test: 支持编译 einnet 单元测试，但不是所有测试都能通过 (#174)
* test: 支持编译 einnet 单元测试，但不是所有测试都能通过 Signed-off-by: YdrMaster <ydrml@hotmail.com> * Fix: locating resource files and skip codegen - Change the path parameters in `matchExprResult` and `checkExprLogSame` to paths relative to the project home - Skip NNetMemboundOp tests as they require codegen --------- Signed-off-by: YdrMaster <ydrml@hotmail.com> Co-authored-by: Haojie Wang <haojie0429@gmail.com> Co-authored-by: Liyan Zheng <liyan-zheng@outlook.com>
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commit
1a6fccccbe
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@ -21,7 +21,6 @@ project(InfiniTensor C CXX)
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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" OFF BUILD_TEST OFF)
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cmake_dependent_option(BUILD_TEST_EINNET "Build tests for EINNET" OFF BUILD_TEST OFF)
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set(DEFAULT_BUILD_TYPE "RelWithDebInfo")
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# Build Type
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@ -95,16 +94,17 @@ add_subdirectory(3rd-party/nlohmann_json_cmake_fetchcontent)
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include_directories(3rd-party/nlohmann_json_cmake_fetchcontent/single_include)
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# TVM backend
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if(BUILD_TEST_EINNET)
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if (NOT TVM_INCLUDE_DIR OR NOT DMLC_INCLUDE_DIR OR NOT DLPACK_INCLUDE_DIR OR NOT DLPACK_INCLUDE_DIR)
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message(FATAL_ERROR "TVM_INCLUDE_DIR, DMLC_INCLUDE_DIR, and DLPACK_INCLUDE_DIR must be set when BUILD_TEST_EINNET is ON")
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endif()
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if(BUILD_NNET AND BUILD_TEST)
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# TVM and DMLC for invoking TVM packed functions
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include_directories(${TVM_INCLUDE_DIR})
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include_directories(${DMLC_INCLUDE_DIR})
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include_directories(${DLPACK_INCLUDE_DIR})
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DDMLC_USE_LOGGING_LIBRARY=\\\<${TVM_INCLUDE_DIR}/tvm/runtime/logging.h\\\> ")
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DINFINI_USE_TVM=1") # Enable TVM codegen kernels
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if (TVM_INCLUDE_DIR AND DMLC_INCLUDE_DIR AND DLPACK_INCLUDE_DIR AND DLPACK_INCLUDE_DIR)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DDMLC_USE_LOGGING_LIBRARY=\\\<${TVM_INCLUDE_DIR}/tvm/runtime/logging.h\\\> ")
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DINFINI_USE_TVM=1") # Enable TVM codegen kernels
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else()
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# message(FATAL_ERROR "TVM_INCLUDE_DIR, DMLC_INCLUDE_DIR, and DLPACK_INCLUDE_DIR must be set when BUILD_NNET AND BUILD_TEST is ON")
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endif()
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endif()
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if(BUILD_TEST)
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@ -130,6 +130,8 @@ if(BUILD_NNET)
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add_compile_definitions(BUILD_NNET=1)
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file(GLOB_RECURSE SRC_NNET src/nnet/*.cc)
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list (APPEND SRC ${SRC_NNET})
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# For locating resource files
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set_source_files_properties(src/nnet/test.cc PROPERTIES COMPILE_OPTIONS "-DINFINI_PROJECT_HOME=${CMAKE_CURRENT_SOURCE_DIR}")
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endif()
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if(USE_CUDA)
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@ -161,7 +163,7 @@ endif()
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target_link_libraries(InfiniTensor pybind11::embed)
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# TVM backend
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if(BUILD_TEST_EINNET)
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if(BUILD_NNET AND BUILD_TEST AND TVM_LIB_DIR)
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target_link_libraries(InfiniTensor ${TVM_LIB_DIR}/libtvm.so)
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endif()
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@ -333,7 +335,7 @@ if(BUILD_TEST)
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if(BUILD_TEST_PET)
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build_test(test/pet/*.cc)
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endif()
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if(BUILD_TEST_EINNET)
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if(BUILD_NNET AND BUILD_TEST)
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build_test(test/nnet/test_*.cc)
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# Build expression reader
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9
Makefile
9
Makefile
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@ -7,12 +7,13 @@ KUNLUN ?= OFF
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INTELCPU ?= off
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BACKTRACE ?= ON
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TEST ?= ON
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NNET ?= OFF
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FORMAT_ORIGIN ?=
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# Docker build options
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DOCKER_NAME ?= infinitensor
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DOCKER_IMAGE_NAME ?= infinitensor
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DOCKER_FILE ?= infinitensor_ubuntu_22.04.dockerfile
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DOCKER_RUN_OPTION ?=
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DOCKER_RUN_OPTION ?=
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# CUDA option.
