1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
|
//===- 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.
// =============================================================================
//
// This is a command line utility that parses an MLIR file, runs an optimization
// pass, then prints the result back out. It is designed to support unit
// testing.
//
//===----------------------------------------------------------------------===//
#include "mlir/Analysis/Passes.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/CFGFunction.h"
#include "mlir/IR/Location.h"
#include "mlir/IR/MLFunction.h"
#include "mlir/IR/MLIRContext.h"
#include "mlir/IR/Module.h"
#include "mlir/Parser.h"
#include "mlir/Pass.h"
#include "mlir/TensorFlow/ControlFlowOps.h"
#include "mlir/TensorFlow/Passes.h"
#include "mlir/Transforms/CFGFunctionViewGraph.h"
#include "mlir/Transforms/Passes.h"
#include "mlir/XLA/Passes.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/FileUtilities.h"
#include "llvm/Support/InitLLVM.h"
#include "llvm/Support/PrettyStackTrace.h"
#include "llvm/Support/Regex.h"
#include "llvm/Support/SourceMgr.h"
#include "llvm/Support/ToolOutputFile.h"
using namespace mlir;
using namespace llvm;
using llvm::SMLoc;
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",
cl::desc("Check that emitted diagnostics match "
"expected-* lines on the corresponding line"),
cl::init(false));
enum Passes {
Canonicalize,
ComposeAffineMaps,
ConstantFold,
ConvertToCFG,
MemRefBoundCheck,
LoopUnroll,
LoopUnrollAndJam,
PipelineDataTransfer,
PrintCFGGraph,
SimplifyAffineStructures,
TFRaiseControlFlow,
Vectorize,
XLALower,
};
static cl::list<Passes> passList(
"", cl::desc("Compiler passes to run"),
cl::values(
clEnumValN(Canonicalize, "canonicalize", "Canonicalize operations"),
clEnumValN(ComposeAffineMaps, "compose-affine-maps",
"Compose affine maps"),
clEnumValN(ConstantFold, "constant-fold",
"Constant fold operations in functions"),
clEnumValN(ConvertToCFG, "convert-to-cfg",
"Convert all ML functions in the module to CFG ones"),
clEnumValN(MemRefBoundCheck, "memref-bound-check",
"Convert all ML functions in the module to CFG ones"),
clEnumValN(LoopUnroll, "loop-unroll", "Unroll loops"),
clEnumValN(LoopUnrollAndJam, "loop-unroll-jam", "Unroll and jam loops"),
clEnumValN(PipelineDataTransfer, "pipeline-data-transfer",
"Pipeline non-blocking data transfers between"
"explicitly managed levels of the memory hierarchy"),
clEnumValN(PrintCFGGraph, "print-cfg-graph",
"Print CFG graph per function"),
clEnumValN(SimplifyAffineStructures, "simplify-affine-structures",
"Simplify affine expressions"),
clEnumValN(TFRaiseControlFlow, "tf-raise-control-flow",
"Dynamic TensorFlow Switch/Match nodes to a CFG"),
clEnumValN(Vectorize, "vectorize",
"Vectorize to a target independent n-D vector abstraction."),
clEnumValN(XLALower, "xla-lower", "Lower to XLA dialect")));
enum OptResult { OptSuccess, OptFailure };
/// Open the specified output file and return it, exiting if there is any I/O or
/// other errors.
static std::unique_ptr<ToolOutputFile> getOutputStream() {
std::error_code error;
auto result =
llvm::make_unique<ToolOutputFile>(outputFilename, error, sys::fs::F_None);
if (error) {
llvm::errs() << error.message() << '\n';
exit(1);
}
return result;
}
/// Given a MemoryBuffer along with a line and column within it, return the
/// location being referenced.
static SMLoc getLocFromLineAndCol(MemoryBuffer &membuf, unsigned lineNo,
unsigned columnNo) {
// TODO: This should really be upstreamed to be a method on llvm::SourceMgr.
// Doing so would allow it to use the offset cache that is already maintained
// by SrcBuffer, making this more efficient.
// Scan for the correct line number.
const char *position = membuf.getBufferStart();
const char *end = membuf.getBufferEnd();
// We start counting line and column numbers from 1.
--lineNo;
--columnNo;
while (position < end && lineNo) {
auto curChar = *position++;
// Scan for newlines. If this isn't one, ignore it.
if (curChar != '\r' && curChar != '\n')
continue;
// We saw a line break, decrement our counter.
--lineNo;
// Check for \r\n and \n\r and treat it as a single escape. We know that
// looking past one character is safe because MemoryBuffer's are always nul
// terminated.
if (*position != curChar && (*position == '\r' || *position == '\n'))
++position;
}
// If the line/column counter was invalid, return a pointer to the start of
// the buffer.
if (lineNo || position + columnNo > end)
return SMLoc::getFromPointer(membuf.getBufferStart());
// Otherwise return the right pointer.
return SMLoc::getFromPointer(position + columnNo);
}
/// Perform the actions on the input file indicated by the command line flags
/// within the specified context.
