();
|
|
bool allEquivalent = true;
|
|
for (AliasingOpOperand alias : aliases) {
|
|
bool isEquiv = alias.relation == BufferRelation::Equivalent;
|
|
bool isInPlace = state.isInPlace(*alias.opOperand);
|
|
Value operand = alias.opOperand->get();
|
|
if (isEquiv && isInPlace && alias.isDefinite) {
|
|
// Found a definite, equivalent alias. Merge equivalence sets.
|
|
// There can only be one definite alias, so we can stop here.
|
|
state.unionEquivalenceClasses(opResult, operand);
|
|
allEquivalent = false;
|
|
break;
|
|
}
|
|
if (!isEquiv || !isInPlace)
|
|
allEquivalent = false;
|
|
if (!state.areEquivalentBufferizedValues(operand, firstOperand))
|
|
allEquivalent = false;
|
|
}
|
|
|
|
// If all "maybe" aliases are equivalent and the OpResult is not a new
|
|
// allocation, it is a definite, equivalent alias. E.g.:
|
|
//
|
|
// 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>
|
|
//
|
|
// If %t0 and %t1 are equivalent, it is safe to union the equivalence
|
|
// classes of %r, %t0 and %t1.
|
|
if (allEquivalent && !bufferizableOp.bufferizesToAllocation(opResult))
|
|
state.unionEquivalenceClasses(opResult, firstOperand);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/// Analyze equivalence of tied OpResult/OpOperand pairs of all ops contained
|
|
/// in `op`.
|
|
static void equivalenceAnalysis(Operation *op, OneShotAnalysisState &state) {
|
|
// Traverse ops in PostOrder: Nested ops first, then enclosing ops.
|
|
SmallVector<Operation *> ops;
|
|
op->walk<WalkOrder::PostOrder>([&](Operation *op) {
|
|
// No tensors => no buffers.
|
|
if (none_of(op->getResultTypes(), isaTensor))
|
|
return;
|
|
ops.push_back(op);
|
|
});
|
|
|
|
equivalenceAnalysis(ops, state);
|
|
}
|
|
|
|
LogicalResult OneShotAnalysisState::analyzeOp(Operation *op,
|
|
const DominanceInfo &domInfo) {
|
|
// Collect ops so we can build our own reverse traversal.
|
|
SmallVector<Operation *> ops;
|
|
op->walk([&](Operation *op) {
|
|
// No tensors => no buffers.
|
|
if (!hasTensorSemantics(op))
|
|
return;
|
|
ops.push_back(op);
|
|
});
|
|
|
|
if (getOptions().analysisFuzzerSeed) {
|
|
// This is a fuzzer. For testing purposes only. Randomize the order in which
|
|
// operations are analyzed. The bufferization quality is likely worse, but
|
|
// we want to make sure that no assertions are triggered anywhere.
|
|
std::mt19937 g(getOptions().analysisFuzzerSeed);
|
|
llvm::shuffle(ops.begin(), ops.end(), g);
|
|
}
|
|
|
|
OneShotBufferizationOptions::AnalysisHeuristic heuristic =
|
|
getOptions().analysisHeuristic;
|
|
if (heuristic == OneShotBufferizationOptions::AnalysisHeuristic::BottomUp) {
|
|
// Default: Walk ops in reverse for better interference analysis.
|
|
for (Operation *op : reverse(ops))
|
|
if (failed(analyzeSingleOp(op, domInfo)))
|
|
return failure();
|
|
} else if (heuristic ==
|
|
OneShotBufferizationOptions::AnalysisHeuristic::TopDown) {
|
|
for (Operation *op : ops)
|
|
if (failed(analyzeSingleOp(op, domInfo)))
|
|
return failure();
|
|
} else {
|
|
llvm_unreachable("unsupported heuristic");
|
|
}
|
|
|
|
equivalenceAnalysis(op, *this);
|
|
return success();
|
|
}
|
|
|
|
/// Assert that the current bufferization decisions are consistent.
|
|
static LogicalResult checkAliasInfoConsistency(Operation *op,
|
|
const DominanceInfo &domInfo,
|
|
OneShotAnalysisState &state) {
|
|
const BufferizationOptions &options = state.getOptions();
|
|
|
|
WalkResult walkResult = op->walk([&](BufferizableOpInterface op) {
|
|
// Skip ops that are not in the filter.
|
|
if (!options.isOpAllowed(op.getOperation()))
|
|
return WalkResult::advance();
|
|
|
|
// Input IR may not contain any ToMemrefOps. These are not supported because
|
|
// the analysis cannot follow the data flow through memrefs.
