CostModel.h

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#ifndef COST_MODEL_H
#define COST_MODEL_H
 
#include <string>
 
#include "Featurization.h"
#include "FunctionDAG.h"
#include "HalideBuffer.h"
#include "PerfectHashMap.h"
 
// An abstract base class for a cost model.
namespace Halide {
 
namespace Internal {
namespace Autoscheduler {
 
typedef PerfectHashMap<FunctionDAG::Node::Stage, ScheduleFeatures> StageMapOfScheduleFeatures;
 
struct Adams2019Params {
    /** Maximum level of parallelism available. */
    int parallelism = 16;
 
    /** Beam size to use in the beam search. Defaults to 32. Use 1 to get a greedy search instead.
     * Formerly HL_BEAM_SIZE */
    int beam_size = 32;
 
    /** percent chance of accepting each state in the beam.
     * Normalized by the number of decisions made, so 5 would be there's a 5 percent chance of never rejecting any states.
     * Formerly HL_RANDOM_DROPOUT */
    int random_dropout = 100;
 
    /** Random seed used by the random dropout. If 0, use time().
     * Formerly HL_SEED */
    int random_dropout_seed = 0;
 
    /** When training or schedule, read weights from this directory or file.
     * (If path ends in `.weights` it is written as a single file, otherwise a directory of files.)
     * Formerly HL_WEIGHTS_DIR */
    std::string weights_path;
 
    /** If set to nonzero value: limits the search space to that of Mullapudi et al.
     * Formerly HL_NO_SUBTILING */
    int disable_subtiling = 0;
 
    /** If set to nonzero value: features of possible schedules are always recalculated, and are not cached across passes.
     * Formerly HL_DISABLE_MEMOIZED_FEATURES */
    int disable_memoized_features = 0;
 
    /** If set to nonzero value: tiling sizes are not cached across passes.
     * Formerly HL_DISABLE_MEMOIZED_BLOCKS */
    int disable_memoized_blocks = 0;
 
    /** If >= 0, only consider schedules that allocate at most this much memory (measured in bytes).
     * Formerly HL_AUTOSCHEDULE_MEMORY_LIMIT */
    int64_t memory_limit = -1;
};
 
}  // namespace Autoscheduler
}  // namespace Internal
 
class CostModel {
public:
    virtual ~CostModel() = default;
 
    // Configure the cost model for the algorithm to be scheduled.
    virtual void set_pipeline_features(const Internal::Autoscheduler::FunctionDAG &dag,
                                       const Internal::Autoscheduler::Adams2019Params &params) = 0;
 
    // Enqueue a schedule to be evaluated. Will annotate the value located at cost_ptr when the evaluation takes place.
    // Note that the dag argument should correspond to the dag specified previously when calling set_pipeline_features.
    virtual void enqueue(const Internal::Autoscheduler::FunctionDAG &dag,
                         const Halide::Internal::Autoscheduler::StageMapOfScheduleFeatures &schedule_feats,
                         double *cost_ptr) = 0;
 
    // Evaluate all schedules in the queue.
    virtual void evaluate_costs() = 0;
 
    // Discard all schedules in the queue.
    virtual void reset() = 0;
};
 
}  // namespace Halide
 
#endif  // COST_MODEL_H