///
/// This typically parses the main source file, runs zero or more optimization
/// passes, then prints the output.
///
static OptResult performActions(SourceMgr &sourceMgr, MLIRContext *context) {
std::unique_ptr<Module> module(parseSourceFile(sourceMgr, context));
if (!module)
return OptFailure;
// Run each of the passes that were selected.
for (unsigned i = 0, e = passList.size(); i != e; ++i) {
auto passKind = passList[i];
Pass *pass = nullptr;
switch (passKind) {
case Canonicalize:
pass = createCanonicalizerPass();
break;
case ComposeAffineMaps:
pass = createComposeAffineMapsPass();
break;
case ConstantFold:
pass = createConstantFoldPass();
break;
case ConvertToCFG:
pass = createConvertToCFGPass();
break;
case MemRefBoundCheck:
pass = createMemRefBoundCheckPass();
break;
case LoopUnroll:
pass = createLoopUnrollPass();
break;
case LoopUnrollAndJam:
pass = createLoopUnrollAndJamPass();
break;
case PipelineDataTransfer:
pass = createPipelineDataTransferPass();
break;
case PrintCFGGraph:
pass = createPrintCFGGraphPass();
break;
case SimplifyAffineStructures:
pass = createSimplifyAffineStructuresPass();
break;
case TFRaiseControlFlow:
pass = createRaiseTFControlFlowPass();
break;
case Vectorize:
pass = createVectorizePass();
break;
case XLALower:
pass = createXLALowerPass();
break;
}
PassResult result = pass->runOnModule(module.get());
delete pass;
if (result)
return OptFailure;
// Verify that the result of the pass is still valid.
if (module->verify())
return OptFailure;
}
// Print the output.
auto output = getOutputStream();
module->print(output->os());
output->keep();
return OptSuccess;
}
/// Given a diagnostic kind, return a human readable string for it.
static StringRef getDiagnosticKindString(MLIRContext::DiagnosticKind kind) {
switch (kind) {
case MLIRContext::DiagnosticKind::Note:
return "note";
case MLIRContext::DiagnosticKind::Warning:
return "warning";
case MLIRContext::DiagnosticKind::Error:
return "error";
}
}
/// Parses the memory buffer. If successfully, run a series of passes against
/// it and print the result.
static OptResult processFile(std::unique_ptr<MemoryBuffer> ownedBuffer) {
// Tell sourceMgr about this buffer, which is what the parser will pick up.
SourceMgr sourceMgr;
auto &buffer = *ownedBuffer;
sourceMgr.AddNewSourceBuffer(std::move(ownedBuffer), SMLoc());
// Parse the input file.
MLIRContext context;
// If we are in verify mode then we have a lot of work to do, otherwise just
// perform the actions without worrying about it.
if (!verifyDiagnostics) {
// Register a simple diagnostic handler that prints out info with context.
context.registerDiagnosticHandler([&](Location *location, StringRef message,
MLIRContext::DiagnosticKind kind) {
unsigned line = 1, column = 1;
if (auto fileLoc = dyn_cast<FileLineColLoc>(location)) {
line = fileLoc->getLine();
column = fileLoc->getColumn();
}
auto unexpectedLoc = getLocFromLineAndCol(buffer, line, column);
sourceMgr.PrintMessage(unexpectedLoc, SourceMgr::DK_Error, message);
});
// Run the test actions.
return performActions(sourceMgr, &context);
}
// Keep track of the result of this file processing. If there are no issues,
// then we succeed.
auto result = OptSuccess;
// Record the expected diagnostic's position, substring and whether it was
// seen.
struct ExpectedDiag {
MLIRContext::DiagnosticKind kind;
unsigned lineNo;
StringRef substring;
SMLoc fileLoc;
bool matched = false;
};
SmallVector<ExpectedDiag, 2> expectedDiags;
// Error checker that verifies reported error was expected.
auto checker = [&](Location *location, StringRef message,
MLIRContext::DiagnosticKind kind) {
unsigned line = 1, column = 1;
if (auto *fileLoc = dyn_cast<FileLineColLoc>(location)) {
line = fileLoc->getLine();
column = fileLoc->getColumn();
}
// If we find something that is close then emit a more specific error.
