238 lines
9.7 KiB
C++
238 lines
9.7 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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// This file implements logic for lowering XLA dialect to Standard dialect.
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#include "third_party/llvm/llvm-project/llvm/include/llvm/ADT/STLExtras.h"
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#include "third_party/llvm/llvm-project/llvm/include/llvm/ADT/StringSwitch.h"
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#include "third_party/llvm/llvm-project/llvm/include/llvm/Support/Casting.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/Dialect/StandardOps/IR/Ops.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/IR/Block.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/IR/BlockAndValueMapping.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/IR/Builders.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/IR/Function.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/IR/PatternMatch.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/IR/StandardTypes.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/IR/TypeUtilities.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/Pass/Pass.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/Pass/PassRegistry.h"
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#include "third_party/llvm/llvm-project/mlir/include/mlir/Support/LogicalResult.h"
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#include "third_party/tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"
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#include "third_party/tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/transforms/passes.h"
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using mlir::PassRegistration;
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namespace mlir {
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namespace xla_hlo {
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namespace {
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struct LegalizeControlFlow
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: public mlir::PassWrapper<LegalizeControlFlow, FunctionPass> {
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// Perform the lowering to MLIR control flow.
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void runOnFunction() override;
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};
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// Replaces terminators for the newly created blocks from a targe region.
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// These terminators are replaced with branch operations to a target block.
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LogicalResult ReplaceTerminators(Region* region, Block* target_block,
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Location loc,
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const BlockAndValueMapping& mapper,
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OpBuilder* builder) {
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for (auto& old_block : region->getBlocks()) {
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Block* block = mapper.lookup(&old_block);
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auto return_op = dyn_cast<xla_hlo::ReturnOp>(block->getTerminator());
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if (!return_op) continue;
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builder->setInsertionPointToEnd(block);
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builder->create<mlir::BranchOp>(loc, target_block, return_op.getOperands());
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return_op.erase();
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}
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return success();
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}
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LogicalResult LowerIfOp(mlir::xla_hlo::IfOp if_op) {
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Operation* op_inst = if_op.getOperation();
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mlir::OpBuilder builder(if_op);
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auto orig_block = op_inst->getBlock();
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auto* tail_block = orig_block->splitBlock(op_inst);
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auto loc = if_op.getLoc();
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// Duplicate the true and false regions in the block between the sections
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// before and after the conditional.
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BlockAndValueMapping mapper;
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if_op.true_branch().cloneInto(orig_block->getParent(),
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Region::iterator(tail_block), mapper);
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if_op.false_branch().cloneInto(orig_block->getParent(),
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Region::iterator(tail_block), mapper);
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// Determine the blocks for the start of the true and false regions.
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Block* true_block = mapper.lookup(&if_op.true_branch().front());
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Block* false_block = mapper.lookup(&if_op.false_branch().front());
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// Perform the conditional branch into the true/false cases.
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builder.setInsertionPointToEnd(orig_block);
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// Extract the predicate for checking branching, then branch to the true and
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// false regions appropriately.
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auto cond_value = builder.create<mlir::ExtractElementOp>(loc, if_op.pred());
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builder.create<mlir::CondBranchOp>(loc, cond_value, true_block,
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if_op.true_arg(), false_block,
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if_op.false_arg());
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// Replace the true case's return operations with a branch to the tail of
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// the condition.
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if (failed(ReplaceTerminators(&if_op.true_branch(), tail_block, loc, mapper,
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&builder)))
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return failure();
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if (failed(ReplaceTerminators(&if_op.false_branch(), tail_block, loc, mapper,
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&builder)))
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return failure();
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tail_block->addArguments(if_op.getResult().getType());
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if_op.getResult().replaceAllUsesWith(tail_block->getArgument(0));
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op_inst->erase();
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return success();
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}
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LogicalResult LowerWhileOp(mlir::xla_hlo::WhileOp while_op) {
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// Converts an XLA while loop into control flow. This generates a set of MLIR
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// blocks and branches, along with inlining the regions provided by the XLA
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// while loop. The structure should be similar to below:
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//
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// <prior operations>
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// %0 = "xla_hlo.while"(%arg0) {^cond(...){...}, ^body(...){...}}
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// <post operations>
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auto* op_inst = while_op.getOperation();
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mlir::OpBuilder builder(while_op);
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auto loc = while_op.getLoc();
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// Break the block into four sections:
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// orig_block - operations before the while and the branch into looping check.
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// tail_block - operations after the while loop completes.
