task_scheduler.h

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 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * 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
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
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#ifndef TVM_META_SCHEDULE_TASK_SCHEDULER_H_
#define TVM_META_SCHEDULE_TASK_SCHEDULER_H_

#include <tvm/meta_schedule/builder.h>
#include <tvm/meta_schedule/cost_model.h>
#include <tvm/meta_schedule/measure_callback.h>
#include <tvm/meta_schedule/runner.h>
#include <tvm/meta_schedule/tune_context.h>
#include <tvm/node/reflection.h>
#include <tvm/runtime/container/array.h>
#include <tvm/runtime/container/optional.h>
#include <tvm/runtime/object.h>
#include <tvm/runtime/packed_func.h>
#include <tvm/support/random_engine.h>

#include <string>
#include <vector>

namespace tvm {
namespace meta_schedule {

class TaskRecordNode : public runtime::Object {
 public:
  TuneContext ctx{nullptr};
  double task_weight{1.0};
  double flop{1.0};
  bool is_terminated = false;
  int build_error_count = 0;
  int run_error_count = 0;
  std::vector<double> latency_ms = {};
  Optional<Array<MeasureCandidate>> measure_candidates = NullOpt;
  Optional<Array<BuilderResult>> builder_results = NullOpt;
  Optional<Array<RunnerFuture>> runner_futures = NullOpt;

  void VisitAttrs(tvm::AttrVisitor* v) {
    v->Visit("ctx", &ctx);
    v->Visit("task_weight", &task_weight);
    v->Visit("flop", &flop);
    v->Visit("is_terminated", &is_terminated);
    v->Visit("build_error_count", &build_error_count);
    v->Visit("run_error_count", &run_error_count);
    // `latency_ms` is not visited
    v->Visit("measure_candidates", &measure_candidates);
    v->Visit("builder_results", &builder_results);
    v->Visit("runner_futures", &runner_futures);
  }

  static constexpr const char* _type_key = "meta_schedule.TaskRecord";
  TVM_DECLARE_FINAL_OBJECT_INFO(TaskRecordNode, Object);
};

class TaskRecord : public runtime::ObjectRef {
 public:
  explicit TaskRecord(TuneContext task, double task_weight);

  TVM_DEFINE_MUTABLE_NOTNULLABLE_OBJECT_REF_METHODS(TaskRecord, ObjectRef, TaskRecordNode);
};

class TaskSchedulerNode : public runtime::Object {
 public:
  PackedFunc logger;
  Array<TaskRecord> tasks_;
  Array<MeasureCallback> measure_callbacks_;
  Optional<Database> database_;
  Optional<CostModel> cost_model_;
  int remaining_tasks_;

  virtual ~TaskSchedulerNode() = default;

  void VisitAttrs(tvm::AttrVisitor* v) {
    // `logger` is not visited
    v->Visit("tasks_", &tasks_);
    v->Visit("measure_callbacks_", &measure_callbacks_);
    v->Visit("database_", &database_);
    v->Visit("cost_model_", &cost_model_);
    v->Visit("remaining_tasks_", &remaining_tasks_);
  }

  virtual int NextTaskId() = 0;
  virtual Array<RunnerResult> JoinRunningTask(int task_id);
  virtual void Tune(Array<TuneContext> tasks,                  //
                    Array<FloatImm> task_weights,              //
                    int max_trials_global,                     //
                    int max_trials_per_task,                   //
                    int num_trials_per_iter,                   //
                    Builder builder,                           //
                    Runner runner,                             //
                    Array<MeasureCallback> measure_callbacks,  //
                    Optional<Database> database,               //
                    Optional<CostModel> cost_model);
  void TerminateTask(int task_id);
  void TouchTask(int task_id);
  void PrintTuningStatistics();

  static constexpr const char* _type_key = "meta_schedule.TaskScheduler";
  TVM_DECLARE_BASE_OBJECT_INFO(TaskSchedulerNode, Object);
};

class TaskScheduler;

class PyTaskSchedulerNode : public TaskSchedulerNode {
 public:
  using FNextTaskId = runtime::TypedPackedFunc<int()>;
  using FJoinRunningTask = runtime::TypedPackedFunc<Array<RunnerResult>(int)>;
  using FTune = runtime::TypedPackedFunc<void(Array<TuneContext> tasks,                  //
                                              Array<FloatImm> task_weights,              //
                                              int max_trials_global,                     //
                                              int max_trials_per_task,                   //
                                              int num_trials_per_iter,                   //
                                              Builder builder,                           //
                                              Runner runner,                             //
                                              Array<MeasureCallback> measure_callbacks,  //
                                              Optional<Database> database,               //
                                              Optional<CostModel> cost_model)>;

  FNextTaskId f_next_task_id;
  FJoinRunningTask f_join_running_task;
  FTune f_tune;

  void VisitAttrs(tvm::AttrVisitor* v) {
    TaskSchedulerNode::VisitAttrs(v);
    // `f_next_task_id` is not visited
    // `f_join_running_task` is not visited
    // `f_tune` is not visited
  }

  int NextTaskId() final;
  Array<RunnerResult> JoinRunningTask(int task_id) final;
  void Tune(Array<TuneContext> tasks, Array<FloatImm> task_weights, int max_trials_global,
            int max_trials_per_task, int num_trials_per_iter, Builder builder, Runner runner,
            Array<MeasureCallback> measure_callbacks, Optional<Database> database,
            Optional<CostModel> cost_model) final;

  static constexpr const char* _type_key = "meta_schedule.PyTaskScheduler";
  TVM_DECLARE_FINAL_OBJECT_INFO(PyTaskSchedulerNode, TaskSchedulerNode);
};

class TaskScheduler : public runtime::ObjectRef {
 public:
  TVM_DLL static TaskScheduler RoundRobin(PackedFunc logger);
  TVM_DLL static TaskScheduler GradientBased(PackedFunc logger, double alpha, int window_size,
                                             support::LinearCongruentialEngine::TRandState seed);
  TVM_DLL static TaskScheduler PyTaskScheduler(
      PackedFunc logger, PyTaskSchedulerNode::FNextTaskId f_next_task_id,
      PyTaskSchedulerNode::FJoinRunningTask f_join_running_task, PyTaskSchedulerNode::FTune f_tune);
  TVM_DEFINE_MUTABLE_NOTNULLABLE_OBJECT_REF_METHODS(TaskScheduler, ObjectRef, TaskSchedulerNode);
};

}  // namespace meta_schedule
}  // namespace tvm

#endif  // TVM_META_SCHEDULE_TASK_SCHEDULER_H_