Add: graph, tensor, and operator
This commit is contained in:
Liyan Zheng
parent
b89495a782
commit
e6101b0336
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---
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Language: Cpp
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Standard: Cpp11
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...
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@ -0,0 +1,311 @@
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"per_command": {}
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}
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@ -30,3 +30,8 @@
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*.exe
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*.out
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*.app
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build/
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build_debug/
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.vscode/
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[submodule "3rd-party/pybind11"]
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path = 3rd-party/pybind11
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url = git@github.com:pybind/pybind11.git
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[submodule "3rd-party/nlohmann_json_cmake_fetchcontent"]
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path = 3rd-party/nlohmann_json_cmake_fetchcontent
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url = git@github.com:ArthurSonzogni/nlohmann_json_cmake_fetchcontent.git
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[submodule "3rd-party/googletest"]
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path = 3rd-party/googletest
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url = git@github.com:google/googletest.git
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Subproject commit e2239ee6043f73722e7aa812a459f54a28552929
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Subproject commit 6aebf09233951e4ce30a63919186a70b2b195756
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@ -0,0 +1 @@
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Subproject commit 1e3400b6742288429f2069aaf5febf92d0662dae
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@ -0,0 +1,73 @@
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# TODO: check the minimum cmake version
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cmake_minimum_required(VERSION 3.9) # Required by find_package(OpenMP)
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include(CMakeDependentOption)
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project(InfiniTensor C CXX)
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# Do not change these options in this file. Use cmake.config, cmake -DOPTION=VALUE, or ccmake to specify them.
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option(BUILD_TEST "Build tests" OFF)
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cmake_dependent_option(BUILD_TEST_CORE "Build tests for core components" ON BUILD_TEST OFF)
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cmake_dependent_option(BUILD_TEST_PET "Build tests for PET" ON BUILD_TEST OFF)
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cmake_dependent_option(BUILD_TEST_EINNET "Build tests for EINNET" ON BUILD_TEST OFF)
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set(DEFAULT_BUILD_TYPE "RelWithDebInfo")
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set(CMAKE_CXX_STANDARD 17)
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set(CMAKE_CXX_EXTENSIONS OFF) # -std=gnu++11 when on, -std=c++11 when off
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall -Werror -Wno-error=deprecated-declarations")
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set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -UNDEBUG") # Enable assertion
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set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "${CMAKE_CXX_FLAGS_RELWITHDEBINFO} -UNDEBUG") # Enable assertion
