STT-tensorflow/tensorflow/lite/kernels/cpu_backend_context.cc
Karim Nosir 2a96849f47 Update source files with used includes.
PiperOrigin-RevId: 316589177
Change-Id: I0aba0ed1cf9ff478e7890fa53a7749bf844bd26d
2020-06-15 18:42:14 -07:00

83 lines
2.8 KiB
C++

/* 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.
==============================================================================*/
#include "tensorflow/lite/kernels/cpu_backend_context.h"
#include <memory>
#include "public/gemmlowp.h"
#include "ruy/context.h" // from @ruy
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/external_cpu_backend_context.h"
#include "tensorflow/lite/kernels/op_macros.h"
namespace {
const int kDefaultNumThreadpoolThreads = 1;
} // namespace
namespace tflite {
CpuBackendContext* CpuBackendContext::GetFromContext(TfLiteContext* context) {
auto* external_context = static_cast<ExternalCpuBackendContext*>(
context->GetExternalContext(context, kTfLiteCpuBackendContext));
if (external_context == nullptr) {
TF_LITE_FATAL(
"ExternalCpuBackendContext isn't properly initialized during TFLite "
"interpreter initialization.");
}
auto* cpu_backend_context = static_cast<CpuBackendContext*>(
external_context->internal_backend_context());
if (cpu_backend_context == nullptr) {
// We do the lazy initialization here for the TfLiteInternalBackendContext
// that's wrapped inside ExternalCpuBackendContext.
cpu_backend_context = new CpuBackendContext();
cpu_backend_context->SetMaxNumThreads(context->recommended_num_threads);
external_context->set_internal_backend_context(
std::unique_ptr<TfLiteInternalBackendContext>(cpu_backend_context));
}
return cpu_backend_context;
}
CpuBackendContext::CpuBackendContext()
: TfLiteInternalBackendContext(),
ruy_context_(new ruy::Context),
gemmlowp_context_(new gemmlowp::GemmContext) {
SetMaxNumThreads(kDefaultNumThreadpoolThreads);
// TODO(b/148289189) Remove when clients have transitioned to runtime flag.
#ifdef TFLITE_WITH_RUY_GEMV
SetUseCaching(true);
#else
SetUseCaching(false);
#endif
}
CpuBackendContext::~CpuBackendContext() {}
void CpuBackendContext::SetMaxNumThreads(int max_num_threads) {
const int target_num_threads =
max_num_threads > -1 ? max_num_threads : kDefaultNumThreadpoolThreads;
max_num_threads_ = target_num_threads;
ruy_context_->set_max_num_threads(target_num_threads);
gemmlowp_context_->set_max_num_threads(target_num_threads);
}
void CpuBackendContext::SetUseCaching(bool flag) { use_caching_ = flag; }
} // namespace tflite