[llvm] 91c96a8 - Revert "[MLGO] ML Regalloc Priority Advisor"
Mircea Trofin via llvm-commits
llvm-commits at lists.llvm.org
Thu Sep 29 18:27:25 PDT 2022
Author: Mircea Trofin
Date: 2022-09-29T18:26:40-07:00
New Revision: 91c96a806cae58539e40c9e443a08bde91ccc91e
URL: https://github.com/llvm/llvm-project/commit/91c96a806cae58539e40c9e443a08bde91ccc91e
DIFF: https://github.com/llvm/llvm-project/commit/91c96a806cae58539e40c9e443a08bde91ccc91e.diff
LOG: Revert "[MLGO] ML Regalloc Priority Advisor"
This reverts commit 8f4f26ba5bd04f7b335836021e5e63b4236c0305.
Buildbot failures, e.g. https://lab.llvm.org/buildbot/#/builders/6/builds/14041
Added:
Modified:
llvm/lib/CodeGen/CMakeLists.txt
llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp
Removed:
llvm/lib/Analysis/models/gen-regalloc-priority-test-model.py
llvm/lib/CodeGen/MLRegallocPriorityAdvisor.cpp
llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll
################################################################################
diff --git a/llvm/lib/Analysis/models/gen-regalloc-priority-test-model.py b/llvm/lib/Analysis/models/gen-regalloc-priority-test-model.py
deleted file mode 100644
index 81de2c70565a8..0000000000000
--- a/llvm/lib/Analysis/models/gen-regalloc-priority-test-model.py
+++ /dev/null
@@ -1,95 +0,0 @@
-"""Generate a mock model for LLVM tests for Register Allocation.
-The generated model is not a neural net - it is just a tf.function with the
-correct input and output parameters.
-"""
-## By construction, the mock model will always output the first liverange that can be evicted.
-
-import os
-import sys
-import tensorflow as tf
-POLICY_DECISION_LABEL = 'priority'
-POLICY_OUTPUT_SPEC = """
-[
- {
- "logging_name": "priority",
- "tensor_spec": {
- "name": "StatefulPartitionedCall",
- "port": 0,
- "type": "float",
- "shape": [
- 1
- ]
- }
- }
-]
-"""
-PER_LIVEINTERVAL_INT64_FEATURE_LIST = [
- 'li_size', 'stage'
-]
-PER_LIVEINTERVAL_FLOAT32_FEATURE_LIST = ['weight'
-]
-PER_LIVEINTERVAL_FEATURE_LIST = PER_LIVEINTERVAL_FLOAT32_FEATURE_LIST + \
- PER_LIVEINTERVAL_INT64_FEATURE_LIST
-CONTEXT_FEATURE_LIST = ('discount', 'reward', 'step_type')
-
-
-def get_input_signature():
- """Returns (time_step_spec, action_spec) for LLVM register allocation."""
- inputs = dict(
- (key, tf.TensorSpec(dtype=tf.int64, shape=(), name=key))
- for key in PER_LIVEINTERVAL_INT64_FEATURE_LIST)
- inputs.update(
- dict((key,
- tf.TensorSpec(dtype=tf.float32, shape=(), name=key))
- for key in PER_LIVEINTERVAL_FLOAT32_FEATURE_LIST))
- inputs.update(
- dict((key, tf.TensorSpec(dtype=tf.float32, shape=(), name=key))
- for key in ['discount', 'reward']))
- inputs.update(
- dict((key, tf.TensorSpec(dtype=tf.int32, shape=(), name=key))
- for key in ['step_type']))
- return inputs
-
-
-def get_output_spec_path(path):
- return os.path.join(path, 'output_spec.json')
-
-
-def build_mock_model(path):
- """Build and save the mock model with the given signature."""
- module = tf.Module()
- # We have to set this useless variable in order for the TF C API to correctly
- # intake it
- module.var = tf.Variable(0, dtype=tf.float32)
-
- def action(*inputs):
- s1 = tf.reduce_sum([
- tf.cast(inputs[0][key], tf.float32) for key in PER_LIVEINTERVAL_FEATURE_LIST
- ],
- axis=0)
- s2 = tf.reduce_sum(
- [tf.cast(inputs[0][key], tf.float32) for key in CONTEXT_FEATURE_LIST])
- # Add a large number so s won't be 0.
