Nigel
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

!42876 [MS][LITE]Change micro Cortex-M working buffer settings 

Merge pull request !42876 from gongdaguo1/micro_fix_fff
This commit is contained in:
i-robot 2022-09-29 12:28:05 +00:00 committed by Gitee
parent c4f2e86de1 75ceb9b85e
commit e0500c9ae5
No known key found for this signature in database
GPG Key ID: 173E9B9CA92EEF8F
14 changed files with 267 additions and 139 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
include/c_api/model_c.h
View File

@ -62,6 +62,11 @@ MS_API void MSModelDestroy(MSModelHandle *model);
/// \param[in] workspace_size Define the workspace size.
MS_API void MSModelSetWorkspace(MSModelHandle model, void *workspace, size_t workspace_size);
/// \brief Calculate the workspace size required for model inference. Only valid for Iot.
///
/// \param[in] model Model object handle.
MS_API size_t MSModelCalcWorkspaceSize(MSModelHandle model);
/// \brief Build the model from model file buffer so that it can run on a device.
///
/// \param[in] model Model object handle.

1
mindspore/lite/CMakeLists.txt
View File

@ -791,6 +791,7 @@ if(MSLITE_GPU_BACKEND STREQUAL opencl)
endif()
file(GLOB FBS_FILES ${CMAKE_CURRENT_SOURCE_DIR}/schema/*.fbs)
ms_build_flatbuffers_lite(FBS_FILES ${CMAKE_CURRENT_SOURCE_DIR}/schema/ fbs_src ${CMAKE_BINARY_DIR}/schema "")
ms_build_flatbuffers_lite(FBS_FILES ${CMAKE_CURRENT_SOURCE_DIR}/schema/ fbs_inner_src ${CMAKE_BINARY_DIR}/schema/inner
"inner")

5
mindspore/lite/src/litert/c_api/model_c.cc
View File

@ -317,6 +317,11 @@ void MSModelSetWorkspace(MSModelHandle model, void *workspace, size_t workspace_
return;
}
size_t MSModelCalcWorkspaceSize(MSModelHandle model) {
MS_LOG(ERROR) << "Unsupported Feature.";
return 0;
}
MSStatus MSModelBuild(MSModelHandle model, const void *model_data, size_t data_size, MSModelType model_type,
const MSContextHandle model_context) {
if (model == nullptr || model_data == nullptr || model_context == nullptr) {

3
mindspore/lite/test/st/scripts/run_benchmark_codegen.sh
View File

@ -199,12 +199,13 @@ function Run_cortex_m_codegen() {
out_data=`cat ${models_path}/input_output/output/${model_name}.ms.out.txt`
sed -i "s/float calib_input0_data\[NET_INPUT0_SIZE\] = {};/float calib_input0_data\[NET_INPUT0_SIZE\] = {${in_data}};/g" benchmark/data.c
sed -i "s/float calib_output0_data\[NET_OUTPUT0_SIZE\] = {};/float calib_output0_data\[NET_OUTPUT0_SIZE\] = {${out_data}};/g" benchmark/data.c
sed -i "s/VERSION_STR=1.8.0/VERSION_STR=${version}/g" build.sh
sed -i "s/VERSION_STR=.*/VERSION_STR=${version}/g" build.sh
bash build.sh || exit 1
cp -r ${output_file}/mindspore-lite-${version}-none-cortex-m7 ${output_file}/build/
cd ${stm_demo_file} || exit 1
[ -n "${stm_demo_file}" ] && rm -rf ${stm_demo_file}/build
sed -i "s/LITE_PACK =/LITE_PACK = mindspore-lite-${version}-none-cortex-m7/g" Makefile
sed -i "s/ if (benchmark() == 0) {/ static char work_space\[300000\];\n if (benchmark(work_space, 300000) == 0) {/g" Core/Src/main.c
make >> "$4" || return 1
continue

276
mindspore/lite/tools/converter/micro/coder/generator/component/common_component.cc
View File