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ifeq ($(CUDA), ON)
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@ -22,13 +23,13 @@ ifeq ($(CUDA), ON)
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DOCKER_RUN_OPTION += --gpus all -it --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 -v `pwd`:`pwd` -w `pwd`
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endif
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CMAKE_OPT = -DCMAKE_BUILD_TYPE=$(TYPE)
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CMAKE_OPT += -DUSE_CUDA=$(CUDA)
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CMAKE_OPT += -DUSE_BANG=$(BANG)
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CMAKE_OPT += -DUSE_KUNLUN=$(KUNLUN)
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CMAKE_OPT += -DUSE_BACKTRACE=$(BACKTRACE)
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CMAKE_OPT += -DBUILD_TEST=$(TEST)
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CMAKE_OPT += -DBUILD_NNET=$(NNET)
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ifeq ($(INTELCPU), ON)
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CMAKE_OPT += -DUSE_INTELCPU=ON -DCMAKE_CXX_COMPILER=dpcpp
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@ -60,7 +61,7 @@ test-api:
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@echo
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python3 pyinfinitensor/tests/test_api.py
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docker-build:
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docker-build:
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docker build -f scripts/dockerfile/$(DOCKER_FILE) -t $(DOCKER_NAME) .
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docker-run:
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@ -71,5 +72,3 @@ docker-start:
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docker-exec:
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docker exec -it $(DOCKER_IMAGE_NAME) bash
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@ -24,7 +24,7 @@
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// clang-format on
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namespace nnet {
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int matchExprResult(Derivator &derivator, string fn);
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bool checkExprLogSame(string fnPrefix, int start, int end);
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int matchExprResult(Derivator &derivator, string pathRelativeToProjectHome);
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bool checkExprLogSame(string pathRelativeToProjectHome, int start, int end);
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bool checkExprsEquvivalence(VecExpr exprs);
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} // namespace nnet
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@ -3,10 +3,30 @@
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#include "nnet/Visitor/HashVisitor.h"
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#include "nnet/Visitor/Interpreter.h"
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#include "nnet/Visitor/Serializer.h"
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#include <filesystem>
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namespace nnet {
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int matchExprResult(Derivator &derivator, string fn) {
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auto ans = Serializer().deserialize(fn);
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std::filesystem::path getProjectHome() {
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#ifndef INFINI_PROJECT_HOME
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#error INFINI_PROJECT_HOME is not defined
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#endif
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#define Q(x) #x
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#define QUOTE(x) Q(x)
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#define PROJECT_HOME QUOTE(INFINI_PROJECT_HOME)
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return std::filesystem::path(PROJECT_HOME);
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#undef PROJECT_HOME
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#undef QUOTE
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#undef Q
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}
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string getResourceFilePath(string path) {
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return (getProjectHome() / path).string();
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}
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int matchExprResult(Derivator &derivator, string pathRelativeToProjectHome) {
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auto fullPath = getResourceFilePath(pathRelativeToProjectHome);
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auto ans = Serializer().deserialize(fullPath);
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auto hashAns = HashVisitor()(ans);
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int match = 0;
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for (const auto &candidate : derivator.getCandidates()) {
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@ -16,16 +36,17 @@ int matchExprResult(Derivator &derivator, string fn) {
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return match;
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}
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bool checkExprLogSame(string fnPrefix, int start, int end) {
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bool checkExprLogSame(string pathRelativeToProjectHome, int start, int end) {
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auto fullPath = getResourceFilePath(pathRelativeToProjectHome);
