* Move Module Bufferization to the bufferization dialect. The implementation is split into `OneShotModuleBufferize.cpp` and `FuncBufferizableOpInterfaceImpl.cpp`, so that the external model implementation can be easily moved to the func dialect in the future. * Split and clean up test cases. A few test cases are still remaining in Linalg and will be updated separately. * `linalg.inplaceable` is renamed to `bufferization.writable` to accurately reflect its current usage. * Attributes and their verifiers are moved from the Linalg dialect to the Bufferization dialect. * Expand documentation. * Add a new flag to One-Shot Bufferize to allow for function boundary bufferization. Differential Revision: https://reviews.llvm.org/D122229
498 lines
20 KiB
C++
498 lines
20 KiB
C++
//===- ModuleBufferization.cpp - Bufferization across Func. Boundaries ----===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// Module Bufferization is an extension of One-Shot Bufferize that
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// bufferizes function boundaries. It provides `BufferizableOpInterface`
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// implementations for FuncOp, CallOp and ReturnOp.
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//
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// Module Bufferization is run via `runOneShotModuleBufferize(ModuleOp, ...)`.
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// This function analyzes the given module and determines the order of analysis
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// and bufferization: Functions that are called are processed before their
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// respective callers.
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//
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// After analyzing a FuncOp, additional information about its bbArgs is
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// gathered through PostAnalysisStepFns and stored in `FuncAnalysisState`.
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//
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// * `aliasingFuncOpBBArgsAnalysis` determines the equivalent/aliasing bbArgs
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// for
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// each tensor return value (if any).
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// * `funcOpBbArgReadWriteAnalysis` determines whether or not a tensor bbArg is
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// read/written.
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//
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// Only tensors that are equivalent to some FuncOp bbArg may be returned.
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// Bufferization currently fails if other tensors (in particular tensors that
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// bufferize out-of-place and result in a new buffer allocation) are returned.
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// In the future, such allocations could be hoisted to the caller.
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//
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// Example: `foo` fails bufferization because %0 is not equivalent to any bbArg.
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// ```
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// func @foo() -> tensor<?xf32> {
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// %0 = linalg.init_tensor [...] : tensor<?xf32>
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// return %0 : tensor<?xf32>
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// }
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// ```
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//
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// Module Bufferization implements the following calling convention.
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//
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// * In the absence of conflicts within a FuncOp, the FuncOp's bbArgs may always
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// be written to in-place.
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// * If a tensor operand of a CallOp is read after the CallOp, the operand of
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// the CallOp must bufferize out-of-place.
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//
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// Example: The tensor.insert op bufferizes in-place because it is allowed to
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// modify the buffer of `%t1` directly. The CallOp in `caller` must bufferize
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// out-of-place because `%t0` is modified by the callee but read by the
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// tensor.extract op. The analysis of CallOps decides whether an OpOperand must
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// bufferize out-of-place based on results of `funcOpBbArgReadWriteAnalysis`.
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// ```
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// func @callee(%t1 : tensor<?xf32>) -> tensor<?xf32> {
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// %f = ... : f32
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// %0 = tensor.insert %f into %t1[...] : tensor<?xf32>
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// return %0 : tensor<?xf32>
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// }
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//
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// func @caller() -> () {
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// %t0 = ... : tensor<?xf32>
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// %1 = call @callee(%t0) : (tensor<?xf32>) -> (tensor<?xf32>)
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// %2 = tensor.extract %1[...] : tensor<?xf32>
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// }
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// ```
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//
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// Note: If a function is external, `funcOpBbArgReadWriteAnalysis` cannot
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// analyze the function body. In such a case, the CallOp analysis conservatively
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// assumes that each tensor OpOperand is both read and written.
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//
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// TODO: Add FuncOp attributes so that bbArgs of external FuncOps can be marked
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// as "not reading" and/or "not writing".
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#include "mlir/Dialect/Bufferization/Transforms/OneShotModuleBufferize.h"
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#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
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#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
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#include "mlir/Dialect/Bufferization/Transforms/Bufferize.h"
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#include "mlir/Dialect/Bufferization/Transforms/FuncBufferizableOpInterfaceImpl.h"
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#include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Dialect/MemRef/IR/MemRef.h"
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#include "mlir/IR/Operation.h"
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using namespace mlir;
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using namespace mlir::bufferization;
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using namespace mlir::bufferization::func_ext;
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/// A mapping of FuncOps to their callers.
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using FuncCallerMap = DenseMap<func::FuncOp, DenseSet<Operation *>>;
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/// Get FuncAnalysisState.