- s = s1 + s2
- result = s + module.var
- return {POLICY_DECISION_LABEL: result}
- module.action = tf.function()(action)
- action = {
- 'action': module.action.get_concrete_function(get_input_signature())
- }
-
- tf.saved_model.save(module, path, signatures=action)
- output_spec_path = get_output_spec_path(path)
- with open(output_spec_path, 'w') as f:
- print(f'Writing output spec to {output_spec_path}.')
- f.write(POLICY_OUTPUT_SPEC)
-
-
-def main(argv):
- assert len(argv) == 2
- model_path = argv[1]
- build_mock_model(model_path)
-
-
-if __name__ == '__main__':
- main(sys.argv)
diff --git a/llvm/lib/CodeGen/CMakeLists.txt b/llvm/lib/CodeGen/CMakeLists.txt
index ce14e1d9d545d..afa37044c81ec 100644
--- a/llvm/lib/CodeGen/CMakeLists.txt
+++ b/llvm/lib/CodeGen/CMakeLists.txt
@@ -143,7 +143,6 @@ add_llvm_component_library(LLVMCodeGen
MIRSampleProfile.cpp
MIRYamlMapping.cpp
MLRegallocEvictAdvisor.cpp
- MLRegallocPriorityAdvisor.cpp
ModuloSchedule.cpp
MultiHazardRecognizer.cpp
PatchableFunction.cpp
diff --git a/llvm/lib/CodeGen/MLRegallocPriorityAdvisor.cpp b/llvm/lib/CodeGen/MLRegallocPriorityAdvisor.cpp
deleted file mode 100644
index cda1e4e8f5126..0000000000000
--- a/llvm/lib/CodeGen/MLRegallocPriorityAdvisor.cpp
+++ /dev/null
@@ -1,335 +0,0 @@
-//===- MLRegAllocPriorityAdvisor.cpp - ML priority advisor-----------------===//
-//
-// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-//
-//===----------------------------------------------------------------------===//
-//
-// Implementation of the ML priority advisor and reward injection pass
-//
-//===----------------------------------------------------------------------===//
-
-#include "AllocationOrder.h"
-#include "RegAllocGreedy.h"
-#include "RegAllocPriorityAdvisor.h"
-#include "llvm/Analysis/AliasAnalysis.h"
-#include "llvm/Analysis/MLModelRunner.h"
-#include "llvm/Analysis/ReleaseModeModelRunner.h"
-#include "llvm/Analysis/TensorSpec.h"
-#include "llvm/CodeGen/CalcSpillWeights.h"
-#include "llvm/CodeGen/LiveRegMatrix.h"
-#include "llvm/CodeGen/MachineBlockFrequencyInfo.h"
-#include "llvm/CodeGen/MachineFunction.h"
-#include "llvm/CodeGen/MachineLoopInfo.h"
-#include "llvm/CodeGen/MachineRegisterInfo.h"
-#include "llvm/CodeGen/Passes.h"
-#include "llvm/CodeGen/RegisterClassInfo.h"
-#include "llvm/CodeGen/SlotIndexes.h"
-#include "llvm/CodeGen/VirtRegMap.h"
-#include "llvm/InitializePasses.h"
-#include "llvm/Pass.h"
-#include "llvm/PassRegistry.h"
-#include "llvm/Support/CommandLine.h"
-
-#if defined(LLVM_HAVE_TF_API)
-#include "llvm/Analysis/ModelUnderTrainingRunner.h"
-#include "llvm/Analysis/NoInferenceModelRunner.h"
-#include "llvm/Analysis/Utils/TrainingLogger.h"
-#endif
-
-using namespace llvm;
-
-// Options that only make sense in development mode
-#ifdef LLVM_HAVE_TF_API
-#include "RegAllocScore.h"
-#include "llvm/Analysis/Utils/TFUtils.h"
-
-static cl::opt<std::string> TrainingLog(
- "regalloc-priority-training-log", cl::Hidden,
- cl::desc("Training log for the register allocator priority model"));
-
-static cl::opt<std::string> ModelUnderTraining(
- "regalloc-priority-model", cl::Hidden,
- cl::desc("The model being trained for register allocation priority"));
-
-#endif // #ifdef LLVM_HAVE_TF_API
-
-namespace llvm {
-
-static const std::vector<int64_t> PerLiveRangeShape{1};
-
-#define RA_PRIORITY_FEATURES_LIST(M) \
- M(int64_t, li_size, PerLiveRangeShape, "size") \
- M(int64_t, stage, PerLiveRangeShape, "stage") \
- M(float, weight, PerLiveRangeShape, "weight")
-
-#define DecisionName "priority"
-
-// Named features index.
