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未验证 提交 2aaa417e 编写于 作者: W Wilber 提交者： GitHub
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[cherry-pick] [Inference] Support NNAdapter and ascend310 (#35882)

上级 c0535200
隐藏空白更改
内联 并排
Showing with 310 addition and 9 deletion
cmake/external/lite.cmake
浏览文件 @ 2aaa417e
......@@ -35,6 +35,14 @@ if (LITE_WITH_XPU)
ENDIF()
endif()
if (LITE_WITH_NNADAPTER)
add_definitions(-DLITE_SUBGRAPH_WITH_NNADAPTER)
if (NNADAPTER_WITH_HUAWEI_ASCEND_NPU)
add_definitions(-DLITE_SUBGRAPH_WITH_NPU)
set(NPU_SDK_ROOT "/usr/local/Ascend/ascend-toolkit/latest" CACHE STRING "default NPU SDK ROOT")
endif()
endif()
if (NOT LITE_SOURCE_DIR OR NOT LITE_BINARY_DIR)
include(ExternalProject)
set(LITE_PROJECT extern_lite)
......@@ -67,6 +75,9 @@ if (NOT LITE_SOURCE_DIR OR NOT LITE_BINARY_DIR)
-DLITE_WITH_XPU=${LITE_WITH_XPU}
-DXPU_SDK_URL=${XPU_BASE_URL}
-DXPU_SDK_ENV=${XPU_SDK_ENV}
-DLITE_WITH_NNADAPTER=${LITE_WITH_NNADAPTER}
-DNNADAPTER_WITH_HUAWEI_ASCEND_NPU=${NNADAPTER_WITH_HUAWEI_ASCEND_NPU}
-DNNADAPTER_HUAWEI_ASCEND_NPU_SDK_ROOT=${NPU_SDK_ROOT}
-DLITE_WITH_CODE_META_INFO=OFF
-DLITE_WITH_ARM=ON)
ExternalProject_Add(
......@@ -110,6 +121,9 @@ if (NOT LITE_SOURCE_DIR OR NOT LITE_BINARY_DIR)
-DLITE_WITH_XPU=${LITE_WITH_XPU}
-DXPU_SDK_URL=${XPU_BASE_URL}
-DXPU_SDK_ENV=${XPU_SDK_ENV}
-DLITE_WITH_NNADAPTER=${LITE_WITH_NNADAPTER}
-DNNADAPTER_WITH_HUAWEI_ASCEND_NPU=${NNADAPTER_WITH_HUAWEI_ASCEND_NPU}
-DNNADAPTER_HUAWEI_ASCEND_NPU_SDK_ROOT=${NPU_SDK_ROOT}
-DLITE_WITH_CODE_META_INFO=OFF
-DLITE_WITH_ARM=OFF)
......@@ -120,6 +134,7 @@ if (NOT LITE_SOURCE_DIR OR NOT LITE_BINARY_DIR)
GIT_TAG ${LITE_GIT_TAG}
PREFIX ${LITE_SOURCES_DIR}
UPDATE_COMMAND ""
PATCH_COMMAND sed -i "s?NNadapter_bridges_path = os.path.abspath('..')+\"\/lite\/kernels\/nnadapter\/bridges\/paddle_use_bridges.h\"?NNadapter_bridges_path = os.path.abspath(\'..\')+\"\/extern_lite\/lite\/kernels\/nnadapter\/bridges\/paddle_use_bridges.h\"?" ${LITE_SOURCES_DIR}/src/extern_lite//lite/tools/cmake_tools/record_supported_kernel_op.py && sed -i "/general::ssa::ConvertToSSA(cpp_prog)$<SEMICOLON>/d" ${LITE_SOURCES_DIR}/src/extern_lite/lite/model_parser/model_parser.cc
BUILD_COMMAND ${LITE_BUILD_COMMAND}
INSTALL_COMMAND ""
CMAKE_ARGS -DCMAKE_CXX_COMPILER=${CMAKE_CXX_COMPILER}
......@@ -146,6 +161,11 @@ endif()
if (WITH_ARM)
if(LITE_WITH_XPU)
set(LITE_OUTPUT_BIN_DIR inference_lite_lib.armlinux.armv8.xpu)
elseif(LITE_WITH_NNADAPTER)
message("Enable LITE_WITH_NNADAPTER")
if (NNADAPTER_WITH_HUAWEI_ASCEND_NPU)
set(LITE_OUTPUT_BIN_DIR inference_lite_lib.armlinux.armv8.nnadapter)
endif()
else()
set(LITE_OUTPUT_BIN_DIR inference_lite_lib.armlinux.armv8)
endif()
......@@ -174,5 +194,16 @@ endfunction()
external_lite_libs(lite_full_static ${LITE_BINARY_DIR}/${LITE_OUTPUT_BIN_DIR}/cxx/lib/libpaddle_full_api_shared.so)
set(LITE_SHARED_LIB ${LITE_BINARY_DIR}/${LITE_OUTPUT_BIN_DIR}/cxx/lib/libpaddle_full_api_shared.so)
if (LITE_WITH_NNADAPTER)