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Serializer serializer;
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string fn0 = fnPrefix + to_string(start) + ".expr";
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string fn0 = fullPath + to_string(start) + ".expr";
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Expr expr0 = serializer.deserialize(fn0);
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RangeOp range0 = as<RangeOpNode>(expr0);
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Interpreter interpreter(range0);
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auto ans0 = interpreter.interpretUniformSample(range0);
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dbg(expr0, ans0);
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for (int i = start + 1; i < end; ++i) {
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string fn1 = fnPrefix + to_string(i) + ".expr";
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string fn1 = fullPath + to_string(i) + ".expr";
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Expr expr1 = serializer.deserialize(fn1);
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RangeOp range1 = as<RangeOpNode>(expr1);
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dbg(fn1, expr1);
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@ -67,4 +88,4 @@ bool checkExprsEquvivalence(VecExpr exprs) {
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return true;
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}
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} // namespace nnet
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} // namespace nnet
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@ -85,7 +85,7 @@ TEST_F(OpSearch, Conv2gemm_NCHW_FCRS_search) {
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EXPECT_GE(derivator.getNumCandidates(), 1);
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int nMatches = matchExprResult(
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derivator, "../test/nnet/log/conv2gemm/Conv2gemm_NCHW_FCRS_11.expr");
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derivator, "test/nnet/log/conv2gemm/Conv2gemm_NCHW_FCRS_11.expr");
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EXPECT_GE(nMatches, 1);
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// derivator.print();
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derivator.printStatistics();
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@ -160,7 +160,7 @@ TEST_F(OpSearch, TConv2gemm_TConv4x4_NHWF_RSFC_search) {
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EXPECT_GE(derivator.getNumCandidates(), 1);
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int nMatches = matchExprResult(
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derivator,
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"../test/nnet/log/TConv4x4_NHWF_RSFC/TConv4x4_NHWF_RSFC_18.expr");
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"test/nnet/log/TConv4x4_NHWF_RSFC/TConv4x4_NHWF_RSFC_18.expr");
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EXPECT_GE(nMatches, 1);
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derivator.printStatistics();
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}
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@ -197,8 +197,7 @@ TEST_F(OpSearch, Conv2conv_5x5_RuleBased_NCHW_FCRS) {
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derivator.search(conv_9x9, 0);
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int nMatches = matchExprResult(
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derivator,
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"../test/nnet/log/conv2conv/Conv2conv_5x5_NCHW_FCRS_15.expr");
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derivator, "test/nnet/log/conv2conv/Conv2conv_5x5_NCHW_FCRS_15.expr");
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// derivator.print();
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derivator.printStatistics();
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EXPECT_GE(nMatches, 1);
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@ -236,8 +235,8 @@ TEST_F(OpSearch, G2BMM_RuleBased) {
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EXPECT_GE(derivator.getNumCandidates(), 1);
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int nMatches =
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matchExprResult(derivator, "../test/nnet/log/g2bmm/G2BMM_9.expr");
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matchExprResult(derivator, "test/nnet/log/g2bmm/G2BMM_9.expr");
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EXPECT_GE(nMatches, 1);
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// derivator.print();
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derivator.printStatistics();
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}
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}
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@ -365,14 +365,14 @@ TEST(TConv2gemm, TConv4x4_NHWF_RSFC_search) {
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// }
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int nMatches = matchExprResult(
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derivator,
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"../test/nnet/log/TConv4x4_NHWF_RSFC/TConv4x4_NHWF_RSFC_18.expr");
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"test/nnet/log/TConv4x4_NHWF_RSFC/TConv4x4_NHWF_RSFC_18.expr");
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EXPECT_GE(nMatches, 1);
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derivator.printStatistics();
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}
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TEST(TConv2gemm, TConv4x4_NHWF_FRSC_CheckDerivationCorrectness_log) {
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const string fnPrefix =