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find_package(
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Python
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COMPONENTS Interpreter Development
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REQUIRED)
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find_package(CUDA REQUIRED)
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# OpenMP
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find_package(OpenMP)
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if(OpenMP_C_FOUND)
|
||||
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}")
|
||||
endif()
|
||||
if(OpenMP_CXX_FOUND)
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
|
||||
endif()
|
||||
|
||||
# add_subdirectory(3rd-party/pybind11)
|
||||
# add_subdirectory(3rd-party/nlohmann_json_cmake_fetchcontent)
|
||||
|
||||
include_directories(include)
|
||||
# include_directories(3rd-party/pybind11/include)
|
||||
# include_directories(3rd-party/nlohmann_json_cmake_fetchcontent/single_include)
|
||||
|
||||
if(BUILD_TEST)
|
||||
set(BUILD_GMOCK off)
|
||||
set(INSTALL_GTEST off)
|
||||
add_subdirectory(3rd-party/googletest)
|
||||
include_directories(3rd-party/googletest/googletest/include)
|
||||
endif()
|
||||
|
||||
file(GLOB_RECURSE SRC src/*.cc src/*.cu)
|
||||
# file(GLOB_RECURSE TEST test/*.cc)
|
||||
# file(GLOB_RECURSE FFI src/ffi/ffi_pet.cc)
|
||||
# list(REMOVE_ITEM SRC ${TEST} ${FFI})
|
||||
|
||||
add_library(InfiniTensor SHARED ${SRC})
|
||||
# Target
|
||||
# cuda_add_library(it SHARED ${SRC})
|
||||
# cuda_add_cublas_to_target(it) # cublas
|
||||
# # target_link_libraries(infini_cpp cudnn curand nlohmann_json::nlohmann_json pybind11::embed)
|
||||
|
||||
# # Python bindings
|
||||
# pybind11_add_module(infini MODULE ${FFI})
|
||||
# target_link_libraries(infini PRIVATE infini_cpp)
|
||||
|
||||
if(BUILD_TEST)
|
||||
enable_testing()
|
||||
# Build all tests file( GLOB TEST_SOURCES test/test_sg2bmm.cc )
|
||||
file(GLOB_RECURSE TEST_SOURCES test/*.cc)
|
||||
foreach(testsourcefile ${TEST_SOURCES})
|
||||
get_filename_component(testname ${testsourcefile} NAME_WE)
|
||||
add_executable(${testname} ${testsourcefile})
|
||||
target_link_libraries(${testname} InfiniTensor gtest_main gtest)
|
||||
add_test(NAME ${testname} COMMAND ${testname})
|
||||
endforeach(testsourcefile ${TEST_SOURCES})
|
||||
endif()
|
||||
|
|
@ -0,0 +1,32 @@
|
|||
#pragma once
|
||||
#include <cassert>
|
||||
#include <iostream>
|
||||
#include <list>
|
||||
#include <map>
|
||||
#include <optional>
|
||||
#include <set>
|
||||
#include <sstream>
|
||||
#include <string>
|
||||
#include <tuple>
|
||||
#include <unordered_map>
|
||||
#include <unordered_set>
|
||||
#include <vector>
|
||||
|
||||
namespace it {
|
||||
using std::list;
|
||||
using std::map;
|
||||
using std::nullopt;
|
||||
using std::optional;
|
||||
using std::pair;
|
||||
using std::set;
|
||||
using std::string;
|
||||
using std::tie;
|
||||
using std::to_string;
|
||||
using std::tuple;
|
||||
using std::unordered_map;
|
||||
using std::vector;
|
||||
|
||||
// Aliases
|
||||
using dtype = float;
|
||||
|
||||
} // namespace it
|
||||
|
|
@ -0,0 +1,36 @@
|
|||
#pragma once
|
||||
#include "core/operator.h"
|
||||
#include "core/tensor.h"
|
||||
|
||||
namespace it {
|
||||
|
||||
class GraphNode : public Object {
|
||||
protected:
|
||||
TensorVec tensors;
|
||||
TensorVec inputs;
|
||||
TensorVec outputs;
|
||||
OpVec ops;
|
||||
|
||||
public:
|
||||
// Graph(OpVec oplist);
|
||||
string toString() const override;
|
||||
|
||||
void addOp(Operator op) { ops.push_back(op); };
|
||||
const TensorVec &getTensors() const { return tensors; }
|
||||
const TensorVec &getInputs() const { return inputs; }
|
||||
const TensorVec &getOutputs() const { return outputs; }
|
||||
const OpVec &getOperators() const { return ops; }
|
||||
// TensorVec &getInputs();
|
||||
// TensorVec &getOutputs();
