experiments/STT-tensorflow
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Refactor the delegate and delegate kernel sources to allow usage in the linter.

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PiperOrigin-RevId: 290600182
Change-Id: Ibbd864013288a7623229076dc8c22eb220178af0
This commit is contained in:
Stefano Galarraga 2020-01-20 05:14:02 -08:00 committed by TensorFlower Gardener
parent a5bcec9a63
commit af04b99a42
2 changed files with 52 additions and 33 deletions
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31
tensorflow/lite/delegates/nnapi/nnapi_delegate.cc
View File

@ -31,6 +31,7 @@ limitations under the License.
#ifdef __ANDROID__
#include <sys/system_properties.h>
#endif
#if defined __ANDROID__ || defined __unix__
#define TFLITE_NNAPI_ALLOW_MMAP_SHARING
#include <sys/mman.h>
@ -470,6 +471,36 @@ TfLiteStatus GetTargetDevices(TfLiteContext* context, TfLiteDelegate* delegate,
namespace delegate {
namespace nnapi {
#ifdef TFLITE_NNAPI_ALLOW_MMAP_SHARING
NNMemory::NNMemory(const NnApi* nnapi, const char* name, size_t size) {
if (name && size > 0) {
nnapi_ = nnapi;
byte_size_ = size;
fd_ = nnapi_->ASharedMemory_create(name, size);
data_ptr_ = reinterpret_cast<uint8_t*>(
mmap(nullptr, size, PROT_READ | PROT_WRITE, MAP_SHARED, fd_, 0));
nnapi_->ANeuralNetworksMemory_createFromFd(size, PROT_READ | PROT_WRITE,
fd_, 0, &nn_memory_handle_);
}
}
#else
NNMemory::NNMemory(const NnApi* /*nnapi*/, const char* /*name*/,
size_t /*size*/)
: nnapi_(nullptr) {}
#endif
NNMemory::~NNMemory() {
#ifdef TFLITE_NNAPI_ALLOW_MMAP_SHARING
if (data_ptr_) {
munmap(data_ptr_, byte_size_);
}
if (nn_memory_handle_) {
nnapi_->ANeuralNetworksMemory_free(nn_memory_handle_);
}
if (fd_ > 0) close(fd_);
#endif
}
// RAII NN API Execution Destructor for use with std::unique_ptr
struct NNFreeExecution {
void operator()(ANeuralNetworksExecution* execution) {

54
tensorflow/lite/delegates/nnapi/nnapi_delegate_kernel.h
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@ -113,58 +113,42 @@ struct NNAPIOpMappingArgs {
};
// RAII NN API Model Destructor for use with std::unique_ptr
struct NNFreeModel {
class NNFreeModel {
public:
explicit NNFreeModel(const NnApi* nnapi) : nnapi_(nnapi) {}
void operator()(ANeuralNetworksModel* model) {
NnApiImplementation()->ANeuralNetworksModel_free(model);
nnapi_->ANeuralNetworksModel_free(model);
}
private:
const NnApi* nnapi_;
};
// RAII NN API Compilation Destructor for use with std::unique_ptr
struct NNFreeCompilation {
class NNFreeCompilation {
public:
explicit NNFreeCompilation(const NnApi* nnapi) : nnapi_(nnapi) {}
void operator()(ANeuralNetworksCompilation* model) {
NnApiImplementation()->ANeuralNetworksCompilation_free(model);
nnapi_->ANeuralNetworksCompilation_free(model);
}
private:
const NnApi* nnapi_;
};
// Manage NNAPI shared memory handle
class NNMemory {
public:
#ifdef TFLITE_NNAPI_ALLOW_MMAP_SHARING
NNMemory(const NnApi* nnapi, const char* name, size_t size) {
if (name && size > 0) {
nnapi_ = nnapi;
byte_size_ = size;
fd_ = nnapi_->ASharedMemory_create(name, size);
data_ptr_ = reinterpret_cast<uint8_t*>(
mmap(nullptr, size, PROT_READ | PROT_WRITE, MAP_SHARED, fd_, 0));
nnapi_->ANeuralNetworksMemory_createFromFd(size, PROT_READ | PROT_WRITE,
fd_, 0, &nn_memory_handle_);
}
}
#else
NNMemory(const NnApi* /*nnapi*/, const char* /*name*/, size_t /*size*/) {}
#endif
NNMemory(const NnApi* nnapi, const char* name, size_t size);
~NNMemory() {
#ifdef TFLITE_NNAPI_ALLOW_MMAP_SHARING
if (data_ptr_) {
munmap(data_ptr_, byte_size_);
}
if (nn_memory_handle_) {
nnapi_->ANeuralNetworksMemory_free(nn_memory_handle_);
}
if (fd_ > 0) close(fd_);
#endif
}
~NNMemory();
ANeuralNetworksMemory* get_handle() { return nn_memory_handle_; }
uint8_t* get_data_ptr() { return data_ptr_; }
private:
#ifdef TFLITE_NNAPI_ALLOW_MMAP_SHARING
const NnApi* nnapi_;
int fd_ = 0;
size_t byte_size_ = 0;
#endif
uint8_t* data_ptr_ = nullptr;
ANeuralNetworksMemory* nn_memory_handle_ = nullptr;
};
@ -239,7 +223,11 @@ struct NNAPIValidationFailure {
// The kernel that represents the node sub set of TF Lite being run on NN API.
class NNAPIDelegateKernel {
public:
NNAPIDelegateKernel() { nnapi_ = NnApiImplementation(); }
explicit NNAPIDelegateKernel(const NnApi* nnapi)
: nnapi_(nnapi),
nn_model_(nullptr, NNFreeModel(nnapi_)),
nn_compilation_(nullptr, NNFreeCompilation(nnapi_)) {}
NNAPIDelegateKernel() : NNAPIDelegateKernel(NnApiImplementation()) {}
~NNAPIDelegateKernel() {
for (auto content : allocation_memory_mapping_) {
nnapi_->ANeuralNetworksMemory_free(content.second);