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"../test/nnet/log/TConv4x4_NHWF_RSFC/TConv4x4_NHWF_RSFC_";
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"test/nnet/log/TConv4x4_NHWF_RSFC/TConv4x4_NHWF_RSFC_";
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EXPECT_TRUE(checkExprLogSame(fnPrefix, 0, 11));
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}
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@ -388,4 +388,4 @@ TEST(Conv2conv, InfoGAN_ConvTranspose_3_OOB_Test) {
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dbg(expr);
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Derivator derivator;
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derivator.checkOOB(as<RangeOpNode>(expr));
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}
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}
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@ -37,10 +37,8 @@ TEST(Conv2conv, 9x9_NCHW_FCRS) {
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derivator.ruleBasedDFS(conv_9x9, 0, rules, {}, true);
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} else
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derivator.search(conv_9x9, 0);
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int nMatches = matchExprResult(
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derivator,
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"../test/nnet/log/conv2conv/Conv2conv_9x9_NCHW_FCRS_14.expr");
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derivator, "test/nnet/log/conv2conv/Conv2conv_9x9_NCHW_FCRS_14.expr");
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derivator.print();
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derivator.printStatistics();
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EXPECT_GE(nMatches, 1);
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@ -81,8 +79,7 @@ TEST(Conv2conv, 6x6_RuleBased_NCHW_FCRS) {
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ASSERT_GE(derivator.getNumCandidates(), 1);
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int nMatches = matchExprResult(
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derivator,
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"../test/nnet/log/conv2conv/Conv2conv_6x6_NCHW_FCRS_14.expr");
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derivator, "test/nnet/log/conv2conv/Conv2conv_6x6_NCHW_FCRS_14.expr");
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derivator.print();
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derivator.printStatistics();
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EXPECT_GE(nMatches, 1);
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@ -121,9 +118,8 @@ TEST(Conv2conv, 5x5_RuleBased_NCHW_FCRS) {
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derivator.search(conv_9x9, 0);
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int nMatches = matchExprResult(
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derivator,
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"../test/nnet/log/conv2conv/Conv2conv_5x5_NCHW_FCRS_15.expr");
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derivator, "test/nnet/log/conv2conv/Conv2conv_5x5_NCHW_FCRS_15.expr");
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derivator.print();
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derivator.printStatistics();
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EXPECT_GE(nMatches, 1);
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}
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}
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@ -147,7 +147,7 @@ TEST(Conv2gemm, timing_NHWC_RSFC_search) {
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// Conv2gemm requires thorough update, this is disabled temporarily
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TEST(Conv2gemm, CheckCorrectness) {
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const string fnPrefix = "../test/nnet/log/conv2gemm/Conv2gemm_NCHW_RSFC_";
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const string fnPrefix = "test/nnet/log/conv2gemm/Conv2gemm_NCHW_RSFC_";
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// conv2gemm_7 has T3
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EXPECT_TRUE(checkExprLogSame(fnPrefix, 0, 7));
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}
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@ -182,7 +182,7 @@ TEST(Conv2gemm, NCHW_RSFC_search) {
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ASSERT_GE(derivator.getNumCandidates(), 1);
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int nMatches = matchExprResult(
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derivator, "../test/nnet/log/conv2gemm/Conv2gemm_NCHW_RSFC_11.expr");
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derivator, "test/nnet/log/conv2gemm/Conv2gemm_NCHW_RSFC_11.expr");
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EXPECT_GE(nMatches, 1);
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// derivator.print();
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derivator.printStatistics();
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@ -278,6 +278,6 @@ TEST(Conv2gemm1x7, NCHW_FCRS_search) {
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ASSERT_GE(derivator.getNumCandidates(), 1);
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int nMatches = matchExprResult(
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derivator,
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"../test/nnet/log/conv2gemm_1x7/Conv2gemm_1x7_NCHW_FCRS_11.expr");
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"test/nnet/log/conv2gemm_1x7/Conv2gemm_1x7_NCHW_FCRS_11.expr");
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EXPECT_GE(nMatches, 1);
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}
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}