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static const FuncAnalysisState &
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getFuncAnalysisState(const AnalysisState &state) {
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Optional<const FuncAnalysisState *> maybeState =
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state.getDialectState<FuncAnalysisState>(
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func::FuncDialect::getDialectNamespace());
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assert(maybeState.hasValue() && "FuncAnalysisState does not exist");
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return **maybeState;
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}
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/// Get or create FuncAnalysisState.
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static FuncAnalysisState &getFuncAnalysisState(AnalysisState &state) {
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return state.getOrCreateDialectState<FuncAnalysisState>(
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func::FuncDialect::getDialectNamespace());
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}
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/// Return the state (phase) of analysis of the FuncOp.
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static FuncOpAnalysisState getFuncOpAnalysisState(const AnalysisState &state,
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func::FuncOp funcOp) {
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const FuncAnalysisState &funcState = getFuncAnalysisState(state);
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auto it = funcState.analyzedFuncOps.find(funcOp);
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if (it == funcState.analyzedFuncOps.end())
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return FuncOpAnalysisState::NotAnalyzed;
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return it->second;
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}
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/// Return the unique ReturnOp that terminates `funcOp`.
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/// Return nullptr if there is no such unique ReturnOp.
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static func::ReturnOp getAssumedUniqueReturnOp(func::FuncOp funcOp) {
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func::ReturnOp returnOp;
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for (Block &b : funcOp.getBody()) {
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if (auto candidateOp = dyn_cast<func::ReturnOp>(b.getTerminator())) {
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if (returnOp)
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return nullptr;
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returnOp = candidateOp;
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}
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}
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return returnOp;
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}
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namespace {
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/// Annotate IR with the results of the analysis. For testing purposes only.
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static void annotateEquivalentReturnBbArg(OpOperand &returnVal,
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BlockArgument bbArg) {
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const char *kEquivalentArgsAttr = "__equivalent_func_args__";
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Operation *op = returnVal.getOwner();
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SmallVector<int64_t> equivBbArgs;
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if (op->hasAttr(kEquivalentArgsAttr)) {
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auto attr = op->getAttr(kEquivalentArgsAttr).cast<ArrayAttr>();
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equivBbArgs = llvm::to_vector<4>(llvm::map_range(attr, [](Attribute a) {
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return a.cast<IntegerAttr>().getValue().getSExtValue();
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}));
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} else {
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equivBbArgs.append(op->getNumOperands(), -1);
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}
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equivBbArgs[returnVal.getOperandNumber()] = bbArg.getArgNumber();
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OpBuilder b(op->getContext());
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op->setAttr(kEquivalentArgsAttr, b.getI64ArrayAttr(equivBbArgs));
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}
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/// Store function BlockArguments that are equivalent to/aliasing a returned
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/// value in FuncAnalysisState.
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static LogicalResult
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aliasingFuncOpBBArgsAnalysis(Operation *op, AnalysisState &state,
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BufferizationAliasInfo &aliasInfo,
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SmallVector<Operation *> &newOps) {
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FuncAnalysisState &funcState = getFuncAnalysisState(state);
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// Support only single return-terminated block in the function.
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auto funcOp = cast<func::FuncOp>(op);
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func::ReturnOp returnOp = getAssumedUniqueReturnOp(funcOp);
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assert(returnOp && "expected func with single return op");
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for (OpOperand &returnVal : returnOp->getOpOperands())
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if (returnVal.get().getType().isa<RankedTensorType>())
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for (BlockArgument bbArg : funcOp.getArguments())
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if (bbArg.getType().isa<RankedTensorType>()) {
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int64_t returnIdx = returnVal.getOperandNumber();
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int64_t bbArgIdx = bbArg.getArgNumber();
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if (aliasInfo.areEquivalentBufferizedValues(returnVal.get(), bbArg)) {
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funcState.equivalentFuncArgs[funcOp][returnIdx] = bbArgIdx;
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if (state.getOptions().testAnalysisOnly)
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annotateEquivalentReturnBbArg(returnVal, bbArg);
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}
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if (aliasInfo.areAliasingBufferizedValues(returnVal.get(), bbArg)) {
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funcState.aliasingFuncArgs[funcOp][returnIdx].push_back(bbArgIdx);
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funcState.aliasingReturnVals[funcOp][bbArgIdx].push_back(returnIdx);
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}
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}
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return success();
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}
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/// Return true if the buffer of the given tensor value is written to. Must not
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/// be called for values inside not yet analyzed functions. (Post-analysis
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/// steps do not have to be run yet, i.e., "in progress" is also OK.)