|
||||
|
||||
void updateConnection();
|
||||
|
||||
// TODO
|
||||
// bool compute();
|
||||
|
||||
// TODO: move to another class
|
||||
// bool exportOnnx(const char *path);
|
||||
// bool importOnnx(const char *net);
|
||||
};
|
||||
|
||||
} // namespace it
|
||||
|
|
@ -0,0 +1,45 @@
|
|||
#pragma once
|
||||
#include "core/common.h"
|
||||
|
||||
namespace it {
|
||||
|
||||
using GuidBaseType = int;
|
||||
|
||||
class Guid {
|
||||
private:
|
||||
GuidBaseType guid;
|
||||
|
||||
private:
|
||||
GuidBaseType generateGuid() {
|
||||
static GuidBaseType guidCnt = 0;
|
||||
return ++guidCnt;
|
||||
}
|
||||
|
||||
public:
|
||||
Guid() { guid = generateGuid(); }
|
||||
Guid(const Guid &rhs) { guid = generateGuid(); }
|
||||
Guid &operator=(const Guid &rhs) {
|
||||
guid = generateGuid();
|
||||
return *this;
|
||||
}
|
||||
|
||||
operator GuidBaseType() const { return guid; }
|
||||
};
|
||||
|
||||
class Object {
|
||||
protected:
|
||||
Guid guid;
|
||||
|
||||
public:
|
||||
virtual ~Object(){};
|
||||
virtual string toString() const = 0;
|
||||
void print() { std::cout << toString() << std::endl; }
|
||||
Guid getGuid() const { return guid; }
|
||||
};
|
||||
|
||||
inline std::ostream &operator<<(std::ostream &os, const Object &obj) {
|
||||
os << obj.toString();
|
||||
return os;
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,21 @@
|
|||
#pragma once
|
||||
#include "core/tensor.h"
|
||||
|
||||
namespace it {
|
||||
|
||||
class OperatorNode : public Object {
|
||||
protected:
|
||||
// OpType type;
|
||||
TensorVec inputs;
|
||||
TensorVec outputs;
|
||||
// vector<WRef<Operator>> predecessors;
|
||||
// vector<WRef<Operator>> successors;
|
||||
public:
|
||||
OperatorNode(TensorVec inputs, TensorVec outputs)
|
||||
: inputs(inputs), outputs(outputs) {}
|
||||
string toString() const override;
|
||||
// Operator(TensorVec inputs) : inputs(inputs) {}
|
||||
|
||||
virtual ~OperatorNode() {}
|
||||
};
|
||||
} // namespace it
|
||||
|
|
@ -0,0 +1,27 @@
|
|||
#pragma once
|
||||
#include "common.h"
|
||||
#include <functional> // hash
|
||||
#include <memory>
|
||||
#include <type_traits>
|
||||
|
||||
namespace it {
|
||||
|
||||
template <typename T> using Ref = std::shared_ptr<T>;
|
||||
template <typename T> using WRef = std::weak_ptr<T>;
|
||||
|
||||
template <typename T> struct is_ref : std::false_type {};
|
||||
template <typename T> struct is_ref<Ref<T>> : std::true_type {};
|
||||
template <typename T> struct is_ref<WRef<T>> : std::true_type {};
|
||||
|
||||
template <typename T, typename... Params> Ref<T> make_ref(Params &&...params) {
|
||||
static_assert(is_ref<T>::value == false, "Ref should not be nested");
|
||||
return std::make_shared<T>(std::forward<Params>(params)...);
|
||||
}
|
||||
|
||||
template <class T, class U,
|
||||
typename std::enable_if_t<std::is_base_of_v<U, T>> * = nullptr>
|
||||
Ref<T> as(const Ref<U> &ref) {
|
||||
return std::dynamic_pointer_cast<T>(ref);
|
||||
}
|
||||
|
||||
} // namespace it
|
||||
|
|
@ -0,0 +1,368 @@
|
|||
#pragma once
|
||||
#include "core/object.h"
|
||||
#include "core/ref.h"
|
||||
|
||||
namespace it {
|
||||
|
||||
// class Tensor;
|
||||
class TensorBaseNode;
|
||||
class OperatorNode;
|
||||
class GraphNode;
|
||||
|
||||
using TensorBase = Ref<TensorBaseNode>;
|
||||
using Operator = Ref<OperatorNode>;
|
||||
using Graph = Ref<GraphNode>;
|
||||
|
||||
using TensorVec = vector<TensorBase>;
|
||||
using OpVec = vector<Operator>;
|
||||
|
||||
// using TensorMap = std::map<size_t, Tensor *>;
|
||||
// using OpMap = std::map<size_t, Operator *>;
|
||||
using VType = uint32_t;
|
||||
// using SplittingPoints = std::vector<std::vector<int>>;
|
||||
|
||||
class TensorBaseNode : public Object {
|
||||
public:
|
||||
enum DataType {
|
||||
Float32,
|
||||
Int32,
|
||||
};
|
||||
|
||||
// enum TensorType {
|
||||
// Input,
|
||||
// Weight,
|
||||
// Invalid,
|
||||
// NotCounted,
|
||||
// };
|
||||
|
||||
// // TODO: is more compute state needed?