|
|
if (isa<ToMemrefOp>(op.getOperation())) {
|
|
op->emitError("to_memref ops are not supported by One-Shot Analysis");
|
|
return WalkResult::interrupt();
|
|
}
|
|
|
|
// Input IR may not contain any ToTensorOps without the "restrict"
|
|
// attribute. Such tensors may alias any other tensor, which is currently
|
|
// not handled in the analysis.
|
|
if (auto toTensorOp = dyn_cast<ToTensorOp>(op.getOperation())) {
|
|
if (!toTensorOp.getRestrict()) {
|
|
op->emitError("to_tensor ops without `restrict` are not supported by "
|
|
"One-Shot Analysis");
|
|
return WalkResult::interrupt();
|
|
}
|
|
}
|
|
|
|
for (OpOperand &opOperand : op->getOpOperands()) {
|
|
if (isa<TensorType>(opOperand.get().getType())) {
|
|
if (wouldCreateReadAfterWriteInterference(
|
|
opOperand, domInfo, state,
|
|
/*checkConsistencyOnly=*/true)) {
|
|
// This error can happen if certain "mustBufferizeInPlace" interface
|
|
// methods are implemented incorrectly, such that the IR already has
|
|
// a RaW conflict before making any bufferization decisions.
|
|
op->emitError("input IR has RaW conflict");
|
|
return WalkResult::interrupt();
|
|
}
|
|
}
|
|
}
|
|
|
|
return WalkResult::advance();
|
|
});
|
|
|
|
return success(!walkResult.wasInterrupted());
|
|
}
|
|
|
|
/// Annotate the IR with the result of the analysis. For testing/debugging only.
|
|
static void
|
|
annotateOpsWithBufferizationMarkers(Operation *op,
|
|
const OneShotAnalysisState &state) {
|
|
// Add __inplace_operands_attr__.
|
|
op->walk([&](Operation *op) {
|
|
for (OpOperand &opOperand : op->getOpOperands())
|
|
if (isa<TensorType>(opOperand.get().getType()))
|
|
setInPlaceOpOperand(opOperand, state.isInPlace(opOperand));
|
|
});
|
|
}
|
|
|
|
static void annotateOpsWithAliasSets(Operation *op,
|
|
const OneShotAnalysisState &state) {
|
|
AsmState asmState(op);
|
|
Builder b(op->getContext());
|
|
op->walk([&](Operation *op) {
|
|
SmallVector<Attribute> aliasSets;
|
|
for (OpResult opResult : op->getOpResults()) {
|
|
if (llvm::isa<TensorType>(opResult.getType())) {
|
|
SmallVector<Attribute> aliases;
|
|
state.applyOnAliases(opResult, [&](Value alias) {
|
|
std::string buffer;
|
|
llvm::raw_string_ostream stream(buffer);
|
|
alias.printAsOperand(stream, asmState);
|
|
aliases.push_back(b.getStringAttr(stream.str()));
|
|
});
|
|
aliasSets.push_back(b.getArrayAttr(aliases));
|
|
}
|
|
}
|
|
if (!aliasSets.empty())
|
|
op->setAttr(kAliasSetAttrName, b.getArrayAttr(aliasSets));
|
|
});
|
|
}
|
|
|
|
/// Assert that every allocation can be deallocated in the same block. I.e.,
|
|
/// every value that is returned or yielded from a block is:
|
|
/// * guaranteed to be aliasing a bbArg of that block or a parent block, or
|
|
/// * guaranteed to be aliasing an OpResult of a op in a parent block.
|
|
///
|
|
/// In that case, buffer deallocation is simple: Every allocated buffer can be
|
|
/// deallocated in the same block. Otherwise, the buffer deallocation pass must
|
|
/// be run.
|
|
///
|
|
/// Note: The current implementation checks for equivalent values instead of
|
|
/// aliasing values, which is stricter than needed. We can currently not check
|
|
/// for aliasing values because the analysis is a maybe-alias analysis and we
|
|
/// need a must-alias analysis here.
|
|
///
|
|
/// Example:
|
|
/// ```
|
|
/// %0 = "some_op" : tensor<?xf32>
|
|
/// %1 = scf.if %c -> (tensor<?xf32>) {
|
|
/// scf.yield %0 : tensor<?xf32>
|
|
/// } else {
|
|
/// %t = linalg.alloc_tensor : tensor<?xf32>
|
|
/// scf.yield %t : tensor<?xf32>
|
|
/// }
|
|
/// ```
|
|
///
|
|
/// In the above example, the second scf.yield op is problematic because the
|
|
/// yielded value %t is defined in the same block as the scf.yield op and
|
|
/// and bufferizes to a new allocation.
|
|
// TODO: Remove buffer deallocation from One-Shot Bufferize and fix the buffer
|
|
// deallocation pass.