set(LITE_NNADAPTER_LIB ${LITE_BINARY_DIR}/${LITE_OUTPUT_BIN_DIR}/cxx/lib/libnnadapter.so)
if (NNADAPTER_WITH_HUAWEI_ASCEND_NPU)
external_lite_libs(lite_nnadapter ${LITE_BINARY_DIR}/${LITE_OUTPUT_BIN_DIR}/cxx/lib/libnnadapter.so ${LITE_BINARY_DIR}/${LITE_OUTPUT_BIN_DIR}/cxx/lib/libnnadapter_driver_huawei_ascend_npu.so)
set(LITE_DEPS lite_full_static lite_nnadapter)
set(LITE_NNADAPTER_NPU_LIB ${LITE_BINARY_DIR}/${LITE_OUTPUT_BIN_DIR}/cxx/lib/libnnadapter_driver_huawei_ascend_npu.so)
endif()
else()
set(LITE_DEPS lite_full_static)
endif()
add_definitions(-DPADDLE_WITH_LITE)
add_definitions(-DLITE_WITH_LOG)
paddle/fluid/inference/analysis/argument.h
浏览文件 @ 2aaa417e
......@@ -239,6 +239,22 @@ struct Argument {
DECL_ARGUMENT_FIELD(xpu_precision, XpuPrecision, std::string);
DECL_ARGUMENT_FIELD(xpu_adaptive_seqlen, XpuAdaptiveSeqlen, bool);
DECL_ARGUMENT_FIELD(use_nnadapter, UseNNAdapter, bool);
DECL_ARGUMENT_FIELD(nnadapter_model_cache_dir, NNAdapterModelCacheDir,
std::string);
DECL_ARGUMENT_FIELD(nnadapter_device_names, NNAdapterDeviceNames,
std::vector<std::string>);
DECL_ARGUMENT_FIELD(nnadapter_context_properties, NNAdapterContextProperties,
std::string);
DECL_ARGUMENT_FIELD(nnadapter_subgraph_partition_config_buffer,
NNAdapterSubgraphPartitionConfigBuffer, std::string);
DECL_ARGUMENT_FIELD(nnadapter_subgraph_partition_config_path,
NNAdapterSubgraphPartitionConfigPath, std::string);
DECL_ARGUMENT_FIELD(nnadapter_model_cache_token, NNAdapterModelCacheToken,
std::vector<std::string>);
DECL_ARGUMENT_FIELD(nnadapter_model_cache_buffer, NNAdapterModelCacheBuffer,
std::vector<std::vector<char>>);
// Memory optimized related.
DECL_ARGUMENT_FIELD(enable_memory_optim, EnableMemoryOptim, bool);
......
paddle/fluid/inference/analysis/ir_pass_manager.cc
浏览文件 @ 2aaa417e
......@@ -202,6 +202,27 @@ void IRPassManager::CreatePasses(Argument *argument,
new std::string(argument->xpu_autotune_file()));
pass->Set("precision", new std::string(argument->xpu_precision()));
pass->Set("adaptive_seqlen", new bool(argument->xpu_adaptive_seqlen()));
// NNAdapter Related
pass->Set("use_nnadapter", new bool(argument->use_nnadapter()));
pass->Set("nnadapter_model_cache_dir",
new std::string(argument->nnadapter_model_cache_dir()));
pass->Set(
"nnadapter_device_names",
new std::vector<std::string>(argument->nnadapter_device_names()));
pass->Set("nnadapter_context_properties",
new std::string(argument->nnadapter_context_properties()));
pass->Set("nnadapter_subgraph_partition_config_buffer",
new std::string(
argument->nnadapter_subgraph_partition_config_buffer()));
pass->Set("nnadapter_subgraph_partition_config_path",
new std::string(
argument->nnadapter_subgraph_partition_config_path()));
pass->Set("nnadapter_model_cache_buffer",
new std::vector<std::vector<char>>(
argument->nnadapter_model_cache_buffer()));
pass->Set("nnadapter_model_cache_token",
new std::vector<std::string>(
argument->nnadapter_model_cache_token()));
}
disable_logs_ = argument->disable_logs();
if (pass_name == "fc_fuse_pass") {
......