@ -22,22 +22,23 @@
#include "coder/log.h"
#include "include/errorcode.h"
#include "nnacl/op_base.h"
#include "include/c_api/model_c.h"
namespace mindspore::lite::micro {
const char model_runtime_init_source[] = R"RAW(
const char micro_model_define_source[] = R"RAW(
typedef struct {
void *runtime_buffer;
bool train_mode; // true: train mode, false: eval mode
MSTensorHandleArray inputs;
MSTensorHandleArray outputs;
} MicroModel;
)RAW";
const char model_runtime_malloc_source[] = R"RAW(
MSModelHandle MSModelCreate() {
MicroModel *micro_model = (MicroModel *)malloc(sizeof(MicroModel));
if (micro_model == NULL) {
return NULL;
}
)RAW";
const char model_runtime_malloc_source[] = R"RAW(
int buffer_size = GetBufferSize();
void *runtime_buffer = malloc(buffer_size);
if (runtime_buffer == NULL) {
@ -50,63 +51,202 @@ const char model_runtime_malloc_source[] = R"RAW(
}
)RAW";
const char handle_array_destroy[] = R"RAW(
void MSTensorHandleArrayDestroy(MSTensorHandleArray inputs) {
if (inputs.handle_list == NULL) {
return;
}
for (size_t i = 0; i < inputs.handle_num; i++) {
MicroTensor *micro_tensor = inputs.handle_list[i];
if (!micro_tensor) {
continue;
}
if (micro_tensor->data) {
free(micro_tensor->data);
micro_tensor->data = NULL;
}
if (micro_tensor->shape) {
free(micro_tensor->shape);
micro_tensor->shape = NULL;
}
free(micro_tensor);
micro_tensor = NULL;
}
free(inputs.handle_list);
inputs.handle_list = NULL;
}
)RAW";
const char cortex_set_workspace[] = R"RAW(
MicroModel *micro_model = (MicroModel *)model;
if (micro_model == NULL) {
return;
}
if (workspace_size < MSModelCalcWorkspaceSize(model)) {
return;
}
if (micro_model->inputs.handle_num != GRAPH_INPUTS_SIZE) {
return;
}
if (micro_model->outputs.handle_num != GRAPH_OUTPUTS_SIZE) {
return;
}
micro_model->runtime_buffer = workspace;
int buffer_size = GetBufferSize();
char* buf = workspace;
SetBuffer(buf);
)RAW";
void CodeMSModelCalcWorkspaceSize(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx,
const Configurator &config) {
if (config.target() == kCortex_M) {
ofs << "size_t MSModelCalcWorkspaceSize(MSModelHandle model) {\n";
ofs << " size_t shape_size=0;\n";
std::vector<Tensor *> inputs = ctx->graph_inputs();
for (size_t i = 0; i < inputs.size(); ++i) {
ofs << " shape_size += " << inputs[i]->shape().size() << " * sizeof(int64_t);\n";
}
std::vector<Tensor *> outputs = ctx->graph_outputs();
for (size_t i = 0; i < outputs.size(); ++i) {
ofs << " shape_size += " << outputs[i]->shape().size() << " * sizeof(int64_t);\n";
}
ofs << " return GetBufferSize() + WEIGHT_BUF_SIZE + shape_size + "
<< "(sizeof(MicroTensor) + sizeof(MicroTensor *)) * "
<< (ctx->graph_inputs().size() + ctx->graph_outputs().size()) << ";\n}\n";
} else {
ofs << "size_t MSModelCalcWorkspaceSize(MSModelHandle model) {\n return 0;\n}\n";
}
ofs << "\n";
}
void CodeMSModelSetWorkspace(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx, const Configurator &config) {
ofs << "void MSModelSetWorkspace(MSModelHandle model, void *workspace, size_t workspace_size) {\n";
if (config.target() == kCortex_M) {
ofs << cortex_set_workspace;
ofs << " " << ctx->weight_name() << " = (uint8_t *)&buf[buffer_size];\n";
ofs << R"RAW(
buffer_size += WEIGHT_BUF_SIZE;
micro_model->inputs.handle_list = (MSTensorHandle *)&buf[buffer_size];