|
||||
// enum ComputeState {
|
||||
// NotComputed,
|
||||
// // Allocated,
|
||||
// // Initialized,
|
||||
// // ComputedPartial,
|
||||
// ComputedFull,
|
||||
// };
|
||||
|
||||
private:
|
||||
int hid;
|
||||
// uint64_t hash;
|
||||
// Shape shape;
|
||||
int dim;
|
||||
|
||||
vector<WRef<TensorBase>> inputOf;
|
||||
WRef<TensorBase> outputOf;
|
||||
Ref<VType> data;
|
||||
DataType dtype;
|
||||
// ComputeState computed;
|
||||
// static int random_seed[256 * 16];
|
||||
// static bool random_inited;
|
||||
|
||||
public:
|
||||
// Tensor(TensorType type = Input, DataType dtype = Float32)
|
||||
// : guid(generateGuid()), hash(generateHash()), outputOf(nullptr),
|
||||
// data(nullptr), dtype(dtype), type(type), computed(NotComputed) {}
|
||||
// Tensor(const Dim &dims, TensorType type = Input, DataType dtype =
|
||||
// Float32)
|
||||
// : guid(generateGuid()), hash(generateHash()), dims(dims),
|
||||
// outputOf(nullptr), data(nullptr), dtype(dtype), type(type),
|
||||
// computed(NotComputed) {
|
||||
// itInit();
|
||||
// }
|
||||
// Tensor(const Tensor &rhs) : Tensor(rhs.dims, rhs.type, rhs.dtype) {
|
||||
// outputOf = nullptr;
|
||||
// data = nullptr;
|
||||
// hash = rhs.hash;
|
||||
// dimPenalty = rhs.dimPenalty;
|
||||
// itInit();
|
||||
// }
|
||||
// Tensor(VType scalar, TensorType type = Weight, DataType dtype = Float32)
|
||||
// : guid(generateGuid()), hash(generateHash()), outputOf(nullptr),
|
||||
// data(nullptr), dtype(dtype), type(type), computed(ComputedFull) {
|
||||
// assert(size() == 1);
|
||||
// dataMalloc();
|
||||
// data[0] = scalar;
|
||||
// }
|
||||
virtual ~TensorBaseNode() {}
|
||||
string toString() const override;
|
||||
|
||||
// // inputOf and outputOf will not be cloned
|
||||
// Tensor *clone() {
|
||||
// Tensor *t = new Tensor(*this);
|
||||
// return t;
|
||||
// }
|
||||
|
||||
// void clone(Tensor *t) {
|
||||
// dims = t->dims;
|
||||
// dtype = t->dtype;
|
||||
// type = t->type;
|
||||
// hash = t->hash;
|
||||
// dimPenalty = t->dimPenalty;
|
||||
// }
|
||||
|
||||
DataType getDType() const { return dtype; }
|
||||
|
||||
// uint64_t getHash() const { return hash; }
|
||||
|
||||
// void setInputOf(const OpVec &ops) {
|
||||
// inputOf.clear();
|
||||
// for (const auto &op : ops)
|
||||
// inputOf.emplace_back(op);
|
||||
// }
|
||||
// void addInputOf(Operator op) { inputOf.emplace_back(op); }
|
||||
// void setOutputOf(Operator op) { outputOf = op; }
|
||||
|
||||
// const OpVec &getInputOf() { return inputOf; }
|
||||
// Operator *getOutputOf() { return outputOf; }
|
||||
// std::pair<Operator *, int> getOutputOfWithIndex();
|
||||
|
||||
// bool dataMalloc() {
|
||||
// if (data == nullptr)
|
||||
// data = new VType[size()];
|
||||
// return data != nullptr;
|
||||
// }
|
||||
|
||||
// const Dim &getDims() const { return dims; }
|
||||
// void setDims(const Dim &dms) { dims = dms; }
