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提交 8d8bbfcf 编写于 作者: 吴 吴承辉
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Merge branch 'minor_fix' into 'master' 

Minor fixes about logging and const tensor interface

See merge request !248
上级 751fd049 9f9dc890
隐藏空白更改
内联 并排
Showing with 65 addition and 52 deletion
mace/core/mace.cc
浏览文件 @ 8d8bbfcf
...@@ -10,7 +10,7 @@ ...@@ -10,7 +10,7 @@
namespace mace { namespace mace {
ConstTensor::ConstTensor(const std::string &name, ConstTensor::ConstTensor(const std::string &name,
unsigned char *data, const unsigned char *data,
const std::vector<int64_t> &dims, const std::vector<int64_t> &dims,
const DataType data_type, const DataType data_type,
uint32_t node_id) : uint32_t node_id) :
...@@ -23,7 +23,7 @@ ConstTensor::ConstTensor(const std::string &name, ...@@ -23,7 +23,7 @@ ConstTensor::ConstTensor(const std::string &name,
node_id_(node_id) {} node_id_(node_id) {}
ConstTensor::ConstTensor(const std::string &name, ConstTensor::ConstTensor(const std::string &name,
unsigned char *data, const unsigned char *data,
const std::vector<int64_t> &dims, const std::vector<int64_t> &dims,
const int data_type, const int data_type,
uint32_t node_id) : uint32_t node_id) :
......
mace/core/net.cc
浏览文件 @ 8d8bbfcf
...@@ -22,7 +22,7 @@ SimpleNet::SimpleNet(const std::shared_ptr<const OperatorRegistry> op_registry, ...@@ -22,7 +22,7 @@ SimpleNet::SimpleNet(const std::shared_ptr<const OperatorRegistry> op_registry,
const NetMode mode) const NetMode mode)
: NetBase(op_registry, net_def, ws, type), : NetBase(op_registry, net_def, ws, type),
device_type_(type) { device_type_(type) {
VLOG(1) << "Constructing SimpleNet " << net_def->name(); MACE_LATENCY_LOGGER(1, "Constructing SimpleNet ", net_def->name());
for (int idx = 0; idx < net_def->op_size(); ++idx) { for (int idx = 0; idx < net_def->op_size(); ++idx) {
const auto &operator_def = net_def->op(idx); const auto &operator_def = net_def->op(idx);
VLOG(3) << "Creating operator " << operator_def.name() << "(" VLOG(3) << "Creating operator " << operator_def.name() << "("
...@@ -41,10 +41,8 @@ bool SimpleNet::Run(RunMetadata *run_metadata) { ...@@ -41,10 +41,8 @@ bool SimpleNet::Run(RunMetadata *run_metadata) {
MACE_LATENCY_LOGGER(1, "Running net"); MACE_LATENCY_LOGGER(1, "Running net");
for (auto iter = operators_.begin(); iter != operators_.end(); ++iter) { for (auto iter = operators_.begin(); iter != operators_.end(); ++iter) {
auto &op = *iter; auto &op = *iter;
VLOG(3) << "Running operator " << op->debug_def().name() << "(" MACE_LATENCY_LOGGER(2, "Running operator ", op->debug_def().name(),
<< op->debug_def().type() << ")."; "(", op->debug_def().type(), ")");
MACE_LATENCY_LOGGER(2, "Running operator ", op->debug_def().name());
bool future_wait = (device_type_ == DeviceType::OPENCL && bool future_wait = (device_type_ == DeviceType::OPENCL &&
(run_metadata != nullptr || (run_metadata != nullptr ||
std::distance(iter, operators_.end()) == 1)); std::distance(iter, operators_.end()) == 1));
......
