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Add nnadapter pybind and remove useless API

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This commit is contained in:
yunyaoXYY
2022-12-07 06:36:56 +00:00
parent 47af3f02bd
commit e791c5e8b7
5 changed files with 56 additions and 30 deletions
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3
fastdeploy/backends/lite/lite_backend.h
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@@ -48,12 +48,9 @@ struct LiteBackendOption {
std::vector<std::string> nnadapter_device_names = {""};
std::string nnadapter_context_properties = "";
std::string nnadapter_model_cache_dir = "";
std::string nnadapter_model_cache_token = "";
std::vector<char> nnadapter_model_cache_buffer = {' '};
std::map<std::string, std::vector<std::vector<int64_t>>>
nnadapter_dynamic_shape_info = {{" ", {{0}}}};
std::string nnadapter_mixed_precision_quantization_config_path = "";
std::string nnadapter_mixed_precision_quantization_config_buffer = "";
bool enable_timvx = false;
bool enable_cann = false;
};

8
fastdeploy/pybind/runtime.cc
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@@ -23,6 +23,7 @@ void BindRuntime(pybind11::module& m) {
.def("use_gpu", &RuntimeOption::UseGpu)
.def("use_cpu", &RuntimeOption::UseCpu)
.def("use_rknpu2", &RuntimeOption::UseRKNPU2)
.def("use_cann", &RuntimeOption::UseCANN)
.def("set_external_stream", &RuntimeOption::SetExternalStream)
.def("set_cpu_thread_num", &RuntimeOption::SetCpuThreadNum)
.def("use_paddle_backend", &RuntimeOption::UsePaddleBackend)
@@ -32,6 +33,13 @@ void BindRuntime(pybind11::module& m) {
.def("use_trt_backend", &RuntimeOption::UseTrtBackend)
.def("use_openvino_backend", &RuntimeOption::UseOpenVINOBackend)
.def("use_lite_backend", &RuntimeOption::UseLiteBackend)
.def("set_lite_nnadapter_device_names", &RuntimeOption::SetLiteNNAdapterDeviceNames)
.def("set_lite_nnadapter_context_properties", &RuntimeOption::SetLiteNNAdapterContextProperties)
.def("set_lite_nnadapter_model_cache_dir", &RuntimeOption::SetLiteNNAdapterModelCacheDir)
.def("set_lite_nnadapter_dynamic_shape_info", &RuntimeOption::SetLiteNNAdapterDynamicShapeInfo)
.def("set_lite_nnadapter_subgraph_partition_path", &RuntimeOption::SetLiteNNAdapterSubgraphPartitionPath)
.def("set_lite_nnadapter_mixed_precision_quantization_config_path", &RuntimeOption::SetLiteNNAdapterMixedPrecisionQuantizationConfigPath)
.def("set_lite_nnadapter_subgraph_partition_config_buffer", &RuntimeOption::SetLiteNNAdapterSubgraphPartitionConfigBuffer)
.def("set_paddle_mkldnn", &RuntimeOption::SetPaddleMKLDNN)
.def("set_openvino_device", &RuntimeOption::SetOpenVINODevice)
.def("set_openvino_shape_info", &RuntimeOption::SetOpenVINOShapeInfo)

11
fastdeploy/runtime.cc
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@@ -386,12 +386,6 @@ void RuntimeOption::SetLiteNNAdapterModelCacheDir(const std::string& nnadapter_m
lite_nnadapter_model_cache_dir = nnadapter_model_cache_dir;
}
void RuntimeOption::SetLiteNNAdapterModelCacheBuffers(
const std::string& nnadapter_model_cache_token,
const std::vector<char>& nnadapter_model_cache_buffer){
lite_nnadapter_model_cache_token = nnadapter_model_cache_token;
lite_nnadapter_model_cache_buffer = nnadapter_model_cache_buffer;
}
void RuntimeOption::SetLiteNNAdapterDynamicShapeInfo(
const std::map<std::string, std::vector<std::vector<int64_t>>>&
@@ -404,10 +398,6 @@ void RuntimeOption::SetLiteNNAdapterMixedPrecisionQuantizationConfigPath(
lite_nnadapter_mixed_precision_quantization_config_path = nnadapter_mixed_precision_quantization_config_path;
}
void RuntimeOption::SetLiteNNAdapterMixedPrecisionQuantizationConfigBuffer(
const std::string& nnadapter_mixed_precision_quantization_config_buffer){
lite_nnadapter_mixed_precision_quantization_config_buffer = nnadapter_mixed_precision_quantization_config_buffer;
}
void RuntimeOption::SetTrtInputShape(const std::string& input_name,
const std::vector<int32_t>& min_shape,
@@ -833,7 +823,6 @@ void Runtime::CreateLiteBackend() {
lite_option.nnadapter_model_cache_dir = option.lite_nnadapter_model_cache_dir;
lite_option.nnadapter_dynamic_shape_info = option.lite_nnadapter_dynamic_shape_info;
lite_option.nnadapter_mixed_precision_quantization_config_path = option.lite_nnadapter_mixed_precision_quantization_config_path;
lite_option.nnadapter_mixed_precision_quantization_config_buffer = option.lite_nnadapter_mixed_precision_quantization_config_buffer;
lite_option.enable_timvx = option.enable_timvx;
lite_option.enable_cann = option.enable_cann;
FDASSERT(option.model_format == ModelFormat::PADDLE,