buffer_size += GRAPH_INPUTS_SIZE * sizeof(MicroTensor *);
MicroTensor **input_tensors = (MicroTensor **)micro_model->inputs.handle_list;
micro_model->outputs.handle_list = (MSTensorHandle *)&buf[buffer_size];
buffer_size += GRAPH_OUTPUTS_SIZE * sizeof(MicroTensor *);
MicroTensor **output_tensors = (MicroTensor **)micro_model->outputs.handle_list;
)RAW";
ofs << " int i;\n"
<< " for (i = 0; i < GRAPH_INPUTS_SIZE; i++) {\n";
std::vector<Tensor *> inputs = ctx->graph_inputs();
for (size_t i = 0; i < inputs.size(); ++i) {
ofs << " input_tensors[i] = (MicroTensor *)&buf[buffer_size];\n"
<< " buffer_size += sizeof(MicroTensor);\n";
ofs << " input_tensors[i]->shape = (int64_t *)&buf[buffer_size];\n"
<< " buffer_size += " << inputs[i]->shape().size() * sizeof(int64_t) << ";\n";
}
ofs << " }\n";
ofs << " for (i = 0; i < GRAPH_OUTPUTS_SIZE; i++) {\n";
std::vector<Tensor *> outputs = ctx->graph_outputs();
for (size_t i = 0; i < outputs.size(); ++i) {
ofs << " output_tensors[i] = (MicroTensor *)&buf[buffer_size];\n"
<< " buffer_size += sizeof(MicroTensor);\n";
ofs << " output_tensors[i]->shape = (int64_t *)&buf[buffer_size];\n"
<< " buffer_size += " << outputs[i]->shape().size() * sizeof(int64_t) << ";\n";
}
ofs << " }\n";
auto array_tostring = [&ofs](Tensor *tensor, const std::string &prefix, size_t index) {
ofs << kAlignedString << prefix << "_tensors[" << index << "]->type = " << EnumNameMSDataType(tensor->data_type())
<< ";\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->format = kMSFormatNHWC;\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->ndim = " << tensor->shape().size() << ";\n";
size_t shape_size = tensor->shape().size();
for (size_t i = 0; i < shape_size; i++) {
ofs << kAlignedString << prefix << "_tensors[" << index << "]->shape[" << i << "]= " << tensor->shape()[i]
<< ";\n";
}
ofs << kAlignedString << prefix << "_tensors[" << index << "]->name = \"" << tensor->tensor_name() << "\";\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->data = NULL;\n";
};
for (size_t i = 0; i < inputs.size(); ++i) {
array_tostring(inputs[i], "input", i);
}
for (size_t i = 0; i < outputs.size(); ++i) {
array_tostring(outputs[i], "output", i);
}
}
ofs << "}\n\n";
}
void CodeMSModelCreate(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx, const Configurator &config) {
ofs << model_runtime_init_source;
ofs << micro_model_define_source;
if (config.target() != kCortex_M) {
ofs << model_runtime_malloc_source;
} else {
ofs << " micro_model->runtime_buffer = " << ctx->buffer_name() << ";\n";
}
if (config.code_mode() == CodeMode::Inference) {
ofs << " micro_model->train_mode = false;\n";
} else if (config.code_mode() == CodeMode::Train) {
ofs << " micro_model->train_mode = true;\n";
}
auto array_tostring = [&ofs](Tensor *tensor, const std::string &prefix, size_t index) {
ofs << kAlignedString << prefix << "_tensors[" << index << "] = malloc(sizeof(MicroTensor));\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->type = " << EnumNameMSDataType(tensor->data_type())
<< ";\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->format = kMSFormatNHWC;\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->ndim = " << tensor->shape().size() << ";\n";