-enum FeatureIDs {
-#define _FEATURE_IDX(_, name, __, ___) name,
- RA_PRIORITY_FEATURES_LIST(_FEATURE_IDX)
-#undef _FEATURE_IDX
- FeatureCount
-};
-
-class MLPriorityAdvisor : public RegAllocPriorityAdvisor {
-public:
- MLPriorityAdvisor(const MachineFunction &MF, const RAGreedy &RA,
- SlotIndexes *const Indexes, MLModelRunner *Runner);
-
-protected:
- const RegAllocPriorityAdvisor &getDefaultAdvisor() const {
- return static_cast<const RegAllocPriorityAdvisor &>(DefaultAdvisor);
- }
-
- // The assumption is that if the Runner could not be constructed, we emit-ed
- // error, and we shouldn't be asking for it here.
- const MLModelRunner &getRunner() const { return *Runner; }
- float getPriorityImpl(const LiveInterval &LI) const;
- unsigned getPriority(const LiveInterval &LI) const override;
-
-private:
- const DefaultPriorityAdvisor DefaultAdvisor;
- MLModelRunner *const Runner;
-};
-
-#define _DECL_FEATURES(type, name, shape, _) \
- TensorSpec::createSpec<type>(#name, shape),
-
-static const std::vector<TensorSpec> InputFeatures{
- {RA_PRIORITY_FEATURES_LIST(_DECL_FEATURES)},
-};
-#undef _DECL_FEATURES
-
-// ===================================
-// Release (AOT) - specifics
-// ===================================
-class ReleaseModePriorityAdvisorAnalysis final
- : public RegAllocPriorityAdvisorAnalysis {
-public:
- ReleaseModePriorityAdvisorAnalysis()
- : RegAllocPriorityAdvisorAnalysis(AdvisorMode::Release) {}
- // support for isa<> and dyn_cast.
- static bool classof(const RegAllocPriorityAdvisorAnalysis *R) {
- return R->getAdvisorMode() == AdvisorMode::Release;
- }
-
-private:
- void getAnalysisUsage(AnalysisUsage &AU) const override {
- AU.setPreservesAll();
- AU.addRequired<SlotIndexes>();
- RegAllocPriorityAdvisorAnalysis::getAnalysisUsage(AU);
- }
-
- std::unique_ptr<RegAllocPriorityAdvisor>
- getAdvisor(const MachineFunction &MF, const RAGreedy &RA) override {
- if (!Runner)
- Runner = std::make_unique<ReleaseModeModelRunner<NoopSavedModelImpl>>(
- MF.getFunction().getContext(), InputFeatures, DecisionName);
- return std::make_unique<MLPriorityAdvisor>(
- MF, RA, &getAnalysis<SlotIndexes>(), Runner.get());
- }
- std::unique_ptr<ReleaseModeModelRunner<NoopSavedModelImpl>> Runner;
-};
-
-// ===================================
-// Development mode-specifics
-// ===================================
-//
-// Features we log
-#ifdef LLVM_HAVE_TF_API
-
-static const TensorSpec Output =
- TensorSpec::createSpec<float>(DecisionName, {1});
-static const TensorSpec Reward = TensorSpec::createSpec<float>("reward", {1});
-
-#define _DECL_TRAIN_FEATURES(type, name, shape, _) \
- TensorSpec::createSpec<type>(std::string("action_") + #name, shape),
-
-static const std::vector<TensorSpec> TrainingInputFeatures{
- {RA_PRIORITY_FEATURES_LIST(_DECL_TRAIN_FEATURES)
- TensorSpec::createSpec<float>("action_discount", {1}),
- TensorSpec::createSpec<int32_t>("action_step_type", {1}),
- TensorSpec::createSpec<float>("action_reward", {1})}};
-#undef _DECL_TRAIN_FEATURES
-
-class DevelopmentModePriorityAdvisor : public MLPriorityAdvisor {
-public:
- DevelopmentModePriorityAdvisor(const MachineFunction &MF, const RAGreedy &RA,
- SlotIndexes *const Indexes,
- MLModelRunner *Runner, Logger *Log)
- : MLPriorityAdvisor(MF, RA, Indexes, Runner), Log(Log) {}
-
-private:
- unsigned getPriority(const LiveInterval &LI) const override;
- Logger *const Log;
-};
-
-class DevelopmentModePriorityAdvisorAnalysis final
- : public RegAllocPriorityAdvisorAnalysis {
-public:
- DevelopmentModePriorityAdvisorAnalysis()
- : RegAllocPriorityAdvisorAnalysis(AdvisorMode::Development) {}
- // support for isa<> and dyn_cast.
