STT-tensorflow/tensorflow/lite/kernels/cpu_backend_threadpool.h
T.J. Alumbaugh 60be0c3c0e Restore functionality of --define=tflite_with_ruy=true
PiperOrigin-RevId: 317677225
Change-Id: If6533fdfeb21f676dd4b77a536b1aca894a03003
2020-06-22 10:49:06 -07:00

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2.0 KiB
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/* 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 "ruy/context.h" // from @ruy
#include "ruy/thread_pool.h" // from @ruy
#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()->mutable_thread_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_