size_t shape_size = tensor->shape().size();
ofs << kAlignedString << prefix << "_tensors[" << index << "]->shape = "
<< "malloc(" << shape_size << " * sizeof(int64_t));\n";
for (size_t i = 0; i < shape_size; i++) {
ofs << kAlignedString << prefix << "_tensors[" << index << "]->shape[" << i << "]= " << tensor->shape()[i]
<< ";\n";
if (config.code_mode() == CodeMode::Inference) {
ofs << " micro_model->train_mode = false;\n";
} else if (config.code_mode() == CodeMode::Train) {
ofs << " micro_model->train_mode = true;\n";
}
ofs << kAlignedString << prefix << "_tensors[" << index << "]->name = \"" << tensor->tensor_name() << "\";\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->data = NULL;\n";
};
std::vector<Tensor *> inputs = ctx->graph_inputs();
std::vector<Tensor *> outputs = ctx->graph_outputs();
if (config.code_mode() == CodeMode::Inference) {
outputs = ctx->graph_outputs();
} else if (config.code_mode() == CodeMode::Train) {
outputs = ctx->graph_train_outputs();
auto array_tostring = [&ofs](Tensor *tensor, const std::string &prefix, size_t index) {
ofs << kAlignedString << prefix << "_tensors[" << index << "] = malloc(sizeof(MicroTensor));\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->type = " << EnumNameMSDataType(tensor->data_type())
<< ";\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->format = kMSFormatNHWC;\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->ndim = " << tensor->shape().size() << ";\n";
size_t shape_size = tensor->shape().size();
ofs << kAlignedString << prefix << "_tensors[" << index << "]->shape = "
<< "malloc(" << shape_size << " * sizeof(int64_t));\n";
for (size_t i = 0; i < shape_size; i++) {
ofs << kAlignedString << prefix << "_tensors[" << index << "]->shape[" << i << "]= " << tensor->shape()[i]
<< ";\n";
}
ofs << kAlignedString << prefix << "_tensors[" << index << "]->name = \"" << tensor->tensor_name() << "\";\n";
ofs << kAlignedString << prefix << "_tensors[" << index << "]->data = NULL;\n";
};
std::vector<Tensor *> inputs = ctx->graph_inputs();
std::vector<Tensor *> outputs = ctx->graph_outputs();
if (config.code_mode() == CodeMode::Inference) {
outputs = ctx->graph_outputs();
} else if (config.code_mode() == CodeMode::Train) {
outputs = ctx->graph_train_outputs();
}
size_t inputs_size = inputs.size();
ofs << " MSTensorHandleArray model_inputs;\n";
ofs << " model_inputs.handle_num = " << inputs_size << ";\n";
ofs << " MicroTensor **input_tensors = malloc(" << inputs_size << " * sizeof(MicroTensor *));\n";
ofs << " model_inputs.handle_list = (MSTensorHandle *)(input_tensors);\n";
ofs << " micro_model->inputs = model_inputs;\n";
for (size_t i = 0; i < inputs_size; ++i) {
Tensor *input = inputs[i];
array_tostring(input, "input", i);
}
size_t outputs_size = outputs.size();
ofs << " MSTensorHandleArray model_outputs;\n";
ofs << " model_outputs.handle_num = " << outputs_size << ";\n";
ofs << " MicroTensor **output_tensors = malloc(" << outputs_size << " * sizeof(MicroTensor *));\n";
ofs << " model_outputs.handle_list = (MSTensorHandle *)(output_tensors);\n";
ofs << " micro_model->outputs = model_outputs;\n";
for (size_t i = 0; i < outputs_size; ++i) {
Tensor *output = outputs[i];
array_tostring(output, "output", i);
}
ofs << " return (MSModelHandle)micro_model;\n";