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static bool isValueWritten(Value value, const AnalysisState &state,
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const BufferizationAliasInfo &aliasInfo) {
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#ifndef NDEBUG
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assert(value.getType().isa<TensorType>() && "expected TensorType");
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func::FuncOp funcOp;
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if (auto bbArg = value.dyn_cast<BlockArgument>()) {
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Operation *owner = bbArg.getOwner()->getParentOp();
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funcOp = isa<func::FuncOp>(owner) ? cast<func::FuncOp>(owner)
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: owner->getParentOfType<func::FuncOp>();
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} else {
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funcOp = value.getDefiningOp()->getParentOfType<func::FuncOp>();
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}
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assert(getFuncOpAnalysisState(state, funcOp) !=
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FuncOpAnalysisState::NotAnalyzed &&
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"FuncOp must be fully analyzed or analysis in progress");
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#endif // NDEBUG
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bool isWritten = false;
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aliasInfo.applyOnAliases(value, [&](Value val) {
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for (OpOperand &use : val.getUses())
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if (state.isInPlace(use) && state.bufferizesToMemoryWrite(use))
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isWritten = true;
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});
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return isWritten;
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}
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static void annotateFuncArgAccess(func::FuncOp funcOp, BlockArgument bbArg,
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bool isRead, bool isWritten) {
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OpBuilder b(funcOp.getContext());
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Attribute accessType;
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if (isRead && isWritten) {
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accessType = b.getStringAttr("read-write");
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} else if (isRead) {
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accessType = b.getStringAttr("read");
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} else if (isWritten) {
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accessType = b.getStringAttr("write");
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} else {
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accessType = b.getStringAttr("none");
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}
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funcOp.setArgAttr(bbArg.getArgNumber(), "bufferization.access", accessType);
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}
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/// Determine which FuncOp bbArgs are read and which are written. If this
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/// PostAnalysisStepFn is run on a function with unknown ops, it will
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/// conservatively assume that such ops bufferize to a read + write.
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static LogicalResult
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funcOpBbArgReadWriteAnalysis(Operation *op, AnalysisState &state,
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BufferizationAliasInfo &aliasInfo,
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SmallVector<Operation *> &newOps) {
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FuncAnalysisState &funcState = getFuncAnalysisState(state);
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auto funcOp = cast<func::FuncOp>(op);
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// If the function has no body, conservatively assume that all args are
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// read + written.
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if (funcOp.getBody().empty()) {
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for (BlockArgument bbArg : funcOp.getArguments()) {
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funcState.readBbArgs[funcOp].insert(bbArg.getArgNumber());
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funcState.writtenBbArgs[funcOp].insert(bbArg.getArgNumber());
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}
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return success();
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}
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for (BlockArgument bbArg : funcOp.getArguments()) {
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if (!bbArg.getType().isa<TensorType>())
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continue;
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bool isRead = state.isValueRead(bbArg);
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bool isWritten = isValueWritten(bbArg, state, aliasInfo);
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if (state.getOptions().testAnalysisOnly)
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annotateFuncArgAccess(funcOp, bbArg, isRead, isWritten);
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if (isRead)
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funcState.readBbArgs[funcOp].insert(bbArg.getArgNumber());
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if (isWritten)
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funcState.writtenBbArgs[funcOp].insert(bbArg.getArgNumber());
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}
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return success();
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}
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} // namespace
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/// Remove bufferization attributes on FuncOp arguments.
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static void removeBufferizationAttributes(BlockArgument bbArg) {
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auto funcOp = cast<func::FuncOp>(bbArg.getOwner()->getParentOp());
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funcOp.removeArgAttr(bbArg.getArgNumber(),
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BufferizationDialect::kBufferLayoutAttrName);
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funcOp.removeArgAttr(bbArg.getArgNumber(),
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BufferizationDialect::kWritableAttrName);
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}
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/// Return the func::FuncOp called by `callOp`.
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static func::FuncOp getCalledFunction(CallOpInterface callOp) {
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SymbolRefAttr sym = callOp.getCallableForCallee().dyn_cast<SymbolRefAttr>();
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if (!sym)
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return nullptr;
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return dyn_cast_or_null<func::FuncOp>(
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SymbolTable::lookupNearestSymbolFrom(callOp, sym));
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}
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/// Gather equivalence info of CallOps.
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/// Note: This only adds new equivalence info if the called function was already
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/// analyzed.
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// TODO: This does not handle cyclic function call graphs etc.