paddle/fluid/inference/analysis/ir_passes/lite_subgraph_pass.cc
浏览文件 @ 2aaa417e
......@@ -250,12 +250,30 @@ void LiteSubgraphPass::SetUpEngine(
std::string autotune_file = Get<std::string>("autotune_file");
std::string precision = Get<std::string>("precision");
bool adaptive_seqlen = Get<bool>("adaptive_seqlen");
// NNAdapter Related
bool use_nnadapter = Get<bool>("use_nnadapter");
std::string nnadapter_model_cache_dir =
Get<std::string>("nnadapter_model_cache_dir");
auto nnadapter_device_names =
Get<std::vector<std::string>>("nnadapter_device_names");
std::string nnadapter_context_properties =
Get<std::string>("nnadapter_context_properties");
std::string nnadapter_subgraph_partition_config_buffer =
Get<std::string>("nnadapter_subgraph_partition_config_buffer");
std::string nnadapter_subgraph_partition_config_path =
Get<std::string>("nnadapter_subgraph_partition_config_path");
auto nnadapter_model_cache_buffer =
Get<std::vector<std::vector<char>>>("nnadapter_model_cache_buffer");
auto nnadapter_model_cache_token =
Get<std::vector<std::string>>("nnadapter_model_cache_token");
lite_api::TargetType target_type;
if (use_gpu) {
target_type = TARGET(kCUDA);
} else if (use_xpu) {
target_type = TARGET(kXPU);
} else if (use_nnadapter) {
target_type = TARGET(kNNAdapter);
} else {
#ifdef PADDLE_WITH_ARM
target_type = TARGET(kARM);
......@@ -292,6 +310,17 @@ void LiteSubgraphPass::SetUpEngine(
config.autotune_file = autotune_file;
config.precision = precision;
config.adaptive_seqlen = adaptive_seqlen;
// NNAdapter Related
config.nnadapter_model_cache_dir = nnadapter_model_cache_dir;
config.nnadapter_device_names = nnadapter_device_names;
config.nnadapter_context_properties = nnadapter_context_properties;
config.nnadapter_subgraph_partition_config_buffer =
nnadapter_subgraph_partition_config_buffer;
config.nnadapter_subgraph_partition_config_path =
nnadapter_subgraph_partition_config_path;
config.nnadapter_model_cache_buffer = nnadapter_model_cache_buffer;
config.nnadapter_model_cache_token = nnadapter_model_cache_token;
if (dump_model) {
lite::StrToBinaryFile("./model.bin", config.model);
lite::StrToBinaryFile("./param.bin", config.param);
......
paddle/fluid/inference/api/analysis_config.cc
浏览文件 @ 2aaa417e
......@@ -207,6 +207,7 @@ AnalysisConfig::AnalysisConfig(const AnalysisConfig &other) {
// NPU related.
CP_MEMBER(use_npu_);
CP_MEMBER(npu_device_id_);
CP_MEMBER(nnadapter_config_);
// profile related.