- static bool classof(const RegAllocPriorityAdvisorAnalysis *R) {
- return R->getAdvisorMode() == AdvisorMode::Development;
- }
-
- /// get the logger for the given function, or nullptr if we didn't collect
- /// one. This is used to inject the score by the RegAllocScoring pass.
- Logger *getLogger(const MachineFunction &MF) const {
- auto I = LogMap.find(MF.getName());
- if (I == LogMap.end())
- return nullptr;
- return I->second.get();
- }
-
- void logRewardIfNeeded(const MachineFunction &MF,
- llvm::function_ref<float()> GetReward) override {
- if (auto *Log = this->getLogger(MF))
- Log->logFloatFinalReward(GetReward());
- }
-
-private:
- void getAnalysisUsage(AnalysisUsage &AU) const override {
- AU.setPreservesAll();
- AU.addRequired<SlotIndexes>();
- RegAllocPriorityAdvisorAnalysis::getAnalysisUsage(AU);
- }
-
- // Save all the logs (when requested).
- bool doFinalization(Module &M) override {
- if (TrainingLog.empty())
- return false;
- std::error_code EC;
- auto OS = std::make_unique<raw_fd_ostream>(TrainingLog, EC);
- if (EC) {
- M.getContext().emitError(EC.message() + ":" + TrainingLog);
- return false;
- }
- Logger::flushLogs(*OS, LogMap);
- return false;
- }
-
- std::unique_ptr<RegAllocPriorityAdvisor>
- getAdvisor(const MachineFunction &MF, const RAGreedy &RA) override {
-
- LLVMContext &Ctx = MF.getFunction().getContext();
- if (ModelUnderTraining.empty() && TrainingLog.empty()) {
- Ctx.emitError("Regalloc development mode should be requested with at "
- "least logging enabled and/or a training model");
- return nullptr;
- }
- if (!Runner) {
- if (ModelUnderTraining.empty())
- Runner = std::make_unique<NoInferenceModelRunner>(Ctx, InputFeatures);
- else
- Runner = ModelUnderTrainingRunner::createAndEnsureValid(
- Ctx, ModelUnderTraining, DecisionName, TrainingInputFeatures);
- if (!Runner) {
- Ctx.emitError("Regalloc: could not set up the model runner");
- return nullptr;
- }
- }
-
- Logger *Log = nullptr;
- if (!TrainingLog.empty()) {
- std::vector<LoggedFeatureSpec> LFS;
- for (const auto &FS : InputFeatures)
- LFS.push_back({FS, None});
- if (auto *MUTR = dyn_cast<ModelUnderTrainingRunner>(Runner.get()))
- if (MUTR->outputLoggedFeatureSpecs().size() > 1)
- append_range(LFS, drop_begin(MUTR->outputLoggedFeatureSpecs()));
- // We always log the output; in particular, if we're not evaluating, we
- // don't have an output spec json file. That's why we handle the
- // 'normal' output separately.