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static void equivalenceAnalysis(func::FuncOp funcOp,
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BufferizationAliasInfo &aliasInfo,
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FuncAnalysisState &funcState) {
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funcOp->walk([&](func::CallOp callOp) {
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func::FuncOp calledFunction = getCalledFunction(callOp);
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assert(calledFunction && "could not retrieved called func::FuncOp");
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// No equivalence info available for the called function.
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if (!funcState.equivalentFuncArgs.count(calledFunction))
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return WalkResult::skip();
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for (auto it : funcState.equivalentFuncArgs[calledFunction]) {
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int64_t returnIdx = it.first;
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int64_t bbargIdx = it.second;
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Value returnVal = callOp.getResult(returnIdx);
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Value argVal = callOp->getOperand(bbargIdx);
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aliasInfo.unionEquivalenceClasses(returnVal, argVal);
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}
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return WalkResult::advance();
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});
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}
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/// Store all functions of the `moduleOp` in `orderedFuncOps`, sorted by
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/// callee-caller order (i.e. callees without callers first).
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/// Store the map of FuncOp to all its callers in `callerMap`.
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/// Return `failure()` if a cycle of calls is detected or if we are unable to
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/// retrieve the called FuncOp from any CallOpInterface.
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static LogicalResult
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getFuncOpsOrderedByCalls(ModuleOp moduleOp,
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SmallVectorImpl<func::FuncOp> &orderedFuncOps,
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FuncCallerMap &callerMap) {
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// For each FuncOp, the set of functions called by it (i.e. the union of
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// symbols of all nested CallOpInterfaceOp).
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DenseMap<func::FuncOp, DenseSet<func::FuncOp>> calledBy;
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// For each FuncOp, the number of CallOpInterface it contains.
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DenseMap<func::FuncOp, unsigned> numberCallOpsContainedInFuncOp;
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WalkResult res = moduleOp.walk([&](func::FuncOp funcOp) -> WalkResult {
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if (!funcOp.getBody().empty()) {
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func::ReturnOp returnOp = getAssumedUniqueReturnOp(funcOp);
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if (!returnOp)
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return funcOp->emitError()
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<< "cannot bufferize a FuncOp with tensors and "
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"without a unique ReturnOp";
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}
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numberCallOpsContainedInFuncOp[funcOp] = 0;
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return funcOp.walk([&](CallOpInterface callOp) -> WalkResult {
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// Only support CallOp for now.
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if (!isa<func::CallOp>(callOp.getOperation()))
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return callOp->emitError() << "expected a CallOp";
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func::FuncOp calledFunction = getCalledFunction(callOp);
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assert(calledFunction && "could not retrieved called func::FuncOp");
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auto it = callerMap.try_emplace(calledFunction, DenseSet<Operation *>{});
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it.first->getSecond().insert(callOp);
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if (calledBy[calledFunction].count(funcOp) == 0) {
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calledBy[calledFunction].insert(funcOp);
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numberCallOpsContainedInFuncOp[funcOp]++;
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}
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return WalkResult::advance();
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});
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});
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if (res.wasInterrupted())
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return failure();
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// Iteratively remove function operation that do not call any of the
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// functions remaining in the callCounter map and add them to the worklist.
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while (!numberCallOpsContainedInFuncOp.empty()) {
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auto it = llvm::find_if(numberCallOpsContainedInFuncOp,
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[](auto entry) { return entry.getSecond() == 0; });
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if (it == numberCallOpsContainedInFuncOp.end())
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return moduleOp.emitOpError(
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"expected callgraph to be free of circular dependencies.");
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orderedFuncOps.push_back(it->getFirst());
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for (auto callee : calledBy[it->getFirst()])
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numberCallOpsContainedInFuncOp[callee]--;
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numberCallOpsContainedInFuncOp.erase(it);
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}
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return success();
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}
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/// Set the attribute that triggers inplace bufferization on a FuncOp argument
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/// `bbArg`.
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static void setInPlaceFuncArgument(BlockArgument bbArg, bool inPlace) {
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auto funcOp = cast<func::FuncOp>(bbArg.getOwner()->getParentOp());
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funcOp.setArgAttr(bbArg.getArgNumber(),
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BufferizableOpInterface::kInplaceableAttrName,
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BoolAttr::get(bbArg.getContext(), inPlace));
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}
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/// Annotate the IR with the result of the analysis. For testing/debugging only.
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static void annotateOpsWithBufferizationMarkers(func::FuncOp funcOp,
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const AnalysisState &state) {
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auto bufferizableOp = cast<BufferizableOpInterface>(funcOp.getOperation());
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for (BlockArgument bbArg : funcOp.getArguments())
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if (bbArg.getType().isa<TensorType>())
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setInPlaceFuncArgument(bbArg, bufferizableOp.isWritable(bbArg, state));
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}
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/// Fold return values that are memref casts and update function return types.