|
||||
|
||||
// bool dataRand(int seed = 0) {
|
||||
// if (data == nullptr)
|
||||
// data = new VType[size()];
|
||||
// if (!random_inited)
|
||||
// initFastrand();
|
||||
// // srand(seed);
|
||||
// // faster rand generator; parallel
|
||||
// size_t iEnd = size();
|
||||
// // std::cerr << "Init beginned " << std::endl;
|
||||
// #pragma omp parallel for
|
||||
// for (size_t i = 0; i < iEnd; ++i)
|
||||
// data[i] = fastrand(random_seed[omp_get_thread_num() * 16]) %
|
||||
// 10000;
|
||||
// // std::cerr << "Init finished" << std::endl;
|
||||
// computed = ComputedFull;
|
||||
// return true;
|
||||
// }
|
||||
|
||||
// bool setData(VType *dptr) {
|
||||
// if (dptr == nullptr)
|
||||
// return false;
|
||||
// auto sz = size();
|
||||
// #pragma omp parallel for
|
||||
// for (size_t i = 0; i < sz; ++i)
|
||||
// data[i] = dptr[i];
|
||||
// computed = ComputedFull;
|
||||
// return true;
|
||||
// }
|
||||
|
||||
// bool setScalar(VType val) {
|
||||
// if (data == nullptr || !dims.empty())
|
||||
// return false;
|
||||
// data[0] = val;
|
||||
// return true;
|
||||
// }
|
||||
|
||||
// bool setData(const Dim &ds, VType val) {
|
||||
// if (data == nullptr || ds.size() != dims.size())
|
||||
// return false;
|
||||
// data[getOffset(ds)] = val;
|
||||
// return true;
|
||||
// }
|
||||
|
||||
// bool setData(size_t pos, VType val) {
|
||||
// if (data == nullptr || pos >= size())
|
||||
// return false;
|
||||
// data[pos] = val;
|
||||
// return true;
|
||||
// }
|
||||
|
||||
// VType getScalar() { return data == nullptr ? 0 : data[0]; }
|
||||
|
||||
// VType getData(const Dim &ds) {
|
||||
// assert(data != nullptr);
|
||||
// auto offset = getOffset(ds);
|
||||
// return offset == (size_t)-1 ? 0 : data[getOffset(ds)];
|
||||
// }
|
||||
|
||||
// VType getData(size_t pos) {
|
||||
// assert(data != nullptr);
|
||||
// assert(pos < size());
|
||||
// return data[pos];
|
||||
// }
|
||||
|
||||
// VType *getDataPtr() const { return data; }
|
||||
|
||||
// size_t getOffset(const Dim &ds) {
|
||||
// auto nDim = ds.size();
|
||||
// assert(dims.size() == nDim);
|
||||
// if (ds.empty())
|
||||
// return 0;
|
||||
// for (size_t i = 0; i < nDim; ++i)
|
||||
// if (ds[i] < 0 || ds[i] >= dims[i])
|
||||
// return (size_t)-1;
|
||||
// size_t idx = ds[0];
|
||||
// size_t dm = 0;
|
||||
// while (++dm < nDim)
|
||||
// idx = idx * dims[dm] + ds[dm];
|
||||
// return idx;
|
||||
// }
|
||||
|
||||
// VType getBroadcastData(const Dim &ds) {
|
||||
// assert(data != nullptr);
|
||||
// auto offset = getBroadcastOffset(ds);
|
||||
// return offset == (size_t)-1 ? 0 : data[getOffset(ds)];
|
||||
// }
|
||||
|
||||
// VType getBroadcastData(size_t pos) {
|
||||
// assert(data != nullptr);
|
||||
// return data[pos % size()];
|
||||
// }
|
||||
|
||||
// size_t getBroadcastOffset(const Dim &ds) {
|
||||
