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Refactor and revise Python module name #19

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Merged
ExplorerRay merged 3 commits into from
Dec 11, 2024
Merged

Refactor and revise Python module name #19

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b5af2bf
fix: revise Python module name
ExplorerRay Dec 11, 2024
3d09932
refactor: all use 2 spaces for indentation
ExplorerRay Dec 11, 2024
0c1e43f
refactor: use get_anal_args() to simplify analyze_node()
ExplorerRay Dec 11, 2024
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10 changes: 5 additions & 5 deletions CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -58,18 +58,18 @@ file(GLOB_RECURSE SOURCES "${onnxinfo_SOURCE_DIR}/src/*.cpp")
list(REMOVE_ITEM SOURCES "${onnxinfo_SOURCE_DIR}/src/main.cpp")

add_library(
${PROJECT_NAME} STATIC
_onnxinfo STATIC

${SOURCES}
${onnxinfo_SOURCE_DIR}/third_party/onnx/onnx.proto3.pb.cc
)
add_dependencies(${PROJECT_NAME} protobuf::protoc)
target_link_libraries(${PROJECT_NAME}
add_dependencies(_onnxinfo protobuf::protoc)
target_link_libraries(_onnxinfo
protobuf::libprotobuf
)

pybind11_add_module(_onnxinfo src/main.cpp)
target_link_libraries(_onnxinfo PRIVATE ${PROJECT_NAME})
pybind11_add_module(${PROJECT_NAME} src/main.cpp)
target_link_libraries(${PROJECT_NAME} PRIVATE _onnxinfo)

# custom cmake target for test
# add_custom_target(test ALL)
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62 changes: 31 additions & 31 deletions include/AttrInfo.hpp
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Expand Up @@ -4,43 +4,43 @@
#include "onnx.proto3.pb.h"

struct AttrInfo_Conv {
std::vector<int64_t> kernel_shape; // got from Weight
std::vector<int64_t> strides; // default 1
std::vector<int64_t> pads; // default 0
std::vector<int64_t> dilations; // default 1

int64_t group = 1; // not used now

void set_default_attr(size_t shape_len) {
for (size_t i = 0; i < shape_len - 2; ++i) {
strides.emplace_back(1);
pads.emplace_back(0);
pads.emplace_back(0);
dilations.emplace_back(1);
}
std::vector<int64_t> kernel_shape; // got from Weight
std::vector<int64_t> strides; // default 1
std::vector<int64_t> pads; // default 0
std::vector<int64_t> dilations; // default 1

int64_t group = 1; // not used now

void set_default_attr(size_t shape_len) {
for (size_t i = 0; i < shape_len - 2; ++i) {
strides.emplace_back(1);
pads.emplace_back(0);
pads.emplace_back(0);
dilations.emplace_back(1);
}
}
};

struct AttrInfo_MaxPool {
std::vector<int64_t> kernel_shape;
std::vector<int64_t> strides; // default 1
std::vector<int64_t> pads; // default 0
std::vector<int64_t> dilations; // default 1

int64_t ceil_mode = 0; // not used now
int64_t storage_order = 0; // not used now

void set_default_attr(size_t shape_len) {
for (size_t i = 0; i < shape_len - 2; ++i) {
strides.emplace_back(1);
pads.emplace_back(0);
pads.emplace_back(0);
dilations.emplace_back(1);
}
std::vector<int64_t> kernel_shape;
std::vector<int64_t> strides; // default 1
std::vector<int64_t> pads; // default 0
std::vector<int64_t> dilations; // default 1

int64_t ceil_mode = 0; // not used now
int64_t storage_order = 0; // not used now

void set_default_attr(size_t shape_len) {
for (size_t i = 0; i < shape_len - 2; ++i) {
strides.emplace_back(1);
pads.emplace_back(0);
pads.emplace_back(0);
dilations.emplace_back(1);
}
}
};

struct AttrInfo_Gemm {
bool transA = false;
bool transB = false;
bool transA = false;
bool transB = false;
};
46 changes: 23 additions & 23 deletions include/InferShape.hpp
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Expand Up @@ -9,32 +9,32 @@

class InferShapeImpl {
public:
InferShapeImpl() = default;
InferShapeImpl(const onnx::GraphProto &in_graph) : graph(in_graph) {}
InferShapeImpl() = default;
InferShapeImpl(const onnx::GraphProto &in_graph) : graph(in_graph) {}

