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//===- 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 <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(int64_t, {1}, sroa_savings, \
"Savings from SROA (scalar replacement of aggregates)") \
M(int64_t, {1}, sroa_losses, \
"Losses from SROA (scalar replacement of aggregates)") \
M(int64_t, {1}, load_elimination, "Cost of load elimination in the call") \
M(int64_t, {1}, call_penalty, \
"Accumulation of penalty applied to call sites when inlining") \
M(int64_t, {1}, call_argument_setup, \
"Accumulation of call argument setup costs") \
M(int64_t, {1}, load_relative_intrinsic, \
"Accumulation of costs of loading relative intrinsics") \
M(int64_t, {1}, lowered_call_arg_setup, \
"Accumulation of cost of lowered call argument setups") \
M(int64_t, {1}, indirect_call_penalty, \
"Accumulation of costs for indirect calls") \
M(int64_t, {1}, jump_table_penalty, "Accumulation of costs for jump tables") \
M(int64_t, {1}, case_cluster_penalty, \
"Accumulation of costs for case clusters") \
M(int64_t, {1}, switch_default_dest_penalty, \
"Accumulation of costs for switch default destination") \
M(int64_t, {1}, switch_penalty, \
"Accumulation of costs for switch statements") \
M(int64_t, {1}, unsimplified_common_instructions, \
"Costs from unsimplified common instructions") \
M(int64_t, {1}, num_loops, "Number of loops in the caller") \
M(int64_t, {1}, dead_blocks, "Number of dead blocks in the caller") \
M(int64_t, {1}, simplified_instructions, \
"Number of simplified instructions") \
M(int64_t, {1}, constant_args, \
"Number of constant arguments in the call site") \
M(int64_t, {1}, constant_offset_ptr_args, \
"Number of constant offset pointer args in the call site") \
M(int64_t, {1}, callsite_cost, "Estimated cost of the call site") \
M(int64_t, {1}, cold_cc_penalty, "Penalty for a cold calling convention") \
M(int64_t, {1}, last_call_to_static_bonus, \
"Bonus for being the last call to static") \
M(int64_t, {1}, is_multiple_blocks, \
"Boolean; is the Callee multiple blocks") \
M(int64_t, {1}, nested_inlines, \
"Would the default inliner perfom nested inlining") \
M(int64_t, {1}, nested_inline_cost_estimate, \
"Estimate of the accumulated cost of nested inlines") \
M(int64_t, {1}, threshold, "Threshold for the heuristic inliner")
// clang-format off
enum class InlineCostFeatureIndex : size_t {
#define POPULATE_INDICES(DTYPE, SHAPE, NAME, DOC) 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::sroa_savings &&
Feature != InlineCostFeatureIndex::is_multiple_blocks &&
Feature != InlineCostFeatureIndex::dead_blocks &&
Feature != InlineCostFeatureIndex::simplified_instructions &&
Feature != InlineCostFeatureIndex::constant_args &&
Feature != InlineCostFeatureIndex::constant_offset_ptr_args &&
Feature != InlineCostFeatureIndex::nested_inlines &&
Feature != InlineCostFeatureIndex::nested_inline_cost_estimate &&
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 ML model binding (so it needs to match the
// names used by the ML 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(int64_t, {1}, callee_basic_block_count, \
"number of basic blocks of the callee") \
M(int64_t, {1}, callsite_height, \
"position of the call site in the original call graph - measured from " \
"the farthest SCC") \
M(int64_t, {1}, node_count, \
"total current number of defined functions in the module") \
M(int64_t, {1}, nr_ctant_params, \
"number of parameters in the call site that are constants") \
M(int64_t, {1}, cost_estimate, "total cost estimate (threshold - free)") \
M(int64_t, {1}, edge_count, "total number of calls in the module") \
M(int64_t, {1}, caller_users, \
"number of module-internal users of the caller, +1 if the caller is " \
"exposed externally") \
M(int64_t, {1}, caller_conditionally_executed_blocks, \
"number of blocks reached from a conditional instruction, in the caller") \
M(int64_t, {1}, caller_basic_block_count, \
"number of basic blocks in the caller") \
M(int64_t, {1}, callee_conditionally_executed_blocks, \
"number of blocks reached from a conditional instruction, in the callee") \
M(int64_t, {1}, callee_users, \
"number of module-internal users of the callee, +1 if the callee is " \
"exposed externally") \
M(int64_t, {1}, is_callee_avail_external, \
"Is callee an available-externally linkage type (i.e. could be DCEd if " \
"not " \
"fully inlined by ElimAvailExtern)") \
M(int64_t, {1}, is_caller_avail_external, \
"Is caller an available-externally linkage type (i.e. could be DCEd if " \
"not " \
"fully inlined by ElimAvailExtern)")
// clang-format off
enum class FeatureIndex : size_t {
#define POPULATE_INDICES(DTYPE, SHAPE, NAME, COMMENT) NAME,
// InlineCost features - these must come first
INLINE_COST_FEATURE_ITERATOR(POPULATE_INDICES)
// Non-cost features
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::vector<TensorSpec> FeatureMap;
extern const char *const DecisionName;
extern const TensorSpec InlineDecisionSpec;
extern const char *const DefaultDecisionName;
extern const TensorSpec DefaultDecisionSpec;
extern const char *const RewardName;
using InlineFeatures = std::vector<int64_t>;
} // namespace llvm
#endif // LLVM_ANALYSIS_INLINEMODELFEATUREMAPS_H
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