STT-tensorflow/tensorflow/lite/kernels/cpu_backend_context.cc
T.J. Alumbaugh cae2f149e1 Add function to check for deprecated paths via weak symbols.
As a first step, define the function and link with CpuBackendContext.

PiperOrigin-RevId: 347446604
Change-Id: Ib7fb6820daa18194dd54081d233c8ae960bda5f1
2020-12-14 12:46:50 -08:00

166 lines
5.4 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>
#ifdef TFLITE_HAVE_CPUINFO
#include "include/cpuinfo.h"
#endif
#include "public/gemmlowp.h"
#include "ruy/context.h" // from @ruy
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/core/macros.h"
#include "tensorflow/lite/external_cpu_backend_context.h"
#include "tensorflow/lite/kernels/internal/compatibility.h"
#include "tensorflow/lite/kernels/op_macros.h"
namespace {
const int kDefaultNumThreadpoolThreads = 1;
} // namespace
namespace tflite {
// Use weak symbols if possible to dispatch to deprecated paths.
#if TFLITE_HAS_ATTRIBUTE_WEAK && !defined(__APPLE__)
extern TFLITE_ATTRIBUTE_WEAK bool UseGemmlowpOnX86();
#endif // defined(TFLITE_HAS_ATTRIBUTE_WEAK) && !(__APPLE__)
// TODO(b/138922878) Enable when Ruy builds on Apple.
#if defined(TFLITE_HAVE_CPUINFO) && !defined(__APPLE__)
CpuBackendContext::CpuInfo::~CpuInfo() {
if (init_status_ == InitStatus::kInitialized) {
cpuinfo_deinitialize();
}
}
bool CpuBackendContext::CpuInfo::EnsureInitialized() {
if (init_status_ == InitStatus::kNotYetAttempted) {
init_status_ = Initialize();
}
return init_status_ == InitStatus::kInitialized;
}
CpuBackendContext::CpuInfo::InitStatus
CpuBackendContext::CpuInfo::Initialize() {
TFLITE_DCHECK_EQ(init_status_, InitStatus::kNotYetAttempted);
if (!cpuinfo_initialize()) {
return InitStatus::kFailed;
}
return InitStatus::kInitialized;
}
bool CpuBackendContext::CpuInfo::Avx2Fma() {
return EnsureInitialized() && cpuinfo_has_x86_avx2() &&
cpuinfo_has_x86_fma3();
}
bool CpuBackendContext::CpuInfo::Avx() {
return EnsureInitialized() && cpuinfo_has_x86_avx();
}
bool CpuBackendContext::CpuInfo::Avx512() {
return EnsureInitialized() && cpuinfo_has_x86_avx512f() &&
cpuinfo_has_x86_avx512dq() && cpuinfo_has_x86_avx512cd() &&
cpuinfo_has_x86_avx512bw() && cpuinfo_has_x86_avx512vl();
}
#else
CpuBackendContext::CpuInfo::~CpuInfo() {}
bool CpuBackendContext::CpuInfo::EnsureInitialized() {
if (init_status_ == InitStatus::kNotYetAttempted) {
init_status_ = InitStatus::kInitialized;
}
TFLITE_DCHECK_EQ(init_status_, InitStatus::kInitialized);
return true;
}
bool CpuBackendContext::CpuInfo::Avx2Fma() { return false; }
bool CpuBackendContext::CpuInfo::Avx() { return false; }
bool CpuBackendContext::CpuInfo::Avx512() { return false; }
#endif // TFLITE_HAVE_CPUINFO
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; }
bool CpuBackendContext::HasAvxOrAbove() {
return cpuinfo_.Avx() || cpuinfo_.Avx2Fma() || cpuinfo_.Avx512();
}
bool CpuBackendContext::PreferGemmlowpOnX86() {
bool use_gemmlowp_on_x86 = false;
#if defined(TFLITE_X86_PLATFORM) && TFLITE_HAS_ATTRIBUTE_WEAK && \
!defined(__APPLE__)
if (::tflite::UseGemmlowpOnX86 != nullptr) {
use_gemmlowp_on_x86 = ::tflite::UseGemmlowpOnX86();
}
#endif // TFLITE_X86_PLATFORM && TFLITE_HAS_ATTRIBUTE_WEAK && !(__APPLE__)
return use_gemmlowp_on_x86 || !HasAvxOrAbove();
}
} // namespace tflite