~InferShapeImpl() = default;
~InferShapeImpl() = default;

void set_io_iniz_shape_to_map(bool analyze);
void infer_shapes(bool analyze = true);
void infer_shapes();
void print_summary();
void set_io_iniz_shape_to_map(bool analyze);
void infer_shapes(bool analyze = true);
void infer_shapes();
void print_summary();

const std::unordered_map<std::string, std::vector<int64_t>> get_ndname_to_shape() {
return this->ndname_to_shape;
}
const std::unordered_map<std::string, std::vector<int64_t>> get_ndname_to_shape() {
return this->ndname_to_shape;
}

private:
onnx::GraphProto graph;
std::unordered_map<std::string, std::vector<int64_t>> ndname_to_shape;
std::unordered_map<std::string, struct AnalyzeData> ndname_to_anal_data;
std::unordered_map<std::string, size_t> ndname_to_dtype_size;

// TODO: more op types
void infer_shapes_Conv(onnx::NodeProto &node);
void infer_shapes_Relu(onnx::NodeProto &node);
void infer_shapes_MaxPool(onnx::NodeProto &node);
void infer_shapes_Add(onnx::NodeProto &node);
void infer_shapes_GlobalAveragePool(onnx::NodeProto &node);
void infer_shapes_Flatten(onnx::NodeProto &node);
void infer_shapes_Gemm(onnx::NodeProto &node);
onnx::GraphProto graph;
std::unordered_map<std::string, std::vector<int64_t>> ndname_to_shape;
std::unordered_map<std::string, struct AnalyzeData> ndname_to_anal_data;
std::unordered_map<std::string, size_t> ndname_to_dtype_size;

// TODO: more op types
void infer_shapes_Conv(onnx::NodeProto &node);
void infer_shapes_Relu(onnx::NodeProto &node);
void infer_shapes_MaxPool(onnx::NodeProto &node);
void infer_shapes_Add(onnx::NodeProto &node);
void infer_shapes_GlobalAveragePool(onnx::NodeProto &node);
void infer_shapes_Flatten(onnx::NodeProto &node);
void infer_shapes_Gemm(onnx::NodeProto &node);
};
13 changes: 10 additions & 3 deletions include/ModelAnalysis.hpp
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Expand Up @@ -8,12 +8,19 @@
#define DIV_MACS 4

struct AnalyzeData {
int64_t mac = 0;
int64_t param = 0;
int64_t mem = 0;
int64_t mac = 0;
int64_t param = 0;
int64_t mem = 0;
};

struct NodeAnalArgs {
std::vector<std::vector<int64_t>> input_shapes;
std::vector<int64_t> output_shape;
std::unordered_map<std::string, size_t> ndname_to_size;
};

int64_t get_prod(std::vector<int64_t> &vec);
NodeAnalArgs get_anal_args(onnx::NodeProto &node, const std::unordered_map<std::string, std::vector<int64_t>> &ndname_to_shape, const std::unordered_map<std::string, size_t> &ndname_to_dtype_size);

AnalyzeData analyze_node_Conv(onnx::NodeProto &node, std::vector<std::vector<int64_t>> &input_shapes, std::vector<int64_t> &output_shape, std::unordered_map<std::string, size_t> &ndname_to_size);
AnalyzeData analyze_node_Relu(onnx::NodeProto &node, std::vector<std::vector<int64_t>> &input_shapes, std::vector<int64_t> &output_shape, std::unordered_map<std::string, size_t> &ndname_to_size);
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