[llvm] 8c63df2 - [MLInliner] Support training that doesn't require partial rewards
Mircea Trofin via llvm-commits
llvm-commits at lists.llvm.org
Mon Aug 24 17:36:53 PDT 2020
Author: Mircea Trofin
Date: 2020-08-24T17:36:29-07:00
New Revision: 8c63df2416dc7a492f6464519b516a202147dc91
URL: https://github.com/llvm/llvm-project/commit/8c63df2416dc7a492f6464519b516a202147dc91
DIFF: https://github.com/llvm/llvm-project/commit/8c63df2416dc7a492f6464519b516a202147dc91.diff
LOG: [MLInliner] Support training that doesn't require partial rewards
If we use training algorithms that don't need partial rewards, we don't
need to worry about an ir2native model. In that case, training logs
won't contain a 'delta_size' feature either (since that's the partial
reward).
Differential Revision: https://reviews.llvm.org/D86481
Added:
Modified:
llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
llvm/test/Transforms/Inline/ML/development-training-log.ll
Removed:
################################################################################
diff --git a/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp b/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
index 19ec8cbd4042..6f8205e19230 100644
--- a/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
+++ b/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
@@ -232,7 +232,9 @@ class DevelopmentModeMLInlineAdvisor : public MLInlineAdvisor {
size_t getTotalSizeEstimate();
virtual ~DevelopmentModeMLInlineAdvisor();
- void updateNativeSizeEstimate(int64_t Change) { CurrentNativeSize += Change; }
+ void updateNativeSizeEstimate(int64_t Change) {
+ *CurrentNativeSize += Change;
+ }
void resetNativeSize(Function *F) {
FAM.invalidate<InlineSizeEstimatorAnalysis>(*F);
}
@@ -242,7 +244,7 @@ class DevelopmentModeMLInlineAdvisor : public MLInlineAdvisor {
std::unique_ptr<MLInlineAdvice>
getAdviceFromModel(CallBase &CB, OptimizationRemarkEmitter &ORE) override;
- size_t getNativeSizeEstimate(const Function &F) const;
+ Optional<size_t> getNativeSizeEstimate(const Function &F) const;
private:
bool isLogging() const { return !!Logger; }
@@ -251,8 +253,8 @@ class DevelopmentModeMLInlineAdvisor : public MLInlineAdvisor {
const bool IsDoingInference;
std::unique_ptr<TrainingLogger> Logger;
- const int32_t InitialNativeSize;
- int32_t CurrentNativeSize = 0;
+ const Optional<int32_t> InitialNativeSize;
+ Optional<int32_t> CurrentNativeSize;
};
/// A variant of MLInlineAdvice that tracks all non-trivial inlining
@@ -261,9 +263,10 @@ class LoggingMLInlineAdvice : public MLInlineAdvice {
public:
LoggingMLInlineAdvice(DevelopmentModeMLInlineAdvisor *Advisor, CallBase &CB,
OptimizationRemarkEmitter &ORE, bool Recommendation,
- TrainingLogger &Logger, size_t CallerSizeEstimateBefore,
- size_t CalleeSizeEstimateBefore, bool DefaultDecision,
- bool Mandatory = false)
+ TrainingLogger &Logger,
+ Optional<size_t> CallerSizeEstimateBefore,
+ Optional<size_t> CalleeSizeEstimateBefore,
+ bool DefaultDecision, bool Mandatory = false)
: MLInlineAdvice(Advisor, CB, ORE, Recommendation), Logger(Logger),
CallerSizeEstimateBefore(CallerSizeEstimateBefore),
CalleeSizeEstimateBefore(CalleeSizeEstimateBefore),
@@ -279,11 +282,12 @@ class LoggingMLInlineAdvice : public MLInlineAdvice {
MLInlineAdvice::recordInliningImpl();
getAdvisor()->resetNativeSize(Caller);
int Reward = std::numeric_limits<int>::max();
- if (!getAdvisor()->isForcedToStop()) {
- int NativeSizeAfter = getAdvisor()->getNativeSizeEstimate(*Caller) +
- CalleeSizeEstimateBefore;
+ if (InlineSizeEstimatorAnalysis::isEvaluatorRequested() &&
+ !getAdvisor()->isForcedToStop()) {
+ int NativeSizeAfter = *getAdvisor()->getNativeSizeEstimate(*Caller) +
+ *CalleeSizeEstimateBefore;
Reward = NativeSizeAfter -
- (CallerSizeEstimateBefore + CalleeSizeEstimateBefore);
+ (*CallerSizeEstimateBefore + *CalleeSizeEstimateBefore);
getAdvisor()->updateNativeSizeEstimate(Reward);
}
log(Reward, /*Success=*/true);
@@ -292,10 +296,11 @@ class LoggingMLInlineAdvice : public MLInlineAdvice {
void recordInliningWithCalleeDeletedImpl() override {
MLInlineAdvice::recordInliningWithCalleeDeletedImpl();
getAdvisor()->resetNativeSize(Caller);
- if (!getAdvisor()->isForcedToStop()) {
- int NativeSizeAfter = getAdvisor()->getNativeSizeEstimate(*Caller);
+ if (InlineSizeEstimatorAnalysis::isEvaluatorRequested() &&
+ !getAdvisor()->isForcedToStop()) {
+ int NativeSizeAfter = *getAdvisor()->getNativeSizeEstimate(*Caller);
int Reward = NativeSizeAfter -