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// cond_block - check the looping condition, then conditionally branch into
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// the loop or, if condition is false, jump to the tail branch.
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// body_block - inlined loop body, then jump back to the condition block.
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auto* orig_block = op_inst->getBlock();
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auto* tail_block = orig_block->splitBlock(op_inst);
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BlockAndValueMapping mapper;
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while_op.cond().cloneInto(orig_block->getParent(),
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Region::iterator(tail_block), mapper);
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while_op.body().cloneInto(orig_block->getParent(),
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Region::iterator(tail_block), mapper);
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// Lookup the entry blocks for both condition and body.
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auto* cond_block = mapper.lookup(&while_op.cond().front());
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auto* body_block = mapper.lookup(&while_op.body().front());
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// Setup the end of the original block:
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// <prior operations>
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// br ^cond(%arg0) // Jumps to the condition statement.
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builder.setInsertionPointToEnd(orig_block);
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builder.create<mlir::BranchOp>(loc, cond_block, while_op.getOperand());
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// Updates the inlined condition blocks by replacing the return op with an
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// extract_element and conditional branch. This changes the block below:
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// ^cond(%0):
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// <inlined conditional region>
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// "xla_hlo".return(%1)
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//
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// Into:
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// ^cond(%0):
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// <inlined conditional region>
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// %2 = extract_element %1[] : tensor<i1> // Extract the condition value.
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// cond_br %2, ^body(%0), ^tail(%0) // Branch.
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builder.setInsertionPointToStart(cond_block);
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// Replace the xla_hlo::ReturnOp with a branch back to the condition block.
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// This is required as the xla_hlo::ReturnOp is used to mark the end of a
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// block for regions nested inside of a operations (MLIR ReturnOp cannot be
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// nested within an non-function region).
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for (auto& block : while_op.cond()) {
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auto new_block = mapper.lookup(&block);
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auto return_op = dyn_cast<xla_hlo::ReturnOp>(new_block->getTerminator());
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if (!return_op) continue;
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builder.setInsertionPointToEnd(new_block);
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auto return_value = return_op.getOperand(0);
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auto cond_value = builder.create<mlir::ExtractElementOp>(loc, return_value);
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// Get the body block arguments.
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llvm::SmallVector<Value, 4> successor_args(cond_block->args_begin(),
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cond_block->args_end());
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builder.create<mlir::CondBranchOp>(loc, cond_value, body_block,
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successor_args, tail_block,
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successor_args);
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return_op.erase();
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}
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// Updates the body blocks by replace the return op with an branch to the
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// conditional block. This changes the block below:
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// ^body(%0):
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// <inlined body block>
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// "xla_hlo".return(%1)
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//
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// Into:
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// ^body(%0):
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// <inlined body block>
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// br ^cond(%0) // Branch.
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for (auto& block : while_op.body()) {
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auto new_block = mapper.lookup(&block);
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auto return_op =
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dyn_cast<mlir::xla_hlo::ReturnOp>(new_block->getTerminator());
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if (!return_op) continue;
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builder.setInsertionPointToEnd(new_block);
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builder.create<mlir::BranchOp>(loc, cond_block, return_op.getOperands());
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return_op.erase();
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}
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// Erase the original while loop.
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tail_block->addArgument(while_op.getType());
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while_op.getResult().replaceAllUsesWith(tail_block->getArgument(0));
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op_inst->erase();
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return success();
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}
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void LegalizeControlFlow::runOnFunction() {
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auto func = getFunction();
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llvm::SmallVector<IfOp, 4> if_ops;
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func.walk([&](IfOp op) { if_ops.push_back(op); });
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for (auto& op : if_ops) {
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if (failed(LowerIfOp(op))) return signalPassFailure();
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}
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llvm::SmallVector<WhileOp, 4> while_ops;
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func.walk([&](WhileOp op) { while_ops.push_back(op); });
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for (auto& op : while_ops) {
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if (failed(LowerWhileOp(op))) return signalPassFailure();
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}
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}
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} // namespace
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} // namespace xla_hlo
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} // namespace mlir
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std::unique_ptr<mlir::OperationPass<mlir::FuncOp>>
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mlir::xla_hlo::createLegalizeControlFlowPass() {
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return std::make_unique<LegalizeControlFlow>();
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}
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static PassRegistration<mlir::xla_hlo::LegalizeControlFlow> legalize_cf_pass(
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"xla-legalize-control-flow",
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"Legalize from XLA control flow to MLIR control flow");
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