- LFS.push_back({Output, None});
- auto I = LogMap.insert(std::make_pair(
- MF.getFunction().getName(),
- std::make_unique<Logger>(LFS, Reward, /*IncludeReward*/ true)));
- assert(I.second);
- Log = I.first->second.get();
- }
-
- return std::make_unique<DevelopmentModePriorityAdvisor>(
- MF, RA, &getAnalysis<SlotIndexes>(), Runner.get(), Log);
- }
-
- std::unique_ptr<MLModelRunner> Runner;
- StringMap<std::unique_ptr<Logger>> LogMap;
-};
-#endif //#ifdef LLVM_HAVE_TF_API
-
-} // namespace llvm
-
-RegAllocPriorityAdvisorAnalysis *llvm::createReleaseModePriorityAdvisor() {
- return new ReleaseModePriorityAdvisorAnalysis();
-}
-
-MLPriorityAdvisor::MLPriorityAdvisor(const MachineFunction &MF,
- const RAGreedy &RA,
- SlotIndexes *const Indexes,
- MLModelRunner *Runner)
- : RegAllocPriorityAdvisor(MF, RA, Indexes), DefaultAdvisor(MF, RA, Indexes),
- Runner(std::move(Runner)) {
- assert(this->Runner);
-}
-
-float MLPriorityAdvisor::getPriorityImpl(const LiveInterval &LI) const {
- const unsigned Size = LI.getSize();
- LiveRangeStage Stage = RA.getExtraInfo().getStage(LI);
-
- *Runner->getTensor<int64_t>(0) = static_cast<int64_t>(Size);
- *Runner->getTensor<int64_t>(1) = static_cast<int64_t>(Stage);
- *Runner->getTensor<float>(2) = static_cast<float>(LI.weight());
-
- return Runner->evaluate<float>();
-}
-
-unsigned MLPriorityAdvisor::getPriority(const LiveInterval &LI) const {
- return static_cast<unsigned>(getPriorityImpl(LI));
-}
-
-#ifdef LLVM_HAVE_TF_API
-RegAllocPriorityAdvisorAnalysis *llvm::createDevelopmentModePriorityAdvisor() {
- return new DevelopmentModePriorityAdvisorAnalysis();
-}
-
-unsigned
-DevelopmentModePriorityAdvisor::getPriority(const LiveInterval &LI) const {
- double Prio = 0;
-
- if (isa<ModelUnderTrainingRunner>(getRunner())) {
- Prio = MLPriorityAdvisor::getPriorityImpl(LI);
- } else {
- Prio = getDefaultAdvisor().getPriority(LI);
- }
-
- if (TrainingLog.empty())
- return Prio;
-
- size_t CurrentFeature = 0;
- for (; CurrentFeature < InputFeatures.size(); ++CurrentFeature) {
- Log->logSpecifiedTensorValue(
- CurrentFeature, reinterpret_cast<const char *>(
- getRunner().getTensorUntyped(CurrentFeature)));
- }
-
- if (auto *MUTR = dyn_cast<ModelUnderTrainingRunner>(&getRunner())) {
- for (size_t I = 1; I < MUTR->outputLoggedFeatureSpecs().size();
- ++I, ++CurrentFeature)
- Log->logSpecifiedTensorValue(
- CurrentFeature,
- reinterpret_cast<const char *>(
- MUTR->lastEvaluationResult()->getUntypedTensorValue(I)));
- }
-
- float Ret = static_cast<float>(Prio);
- Log->logFloatValue(CurrentFeature, &Ret);
-
- return static_cast<unsigned>(Prio);
-}
-
-#endif // #ifdef LLVM_HAVE_TF_API
diff --git a/llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp b/llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp
index 88fd47e600983..5ace3ddba8769 100644
--- a/llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp
+++ b/llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp
@@ -76,14 +76,10 @@ template <> Pass *llvm::callDefaultCtor<RegAllocPriorityAdvisorAnalysis>() {
Ret = new DefaultPriorityAdvisorAnalysis(/*NotAsRequested*/ false);
break;
case RegAllocPriorityAdvisorAnalysis::AdvisorMode::Development:
-#if defined(LLVM_HAVE_TF_API)
- Ret = createDevelopmentModePriorityAdvisor();
-#endif
+ // TODO: add implementation
break;
case RegAllocPriorityAdvisorAnalysis::AdvisorMode::Release:
-#if defined(LLVM_HAVE_TF_AOT_REGALLOCPRIORITYMODEL)
- Ret = createReleaseModePriorityAdvisor();
-#endif
+ // TODO: add implementation
break;
}
if (Ret)
diff --git a/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt b/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
deleted file mode 100644
index 271480214546d..0000000000000
--- a/llvm/test/CodeGen/MLRegalloc/Inputs/reference-prio-log-noml.txt
+++ /dev/null
@@ -1,361 +0,0 @@
-fields {
- key: "SyFgets"
- value {
- string_value: "feature_lists {
- feature_list {
- key: \"li_size\" value {
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } } } }
- feature_list {
- key: \"priority\" value {
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 2.68435866e+09 } }
- feature { float_list { value: 2.68435789e+09 } }
- feature { float_list { value: 3.75810074e+09 } }
- feature { float_list { value: 3.7580969e+09 } }
- feature { float_list { value: 2.14748518e+09 } }
- feature { float_list { value: 2.14748493e+09 } }
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 2.14748493e+09 } }
- feature { float_list { value: 2.14748493e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435763e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.14748467e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435763e+09 } }