mace/core/runtime/hexagon/hexagon_control_wrapper.cc
浏览文件 @ 8d8bbfcf
...@@ -64,29 +64,29 @@ bool HexagonControlWrapper::SetupGraph(const NetDef &net_def) { ...@@ -64,29 +64,29 @@ bool HexagonControlWrapper::SetupGraph(const NetDef &net_def) {
std::thread const_thread([&]() { std::thread const_thread([&]() {
std::cout << "thread function\n"; std::cout << "thread function\n";
std::vector<hexagon_nn_const_node> const_node_list; std::vector<hexagon_nn_const_node> const_node_list;
for (const ConstTensor &tensor_proto: net_def.tensors()) { for (const ConstTensor &const_tensor: net_def.tensors()) {
std::vector<int> tensor_shape(tensor_proto.dims().begin(), std::vector<int> tensor_shape(const_tensor.dims().begin(),
tensor_proto.dims().end()); const_tensor.dims().end());
while (tensor_shape.size() < 4) { while (tensor_shape.size() < 4) {
tensor_shape.insert(tensor_shape.begin(), 1); tensor_shape.insert(tensor_shape.begin(), 1);
} }
hexagon_nn_const_node const_node; hexagon_nn_const_node const_node;
const_node.node_id = node_id(tensor_proto.node_id()); const_node.node_id = node_id(const_tensor.node_id());
const_node.tensor.batches = tensor_shape[0]; const_node.tensor.batches = tensor_shape[0];
const_node.tensor.height = tensor_shape[1]; const_node.tensor.height = tensor_shape[1];
const_node.tensor.width = tensor_shape[2]; const_node.tensor.width = tensor_shape[2];
const_node.tensor.depth = tensor_shape[3]; const_node.tensor.depth = tensor_shape[3];
if (tensor_proto.data_type() == DataType::DT_INT32 if (const_tensor.data_type() == DataType::DT_INT32
&& tensor_proto.data_size() == 0) { && const_tensor.data_size() == 0) {
const_node.tensor.data = NULL; const_node.tensor.data = NULL;
const_node.tensor.dataLen = 0; const_node.tensor.dataLen = 0;
} else { } else {
const_node.tensor.data = const_node.tensor.data =
const_cast<unsigned char *>(tensor_proto.data()); const_cast<unsigned char *>(const_tensor.data());
const_node.tensor.dataLen = const_node.tensor.dataLen =
tensor_proto.data_size() * GetEnumTypeSize(tensor_proto.data_type()); const_tensor.data_size() * GetEnumTypeSize(const_tensor.data_type());
} }
const_node_list.push_back(const_node); const_node_list.push_back(const_node);
// 255 is magic number: why fastrpc limits sequence length to that? // 255 is magic number: why fastrpc limits sequence length to that?
......
mace/core/serializer.cc
浏览文件 @ 8d8bbfcf
...@@ -12,56 +12,64 @@ std::unique_ptr<ConstTensor> Serializer::Serialize(const Tensor &tensor, ...@@ -12,56 +12,64 @@ std::unique_ptr<ConstTensor> Serializer::Serialize(const Tensor &tensor,
return nullptr; return nullptr;
} }
std::unique_ptr<Tensor> Serializer::Deserialize(const ConstTensor &proto, std::unique_ptr<Tensor> Serializer::Deserialize(const ConstTensor &const_tensor,
DeviceType type) { DeviceType type) {
std::unique_ptr<Tensor> tensor( std::unique_ptr<Tensor> tensor(
new Tensor(GetDeviceAllocator(type), proto.data_type())); new Tensor(GetDeviceAllocator(type), const_tensor.data_type()));
std::vector<index_t> dims; std::vector<index_t> dims;
for (const index_t d : proto.dims()) { for (const index_t d : const_tensor.dims()) {
dims.push_back(d); dims.push_back(d);
} }
tensor->Resize(dims); tensor->Resize(dims);
switch (proto.data_type()) { switch (const_tensor.data_type()) {
case DT_HALF: case DT_HALF:
tensor->Copy<half>(reinterpret_cast<const half*>(proto.data()), tensor->Copy<half>(reinterpret_cast<const half *>(const_tensor.data()),
proto.data_size()); const_tensor.data_size());
break; break;
case DT_FLOAT: case DT_FLOAT:
tensor->Copy<float>(reinterpret_cast<const float *>(proto.data()), tensor->Copy<float>(reinterpret_cast<const float *>(const_tensor.data()),