// assert(ds.size() >= dims.size());
|
||||
// auto nDim = dims.size();
|
||||
// auto nBroadcastDim = ds.size() - nDim;
|
||||
// for (size_t i = 0; i < nDim; ++i)
|
||||
// if (ds[nBroadcastDim + i] < 0 || ds[nBroadcastDim + i] >=
|
||||
// dims[i])
|
||||
// return (size_t)-1;
|
||||
// size_t idx = 0;
|
||||
// for (size_t i = 0; i < nDim; ++i)
|
||||
// idx = idx * dims[i] + ds[nBroadcastDim + i];
|
||||
// return idx;
|
||||
// }
|
||||
|
||||
// void itInit() { it = Dim(dims.size(), 0); }
|
||||
|
||||
// void itReset() {
|
||||
// itInit();
|
||||
// for (size_t i = 0, iEnd = it.size(); i < iEnd; ++i)
|
||||
// it[i] = 0;
|
||||
// }
|
||||
|
||||
// bool itValid() {
|
||||
// if (it.size() != dims.size())
|
||||
// return false;
|
||||
// for (size_t i = 0, iEnd = it.size(); i < iEnd; ++i)
|
||||
// if (it[i] >= dims[i])
|
||||
// return false;
|
||||
// return true;
|
||||
// }
|
||||
|
||||
// const Dim &itGet() { return it; }
|
||||
|
||||
// void itNext() {
|
||||
// auto p = it.size() - 1;
|
||||
// it[p] += 1;
|
||||
// while (p >= 1) {
|
||||
// if (it[p] == dims[p]) {
|
||||
// it[p] = 0;
|
||||
// it[--p] += 1;
|
||||
// } else
|
||||
// break;
|
||||
// }
|
||||
// }
|
||||
|
||||
// size_t size() const {
|
||||
// size_t sz = 1;
|
||||
// auto dm = dims.size();
|
||||
// while (dm > 0)
|
||||
// sz *= dims[--dm];
|
||||
// return sz;
|
||||
// }
|
||||
|
||||
// TensorType getType() const { return type; }
|
||||
// void setType(TensorType ty) { type = ty; }
|
||||
|
||||
// void print() {
|
||||
// if (type == Invalid) {
|
||||
// std::cout << "Invalid tensor" << std::endl;
|
||||
// return;
|
||||
// }
|
||||
|
||||
// if (data == nullptr || dims.size() == 0) {
|
||||
// std::cout << "Empty tensor" << std::endl;
|
||||
// return;
|
||||
// }
|
||||
|
||||
// // TODO: can be uncommented after tensor's compute type is
|
||||
// correctly set if (computed == NotComputed) {
|
||||
// std::cout << "Uncomputed tensor" << std::endl;
|
||||
// return;
|
||||
// }
|
||||
|
||||
// std::cout << "Tensor: " << guid << std::endl;
|
||||
// auto numDims = dims.size();
|
||||
// auto dimSzVec = std::vector<int>(numDims, 1);
|
||||
// dimSzVec[numDims - 1] = dims[numDims - 1];
|
||||
// for (int i = numDims - 1; i != 0; --i)
|
||||
// dimSzVec[i - 1] = dimSzVec[i] * dims[i - 1];
|
||||
// for (size_t i = 0, iEnd = size(); i < iEnd; ++i) {
|
||||
// for (size_t j = 0; j < numDims; ++j) {
|
||||
// if (i % dimSzVec[j] == 0) {
|
||||
// std::cout << "[";
|
||||
// }
|
||||
// }
|
||||
// std::cout << data[i];
|
||||
// for (size_t j = 0; j < numDims; ++j) {
|
||||
// if ((int)i % dimSzVec[j] == dimSzVec[j] - 1) {
|
||||
// std::cout << "]";
|
||||
// }
|
||||
// }
|
||||
// if (i != size() - 1)
|
||||
// std::cout << ", ";
|
||||
// if ((int)i % dimSzVec[numDims - 1] == dimSzVec[numDims - 1] -
|
||||
// 1)
|
||||
// std::cout << std::endl;