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///
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/// During FuncOp bufferization, the exact type of the returned memrefs (if any)
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/// is not known yet. Therefore, the bufferization uses memref types with the
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/// most generic layout map as function return types. After bufferizing the
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/// entire function body, a more concise memref type can potentially be used for
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/// the return type of the function.
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static void foldMemRefCasts(func::FuncOp funcOp) {
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if (funcOp.getBody().empty())
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return;
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func::ReturnOp returnOp = getAssumedUniqueReturnOp(funcOp);
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SmallVector<Type> resultTypes;
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for (OpOperand &operand : returnOp->getOpOperands()) {
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if (auto castOp = operand.get().getDefiningOp<memref::CastOp>()) {
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operand.set(castOp.source());
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resultTypes.push_back(castOp.source().getType());
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} else {
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resultTypes.push_back(operand.get().getType());
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}
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}
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auto newFuncType = FunctionType::get(
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funcOp.getContext(), funcOp.getFunctionType().getInputs(), resultTypes);
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funcOp.setType(newFuncType);
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}
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LogicalResult mlir::bufferization::runOneShotModuleBufferize(
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ModuleOp moduleOp, OneShotBufferizationOptions options) {
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IRRewriter rewriter(moduleOp.getContext());
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OneShotAnalysisState analysisState(moduleOp, options);
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BufferizationState bufferizationState(analysisState);
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FuncAnalysisState &funcState = getFuncAnalysisState(analysisState);
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BufferizationAliasInfo &aliasInfo = analysisState.getAliasInfo();
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// A list of functions in the order in which they are analyzed + bufferized.
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SmallVector<func::FuncOp> orderedFuncOps;
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// A mapping of FuncOps to their callers.
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FuncCallerMap callerMap;
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if (failed(getFuncOpsOrderedByCalls(moduleOp, orderedFuncOps, callerMap)))
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return failure();
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// Collect bbArg/return value information after the analysis.
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options.addPostAnalysisStep(aliasingFuncOpBBArgsAnalysis);
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|
options.addPostAnalysisStep(funcOpBbArgReadWriteAnalysis);
|
|
|
|
// Analyze ops.
|
|
for (func::FuncOp funcOp : orderedFuncOps) {
|
|
// No body => no analysis.
|
|
if (funcOp.getBody().empty())
|
|
continue;
|
|
|
|
// Now analyzing function.
|
|
funcState.startFunctionAnalysis(funcOp);
|
|
|
|
// Gather equivalence info for CallOps.
|
|
equivalenceAnalysis(funcOp, aliasInfo, funcState);
|
|
|
|
// Analyze funcOp.
|
|
if (failed(analyzeOp(funcOp, analysisState)))
|
|
return failure();
|
|
|
|
// Mark op as fully analyzed.
|
|
funcState.analyzedFuncOps[funcOp] = FuncOpAnalysisState::Analyzed;
|
|
|
|
// Add annotations to function arguments.
|
|
if (options.testAnalysisOnly)
|
|
annotateOpsWithBufferizationMarkers(funcOp, analysisState);
|
|
}
|
|
|
|
if (options.testAnalysisOnly)
|
|
return success();
|
|
|
|
// Bufferize functions.
|
|
for (func::FuncOp funcOp : orderedFuncOps) {
|
|
// Note: It would be good to apply cleanups here but we cannot as aliasInfo
|
|
// would be invalidated.
|
|
if (failed(bufferizeOp(funcOp, bufferizationState)))
|
|
return failure();
|
|
foldMemRefCasts(funcOp);
|
|
}
|
|
|
|
// Check result.
|
|
for (func::FuncOp funcOp : orderedFuncOps) {
|
|
if (!options.allowReturnAllocs &&
|
|
llvm::any_of(funcOp.getFunctionType().getResults(), [](Type t) {
|
|
return t.isa<MemRefType, UnrankedMemRefType>();
|
|
})) {
|
|
funcOp->emitError("memref return type is unsupported");
|
|
return failure();
|
|
}
|
|
}
|
|
|
|
// Finalize all buffers.
|
|
if (failed(finalizeBuffers(moduleOp, options)))
|
|
return failure();
|
|
|
|
// Post-pass cleanup of function argument attributes.
|
|
moduleOp.walk([&](func::FuncOp op) {
|
|
for (BlockArgument bbArg : op.getArguments())
|
|
removeBufferizationAttributes(bbArg);
|
|
});
|
|
|
|
return success();
|
|
}
|