- feature { float_list { value: 2.68435763e+09 } }
- feature { float_list { value: 2.1474839e+09 } }
- feature { float_list { value: 2.1474839e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.1474839e+09 } }
- feature { float_list { value: 3.22122547e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.14748365e+09 } }
- feature { float_list { value: 2.14748493e+09 } }
- feature { float_list { value: 2.14748493e+09 } }
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435584e+09 } }
- feature { float_list { value: 2.68435482e+09 } }
- feature { float_list { value: 2.68435482e+09 } }
- feature { float_list { value: 2.68435763e+09 } }
- feature { float_list { value: 2.68435584e+09 } }
- feature { float_list { value: 2.14748365e+09 } }
- feature { float_list { value: 3.75810074e+09 } }
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 3584 } }
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 3550 } }
- feature { float_list { value: 2.68435814e+09 } }
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- feature { float_list { value: 3.75809946e+09 } }
- feature { float_list { value: 2.68435866e+09 } }
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- feature { float_list { value: 3.75810074e+09 } }
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- feature { float_list { value: 2.6843584e+09 } }
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- feature { float_list { value: 2.68435482e+09 } }
- feature { float_list { value: 2.68435482e+09 } }
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 2.68435482e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 2.14748493e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435814e+09 } }
- feature { float_list { value: 2.14748493e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435456e+09 } }
- feature { float_list { value: 2.68435456e+09 } } } }
- feature_list {
- key: \"reward\" value {
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- feature { float_list { value: 0 } }
- feature { float_list { value: 0 } }
- feature { float_list { value: 0 } }
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- feature_list {
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- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
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- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } }
- feature { int64_list { value: 0 } } } }
- feature_list {
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- feature { float_list { value: 0 } }
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- feature { float_list { value: 0 } }
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- feature { float_list { value: 0 } }
- feature { float_list { value: 0 } }
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- feature { float_list { value: 0 } } } } } "
- }
-}
diff --git a/llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll b/llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll
deleted file mode 100644
index e8b05d5dfce19..0000000000000
--- a/llvm/test/CodeGen/MLRegalloc/dev-mode-prio-logging.ll
+++ /dev/null
@@ -1,29 +0,0 @@
-; REQUIRES: have_tf_api
-; REQUIRES: x86_64-linux
-;
-; Check that we log correctly, both with a learned policy, and the default policy
-;
-; RUN: llc -mtriple=x86_64-linux-unknown -regalloc=greedy -regalloc-enable-priority-advisor=development \
-; RUN: -regalloc-priority-training-log=%t1 -tfutils-text-log < %S/Inputs/input.ll
-; RUN: sed -i 's/ \+/ /g' %t1
-; RUN: sed -i 's/\\n key:/\n key:/g' %t1
-; RUN: sed -i 's/\\n feature/\n feature/g' %t1
-; RUN: sed -i 's/\\n/ /g' %t1
-; RUN: FileCheck --input-file %t1 %s --check-prefixes=CHECK,NOML
-; RUN:
diff %t1 %S/Inputs/reference-prio-log-noml.txt
-
-; RUN: rm -rf %t && mkdir %t
-; RUN: %python %S/../../../lib/Analysis/models/gen-regalloc-priority-test-model.py %t
-; RUN: llc -mtriple=x86_64-linux-unknown -regalloc=greedy -regalloc-enable-priority-advisor=development \
-; RUN: -regalloc-priority-training-log=%t2 -tfutils-text-log -regalloc-priority-model=%t < %S/Inputs/input.ll
-; RUN: sed -i 's/ \+/ /g' %t2
-; RUN: sed -i 's/\\n key:/\n key:/g' %t2
-; RUN: sed -i 's/\\n feature/\n feature/g' %t2
-; RUN: sed -i 's/\\n/ /g' %t2
-; RUN: FileCheck --input-file %t2 %s --check-prefixes=CHECK,ML
-
-; CHECK-NOT: nan
-; CHECK-LABEL: key: \"priority\"
-; NOML-NEXT: feature { float_list { value: 2.68435814e+09 } }
-; ML-NEXT: feature { float_list { value: 3551 } }
-; CHECK-LABEL: key: \"reward\"
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