} else {
ofs << "#define GRAPH_INPUTS_SIZE " << ctx->graph_inputs().size() << "\n";
ofs << "#define GRAPH_OUTPUTS_SIZE " << ctx->graph_outputs().size() << "\n";
ofs << "#define WEIGHT_BUF_SIZE " << ctx->weight_buffer_size() << "\n";
ofs << "MSModelHandle MSModelCreate() {\n";
ofs << " static MicroModel model;\n";
ofs << " model.runtime_buffer = NULL;\n";
ofs << " model.inputs.handle_num = GRAPH_INPUTS_SIZE;\n";
ofs << " model.inputs.handle_list = NULL;\n";
ofs << " model.outputs.handle_num = GRAPH_OUTPUTS_SIZE;\n";
ofs << " model.outputs.handle_list = NULL;\n";
ofs << " model.train_mode = false;\n";
ofs << " return (MSModelHandle)&model;\n";
}
size_t inputs_size = inputs.size();
ofs << " MSTensorHandleArray model_inputs;\n";
ofs << " model_inputs.handle_num = " << inputs_size << ";\n";
ofs << " MicroTensor **input_tensors = malloc(" << inputs_size << " * sizeof(MicroTensor *));\n";
ofs << " model_inputs.handle_list = (MSTensorHandle *)(input_tensors);\n";
ofs << " micro_model->inputs = model_inputs;\n";
for (size_t i = 0; i < inputs_size; ++i) {
Tensor *input = inputs[i];
array_tostring(input, "input", i);
}
size_t outputs_size = outputs.size();
ofs << " MSTensorHandleArray model_outputs;\n";
ofs << " model_outputs.handle_num = " << outputs_size << ";\n";
ofs << " MicroTensor **output_tensors = malloc(" << outputs_size << " * sizeof(MicroTensor *));\n";
ofs << " model_outputs.handle_list = (MSTensorHandle *)(output_tensors);\n";
ofs << " micro_model->outputs = model_outputs;\n";
for (size_t i = 0; i < outputs_size; ++i) {
Tensor *output = outputs[i];
array_tostring(output, "output", i);
}
ofs << " return (MSModelHandle)micro_model;\n";
ofs << "}\n\n";
}
@ -116,6 +256,9 @@ void CodeMSModelBuild(std::ofstream &ofs, const Configurator *config) {
" const MSContextHandle model_context) {\n"
" if (model_type != kMSModelTypeMindIR) {\n"
" return kMSStatusLiteNotSupport;\n"
" }\n"
" if (((MicroModel *)model)->runtime_buffer == NULL) {\n"
" return kMSStatusLiteMemoryFailed;\n"
" }\n";
ofs << " int ret = RET_OK;\n";
if (config->target() != kCortex_M) {
@ -139,23 +282,26 @@ void CodeMSModelBuild(std::ofstream &ofs, const Configurator *config) {
}
void CodeMSModelDestory(std::ofstream &ofs, const Configurator *config) {
ofs << "void MSModelDestroy(MSModelHandle *model) {\n";
ofs << " if (*model) {\n"
" MicroModel *micro_model = (MicroModel *)*model;\n";
if (config->target() != kCortex_M) {
ofs << handle_array_destroy;
}
ofs << "void MSModelDestroy(MSModelHandle *model) {\n";
if (config->target() != kCortex_M) {
ofs << " if (*model) {\n"
" MicroModel *micro_model = (MicroModel *)*model;\n";
ofs << " if (micro_model->runtime_buffer) {\n"
" free(micro_model->runtime_buffer);\n"
" micro_model->runtime_buffer = NULL;\n"
" }\n";
}
ofs << " MSTensorHandleArrayDestroy(micro_model->inputs);\n"
" MSTensorHandleArrayDestroy(micro_model->outputs);\n"
" free(*model);\n"
" *model = NULL;\n"
" }\n";
ofs << " MSTensorHandleArrayDestroy(micro_model->inputs);\n"
" MSTensorHandleArrayDestroy(micro_model->outputs);\n"
" free(*model);\n"
" *model = NULL;\n"
" }\n";
if (config->support_parallel()) {
ofs << " ClearThreadPool();\n";
if (config->support_parallel()) {
ofs << " ClearThreadPool();\n";
}
}
ofs << "}\n";
}

