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