142 lines
6.9 KiB
C++
142 lines
6.9 KiB
C++
//===- InlineModelFeatureMaps.h - common model runner defs ------*- C++ -*-===//
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//
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// Part of the LLVM 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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//
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//===----------------------------------------------------------------------===//
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//
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#ifndef LLVM_ANALYSIS_INLINEMODELFEATUREMAPS_H
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#define LLVM_ANALYSIS_INLINEMODELFEATUREMAPS_H
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#include "llvm/Analysis/TensorSpec.h"
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#include <array>
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#include <string>
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#include <vector>
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namespace llvm {
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// List of cost features. A "cost" feature is a summand of the heuristic-based
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// inline cost, and we define them separately to preserve the original heuristic
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// behavior.
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#define INLINE_COST_FEATURE_ITERATOR(M) \
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M(SROASavings, "sroa_savings") \
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M(SROALosses, "sroa_losses") \
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M(LoadElimination, "load_elimination") \
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M(CallPenalty, "call_penalty") \
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M(CallArgumentSetup, "call_argument_setup") \
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M(LoadRelativeIntrinsic, "load_relative_intrinsic") \
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M(LoweredCallArgSetup, "lowered_call_arg_setup") \
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M(IndirectCallPenalty, "indirect_call_penalty") \
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M(JumpTablePenalty, "jump_table_penalty") \
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M(CaseClusterPenalty, "case_cluster_penalty") \
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M(SwitchPenalty, "switch_penalty") \
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M(UnsimplifiedCommonInstructions, "unsimplified_common_instructions") \
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M(NumLoops, "num_loops") \
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M(DeadBlocks, "dead_blocks") \
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M(SimplifiedInstructions, "simplified_instructions") \
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M(ConstantArgs, "constant_args") \
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M(ConstantOffsetPtrArgs, "constant_offset_ptr_args") \
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M(CallSiteCost, "callsite_cost") \
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M(ColdCcPenalty, "cold_cc_penalty") \
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M(LastCallToStaticBonus, "last_call_to_static_bonus") \
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M(IsMultipleBlocks, "is_multiple_blocks") \
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M(NestedInlines, "nested_inlines") \
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M(NestedInlineCostEstimate, "nested_inline_cost_estimate") \
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M(Threshold, "threshold")
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// clang-format off
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enum class InlineCostFeatureIndex : size_t {
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#define POPULATE_INDICES(INDEX_NAME, NAME) INDEX_NAME,
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INLINE_COST_FEATURE_ITERATOR(POPULATE_INDICES)
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#undef POPULATE_INDICES
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NumberOfFeatures
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};
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// clang-format on
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using InlineCostFeatures =
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std::array<int,
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static_cast<size_t>(InlineCostFeatureIndex::NumberOfFeatures)>;
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constexpr bool isHeuristicInlineCostFeature(InlineCostFeatureIndex Feature) {
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return Feature != InlineCostFeatureIndex::SROASavings &&
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Feature != InlineCostFeatureIndex::IsMultipleBlocks &&
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Feature != InlineCostFeatureIndex::DeadBlocks &&
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Feature != InlineCostFeatureIndex::SimplifiedInstructions &&
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Feature != InlineCostFeatureIndex::ConstantArgs &&
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Feature != InlineCostFeatureIndex::ConstantOffsetPtrArgs &&
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Feature != InlineCostFeatureIndex::NestedInlines &&
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Feature != InlineCostFeatureIndex::NestedInlineCostEstimate &&
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Feature != InlineCostFeatureIndex::Threshold;
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}
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// List of features. Each feature is defined through a triple:
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// - the name of an enum member, which will be the feature index
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// - a textual name, used for Tensorflow model binding (so it needs to match the
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// names used by the Tensorflow model)
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// - a documentation description. Currently, that is not used anywhere
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// programmatically, and serves as workaround to inability of inserting comments
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// in macros.
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#define INLINE_FEATURE_ITERATOR(M) \
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M(CalleeBasicBlockCount, "callee_basic_block_count", \
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"number of basic blocks of the callee") \
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M(CallSiteHeight, "callsite_height", \
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"position of the call site in the original call graph - measured from " \
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"the farthest SCC") \
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M(NodeCount, "node_count", \
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"total current number of defined functions in the module") \
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M(NrCtantParams, "nr_ctant_params", \
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"number of parameters in the call site that are constants") \
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M(CostEstimate, "cost_estimate", "total cost estimate (threshold - free)") \
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M(EdgeCount, "edge_count", "total number of calls in the module") \
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M(CallerUsers, "caller_users", \
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"number of module-internal users of the caller, +1 if the caller is " \
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"exposed externally") \
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M(CallerConditionallyExecutedBlocks, "caller_conditionally_executed_blocks", \
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"number of blocks reached from a conditional instruction, in the caller") \
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M(CallerBasicBlockCount, "caller_basic_block_count", \
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"number of basic blocks in the caller") \
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M(CalleeConditionallyExecutedBlocks, "callee_conditionally_executed_blocks", \
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"number of blocks reached from a conditional instruction, in the callee") \
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M(CalleeUsers, "callee_users", \
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"number of module-internal users of the callee, +1 if the callee is " \
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"exposed externally")
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// clang-format off
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enum class FeatureIndex : size_t {
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// InlineCost features - these must come first
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#define POPULATE_INDICES(INDEX_NAME, NAME) INDEX_NAME,
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INLINE_COST_FEATURE_ITERATOR(POPULATE_INDICES)
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#undef POPULATE_INDICES
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// Non-cost features
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#define POPULATE_INDICES(INDEX_NAME, NAME, COMMENT) INDEX_NAME,
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INLINE_FEATURE_ITERATOR(POPULATE_INDICES)
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#undef POPULATE_INDICES
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NumberOfFeatures
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};
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// clang-format on
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constexpr FeatureIndex
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inlineCostFeatureToMlFeature(InlineCostFeatureIndex Feature) {
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return static_cast<FeatureIndex>(static_cast<size_t>(Feature));
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}
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constexpr size_t NumberOfFeatures =
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static_cast<size_t>(FeatureIndex::NumberOfFeatures);
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extern const std::array<TensorSpec, NumberOfFeatures> FeatureMap;
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extern const char *const DecisionName;
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extern const char *const DefaultDecisionName;
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extern const char *const RewardName;
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using InlineFeatures = std::vector<int64_t>;
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} // namespace llvm
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#endif // LLVM_ANALYSIS_INLINEMODELFEATUREMAPS_H
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