CP_MEMBER(with_profile_);
......@@ -554,7 +555,7 @@ void AnalysisConfig::Update() {
}
if (use_npu_) {
#ifdef PADDLE_WITH_ASCEND_CL
#if defined(PADDLE_WITH_ASCEND_CL) || defined(LITE_SUBGRAPH_WITH_NPU)
PADDLE_ENFORCE_EQ(use_gpu_, false,
platform::errors::Unavailable(
"Currently, NPU and GPU cannot be enabled in the "
......@@ -833,6 +834,61 @@ std::string AnalysisConfig::Summary() {
return os.PrintTable();
}
LiteNNAdapterConfig &LiteNNAdapterConfig::SetDeviceNames(
const std::vector<std::string> &names) {
nnadapter_device_names = names;
return *this;
}
LiteNNAdapterConfig &LiteNNAdapterConfig::SetContextProperties(
const std::string &properties) {
nnadapter_context_properties = properties;
return *this;
}
LiteNNAdapterConfig &LiteNNAdapterConfig::SetModelCacheDir(
const std::string &dir) {
nnadapter_model_cache_dir = dir;
return *this;
}
LiteNNAdapterConfig &LiteNNAdapterConfig::SetModelCacheBuffers(
const std::string &model_cache_token,
const std::vector<char> &model_cache_buffer) {
PADDLE_ENFORCE_EQ(model_cache_token.empty(), false,
platform::errors::InvalidArgument(
"model_cache_token should not be empty."));
PADDLE_ENFORCE_EQ(model_cache_buffer.empty(), false,
platform::errors::InvalidArgument(
"model_cache_buffer should not be empty."));
PADDLE_ENFORCE_EQ(nnadapter_model_cache_buffers.count(model_cache_token),
false, platform::errors::InvalidArgument(
"model_cache_token has already been set."));
nnadapter_model_cache_buffers[model_cache_token] = model_cache_buffer;
return *this;
}
LiteNNAdapterConfig &LiteNNAdapterConfig::SetSubgraphPartitionConfigPath(
const std::string &path) {
nnadapter_subgraph_partition_config_path = path;
return *this;
}
LiteNNAdapterConfig &LiteNNAdapterConfig::SetSubgraphPartitionConfigBuffer(
const std::string &buffer) {
nnadapter_subgraph_partition_config_buffer = buffer;
return *this;
}
LiteNNAdapterConfig &LiteNNAdapterConfig::Enable() {
use_nnadapter = true;
return *this;
}
LiteNNAdapterConfig &LiteNNAdapterConfig::Disable() {
use_nnadapter = false;
return *this;
}
void AnalysisConfig::CollectShapeRangeInfo(
const std::string &shape_range_info_path) {
LOG(INFO) << "In CollectShapeInfo mode, we will disable optimizations and "
......
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @ 2aaa417e
......@@ -276,6 +276,22 @@ bool AnalysisPredictor::CreateExecutor() {
"You tried to use NPU forward propagation, but Paddle was not compiled "
"with WITH_ASCEND_CL."));
#endif
} else if (config_.NNAdapter().use_nnadapter) {
if (config_.lite_engine_enabled()) {
place_ = paddle::platform::CPUPlace();
#ifndef LITE_SUBGRAPH_WITH_NNADAPTER
PADDLE_THROW(
platform::errors::Unavailable("You tried to use an NNAdapter lite "
"engine, but Paddle was not compiled "
"with it."));
#endif // LITE_SUBGRAPH_WITH_NNADAPTER
} else {
PADDLE_THROW(
platform::errors::Unavailable("You tried to use NNadapter forward "
"propagation (inference without lite "
"engine), but Paddle was not compiled "
"with LITE_WITH_NNADAPTER."));
}
} else {
place_ = paddle::platform::CPUPlace();
}
......@@ -601,6 +617,26 @@ void AnalysisPredictor::PrepareArgument() {
argument_.SetXpuAutotuneFile(config_.xpu_autotune_file_);
argument_.SetXpuPrecision(config_.xpu_precision_);
argument_.SetXpuAdaptiveSeqlen(config_.xpu_adaptive_seqlen_);
// NNAdapter related
argument_.SetUseNNAdapter(config_.NNAdapter().use_nnadapter);
argument_.SetNNAdapterDeviceNames(
config_.NNAdapter().nnadapter_device_names);
argument_.SetNNAdapterContextProperties(
config_.NNAdapter().nnadapter_context_properties);
argument_.SetNNAdapterModelCacheDir(
config_.NNAdapter().nnadapter_model_cache_dir);
argument_.SetNNAdapterSubgraphPartitionConfigBuffer(
config_.NNAdapter().nnadapter_subgraph_partition_config_buffer);
argument_.SetNNAdapterSubgraphPartitionConfigPath(
config_.NNAdapter().nnadapter_subgraph_partition_config_path);
std::vector<std::string> buffer_keys;
std::vector<std::vector<char>> buffer_vals;
for (auto it : config_.NNAdapter().nnadapter_model_cache_buffers) {
buffer_keys.emplace_back(it.first);
buffer_vals.emplace_back(it.second);
}
argument_.SetNNAdapterModelCacheToken(buffer_keys);
argument_.SetNNAdapterModelCacheBuffer(buffer_vals);
LOG(INFO) << "Lite subgraph engine is enabled";
}
......