3
mindspore/lite/tools/converter/micro/coder/generator/component/common_component.h
View File

@ -27,6 +27,9 @@
#include "tools/converter/micro/coder/config.h"
namespace mindspore::lite::micro {
void CodeMSModelCalcWorkspaceSize(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx,
const Configurator &config);
void CodeMSModelSetWorkspace(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx, const Configurator &config);
void CodeMSModelCreate(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx, const Configurator &config);
void CodeMSModelBuild(std::ofstream &ofs, const Configurator *config);
void CodeMSModelDestory(std::ofstream &ofs, const Configurator *config);

12
mindspore/lite/tools/converter/micro/coder/generator/component/const_blocks/benchmark.cc
View File

@ -291,6 +291,7 @@ const char benchmark_source_cortex[] = R"RAW(/**
* limitations under the License.
*/
#include "benchmark.h"
#include "calib_output.h"
#include "load_input.h"
#include "data.h"
@ -351,7 +352,7 @@ void PrintTensorHandle(MSTensorHandle tensor) {
}
}
int benchmark() {
int benchmark(char *work_space, unsigned int work_space_size) {
int ret;
printf("========run benchmark======\n");
printf("========Model build========\n");
@ -360,6 +361,12 @@ int benchmark() {
printf("MSModelCreate failed.\n");
return kMSStatusLiteNullptr;
}
size_t workspace_size = MSModelCalcWorkspaceSize(model_handle);
if (workspace_size > work_space_size) {
printf("This Model inference requires %ul bytes of memory.\n", workspace_size);
return kMSStatusLiteError;
}
MSModelSetWorkspace(model_handle, work_space, work_space_size);
ret = MSModelBuild(model_handle, NULL, 0, kMSModelTypeMindIR, NULL);
if (ret != kMSStatusSuccess) {
printf("MSModelBuildFromFile failed, ret : %d.\n", ret);
@ -421,6 +428,7 @@ int benchmark() {
MSModelDestroy(&model_handle);
return kMSStatusSuccess;
}
)RAW";
const char benchmark_h_cortex[] = R"RAW(/**
@ -444,7 +452,7 @@ const char benchmark_h_cortex[] = R"RAW(/**
#ifdef __cplusplus
extern "C" {
#endif
int benchmark();
int benchmark(char *work_space, unsigned int work_space_size);
#ifdef __cplusplus
}
#endif

5
mindspore/lite/tools/converter/micro/coder/generator/component/const_blocks/cmake_lists.cc
View File

@ -59,9 +59,10 @@ if("${CMAKE_BUILD_TYPE}" STREQUAL "Debug")
else()
message(STATUS "build benchmark release version")
set(CMAKE_C_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O3 -Wall -Werror -fstack-protector-strong -Wno-attributes \
-Wno-deprecated-declarations -Wno-missing-braces ${CMAKE_C_FLAGS}")
-Wno-deprecated-declarations -Wno-incompatible-pointer-types -Wno-missing-braces ${CMAKE_C_FLAGS}")
set(CMAKE_CXX_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O3 -Wall -Werror -fstack-protector-strong -Wno-attributes \
-Wno-deprecated-declarations -Wno-missing-braces -Wno-overloaded-virtual ${CMAKE_CXX_FLAGS}")
-Wno-deprecated-declarations -Wno-incompatible-pointer-types -Wno-missing-braces -Wno-overloaded-virtual \
${CMAKE_CXX_FLAGS}")
string(REPLACE "-g" "" CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
string(REPLACE "-g" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
endif()

11
mindspore/lite/tools/converter/micro/coder/generator/component/const_blocks/load_input.cc
View File

@ -293,16 +293,17 @@ set -e
BASEPATH=$(cd "$(dirname $0)"; pwd)
mkdir -p build
VERSION_STR=1.8.0
VERSION_STR=1.8.1
MINDSPORE_FILE_NAME="mindspore-lite-${VERSION_STR}-none-cortex-m7"
MINDSPORE_FILE="${MINDSPORE_FILE_NAME}.tar.gz"
MINDSPORE_LITE_DOWNLOAD_URL=\
"https://ms-release.obs.cn-north-4.myhuaweicloud.com/${VERSION_STR}/MindSpore/lite/release/cortex-m/${MINDSPORE_FILE}"
"https://ms-release.obs.cn-north-4.myhuaweicloud.com/${VERSION_STR}/MindSpore/lite/none_cortex-m/${MINDSPORE_FILE}"
if [ ! -e ${BASEPATH}/${MINDSPORE_FILE} ]; then
wget -c -O ${BASEPATH}/${MINDSPORE_FILE} --no-check-certificate ${MINDSPORE_LITE_DOWNLOAD_URL}+
wget -c -O ${BASEPATH}/${MINDSPORE_FILE} --no-check-certificate ${MINDSPORE_LITE_DOWNLOAD_URL}
fi
if [ ! -e ${BASEPATH}/${MINDSPORE_FILE_NAME} ]; then
tar xzf ${BASEPATH}/${MINDSPORE_FILE} -C ${BASEPATH}/
fi
tar xzf ${BASEPATH}/${MINDSPORE_FILE} -C ${BASEPATH}/
cd build
cmake -DPKG_PATH=../${MINDSPORE_FILE_NAME} -DCMAKE_TOOLCHAIN_FILE=../cortex-m7.toolchain.cmake ..
make