ExpectedDiag *nearMiss = nullptr;
// If this was an expected error, remember that we saw it and return.
for (auto &e : expectedDiags) {
if (line == e.lineNo && message.contains(e.substring)) {
if (e.kind == kind) {
e.matched = true;
return;
}
// If this only differs based on the diagnostic kind, then consider it
// to be a near miss.
nearMiss = &e;
}
}
// If there was a near miss, emit a specific diagnostic.
if (nearMiss) {
sourceMgr.PrintMessage(nearMiss->fileLoc, SourceMgr::DK_Error,
"'" + getDiagnosticKindString(kind) +
"' diagnostic emitted when expecting a '" +
getDiagnosticKindString(nearMiss->kind) + "'");
result = OptFailure;
return;
}
// If this error wasn't expected, produce an error out of mlir-opt saying
// so.
auto unexpectedLoc = getLocFromLineAndCol(buffer, line, column);
sourceMgr.PrintMessage(unexpectedLoc, SourceMgr::DK_Error,
"unexpected error: " + Twine(message));
result = OptFailure;
};
// Scan the file for expected-* designators and register a callback for the
// error handler.
// Extract the expected errors from the file.
llvm::Regex expected(
"expected-(error|note|warning) *(@[+-][0-9]+)? *{{(.*)}}");
SmallVector<StringRef, 100> lines;
buffer.getBuffer().split(lines, '\n');
for (unsigned lineNo = 0, e = lines.size(); lineNo < e; ++lineNo) {
SmallVector<StringRef, 3> matches;
if (expected.match(lines[lineNo], &matches)) {
// Point to the start of expected-*.
SMLoc expectedStart = SMLoc::getFromPointer(matches[0].data());
MLIRContext::DiagnosticKind kind;
if (matches[1] == "error")
kind = MLIRContext::DiagnosticKind::Error;
else if (matches[1] == "warning")
kind = MLIRContext::DiagnosticKind::Warning;
else {
assert(matches[1] == "note");
kind = MLIRContext::DiagnosticKind::Note;
}
ExpectedDiag record{kind, lineNo + 1, matches[3], expectedStart, false};
auto offsetMatch = matches[2];
if (!offsetMatch.empty()) {
int offset;
// Get the integer value without the @ and +/- prefix.
if (!offsetMatch.drop_front(2).getAsInteger(0, offset)) {
if (offsetMatch[1] == '+')
record.lineNo += offset;
else
record.lineNo -= offset;
}
}
expectedDiags.push_back(record);
}
}
// Finally, register the error handler to capture them.
context.registerDiagnosticHandler(checker);
// Do any processing requested by command line flags. We don't care whether
// these actions succeed or fail, we only care what diagnostics they produce
// and whether they match our expectations.
performActions(sourceMgr, &context);
// Verify that all expected errors were seen.
for (auto &err : expectedDiags) {
if (!err.matched) {
SMRange range(err.fileLoc,
SMLoc::getFromPointer(err.fileLoc.getPointer() +
err.substring.size()));
auto kind = getDiagnosticKindString(err.kind);
sourceMgr.PrintMessage(err.fileLoc, SourceMgr::DK_Error,
"expected " + kind + " \"" + err.substring +
"\" was not produced",
range);
result = OptFailure;
}
}
return result;
}
/// Split the specified file on a marker and process each chunk independently
/// according to the normal processFile logic. This is primarily used to
/// allow a large number of small independent parser tests to be put into a
/// single test, but could be used for other purposes as well.
static OptResult
splitAndProcessFile(std::unique_ptr<MemoryBuffer> originalBuffer) {
const char marker[] = "-----";
auto *origMemBuffer = originalBuffer.get();
SmallVector<StringRef, 8> sourceBuffers;
origMemBuffer->getBuffer().split(sourceBuffers, marker);
// Add the original buffer to the source manager.
SourceMgr fileSourceMgr;
fileSourceMgr.AddNewSourceBuffer(std::move(originalBuffer), SMLoc());
bool hadUnexpectedResult = false;
// Process each chunk in turn. If any fails, then return a failure of the
// tool.
for (auto &subBuffer : sourceBuffers) {
auto splitLoc = SMLoc::getFromPointer(subBuffer.data());
unsigned splitLine = fileSourceMgr.getLineAndColumn(splitLoc).first;
auto subMemBuffer = MemoryBuffer::getMemBufferCopy(
subBuffer, origMemBuffer->getBufferIdentifier() +
Twine(" split at line #") + Twine(splitLine));
if (processFile(std::move(subMemBuffer)))
hadUnexpectedResult = true;
}
return hadUnexpectedResult ? OptFailure : OptSuccess;
}
int main(int argc, char **argv) {
llvm::PrettyStackTraceProgram x(argc, argv);
InitLLVM y(argc, argv);
cl::ParseCommandLineOptions(argc, argv, "MLIR modular optimizer driver\n");
// Set up the input file.
auto fileOrErr = MemoryBuffer::getFileOrSTDIN(inputFilename);
if (std::error_code error = fileOrErr.getError()) {
llvm::errs() << argv[0] << ": could not open input file '" << inputFilename
<< "': " << error.message() << "\n";
return 1;
}
// The split-input-file mode is a very specific mode that slices the file
// up into small pieces and checks each independently.
if (splitInputFile)
return splitAndProcessFile(std::move(*fileOrErr));
return processFile(std::move(*fileOrErr));
}
|