16
fastdeploy/runtime.h
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@@ -222,13 +222,6 @@ struct FASTDEPLOY_DECL RuntimeOption {
void SetLiteNNAdapterModelCacheDir(
const std::string& nnadapter_model_cache_dir);
/**
* @brief Set nnadapter model cache buffer for Paddle Lite backend.
*/
void SetLiteNNAdapterModelCacheBuffers(
const std::string& nnadapter_model_cache_token,
const std::vector<char>& nnadapter_model_cache_buffer);
/**
* @brief Set nnadapter dynamic shape info for Paddle Lite backend.
*/
@@ -242,12 +235,6 @@ struct FASTDEPLOY_DECL RuntimeOption {
void SetLiteNNAdapterMixedPrecisionQuantizationConfigPath(
const std::string& nnadapter_mixed_precision_quantization_config_path);
/**
* @brief Set nnadapter mixed precision quantization config buffer for Paddle Lite backend.
*/
void SetLiteNNAdapterMixedPrecisionQuantizationConfigBuffer(
const std::string& nnadapter_mixed_precision_quantization_config_buffer);
/**
* @brief enable half precision while use paddle lite backend
*/
@@ -411,12 +398,9 @@ struct FASTDEPLOY_DECL RuntimeOption {
std::vector<std::string> lite_nnadapter_device_names = {""};
std::string lite_nnadapter_context_properties = "";
std::string lite_nnadapter_model_cache_dir = "";
std::string lite_nnadapter_model_cache_token = "";
std::vector<char> lite_nnadapter_model_cache_buffer = {' '};
std::map<std::string, std::vector<std::vector<int64_t>>>
lite_nnadapter_dynamic_shape_info = {{" ", {{0}}}};
std::string lite_nnadapter_mixed_precision_quantization_config_path = "";
std::string lite_nnadapter_mixed_precision_quantization_config_buffer = "";
bool enable_timvx = false;
bool enable_cann = false;

48
python/fastdeploy/runtime.py
View File

@@ -255,6 +255,11 @@ class RuntimeOption:
rknpu2_core=rknpu2.CoreMask.RKNN_NPU_CORE_0):
return self._option.use_rknpu2(rknpu2_name, rknpu2_core)
def use_cann(self):
"""Inference with Huawei Ascend NPU
"""
return self._option.use_cann()
def set_cpu_thread_num(self, thread_num=-1):
"""Set number of threads if inference with CPU
@@ -309,6 +314,49 @@ class RuntimeOption:
"""
return self.use_lite_backend()
def set_lite_nnadapter_device_names(self, device_names):
"""Set nnadapter device name for Paddle Lite backend.
"""
return self._option.set_lite_nnadapter_device_names(device_names)
def set_lite_nnadapter_context_properties(self, context_properties):
"""Set nnadapter context properties for Paddle Lite backend.
"""
return self._option.set_lite_nnadapter_context_properties(
context_properties)
def set_lite_nnadapter_model_cache_dir(self, model_cache_dir):
"""Set nnadapter model cache dir for Paddle Lite backend.
"""
return self._option.set_lite_nnadapter_model_cache_dir(model_cache_dir)
def set_lite_nnadapter_dynamic_shape_info(self, dynamic_shape_info):
""" Set nnadapter dynamic shape info for Paddle Lite backend.
"""
return self._option.set_lite_nnadapter_dynamic_shape_info(
dynamic_shape_info)
def set_lite_nnadapter_subgraph_partition_path(self,
subgraph_partition_path):
""" Set nnadapter subgraph partition path for Paddle Lite backend.
"""
return self._option.set_lite_nnadapter_subgraph_partition_path(
subgraph_partition_path)
def set_lite_nnadapter_subgraph_partition_config_buffer(
self, subgraph_partition_buffer):
""" Set nnadapter subgraph partition buffer for Paddle Lite backend.
"""
return self._option.set_lite_nnadapter_subgraph_partition_config_buffer(
subgraph_partition_buffer)
def set_lite_nnadapter_mixed_precision_quantization_config_path(
self, mixed_precision_quantization_config_path):
""" Set nnadapter mixed precision quantization config path for Paddle Lite backend..
"""
return self._option.set_lite_nnadapter_mixed_precision_quantization_config_path(
mixed_precision_quantization_config_path)
def set_paddle_mkldnn(self, use_mkldnn=True):
"""Enable/Disable MKLDNN while using Paddle Inference backend, mkldnn is enabled by default.
"""