paddle/fluid/inference/api/analysis_predictor_tester.cc
浏览文件 @ 2aaa417e
......@@ -61,6 +61,26 @@ TEST(AnalysisPredictor, analysis_off) {
ASSERT_TRUE(predictor->Run(inputs, &outputs));
}
#ifndef WIN32
TEST(AnalysisPredictor, lite_nn_adapter_npu) {
AnalysisConfig config;
config.SetModel(FLAGS_dirname);
config.EnableLiteEngine();
config.NNAdapter()
.Disable()
.Enable()
.SetDeviceNames({"huawei_ascend_npu"})
.SetContextProperties("HUAWEI_ASCEND_NPU_SELECTED_DEVICE_IDS=0")
.SetModelCacheDir("cache_dirr")
.SetSubgraphPartitionConfigPath("")
.SetModelCacheBuffers("c1", {'c'});
#ifndef LITE_SUBGRAPH_WITH_NNADAPTER
EXPECT_THROW(CreatePaddlePredictor<AnalysisConfig>(config),
paddle::platform::EnforceNotMet);
#endif
}
#endif
TEST(AnalysisPredictor, analysis_on) {
AnalysisConfig config;
config.SetModel(FLAGS_dirname);
......
paddle/fluid/inference/api/paddle_analysis_config.h
浏览文件 @ 2aaa417e
......@@ -48,6 +48,34 @@ namespace paddle {
class AnalysisPredictor;
struct MkldnnQuantizerConfig;
struct LiteNNAdapterConfig {
bool use_nnadapter{false};
std::string nnadapter_model_cache_dir;
std::map<std::string, std::vector<char>> nnadapter_model_cache_buffers;
std::vector<std::string> nnadapter_device_names;
std::string nnadapter_context_properties;
std::string nnadapter_subgraph_partition_config_path;
std::string nnadapter_subgraph_partition_config_buffer;
LiteNNAdapterConfig& SetDeviceNames(const std::vector<std::string>& names);
LiteNNAdapterConfig& SetContextProperties(const std::string& properties);
LiteNNAdapterConfig& SetModelCacheDir(const std::string& dir);
LiteNNAdapterConfig& SetModelCacheBuffers(
const std::string& model_cache_token,
const std::vector<char>& model_cache_buffer);
LiteNNAdapterConfig& SetSubgraphPartitionConfigPath(const std::string& path);
LiteNNAdapterConfig& SetSubgraphPartitionConfigBuffer(
const std::string& buffer);
LiteNNAdapterConfig& Enable();
LiteNNAdapterConfig& Disable();
};
///
/// \brief configuration manager for AnalysisPredictor.
/// \since 1.7.0
......@@ -692,6 +720,8 @@ struct PD_INFER_DECL AnalysisConfig {
///
std::string Summary();
LiteNNAdapterConfig& NNAdapter() { return nnadapter_config_; }
protected:
// Update the config.
void Update();
......@@ -800,6 +830,9 @@ struct PD_INFER_DECL AnalysisConfig {
std::string xpu_precision_;
bool xpu_adaptive_seqlen_;
// NNAdapter related
LiteNNAdapterConfig nnadapter_config_;
// mkldnn related.
int mkldnn_cache_capacity_{10};
bool use_mkldnn_quantizer_{false};
......