- (CallerSizeEstimateBefore + CalleeSizeEstimateBefore);
+ (*CallerSizeEstimateBefore + *CalleeSizeEstimateBefore);
getAdvisor()->updateNativeSizeEstimate(Reward);
log(Reward, /*Success=*/true);
}
@@ -324,8 +329,8 @@ class LoggingMLInlineAdvice : public MLInlineAdvice {
static const int64_t NoReward = 0;
TrainingLogger &Logger;
- const size_t CallerSizeEstimateBefore;
- const size_t CalleeSizeEstimateBefore;
+ const Optional<size_t> CallerSizeEstimateBefore;
+ const Optional<size_t> CalleeSizeEstimateBefore;
const bool DefaultDecision;
const bool Mandatory;
};
@@ -448,9 +453,11 @@ void TrainingLogger::print() {
writeRawTensorsAsFeatureLists(
OutFile, TensorSpec::createSpec<int64_t>(DecisionName, {1}),
Outputs[0].data(), NumberOfRecords);
- writeTensorsAsFeatureLists(OutFile,
- TensorSpec::createSpec<int64_t>(RewardName, {1}),
- Rewards.data(), NumberOfRecords);
+
+ if (InlineSizeEstimatorAnalysis::isEvaluatorRequested())
+ writeTensorsAsFeatureLists(OutFile,
+ TensorSpec::createSpec<int64_t>(RewardName, {1}),
+ Rewards.data(), NumberOfRecords);
for (size_t I = 1; I < Outputs.size(); ++I)
writeRawTensorsAsFeatureLists(OutFile, MUTR->outputSpecs()[I],
@@ -479,8 +486,10 @@ DevelopmentModeMLInlineAdvisor::~DevelopmentModeMLInlineAdvisor() {
Logger->print();
}
-size_t
+Optional<size_t>
DevelopmentModeMLInlineAdvisor::getNativeSizeEstimate(const Function &F) const {
+ if (!InlineSizeEstimatorAnalysis::isEvaluatorRequested())
+ return None;
auto &R =
FAM.getResult<InlineSizeEstimatorAnalysis>(const_cast<Function &>(F));
if (!R) {
@@ -496,6 +505,7 @@ DevelopmentModeMLInlineAdvisor::getMandatoryAdvice(
CallBase &CB, OptimizationRemarkEmitter &ORE) {
if (!isLogging())
return MLInlineAdvisor::getMandatoryAdvice(CB, ORE);
+
return std::make_unique<LoggingMLInlineAdvice>(
/*Advisor=*/this,
/*CB=*/CB, /*ORE=*/ORE, /*Recommendation=*/true, /*Logger=*/*Logger,
@@ -524,13 +534,15 @@ DevelopmentModeMLInlineAdvisor::getAdviceFromModel(
}
size_t DevelopmentModeMLInlineAdvisor::getTotalSizeEstimate() {
+ if (!InlineSizeEstimatorAnalysis::isEvaluatorRequested())
+ return 0;
size_t Ret = 0;
for (auto &F : M) {
if (F.isDeclaration())
continue;
if (isFunctionDeleted(&F))
continue;
- Ret += getNativeSizeEstimate(F);
+ Ret += *getNativeSizeEstimate(F);
}
return Ret;
}
@@ -642,14 +654,6 @@ std::unique_ptr<InlineAdvisor> llvm::getDevelopmentModeAdvisor(
Module &M, ModuleAnalysisManager &MAM,
std::function<bool(CallBase &)> GetDefaultAdvice) {
auto &Ctx = M.getContext();
- if (TrainingLog.empty() !=
- !InlineSizeEstimatorAnalysis::isEvaluatorRequested()) {
- Ctx.emitError("For development mode, if training logs are requested, then "
- "a size estimator must be available; either that, or neither "
- "are specified.");
- return nullptr;
- }
-
std::unique_ptr<MLModelRunner> Runner;
ModelUnderTrainingRunner *MUTRPtr = nullptr;
bool IsDoingInference = false;
diff --git a/llvm/test/Transforms/Inline/ML/development-training-log.ll b/llvm/test/Transforms/Inline/ML/development-training-log.ll
index 77347455958b..82dea452497d 100644
--- a/llvm/test/Transforms/Inline/ML/development-training-log.ll
+++ b/llvm/test/Transforms/Inline/ML/development-training-log.ll
@@ -1,8 +1,10 @@
; Test that we can produce a log if we have or do not have a model, in development mode.
; REQUIRES: have_tf_api
; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s | FileCheck %s
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-output-spec-override=%S/Inputs/test_output_spec.json -S < %s | FileCheck %s --check-prefix=EXTRA-OUTPUTS
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-output-spec-override=%S/Inputs/test_output_spec.json -S < %s | FileCheck %s --check-prefixes=EXTRA-OUTPUTS,CHECK
; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s | FileCheck %s
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -S < %s | FileCheck %s --check-prefix=NOREWARD
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -S < %s | FileCheck %s --check-prefix=NOREWARD
target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
target triple = "x86_64-pc-linux-gnu"
@@ -50,6 +52,7 @@ define dso_local i32 @top() {
; CHECK-NEXT: feature: { int64_list: { value: [0] } }
; CHECK-NEXT: }
; CHECK-NEXT: }
+; NOREWARD-NOT: key: "delta_size" value: {
; CHECK-NOT: fake_extra_output
; EXTRA-OUTPUTS: key: "fake_extra_output" value: {
; EXTRA-OUTPUTS-NEXT: feature: { int64_list: { value: [1] } }
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