proto.data_size()); const_tensor.data_size());
break; break;
case DT_DOUBLE: case DT_DOUBLE:
tensor->Copy<double>(reinterpret_cast<const double *>(proto.data()), tensor->Copy<double>(
proto.data_size()); reinterpret_cast<const double *>(const_tensor.data()),
const_tensor.data_size());
break; break;
case DT_INT32: case DT_INT32:
tensor->Copy<int32_t>(reinterpret_cast<const int32_t *>(proto.data()), tensor->Copy<int32_t>(
proto.data_size()); reinterpret_cast<const int32_t *>(const_tensor.data()),
const_tensor.data_size());
break; break;
case DT_INT64: case DT_INT64:
tensor->Copy<int64_t>(reinterpret_cast<const int64_t *>(proto.data()), tensor->Copy<int64_t>(
proto.data_size()); reinterpret_cast<const int64_t *>(const_tensor.data()),
const_tensor.data_size());
break; break;
case DT_UINT8: case DT_UINT8:
tensor->Copy<uint8_t>(reinterpret_cast<const uint8_t *>(proto.data()), tensor->Copy<uint8_t>(
proto.data_size()); reinterpret_cast<const uint8_t *>(const_tensor.data()),
const_tensor.data_size());
break; break;
case DT_INT16: case DT_INT16:
tensor->CopyWithCast<int32_t, uint16_t>( tensor->CopyWithCast<int32_t, uint16_t>(
reinterpret_cast<const int32_t *>(proto.data()), proto.data_size()); reinterpret_cast<const int32_t *>(const_tensor.data()),
const_tensor.data_size());
break; break;
case DT_INT8: case DT_INT8:
tensor->CopyWithCast<int32_t, int8_t>( tensor->CopyWithCast<int32_t, int8_t>(
reinterpret_cast<const int32_t *>(proto.data()), proto.data_size()); reinterpret_cast<const int32_t *>(const_tensor.data()),
const_tensor.data_size());
break; break;
case DT_UINT16: case DT_UINT16:
tensor->CopyWithCast<int32_t, int16_t>( tensor->CopyWithCast<int32_t, int16_t>(
reinterpret_cast<const int32_t *>(proto.data()), proto.data_size()); reinterpret_cast<const int32_t *>(const_tensor.data()),
const_tensor.data_size());
break; break;
case DT_BOOL: case DT_BOOL:
tensor->CopyWithCast<int32_t, bool>( tensor->CopyWithCast<int32_t, bool>(
reinterpret_cast<const int32_t *>(proto.data()), proto.data_size()); reinterpret_cast<const int32_t *>(const_tensor.data()),
const_tensor.data_size());
break; break;
default: default:
MACE_NOT_IMPLEMENTED; MACE_NOT_IMPLEMENTED;
......
mace/core/serializer.h
浏览文件 @ 8d8bbfcf
...@@ -15,9 +15,11 @@ class Serializer { ...@@ -15,9 +15,11 @@ class Serializer {
Serializer() {} Serializer() {}
~Serializer() {} ~Serializer() {}
std::unique_ptr<ConstTensor> Serialize(const Tensor &tensor, const std::string &name); std::unique_ptr<ConstTensor> Serialize(const Tensor &tensor,
const std::string &name);
std::unique_ptr<Tensor> Deserialize(const ConstTensor &proto, DeviceType type); std::unique_ptr<Tensor> Deserialize(const ConstTensor &const_tensor,
DeviceType type);
DISABLE_COPY_AND_ASSIGN(Serializer); DISABLE_COPY_AND_ASSIGN(Serializer);
}; };
......
mace/core/tensor.h
浏览文件 @ 8d8bbfcf
...@@ -324,12 +324,12 @@ class Tensor { ...@@ -324,12 +324,12 @@ class Tensor {
} }
} }
} }
MappingGuard(MappingGuard &&other) { MappingGuard(MappingGuard &&other) {
tensor_ = other.tensor_; tensor_ = other.tensor_;
other.tensor_ = nullptr; other.tensor_ = nullptr;
} }
MappingGuard(const MappingGuard &other) = delete;
MappingGuard & operator = (const MappingGuard &other) = delete;
~MappingGuard() { ~MappingGuard() {
if (tensor_ != nullptr) tensor_->Unmap(); if (tensor_ != nullptr) tensor_->Unmap();
} }
...@@ -339,6 +339,8 @@ class Tensor { ...@@ -339,6 +339,8 @@ class Tensor {
private: private:
const Tensor *tensor_; const Tensor *tensor_;
std::vector<size_t> mapped_image_pitch_; std::vector<size_t> mapped_image_pitch_;
DISABLE_COPY_AND_ASSIGN(MappingGuard);
}; };
private: private:
......
