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model_tests.cc
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// Copyright (c) Microsoft Corporation. All rights reserved.
// SPDX-FileCopyrightText: Copyright 2024 Arm Limited and/or its affiliates <[email protected]>
// Licensed under the MIT License.
#include <iostream>
#include <iterator>
#include <string>
#include <codecvt>
#include <locale>
#include <filesystem>
#include <utility>
#include <unordered_map>
#include <gtest/gtest.h>
#include "core/session/onnxruntime_c_api.h"
#include "core/session/onnxruntime_cxx_api.h"
#include "core/session/ort_apis.h"
#include "core/session/inference_session.h"
#include "core/session/ort_env.h"
#include "core/providers/tensorrt/tensorrt_provider_options.h"
#include "asserts.h"
#include <core/platform/path_lib.h>
#include "default_providers.h"
#include "test/onnx/TestCase.h"
#ifdef USE_DNNL
#include "core/providers/dnnl/dnnl_provider_factory.h"
#endif
#ifdef USE_NNAPI
#include "core/providers/nnapi/nnapi_provider_factory.h"
#endif
#ifdef USE_VSINPU
#include "core/providers/vsinpu/vsinpu_provider_factory.h"
#endif
#ifdef USE_RKNPU
#include "core/providers/rknpu/rknpu_provider_factory.h"
#endif
#ifdef USE_ACL
#include "core/providers/acl/acl_provider_factory.h"
#endif
#ifdef USE_ARMNN
#include "core/providers/armnn/armnn_provider_factory.h"
#endif
#include "test/common/cuda_op_test_utils.h"
// test infrastructure
#include "test/onnx/testenv.h"
#include "test/onnx/TestCase.h"
#include "test/compare_ortvalue.h"
#include "test/onnx/heap_buffer.h"
#include "test/onnx/onnx_model_info.h"
#include "test/onnx/testcase_request.h"
extern std::unique_ptr<Ort::Env> ort_env;
// asserts that the OrtStatus* result of `status_expr` does not indicate an error
// note: this takes ownership of the OrtStatus* result
#define ASSERT_ORT_STATUS_OK(status_expr) \
do { \
if (OrtStatus* _status = (status_expr); _status != nullptr) { \
std::unique_ptr<OrtStatus, decltype(&OrtApis::ReleaseStatus)> _rel_status{ \
_status, &OrtApis::ReleaseStatus}; \
FAIL() << "OrtStatus error: " << OrtApis::GetErrorMessage(_rel_status.get()); \
} \
} while (false)
using namespace onnxruntime::common;
namespace onnxruntime {
namespace test {
// parameter is provider_name + "_" + model_path
class ModelTest : public testing::TestWithParam<std::basic_string<ORTCHAR_T>> {};
#ifdef GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST
GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(ModelTest);
#endif
void SkipTest(const std::string& reason = "") {
GTEST_SKIP() << "Skipping single test " << reason;
}
TEST_P(ModelTest, Run) {
std::basic_string<ORTCHAR_T> param = GetParam();
size_t pos = param.find(ORT_TSTR("_"));
ASSERT_NE(pos, std::string::npos);
std::string provider_name = ToUTF8String(param.substr(0, pos));
std::basic_string<ORTCHAR_T> model_path = param.substr(pos + 1);
double per_sample_tolerance = 1e-3;
double relative_per_sample_tolerance = 1e-3;
// when cuda or openvino is enabled, set it to a larger value for resolving random MNIST test failure
if (model_path.find(ORT_TSTR("_MNIST")) > 0) {
if (provider_name == "cuda" || provider_name == "openvino" || provider_name == "rocm") {
per_sample_tolerance = 2.5e-2;
relative_per_sample_tolerance = 1e-2;
}
}
std::unique_ptr<OnnxModelInfo> model_info = std::make_unique<OnnxModelInfo>(model_path.c_str());
if (model_info->HasDomain(ONNX_NAMESPACE::AI_ONNX_TRAINING_DOMAIN) ||
model_info->HasDomain(ONNX_NAMESPACE::AI_ONNX_PREVIEW_TRAINING_DOMAIN)) {
SkipTest("it has the training domain. No pipeline should need to run these tests.");
return;
}
auto broken_tests = GetBrokenTests(provider_name);
auto broken_tests_keyword_set = GetBrokenTestsKeyWordSet(provider_name);
std::basic_string<ORTCHAR_T> model_dir;
(void)GetDirNameFromFilePath(model_path, model_dir);
std::basic_string<PATH_CHAR_TYPE> test_case_name = GetLastComponent(model_dir);
if (test_case_name.compare(0, 5, ORT_TSTR("test_")) == 0)
test_case_name = test_case_name.substr(5);
{
BrokenTest t = {ToUTF8String(test_case_name), ""};
auto iter = broken_tests->find(t);
auto opset_version = model_info->GetNominalOpsetVersion();
if (iter != broken_tests->end() &&
(opset_version == TestModelInfo::unknown_version || iter->broken_opset_versions_.empty() ||
iter->broken_opset_versions_.find(opset_version) != iter->broken_opset_versions_.end())) {
SkipTest("It's in broken_tests");