22
mindspore/lite/tools/converter/micro/coder/generator/component/const_blocks/mcontext.cc
View File

@ -38,6 +38,7 @@ const char context_header[] = R"RAW(
#define MINDSPORE_LITE_MICRO_LIBRARY_SOURCE_CONTEXT_H_
#include <stdbool.h>
#include "c_api/context_c.h"
typedef struct MicroContext {
char* vendor_name_;
@ -69,29 +70,14 @@ const char context_source_cortex[] = R"RAW(
*/
#include "context.h"
#include "c_api/context_c.h"
#include <stdlib.h>
#include <string.h>
MSContextHandle MSContextCreate() {
MicroContext *micro_context = (MicroContext *)malloc(sizeof(MicroContext));
if (micro_context == NULL) {
return NULL;
}
micro_context->enable_parallel_ = false;
micro_context->thread_num_ = 1;
micro_context->affinity_core_list_ = NULL;
micro_context->core_num = 0;
micro_context->affinity_mode = 0;
return micro_context;
return NULL;
}
void MSContextDestroy(MSContextHandle *context) {
MicroContext *micro_context = (MicroContext *)(*context);
if (micro_context) {
free(micro_context);
micro_context = NULL;
}
}
void MSContextSetThreadNum(MSContextHandle context, int32_t thread_num) {
@ -127,7 +113,6 @@ const char context_source_no_parallel[] = R"RAW(
*/
#include "context.h"
#include "c_api/context_c.h"
#include <stdlib.h>
#include <string.h>
@ -185,10 +170,9 @@ const char context_source[] = R"RAW(
*/
#include "context.h"
#include "c_api/context_c.h"
#include "wrapper/thread/micro_core_affinity.h"
#include <stdlib.h>
#include <string.h>
#include "wrapper/thread/micro_core_affinity.h"
#define MAX_THREAD_NUM 4

24
mindspore/lite/tools/converter/micro/coder/generator/component/const_blocks/msession.cc
View File

@ -18,30 +18,6 @@
namespace mindspore::lite::micro {
const char model_runtime_other_source[] = R"RAW(
void MSTensorHandleArrayDestroy(MSTensorHandleArray inputs) {
if (inputs.handle_list == NULL) {
return;
}
for (size_t i = 0; i < inputs.handle_num; i++) {
MicroTensor *micro_tensor = inputs.handle_list[i];
if (!micro_tensor) {
continue;
}
if (micro_tensor->data) {
free(micro_tensor->data);
micro_tensor->data = NULL;
}
if (micro_tensor->shape) {
free(micro_tensor->shape);
micro_tensor->shape = NULL;
}
free(micro_tensor);
micro_tensor = NULL;
}
free(inputs.handle_list);
inputs.handle_list = NULL;
}
MSTensorHandleArray MSModelGetInputs(const MSModelHandle model) {
MicroModel *micro_model = (MicroModel *)model;
return micro_model->inputs;

4
mindspore/lite/tools/converter/micro/coder/generator/component/weight_component.cc
View File

@ -172,11 +172,13 @@ void CodeWeightInitFunc(std::ofstream &ofs, const std::unique_ptr<CoderContext>
ofs << " }\n";
} else {
ofs << "int Init(void *weight_buffer, int weight_size) {\n";
ofs << " if (" << ctx->weight_name() << "== NULL) {\n";
ofs << " return RET_ERROR;\n }\n";
ofs << " const size_t w_size = " << ctx->weight_buffer_size() << ";\n";
}
ofs << " size_t " << ctx->weight_offset_name() << " = 0;\n";
for (const auto &block : ctx->init_contents()) {
ofs << "{\n" << block << "}\n";
ofs << "\n{\n" << block << "}\n";
}
ofs << " if (" << ctx->weight_size_name() << " < " << ctx->weight_offset_name()
<< ") {\n return RET_ERROR;\n }\n";