paddle/fluid/inference/lite/CMakeLists.txt
浏览文件 @ 2aaa417e
......@@ -2,8 +2,8 @@ if(XPU_SDK_ROOT)
set(XPU_DEPS xpuapi xpurt)
endif()
cc_library(lite_op_teller SRCS op_teller.cc DEPS lite_full_static framework_proto device_context boost xxhash)
cc_library(lite_engine SRCS engine.cc DEPS lite_full_static framework_proto ${XPU_DEPS})
cc_library(lite_tensor_utils SRCS tensor_utils.cc DEPS memcpy lite_full_static framework_proto boost device_context ${XPU_DEPS})
cc_library(lite_op_teller SRCS op_teller.cc DEPS ${LITE_DEPS} framework_proto device_context boost xxhash)
cc_library(lite_engine SRCS engine.cc DEPS ${LITE_DEPS} framework_proto ${XPU_DEPS})
cc_library(lite_tensor_utils SRCS tensor_utils.cc DEPS memcpy ${LITE_DEPS} framework_proto boost device_context ${XPU_DEPS})
cc_test(test_lite_engine SRCS test_engine_lite.cc DEPS lite_engine protobuf framework_proto glog gtest analysis)
cc_test(test_lite_tensor_utils SRCS test_tensor_utils.cc DEPS lite_engine lite_tensor_utils)
paddle/fluid/inference/lite/engine.cc
浏览文件 @ 2aaa417e
......@@ -69,6 +69,25 @@ paddle::lite_api::PaddlePredictor* EngineManager::Create(
cfg.adaptive_seqlen);
#endif
#ifdef LITE_SUBGRAPH_WITH_NPU
lite_cxx_config.set_nnadapter_device_names(cfg.nnadapter_device_names);
lite_cxx_config.set_nnadapter_context_properties(
cfg.nnadapter_context_properties);
lite_cxx_config.set_nnadapter_model_cache_dir(cfg.nnadapter_model_cache_dir);
if (!cfg.nnadapter_subgraph_partition_config_path.empty()) {
lite_cxx_config.set_nnadapter_subgraph_partition_config_path(
cfg.nnadapter_subgraph_partition_config_path);
}
if (!cfg.nnadapter_subgraph_partition_config_buffer.empty()) {
lite_cxx_config.set_nnadapter_subgraph_partition_config_buffer(
cfg.nnadapter_subgraph_partition_config_buffer);
}
for (size_t i = 0; i < cfg.nnadapter_model_cache_token.size(); ++i) {
lite_cxx_config.set_nnadapter_model_cache_buffers(
cfg.nnadapter_model_cache_token[i],
cfg.nnadapter_model_cache_buffer[i]);
}
#endif
// create predictor
std::shared_ptr<paddle::lite_api::PaddlePredictor> p =
paddle::lite_api::CreatePaddlePredictor(lite_cxx_config);
......
paddle/fluid/inference/lite/engine.h
浏览文件 @ 2aaa417e
......@@ -53,6 +53,15 @@ struct EngineConfig {
// for cuda
bool use_multi_stream{false};
// for nnadapter or npu.
std::string nnadapter_model_cache_dir;
std::vector<std::string> nnadapter_device_names;
std::string nnadapter_context_properties;
std::string nnadapter_subgraph_partition_config_buffer;
std::string nnadapter_subgraph_partition_config_path;
std::vector<std::string> nnadapter_model_cache_token;
std::vector<std::vector<char>> nnadapter_model_cache_buffer;
};
class EngineManager {
......
paddle/fluid/operators/lite/lite_engine_op_test.cc
浏览文件 @ 2aaa417e
......@@ -30,6 +30,8 @@ using paddle::inference::lite::CreateTensor;
using paddle::inference::lite::serialize_params;
namespace paddle {
namespace operators {
#if defined(PADDLE_WITH_CUDA)
TEST(LiteEngineOp, engine_op) {
framework::ProgramDesc program;
auto* block_ = program.Proto()->mutable_blocks(0);
......@@ -75,8 +77,8 @@ TEST(LiteEngineOp, engine_op) {
platform::CPUDeviceContext ctx(place);
#endif
// Prepare variables.