mace/core/workspace.cc
浏览文件 @ 8d8bbfcf
...@@ -72,15 +72,15 @@ Tensor *Workspace::GetTensor(const std::string &name) { ...@@ -72,15 +72,15 @@ Tensor *Workspace::GetTensor(const std::string &name) {
void Workspace::LoadModelTensor(const NetDef &net_def, DeviceType type) { void Workspace::LoadModelTensor(const NetDef &net_def, DeviceType type) {
MACE_LATENCY_LOGGER(1, "Load model tensors"); MACE_LATENCY_LOGGER(1, "Load model tensors");
Serializer serializer; Serializer serializer;
for (auto &tensor_proto : net_def.tensors()) { for (auto &const_tensor : net_def.tensors()) {
MACE_LATENCY_LOGGER(2, "Load tensor ", tensor_proto.name()); MACE_LATENCY_LOGGER(2, "Load tensor ", const_tensor.name());
VLOG(3) << "Load tensor: " << tensor_proto.name() VLOG(3) << "Tensor name: " << const_tensor.name()
<< ", with data type: " << tensor_proto.data_type() << ", data type: " << const_tensor.data_type()
<< ", has shape: " << ", shape: "
<< MakeString(std::vector<index_t>(tensor_proto.dims().begin(), << MakeString(std::vector<index_t>(const_tensor.dims().begin(),
tensor_proto.dims().end())); const_tensor.dims().end()));
tensor_map_[tensor_proto.name()] = tensor_map_[const_tensor.name()] =
serializer.Deserialize(tensor_proto, type); serializer.Deserialize(const_tensor, type);
} }
if (type == DeviceType::OPENCL) { if (type == DeviceType::OPENCL) {
CreateImageOutputTensor(net_def); CreateImageOutputTensor(net_def);
......
mace/public/mace.h
浏览文件 @ 8d8bbfcf
...@@ -73,12 +73,12 @@ enum DataType { ...@@ -73,12 +73,12 @@ enum DataType {
class ConstTensor { class ConstTensor {
public: public:
ConstTensor(const std::string &name, ConstTensor(const std::string &name,
unsigned char *data, const unsigned char *data,
const std::vector<int64_t> &dims, const std::vector<int64_t> &dims,
const DataType data_type = DT_FLOAT, const DataType data_type = DT_FLOAT,
uint32_t node_id = 0); uint32_t node_id = 0);
ConstTensor(const std::string &name, ConstTensor(const std::string &name,
unsigned char *data, const unsigned char *data,
const std::vector<int64_t> &dims, const std::vector<int64_t> &dims,
const int data_type, const int data_type,
uint32_t node_id = 0); uint32_t node_id = 0);
......
mace/utils/logging.h
浏览文件 @ 8d8bbfcf
...@@ -113,6 +113,7 @@ class LatencyLogger { ...@@ -113,6 +113,7 @@ class LatencyLogger {
: vlog_level_(vlog_level), message_(message) { : vlog_level_(vlog_level), message_(message) {
if (VLOG_IS_ON(vlog_level_)) { if (VLOG_IS_ON(vlog_level_)) {
start_micros_ = NowMicros(); start_micros_ = NowMicros();
VLOG(vlog_level_) << message_ << " started";
} }
} }
~LatencyLogger() { ~LatencyLogger() {
......
tools/export_lib.sh
浏览文件 @ 8d8bbfcf
...@@ -161,8 +161,10 @@ rm -rf ${EXPORT_LIB_DIR} ...@@ -161,8 +161,10 @@ rm -rf ${EXPORT_LIB_DIR}
mkdir -p ${EXPORT_LIB_DIR} mkdir -p ${EXPORT_LIB_DIR}
cp ${MACE_SOURCE_DIR}/mace/public/*.h ${EXPORT_INCLUDE_DIR}/mace/public/ || exit 1 cp ${MACE_SOURCE_DIR}/mace/public/*.h ${EXPORT_INCLUDE_DIR}/mace/public/ || exit 1
# utils is noti part of public API # utils is not part of public API
cp ${MACE_SOURCE_DIR}/mace/utils/*.h ${EXPORT_INCLUDE_DIR}/mace/utils/ || exit 1 cp ${MACE_SOURCE_DIR}/mace/utils/env_time.h ${EXPORT_INCLUDE_DIR}/mace/utils/ || exit 1
cp ${MACE_SOURCE_DIR}/mace/utils/logging.h ${EXPORT_INCLUDE_DIR}/mace/utils/ || exit 1
cp ${MACE_SOURCE_DIR}/mace/utils/string_util.h ${EXPORT_INCLUDE_DIR}/mace/utils/ || exit 1
cp ${LIBMACE_TEMP_DIR}/libmace.a ${LIBMACE_TEMP_DIR}/libmace_dev.a ${LIBMACE_TEMP_DIR}/libmace_prod.a ${EXPORT_LIB_DIR}/ || exit 1 cp ${LIBMACE_TEMP_DIR}/libmace.a ${LIBMACE_TEMP_DIR}/libmace_dev.a ${LIBMACE_TEMP_DIR}/libmace_prod.a ${EXPORT_LIB_DIR}/ || exit 1
echo "Step 6: Remove temporary file" echo "Step 6: Remove temporary file"
......
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