|
||||
// }
|
||||
// }
|
||||
|
||||
// static inline void initFastrand() {
|
||||
// assert(omp_get_max_threads() <= 256);
|
||||
// // srand(0); // constant seed for test
|
||||
// // align random_seed to avoid false sharing
|
||||
// for (int i = 0; i < 256 * 16; ++i) {
|
||||
// // random_seed[i] = rand();
|
||||
// // constant random seed for test
|
||||
// random_seed[i] = i;
|
||||
// }
|
||||
// random_inited = true;
|
||||
// }
|
||||
|
||||
// static inline int fastrand(int &g_seed) {
|
||||
// g_seed = (214013 * g_seed + 2531011);
|
||||
// return (g_seed >> 16) & 0x7FFF;
|
||||
// }
|
||||
|
||||
// std::vector<std::vector<int>> const *getSplittingPoints() const {
|
||||
// assert(!splittingPoints.empty());
|
||||
// return &splittingPoints;
|
||||
// }
|
||||
|
||||
// bool setSplittingPoints(std::vector<std::vector<int>> value) {
|
||||
// assert(!value.empty());
|
||||
// splittingPoints = value;
|
||||
// return true;
|
||||
// }
|
||||
|
||||
// void printSplittingPoints() {
|
||||
// if (splittingPoints.empty())
|
||||
// printf("Empty SplittingPoints");
|
||||
// else {
|
||||
// printf("[");
|
||||
// for (auto &vs : splittingPoints) {
|
||||
// printf("[");
|
||||
// for (auto v : vs)
|
||||
// printf("%2d,", v);
|
||||
// printf("],");
|
||||
// }
|
||||
// printf("]");
|
||||
// }
|
||||
// }
|
||||
|
||||
// void initSplittingPoints() {
|
||||
// splittingPoints.resize(getDims().size()); }
|
||||
|
||||
// void printShape();
|
||||
};
|
||||
|
||||
} // namespace it
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
#pragma once
|
||||
#include "core/common.h"
|
||||
#include "gtest/gtest.h"
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
#include "core/graph.h"
|
||||
|
||||
namespace it {
|
||||
|
||||
void GraphNode::updateConnection() {
|
||||
// TODO
|
||||
}
|
||||
|
||||
string GraphNode::toString() const {
|
||||
std::ostringstream oss;
|
||||
oss << "GraphNode: ";
|
||||
return oss.str();
|
||||
}
|
||||
|
||||
} // namespace it
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
#include "core/operator.h"
|
||||
|
||||
namespace it {
|
||||
|
||||
string OperatorNode::toString() const {
|
||||
std::ostringstream oss;
|
||||
oss << "Operator: ";
|
||||
return oss.str();
|
||||
}
|
||||
|
||||
} // namespace it
|
||||
|
|
@ -0,0 +1,8 @@
|
|||
#include <core/tensor.h>
|
||||
namespace it {
|
||||
|
||||
string TensorBaseNode::toString() const {
|
||||
return "TensorBaseNode " + std::to_string(guid);
|
||||
}
|
||||
|
||||
}; // namespace it
|
||||
|
|
@ -0,0 +1,12 @@
|
|||
#include "core/graph.h"
|
||||
#include "test.h"
|
||||
|
||||
namespace it {
|
||||
|
||||
TEST(Graph, build) {
|
||||
Graph g = make_ref<GraphNode>();
|
||||
g->addOp(make_ref<OperatorNode>(TensorVec{}, TensorVec{}));
|
||||
g->print();
|
||||
}
|
||||
|
||||
} // namespace it
|
||||
Loading…
Reference in New Issue