| /freebsd-src/contrib/llvm-project/llvm/include/llvm/Analysis/ |
| H A D | TensorSpec.h | 1 //===- TensorSpec.h - type descriptor for a tensor --------------*- C++ -*-===// 27 /// TensorSpec encapsulates the specification of a tensor: its dimensions, or 28 /// "shape" (row-major), its type (see TensorSpec::getDataType specializations 37 /// right is a name we can use to identify the type (to implement TensorSpec 62 class TensorSpec final { 65 static TensorSpec createSpec(const std::string &Name, 68 return TensorSpec(Name, Port, getDataType<T>(), sizeof(T), Shape); in port() 76 bool operator==(const TensorSpec &Other) const { 81 bool operator!=(const TensorSpec &Other) const { return !(*this == Other); } 94 TensorSpec(cons 90 TensorSpec(const std::string &NewName, const TensorSpec &Other) TensorSpec() function [all...] |
| H A D | ModelUnderTrainingRunner.h | 38 const std::vector<TensorSpec> &extraOutputsForLoggingSpecs() const { in extraOutputsForLoggingSpecs() 57 const std::vector<TensorSpec> &InputSpecs, 62 const std::vector<TensorSpec> &InputSpecs, 63 const std::vector<TensorSpec> &OutputSpecs, 64 const std::vector<TensorSpec> &ExtraOutputsForLogging = {}); 70 const std::vector<TensorSpec> OutputSpecs; 71 const std::vector<TensorSpec> ExtraOutputsForLogging;
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| H A D | InteractiveModelRunner.h | 44 const std::vector<TensorSpec> &Inputs, 45 const TensorSpec &Advice, StringRef OutboundName, 63 const std::vector<TensorSpec> InputSpecs; 64 const TensorSpec OutputSpec;
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| H A D | InlineModelFeatureMaps.h | 13 #include "llvm/Analysis/TensorSpec.h" 156 extern const std::vector<TensorSpec> FeatureMap; 159 extern const TensorSpec InlineDecisionSpec; 161 extern const TensorSpec DefaultDecisionSpec;
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| H A D | NoInferenceModelRunner.h | 23 const std::vector<TensorSpec> &Inputs);
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| H A D | MLModelRunner.h | 63 void setUpBufferForTensor(size_t Index, const TensorSpec &Spec, in setUpBufferForTensor()
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| /freebsd-src/contrib/llvm-project/llvm/lib/Analysis/ |
| H A D | ModelUnderTrainingRunner.cpp | 25 TensorSpec Spec; 60 if (auto TensorSpec = getTensorSpecFromJSON(Ctx, *SpecPart)) in loadOutputSpecs() local 62 if (!TensorSpec->isElementType<int64_t>() && in loadOutputSpecs() 63 !TensorSpec->isElementType<int32_t>() && in loadOutputSpecs() 64 !TensorSpec->isElementType<float>()) { in loadOutputSpecs() 68 TensorSpec->name()); in loadOutputSpecs() 71 Ret.push_back({*TensorSpec, LoggingName->str()}); in loadOutputSpecs() 95 const std::vector<TensorSpec> &InputSpecs, in ModelUnderTrainingRunner() 96 const std::vector<TensorSpec> &OutputSpecs, in ModelUnderTrainingRunner() 97 const std::vector<TensorSpec> &ExtraOutputsForLogging) in ModelUnderTrainingRunner() [all …]
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| H A D | TensorSpec.cpp | 33 template <> TensorType TensorSpec::getDataType<T>() { return TensorType::E; } 50 void TensorSpec::toJSON(json::OStream &OS) const { in toJSON() 62 TensorSpec::TensorSpec(const std::string &Name, int Port, TensorType Type, in TensorSpec() function in llvm::TensorSpec 69 std::optional<TensorSpec> getTensorSpecFromJSON(LLVMContext &Ctx, in getTensorSpecFromJSON() 72 [&](const llvm::Twine &Message) -> std::optional<TensorSpec> { in getTensorSpecFromJSON() 101 return TensorSpec::createSpec<T>(TensorName, TensorShape, TensorPort); in getTensorSpecFromJSON() 107 std::string tensorValueToString(const char *Buffer, const TensorSpec &Spec) { in tensorValueToString()
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| H A D | TFLiteUtils.cpp | 56 const std::vector<TensorSpec> &InputSpecs, 57 const std::vector<TensorSpec> &OutputSpecs, 95 const TensorSpec &Spec); 101 StringRef SavedModelPath, const std::vector<TensorSpec> &InputSpecs, in TFModelEvaluatorImpl() 102 const std::vector<TensorSpec> &OutputSpecs, const char *Tags = "serve") in TFModelEvaluatorImpl() 185 const std::vector<TensorSpec> &InputSpecs, in TFModelEvaluator() 186 const std::vector<TensorSpec> &OutputSpecs, in TFModelEvaluator() 197 const TensorSpec &Spec) { in checkReportAndInvalidate()