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@ -36,10 +36,8 @@ TEST(GBMM, RuleBased) {
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} else {
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derivator.search(dialted_g2bmm, 0);
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}
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ASSERT_GE(derivator.getNumCandidates(), 1);
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int nMatches =
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matchExprResult(derivator, "../test/nnet/log/gbmm/GBMM_9.expr");
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int nMatches = matchExprResult(derivator, "test/nnet/log/gbmm/GBMM_9.expr");
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EXPECT_GE(nMatches, 1);
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derivator.print();
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derivator.printStatistics();
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@ -78,7 +76,7 @@ TEST(G2BMM, RuleBased) {
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ASSERT_GE(derivator.getNumCandidates(), 1);
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int nMatches =
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matchExprResult(derivator, "../test/nnet/log/g2bmm/G2BMM_9.expr");
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matchExprResult(derivator, "test/nnet/log/g2bmm/G2BMM_9.expr");
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EXPECT_GE(nMatches, 1);
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derivator.print();
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derivator.printStatistics();
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@ -1,3 +1,5 @@
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#ifdef USE_CUDA
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#include "core/graph.h"
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#include "core/runtime.h"
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#include "cuda/cuda_runtime.h"
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@ -12,7 +14,22 @@
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using namespace infini;
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using namespace std;
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TEST(nnet, MemboundOpInterpretation) {
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class NNetMemboundOp : public ::testing::Test {
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protected:
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void SetUp() override {
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if (!hasTVMBackend())
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GTEST_SKIP() << "Skipping test since no TVM backend.\n";
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}
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private:
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static bool hasTVMBackend() {
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// TODO: as the dispatch mechanism of backend is going to change, this
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// function is to be implemented.
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return false;
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}
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};
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TEST_F(NNetMemboundOp, MemboundOpInterpretation) {
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Runtime runtime = NativeCpuRuntimeObj::getInstance();
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Graph g = make_ref<GraphObj>(runtime);
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Tensor i0 = g->addTensor({1, 2, 3}, DataType::UInt32);
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@ -41,7 +58,7 @@ TEST(nnet, MemboundOpInterpretation) {
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EXPECT_TRUE(membound->getOutput()->equalData(ans));
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}
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TEST(nnet, MemboundOp_Ansor_Codegen) {
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TEST_F(NNetMemboundOp, MemboundOp_Ansor_Codegen) {
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auto runtime = make_ref<CudaRuntimeObj>();
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Runtime cpu = NativeCpuRuntimeObj::getInstance();
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Graph gCpu = make_ref<GraphObj>(cpu);
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@ -91,7 +108,7 @@ pair<std::vector<nnet::Tensor>, nnet::Expr> getPReluExpr(int size) {
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return {{A, B}, ret};
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}
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TEST(nnet, PRelu_Ansor_Codegen) {
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TEST_F(NNetMemboundOp, PRelu_Ansor_Codegen) {
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auto cuda = make_ref<CudaRuntimeObj>();
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Runtime cpu = NativeCpuRuntimeObj::getInstance();
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||||
Graph g = make_ref<GraphObj>(cuda);
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@ -116,3 +133,5 @@ TEST(nnet, PRelu_Ansor_Codegen) {
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auto oCpu = gCpu->cloneTensor(o0);
|
||||
EXPECT_TRUE(oCpu->equalData(ans));
|
||||
}
|
||||
|
||||
#endif
|
||||
|
|
|
|||
|
|
@ -1,3 +1,5 @@
|
|||
#ifdef USE_CUDA
|
||||
|
||||
#include "core/blob.h"
|
||||
#include "core/dummy_mutator.h"
|
||||
#include "core/graph.h"
|
||||
|
|
@ -477,3 +479,5 @@ TEST(Mutator, InfoGAN_TConv_3_correctness) {
|
|||
// EXPECT_TRUE(graph->verification(bestGraph.get(), true));
|
||||
// }
|
||||
} // namespace infini
|
||||
|
||||
#endif
|
||||
|
|
|
|||
Loading…
Reference in New Issue