10
mindspore/lite/tools/converter/micro/coder/generator/generator.cc
View File

@ -214,11 +214,14 @@ int Generator::CodeMSModelImplement() {
ofs << "#include \"context.h\"\n";
ofs << "#include \"c_api/model_c.h\"\n";
ofs << "#include \"net.h\"\n";
ofs << "#include \"weight.h\"\n\n";
if (config_->support_parallel()) {
ofs << "#include \"" << kThreadWrapper << "\"\n";
}
ofs << "#include \"weight.h\"\n\n";
CodeMSModelCreate(ofs, ctx_, *config_);
CodeMSModelCalcWorkspaceSize(ofs, ctx_, *config_);
CodeMSModelSetWorkspace(ofs, ctx_, *config_);
CodeMSModelBuild(ofs, config_);
ofs << model_runtime_other_source;
if (config_->code_mode() == CodeMode::Train) {
@ -264,9 +267,8 @@ int Generator::CodeWeightFile() {
return RET_ERROR;
}
cofs << "int __errno; \n";
cofs << "unsigned char g_buf[" << ctx_->total_buffer_size() + ctx_->weight_buffer_size() << "]; \n";
cofs << "unsigned char * " << ctx_->buffer_name() << " = &g_buf[0]; \n";
cofs << "unsigned char * " << ctx_->weight_name() << " = &g_buf[" << ctx_->total_buffer_size() << "]; \n";
cofs << "unsigned char * " << ctx_->buffer_name() << " = NULL; \n";
cofs << "unsigned char * " << ctx_->weight_name() << " = NULL; \n";
CodeModelParamsData(cofs, ctx_->saved_weights());
}
CodeModelParamsForNet(hofs, cofs, ctx_, *config_);

25
mindspore/lite/tools/converter/micro/coder/utils/type_cast.h
View File

@ -48,22 +48,15 @@ std::string EnumNameTarget(Target target);
*/
template <typename T>
std::string GetVariableTypeName() {
std::map<std::type_index, std::string> types_name = {{std::type_index(typeid(int)), "int"},
{std::type_index(typeid(int32_t)), "int32_t"},
{std::type_index(typeid(int16_t)), "int16_t"},
{std::type_index(typeid(int8_t)), "int8_t"},
{std::type_index(typeid(uint8_t)), "uint8_t"},
{std::type_index(typeid(float)), "float"},
{std::type_index(typeid(double)), "double"},
{std::type_index(typeid(::QuantArg)), "QuantArg"},
{std::type_index(typeid(void *)), "void *"},
{std::type_index(typeid(std::string)), "float *"},
{std::type_index(typeid(int *)), "int *"},
{std::type_index(typeid(int32_t *)), "int32_t *"},
{std::type_index(typeid(int16_t *)), "int16_t *"},
{std::type_index(typeid(int8_t *)), "int8_t *"},
{std::type_index(typeid(uint8_t *)), "uint8_t *"},
{std::type_index(typeid(float *)), "float *"}};
std::map<std::type_index, std::string> types_name = {
{std::type_index(typeid(int)), "int32_t"}, {std::type_index(typeid(int32_t)), "int32_t"},
{std::type_index(typeid(int16_t)), "int16_t"}, {std::type_index(typeid(int8_t)), "int8_t"},
{std::type_index(typeid(uint8_t)), "uint8_t"}, {std::type_index(typeid(float)), "float"},
{std::type_index(typeid(double)), "double"}, {std::type_index(typeid(::QuantArg)), "QuantArg"},
{std::type_index(typeid(void *)), "void *"}, {std::type_index(typeid(std::string)), "float *"},
{std::type_index(typeid(int *)), "int32_t *"}, {std::type_index(typeid(int32_t *)), "int32_t *"},
{std::type_index(typeid(int16_t *)), "int16_t *"}, {std::type_index(typeid(int8_t *)), "int8_t *"},
{std::type_index(typeid(uint8_t *)), "uint8_t *"}, {std::type_index(typeid(float *)), "float *"}};
auto item = types_name.find(std::type_index(typeid(T)));
if (item != types_name.end()) {
return item->second;