2018-06-22 00:49:33 +08:00
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//===- mlir-opt.cpp - MLIR Optimizer Driver -------------------------------===//
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//
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2019-12-24 01:35:36 +08:00
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// Part of the MLIR 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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2018-06-22 00:49:33 +08:00
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//
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2019-12-24 01:35:36 +08:00
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//===----------------------------------------------------------------------===//
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2018-06-22 00:49:33 +08:00
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//
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2019-06-24 23:41:52 +08:00
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// Main entry function for mlir-opt for when built as standalone binary.
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2018-06-22 00:49:33 +08:00
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//
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//===----------------------------------------------------------------------===//
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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
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#include "mlir/Analysis/Passes.h"
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2019-02-28 06:45:36 +08:00
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#include "mlir/Pass/Pass.h"
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2019-02-28 02:59:29 +08:00
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#include "mlir/Pass/PassManager.h"
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2019-01-11 23:22:57 +08:00
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#include "mlir/Support/FileUtilities.h"
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2019-06-24 23:41:52 +08:00
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#include "mlir/Support/MlirOptMain.h"
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2018-06-22 00:49:33 +08:00
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/InitLLVM.h"
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2018-07-08 10:12:22 +08:00
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#include "llvm/Support/SourceMgr.h"
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2018-06-22 06:22:42 +08:00
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#include "llvm/Support/ToolOutputFile.h"
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2018-08-31 08:35:15 +08:00
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2018-06-22 06:22:42 +08:00
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using namespace llvm;
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2019-06-24 23:41:52 +08:00
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using namespace mlir;
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2018-06-22 06:22:42 +08:00
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static cl::opt<std::string>
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2019-06-24 23:41:52 +08:00
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inputFilename(cl::Positional, cl::desc("<input file>"), cl::init("-"));
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2018-06-22 06:22:42 +08:00
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2019-06-24 23:41:52 +08:00
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static cl::opt<std::string> outputFilename("o", cl::desc("Output filename"),
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cl::value_desc("filename"),
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cl::init("-"));
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2018-06-22 06:22:42 +08:00
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2018-06-25 00:10:36 +08:00
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static cl::opt<bool>
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2018-09-03 13:01:45 +08:00
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splitInputFile("split-input-file",
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cl::desc("Split the input file into pieces and process each "
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"chunk independently"),
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cl::init(false));
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static cl::opt<bool>
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2019-06-20 02:21:41 +08:00
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verifyDiagnostics("verify-diagnostics",
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2018-09-03 13:01:45 +08:00
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cl::desc("Check that emitted diagnostics match "
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"expected-* lines on the corresponding line"),
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cl::init(false));
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2018-06-22 06:22:42 +08:00
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2019-03-05 04:33:13 +08:00
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static cl::opt<bool>
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verifyPasses("verify-each",
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cl::desc("Run the verifier after each transformation pass"),
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cl::init(true));
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2018-06-25 00:10:36 +08:00
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int main(int argc, char **argv) {
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2018-08-06 12:12:29 +08:00
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InitLLVM y(argc, argv);
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2018-06-23 13:03:48 +08:00
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2019-03-17 11:34:23 +08:00
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// Register any pass manager command line options.
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registerPassManagerCLOptions();
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2019-09-14 03:09:50 +08:00
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PassPipelineCLParser passPipeline("", "Compiler passes to run");
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2019-03-17 11:34:23 +08:00
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2018-11-07 10:34:18 +08:00
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// Parse pass names in main to ensure static initialization completed.
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2018-06-22 06:22:42 +08:00
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cl::ParseCommandLineOptions(argc, argv, "MLIR modular optimizer driver\n");
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2018-06-22 00:49:33 +08:00
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2018-06-23 01:39:19 +08:00
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// Set up the input file.
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2019-01-11 23:22:57 +08:00
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std::string errorMessage;
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auto file = openInputFile(inputFilename, &errorMessage);
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if (!file) {
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llvm::errs() << errorMessage << "\n";
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2019-06-24 23:41:52 +08:00
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return 1;
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2018-06-23 01:39:19 +08:00
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}
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2019-06-24 23:41:52 +08:00
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auto output = openOutputFile(outputFilename, &errorMessage);
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if (!output) {
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llvm::errs() << errorMessage << "\n";
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exit(1);
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}
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2018-06-25 23:10:46 +08:00
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2019-09-14 03:09:50 +08:00
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return failed(MlirOptMain(output->os(), std::move(file), passPipeline,
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2019-06-24 23:41:52 +08:00
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splitInputFile, verifyDiagnostics, verifyPasses));
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2018-06-22 00:49:33 +08:00
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}
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