text: /* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
  
  Licensed 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 under the License.
  ==============================================================================*/
  
  #ifndef TENSORFLOW_LITE_KERNELS_CPU_BACKEND_THREADPOOL_H_
  #define TENSORFLOW_LITE_KERNELS_CPU_BACKEND_THREADPOOL_H_
  
  #include "tensorflow/lite/kernels/cpu_backend_context.h"
  #include "tensorflow/lite/kernels/internal/compatibility.h"
  
  #ifdef TFLITE_WITH_RUY
  #include "tensorflow/lite/experimental/ruy/context.h"
  #include "tensorflow/lite/experimental/ruy/thread_pool.h"
  #else
  #include "public/gemmlowp.h"
  #endif
  
  namespace tflite {
  namespace cpu_backend_threadpool {
  
  #ifdef TFLITE_WITH_RUY
  
  using Task = ruy::Task;
  
  template <typename TaskType>
  void Execute(int tasks_count, TaskType* tasks,
               CpuBackendContext* cpu_backend_context) {
    TFLITE_DCHECK_LE(tasks_count, cpu_backend_context->max_num_threads());
    cpu_backend_context->ruy_context()->workers_pool.Execute(tasks_count, tasks);
  }
  
  #else  // not TFLITE_WITH_RUY
  
  using Task = gemmlowp::Task;
  
  template <typename TaskType>
  void Execute(int tasks_count, TaskType* tasks,
               CpuBackendContext* cpu_backend_context) {
    TFLITE_DCHECK_LE(tasks_count, cpu_backend_context->max_num_threads());
    cpu_backend_context->gemmlowp_context()->workers_pool()->Execute(tasks_count,
                                                                     tasks);
  }
  
  #endif
  
  }  // namespace cpu_backend_threadpool
  }  // namespace tflite
  
  #endif  // TENSORFLOW_LITE_KERNELS_CPU_BACKEND_THREADPOOL_H_
  