CreateTensor(&scope, "x", std::vector<int64_t>({2, 4}), false);
CreateTensor(&scope, "y", std::vector<int64_t>({2, 4}), false);
CreateTensor(&scope, "x", std::vector<int64_t>({2, 4}), true);
CreateTensor(&scope, "y", std::vector<int64_t>({2, 4}), true);
CreateTensor(&scope, "out", std::vector<int64_t>({2, 4}), false);
ASSERT_EQ(block_->ops_size(), 4);
......@@ -113,5 +115,7 @@ TEST(LiteEngineOp, engine_op) {
engine_op->Run(scope, place);
LOG(INFO) << "done";
}
#endif
} // namespace operators
} // namespace paddle
paddle/fluid/pybind/inference_api.cc
浏览文件 @ 2aaa417e
......@@ -87,6 +87,7 @@ void BindPaddlePlace(py::module *m);
void BindPaddlePredictor(py::module *m);
void BindNativeConfig(py::module *m);
void BindNativePredictor(py::module *m);
void BindLiteNNAdapterConfig(py::module *m);
void BindAnalysisConfig(py::module *m);
void BindAnalysisPredictor(py::module *m);
void BindZeroCopyTensor(py::module *m);
......@@ -303,6 +304,7 @@ void BindInferenceApi(py::module *m) {
BindPaddlePredictor(m);
BindNativeConfig(m);
BindNativePredictor(m);
BindLiteNNAdapterConfig(m);
BindAnalysisConfig(m);
BindAnalysisPredictor(m);
BindPaddleInferPredictor(m);
......@@ -624,7 +626,26 @@ void BindAnalysisConfig(py::module *m) {
[](AnalysisConfig &self) {
return dynamic_cast<PaddlePassBuilder *>(self.pass_builder());
},
py::return_value_policy::reference);
py::return_value_policy::reference)
.def("nnadapter", &AnalysisConfig::NNAdapter);
}
void BindLiteNNAdapterConfig(py::module *m) {
py::class_<LiteNNAdapterConfig> lite_nnadapter_config(*m,
"LiteNNAdapterConfig");
lite_nnadapter_config
.def("set_device_names", &LiteNNAdapterConfig::SetDeviceNames)
.def("set_context_properties", &LiteNNAdapterConfig::SetContextProperties)
.def("set_model_cache_dir", &LiteNNAdapterConfig::SetModelCacheDir)
.def("set_model_cache_buffers",
&LiteNNAdapterConfig::SetModelCacheBuffers)
.def("set_subgraph_partition_config_path",
&LiteNNAdapterConfig::SetSubgraphPartitionConfigPath)
.def("set_subgraph_partition_config_buffer",
&LiteNNAdapterConfig::SetSubgraphPartitionConfigBuffer)
.def("enable", &LiteNNAdapterConfig::Enable)
.def("disable", &LiteNNAdapterConfig::Disable);
}
#ifdef PADDLE_WITH_MKLDNN
......
paddle/scripts/paddle_build.sh
浏览文件 @ 2aaa417e
......@@ -223,7 +223,7 @@ function cmake_base() {
-DWITH_GLOO=${gloo_flag}
-DWITH_LITE=${WITH_LITE:-OFF}
-DWITH_XPU=${WITH_XPU:-OFF}
-DLITE_GIT_TAG=release/v2.8
-DLITE_GIT_TAG=_release/v2.10
-DWITH_UNITY_BUILD=${WITH_UNITY_BUILD:-OFF}
-DWITH_XPU_BKCL=${WITH_XPU_BKCL:-OFF}
-DWITH_ARM=${WITH_ARM:-OFF}
......@@ -266,7 +266,7 @@ EOF
-DWITH_PSCORE=${distibuted_flag} \
-DWITH_PSLIB=${WITH_PSLIB:-OFF} \
-DWITH_GLOO=${gloo_flag} \
-DLITE_GIT_TAG=release/v2.8 \
-DLITE_GIT_TAG=_release/v2.10 \
-DWITH_XPU=${WITH_XPU:-OFF} \
-DXPU_SDK_ROOT=${XPU_SDK_ROOT:-""} \
-DWITH_LITE=${WITH_LITE:-OFF} \
......
python/setup.py.in
浏览文件 @ 2aaa417e
......@@ -338,6 +338,12 @@ else:
if '${WITH_LITE}' == 'ON':
shutil.copy('${LITE_SHARED_LIB}', libs_path)
package_data['paddle.libs']+=['libpaddle_full_api_shared' + ext_name]
if '${LITE_WITH_NNADAPTER}' == 'ON':
shutil.copy('${LITE_NNADAPTER_LIB}', libs_path)
package_data['paddle.libs']+=['libnnadapter' + ext_name]
if '${NNADAPTER_WITH_HUAWEI_ASCEND_NPU}' == 'ON':
shutil.copy('${LITE_NNADAPTER_NPU_LIB}', libs_path)
package_data['paddle.libs']+=['libnnadapter_driver_huawei_ascend_npu' + ext_name]
if '${WITH_PSLIB}' == 'ON':
shutil.copy('${PSLIB_LIB}', libs_path)
......
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