cost_model.h

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 * distributed with this work for additional information
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 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
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 * KIND, either express or implied.  See the License for the
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#ifndef TVM_S_TIR_META_SCHEDULE_COST_MODEL_H_
#define TVM_S_TIR_META_SCHEDULE_COST_MODEL_H_
 
#include <tvm/ffi/container/array.h>
#include <tvm/ffi/function.h>
#include <tvm/ffi/reflection/registry.h>
#include <tvm/ffi/string.h>
#include <tvm/ir/prim/expr.h>
#include <tvm/runtime/base.h>
#include <tvm/s_tir/meta_schedule/arg_info.h>
#include <tvm/s_tir/meta_schedule/measure_candidate.h>
#include <tvm/s_tir/meta_schedule/runner.h>
#include <tvm/s_tir/schedule/schedule.h>
 
#include <vector>
 
namespace tvm {
namespace s_tir {
namespace meta_schedule {
 
class TuneContext;
 
class CostModelObj : public ffi::Object {
 public:
  virtual ~CostModelObj() = default;
 
  virtual void Load(const ffi::String& path) = 0;
 
  virtual void Save(const ffi::String& path) = 0;
 
  virtual void Update(const TuneContext& context, const ffi::Array<MeasureCandidate>& candidates,
                      const ffi::Array<RunnerResult>& results) = 0;
 
  virtual std::vector<double> Predict(const TuneContext& context,
                                      const ffi::Array<MeasureCandidate>& candidates) = 0;
 
  static constexpr const bool _type_mutable = true;
  TVM_FFI_DECLARE_OBJECT_INFO("s_tir.meta_schedule.CostModel", CostModelObj, ffi::Object);
};
 
class PyCostModelObj : public CostModelObj {
 public:
  using FLoad = ffi::TypedFunction<void(ffi::String)>;
  using FSave = ffi::TypedFunction<void(ffi::String)>;
  using FUpdate = ffi::TypedFunction<void(const TuneContext&, const ffi::Array<MeasureCandidate>&,
                                          const ffi::Array<RunnerResult>&)>;
  using FPredict = ffi::TypedFunction<void(const TuneContext&, const ffi::Array<MeasureCandidate>&,
                                           void* p_addr)>;
  FLoad f_load;
  FSave f_save;
  FUpdate f_update;
  FPredict f_predict;
 
  void Load(const ffi::String& path);
  void Save(const ffi::String& path);
  void Update(const TuneContext& context, const ffi::Array<MeasureCandidate>& candidates,
              const ffi::Array<RunnerResult>& results);
  std::vector<double> Predict(const TuneContext& context,
                              const ffi::Array<MeasureCandidate>& candidates);
  TVM_FFI_DECLARE_OBJECT_INFO_FINAL("s_tir.meta_schedule.PyCostModel", PyCostModelObj,
                                    CostModelObj);
};
 
class CostModel : public ffi::ObjectRef {
 public:
  explicit CostModel(ffi::UnsafeInit tag, ffi::ObjectPtr<CostModelObj> data) : ffi::ObjectRef(tag) {
    data_ = std::move(data);
  }
 
  TVM_DLL static CostModel PyCostModel(PyCostModelObj::FLoad f_load,      //
                                       PyCostModelObj::FSave f_save,      //
                                       PyCostModelObj::FUpdate f_update,  //
                                       PyCostModelObj::FPredict f_predict);
  TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE(CostModel, ffi::ObjectRef, CostModelObj);
};
 
}  // namespace meta_schedule
}  // namespace s_tir
}  // namespace tvm
 
#endif  // TVM_S_TIR_META_SCHEDULE_COST_MODEL_H_