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| H A D | TrainingLogger.cpp | 30 void Logger::writeHeader(std::optional<TensorSpec> AdviceSpec) { in writeHeader() 83 const std::vector<TensorSpec> &FeatureSpecs, in Logger() 84 const TensorSpec &RewardSpec, bool IncludeReward, in Logger() 85 std::optional<TensorSpec> AdviceSpec) in Logger()
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| H A D | InlineSizeEstimatorAnalysis.cpp | 221 std::vector<TensorSpec> InputSpecs{TensorSpec::createSpec<int32_t>( in InlineSizeEstimatorAnalysis() 225 std::vector<TensorSpec> OutputSpecs{ in InlineSizeEstimatorAnalysis() 226 TensorSpec::createSpec<float>("StatefulPartitionedCall", {1})}; in InlineSizeEstimatorAnalysis()
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| H A D | InteractiveModelRunner.cpp | 27 LLVMContext &Ctx, const std::vector<TensorSpec> &Inputs, in InteractiveModelRunner() 28 const TensorSpec &Advice, StringRef OutboundName, StringRef InboundName) in InteractiveModelRunner()
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| H A D | MLInlineAdvisor.cpp | 110 const std::vector<TensorSpec> llvm::FeatureMap{ 111 #define POPULATE_NAMES(DTYPE, SHAPE, NAME, __) TensorSpec::createSpec<DTYPE>(#NAME, SHAPE), 122 const TensorSpec llvm::InlineDecisionSpec = in getInlinableCS() 123 TensorSpec::createSpec<int64_t>(DecisionName, {1}); 125 const TensorSpec llvm::DefaultDecisionSpec = in MLInlineAdvisor() 126 TensorSpec::createSpec<int64_t>(DefaultDecisionName, {1}); in MLInlineAdvisor()
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| H A D | NoInferenceModelRunner.cpp | 18 LLVMContext &Ctx, const std::vector<TensorSpec> &Inputs) in NoInferenceModelRunner()
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| H A D | DevelopmentModeInlineAdvisor.cpp | 13 #include "llvm/Analysis/TensorSpec.h" 48 - "tensor_spec, followed by the TensorSpec description of the 256 static const std::vector<TensorSpec> TrainingOnlyFeatures{ 257 TensorSpec::createSpec<float>(TFFeedPrefix + "discount", {1}), 258 TensorSpec::createSpec<float>(TFFeedPrefix + "reward", {1}), 259 TensorSpec::createSpec<int32_t>(TFFeedPrefix + "step_type", {1})}; 261 static const std::vector<TensorSpec> getInputFeatures() { 262 std::vector<TensorSpec> InputSpecs; 264 InputSpecs.push_back(TensorSpec::createSpec<int64_t>( 276 std::vector<TensorSpec> F [all...] |
| /freebsd-src/contrib/llvm-project/llvm/include/llvm/Analysis/Utils/ |
| H A D | TrainingLogger.h | 93 const std::vector<TensorSpec> FeatureSpecs; 94 const TensorSpec RewardSpec; 99 void writeHeader(std::optional<TensorSpec> AdviceSpec); 100 void writeTensor(const TensorSpec &Spec, const char *RawData) { in writeTensor() 113 const std::vector<TensorSpec> &FeatureSpecs, 114 const TensorSpec &RewardSpec, bool IncludeReward, 115 std::optional<TensorSpec> AdviceSpec = std::nullopt);
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| H A D | TFUtils.h | 77 const std::vector<TensorSpec> &InputSpecs, 78 const std::vector<TensorSpec> &OutputSpecs,
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| /freebsd-src/contrib/llvm-project/llvm/lib/CodeGen/ |
| H A D | MLRegAllocPriorityAdvisor.cpp | 20 #include "llvm/Analysis/TensorSpec.h" 80 static const TensorSpec DecisionSpec = 81 TensorSpec::createSpec<float>(DecisionName, {1}); 114 TensorSpec::createSpec<type>(#name, shape), 116 static const std::vector<TensorSpec> InputFeatures{ 165 static const TensorSpec Reward = TensorSpec::createSpec<float>("reward", {1}); 168 TensorSpec::createSpec<type>(std::string("action_") + #name, shape), 170 static const std::vector<TensorSpec> TrainingInputFeatures{ 172 TensorSpec [all...] |
| H A D | MLRegAllocEvictAdvisor.cpp | 18 #include "llvm/Analysis/TensorSpec.h" 227 static const TensorSpec DecisionSpec = 228 TensorSpec::createSpec<int64_t>(DecisionName, {1}); 364 TensorSpec::createSpec<type>(#name, shape), 388 std::vector<TensorSpec> InputFeatures; 422 static const TensorSpec Reward = TensorSpec::createSpec<float>("reward", {1}); 429 TensorSpec::createSpec<type>(std::string("action_") + #name, shape), 461 TensorSpec::createSpec<float>("action_discount", {1}), in DevelopmentModeEvictionAdvisorAnalysis() 462 TensorSpec in DevelopmentModeEvictionAdvisorAnalysis() [all...] |
| /freebsd-src/lib/clang/libllvm/ |
| H A D | Makefile | 153 SRCS_MIN+= Analysis/TensorSpec.cpp
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