llvm-project/mlir/tools/mlir-opt/mlir-opt.cpp

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//===- mlir-opt.cpp - MLIR Optimizer Driver -------------------------------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
//
// Main entry function for mlir-opt for when built as standalone binary.
//
//===----------------------------------------------------------------------===//
Introduce memref bound checking. Introduce analysis to check memref accesses (in MLFunctions) for out of bound ones. It works as follows: $ mlir-opt -memref-bound-check test/Transforms/memref-bound-check.mlir /tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#2 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#2 %x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32> ^ /tmp/single.mlir:12:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1 %y = load %B[%idy] : memref<128 x i32> ^ /tmp/single.mlir:12:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1 %y = load %B[%idy] : memref<128 x i32> ^ #map0 = (d0, d1) -> (d0, d1) #map1 = (d0, d1) -> (d0 * 128 - d1) mlfunc @test() { %0 = alloc() : memref<9x9xi32> %1 = alloc() : memref<128xi32> for %i0 = -1 to 9 { for %i1 = -1 to 9 { %2 = affine_apply #map0(%i0, %i1) %3 = load %0[%2tensorflow/mlir#0, %2tensorflow/mlir#1] : memref<9x9xi32> %4 = affine_apply #map1(%i0, %i1) %5 = load %1[%4] : memref<128xi32> } } return } - Improves productivity while manually / semi-automatically developing MLIR for testing / prototyping; also provides an indirect way to catch errors in transformations. - This pass is an easy way to test the underlying affine analysis machinery including low level routines. Some code (in getMemoryRegion()) borrowed from @andydavis cl/218263256. While on this: - create mlir/Analysis/Passes.h; move Pass.h up from mlir/Transforms/ to mlir/ - fix a bug in AffineAnalysis.cpp::toAffineExpr TODO: extend to non-constant loop bounds (straightforward). Will transparently work for all accesses once floordiv, mod, ceildiv are supported in the AffineMap -> FlatAffineConstraints conversion. PiperOrigin-RevId: 219397961
2018-10-31 08:43:06 +08:00
#include "mlir/Analysis/Passes.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Pass/PassManager.h"
#include "mlir/Support/FileUtilities.h"
#include "mlir/Support/MlirOptMain.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/InitLLVM.h"
#include "llvm/Support/SourceMgr.h"
#include "llvm/Support/ToolOutputFile.h"
using namespace llvm;
using namespace mlir;
static cl::opt<std::string>
inputFilename(cl::Positional, cl::desc("<input file>"), cl::init("-"));
static cl::opt<std::string> outputFilename("o", cl::desc("Output filename"),
cl::value_desc("filename"),
cl::init("-"));
static cl::opt<bool>
splitInputFile("split-input-file",
cl::desc("Split the input file into pieces and process each "
"chunk independently"),
cl::init(false));
static cl::opt<bool>
verifyDiagnostics("verify-diagnostics",
cl::desc("Check that emitted diagnostics match "
"expected-* lines on the corresponding line"),
cl::init(false));
static cl::opt<bool>
verifyPasses("verify-each",
cl::desc("Run the verifier after each transformation pass"),
cl::init(true));
int main(int argc, char **argv) {
InitLLVM y(argc, argv);
// Register any pass manager command line options.
registerPassManagerCLOptions();
PassPipelineCLParser passPipeline("", "Compiler passes to run");
// Parse pass names in main to ensure static initialization completed.
cl::ParseCommandLineOptions(argc, argv, "MLIR modular optimizer driver\n");
// Set up the input file.
std::string errorMessage;
auto file = openInputFile(inputFilename, &errorMessage);
if (!file) {
llvm::errs() << errorMessage << "\n";
return 1;
}
auto output = openOutputFile(outputFilename, &errorMessage);
if (!output) {
llvm::errs() << errorMessage << "\n";
exit(1);
}
return failed(MlirOptMain(output->os(), std::move(file), passPipeline,
splitInputFile, verifyDiagnostics, verifyPasses));
}