|
|
static LogicalResult assertNoAllocsReturned(Operation *op,
|
|
const OneShotAnalysisState &state) {
|
|
LogicalResult status = success();
|
|
DominanceInfo domInfo(op);
|
|
op->walk([&](Operation *returnOp) {
|
|
if (!isRegionReturnLike(returnOp) ||
|
|
!state.getOptions().isOpAllowed(returnOp))
|
|
return WalkResult::advance();
|
|
|
|
for (OpOperand &returnValOperand : returnOp->getOpOperands()) {
|
|
Value returnVal = returnValOperand.get();
|
|
// Skip non-tensor values.
|
|
if (!isa<TensorType>(returnVal.getType()))
|
|
continue;
|
|
|
|
bool foundEquivValue = false;
|
|
state.applyOnEquivalenceClass(returnVal, [&](Value equivVal) {
|
|
if (auto bbArg = dyn_cast<BlockArgument>(equivVal)) {
|
|
Operation *definingOp = bbArg.getOwner()->getParentOp();
|
|
if (definingOp->isProperAncestor(returnOp))
|
|
foundEquivValue = true;
|
|
return;
|
|
}
|
|
|
|
Operation *definingOp = equivVal.getDefiningOp();
|
|
if (definingOp->getBlock()->findAncestorOpInBlock(
|
|
*returnOp->getParentOp()))
|
|
// Skip ops that happen after `returnOp` and parent ops.
|
|
if (happensBefore(definingOp, returnOp, domInfo))
|
|
foundEquivValue = true;
|
|
});
|
|
|
|
// Note: Returning/yielding buffer allocations is allowed only if
|
|
// `allowReturnAllocs` is set.
|
|
if (!foundEquivValue)
|
|
status = returnOp->emitError()
|
|
<< "operand #" << returnValOperand.getOperandNumber()
|
|
<< " may return/yield a new buffer allocation";
|
|
}
|
|
|
|
return WalkResult::advance();
|
|
});
|
|
|
|
return status;
|
|
}
|
|
|
|
LogicalResult bufferization::analyzeOp(Operation *op,
|
|
OneShotAnalysisState &state,
|
|
BufferizationStatistics *statistics) {
|
|
DominanceInfo domInfo(op);
|
|
const OneShotBufferizationOptions &options = state.getOptions();
|
|
|
|
if (failed(checkAliasInfoConsistency(op, domInfo, state)))
|
|
return failure();
|
|
|
|
// If the analysis fails, just return.
|
|
if (failed(state.analyzeOp(op, domInfo)))
|
|
return failure();
|
|
|
|
if (statistics) {
|
|
statistics->numTensorInPlace = state.getStatNumTensorInPlace();
|
|
statistics->numTensorOutOfPlace = state.getStatNumTensorOutOfPlace();
|
|
}
|
|
|
|
bool failedAnalysis = false;
|
|
if (!options.allowReturnAllocs)
|
|
failedAnalysis |= failed(assertNoAllocsReturned(op, state));
|
|
|
|
// Gather some extra analysis data.
|
|
state.gatherYieldedTensors(op);
|
|
state.gatherUndefinedTensorUses(op);
|
|
|
|
// Analysis verification: After setting up alias/equivalence sets, each op
|
|
// can check for expected invariants/limitations and fail the analysis if
|
|
// necessary.
|
|
op->walk([&](Operation *op) {
|
|
if (BufferizableOpInterface bufferizableOp =
|
|
options.dynCastBufferizableOp(op))
|
|
failedAnalysis |= failed(bufferizableOp.verifyAnalysis(state));
|
|
});
|
|
|
|
// Annotate operations if we only want to report the analysis.
|
|
if (options.testAnalysisOnly)
|
|
annotateOpsWithBufferizationMarkers(op, state);
|
|
if (options.dumpAliasSets)
|
|
annotateOpsWithAliasSets(op, state);
|
|
|
|
return success(!failedAnalysis);
|
|
}
|
|
|
|
LogicalResult
|
|
bufferization::runOneShotBufferize(Operation *op,
|
|
const OneShotBufferizationOptions &options,
|
|
BufferizationStatistics *statistics) {
|
|
assert(!(options.copyBeforeWrite && options.testAnalysisOnly) &&
|
|
"invalid combination of bufferization flags");
|
|
if (!options.copyBeforeWrite) {
|
|
// If a buffer is copied before every write, no analysis is needed.
|
|
if (failed(insertTensorCopies(op, options, statistics)))
|
|
return failure();
|
|
}
|
|
if (options.testAnalysisOnly)
|
|
return success();
|
|
return bufferizeOp(op, options, /*copyBeforeWrite=*/options.copyBeforeWrite,
|
|
/*opFilter=*/nullptr, statistics);
|
|
}
|