return;
}
for (auto iter2 = broken_tests_keyword_set->begin(); iter2 != broken_tests_keyword_set->end(); ++iter2) {
std::string keyword = *iter2;
if (ToUTF8String(test_case_name).find(keyword) != std::string::npos) {
SkipTest("It's in broken_tests_keyword");
return;
}
}
}
// TODO(leca): move the parallel run test list to a config file and load it in GetParameterStrings() to make the load process run only once
std::set<std::string> tests_run_parallel = {"test_resnet18v2",
"test_resnet34v2",
"test_resnet50",
"test_resnet50v2",
"test_resnet101v2",
"test_resnet152v2",
"keras_lotus_resnet3D",
"coreml_Resnet50_ImageNet",
"mlperf_mobilenet",
"mlperf_resnet",
"mlperf_ssd_mobilenet_300",
"mlperf_ssd_resnet34_1200"};
bool is_single_node = !model_info->GetNodeName().empty();
std::vector<ExecutionMode> execution_modes = {ExecutionMode::ORT_SEQUENTIAL};
if (provider_name == "cpu" && !is_single_node)
execution_modes.push_back(ExecutionMode::ORT_PARALLEL);
std::vector<bool> use_single_thread{false};
// Test the model with intra op threadpool disabled
if (provider_name == "cpu" && is_single_node)
use_single_thread.push_back(true);
std::unique_ptr<ITestCase> l = CreateOnnxTestCase(ToUTF8String(test_case_name), std::move(model_info),
per_sample_tolerance, relative_per_sample_tolerance);
#ifndef USE_DNNL
auto tp = TestEnv::CreateThreadPool(Env::Default());
#endif
for (bool is_single_thread : use_single_thread) {
for (ExecutionMode execution_mode : execution_modes) {
Ort::SessionOptions ortso{};
if (!is_single_thread) {
ortso.DisablePerSessionThreads();
} else {
ortso.SetIntraOpNumThreads(1);
}
ortso.SetExecutionMode(execution_mode);
ortso.SetLogId(ToUTF8String(test_case_name).c_str());
ortso.SetLogSeverityLevel(ORT_LOGGING_LEVEL_ERROR);
if (provider_name == "cuda") {
OrtCUDAProviderOptionsV2* cuda_options = nullptr;
ASSERT_ORT_STATUS_OK(OrtApis::CreateCUDAProviderOptions(&cuda_options));
std::unique_ptr<OrtCUDAProviderOptionsV2, decltype(&OrtApis::ReleaseCUDAProviderOptions)> rel_cuda_options(
cuda_options, &OrtApis::ReleaseCUDAProviderOptions);
std::vector<const char*> keys{"device_id", "use_tf32"};
std::vector<const char*> values;
std::string device_id = Env::Default().GetEnvironmentVar("ONNXRUNTIME_TEST_GPU_DEVICE_ID");
values.push_back(device_id.empty() ? "0" : device_id.c_str());
values.push_back("0");
ASSERT_ORT_STATUS_OK(OrtApis::UpdateCUDAProviderOptions(cuda_options, keys.data(), values.data(), 2));
ortso.AppendExecutionProvider_CUDA_V2(*cuda_options);
} else if (provider_name == "rocm") {
OrtROCMProviderOptions ep_options;
ortso.AppendExecutionProvider_ROCM(ep_options);
}
#ifdef USE_DNNL
else if (provider_name == "dnnl") {
OrtDnnlProviderOptions* ep_option;
ASSERT_ORT_STATUS_OK(OrtApis::CreateDnnlProviderOptions(&ep_option));
std::unique_ptr<OrtDnnlProviderOptions, decltype(&OrtApis::ReleaseDnnlProviderOptions)>
rel_dnnl_options(ep_option, &OrtApis::ReleaseDnnlProviderOptions);
ep_option->use_arena = 0;
ASSERT_ORT_STATUS_OK(OrtApis::SessionOptionsAppendExecutionProvider_Dnnl(ortso, ep_option));
}
#endif
else if (provider_name == "tensorrt") {
if (test_case_name.find(ORT_TSTR("FLOAT16")) != std::string::npos) {
OrtTensorRTProviderOptionsV2 params;
ortso.AppendExecutionProvider_TensorRT_V2(params);
} else {
OrtTensorRTProviderOptionsV2* ep_option = nullptr;
ASSERT_ORT_STATUS_OK(OrtApis::CreateTensorRTProviderOptions(&ep_option));
std::unique_ptr<OrtTensorRTProviderOptionsV2, decltype(&OrtApis::ReleaseTensorRTProviderOptions)>
rel_cuda_options(ep_option, &OrtApis::ReleaseTensorRTProviderOptions);
ortso.AppendExecutionProvider_TensorRT_V2(*ep_option);
}
// Enable CUDA fallback
OrtCUDAProviderOptionsV2* cuda_options = nullptr;
ASSERT_ORT_STATUS_OK(OrtApis::CreateCUDAProviderOptions(&cuda_options));
std::unique_ptr<OrtCUDAProviderOptionsV2, decltype(&OrtApis::ReleaseCUDAProviderOptions)> rel_cuda_options(
cuda_options, &OrtApis::ReleaseCUDAProviderOptions);
std::vector<const char*> keys{"device_id", "use_tf32"};
std::vector<const char*> values;
std::string device_id = Env::Default().GetEnvironmentVar("ONNXRUNTIME_TEST_GPU_DEVICE_ID");
values.push_back(device_id.empty() ? "0" : device_id.c_str());
values.push_back("0");
ASSERT_ORT_STATUS_OK(OrtApis::UpdateCUDAProviderOptions(cuda_options, keys.data(), values.data(), 2));
ortso.AppendExecutionProvider_CUDA_V2(*cuda_options);
} else if (provider_name == "migraphx") {
OrtMIGraphXProviderOptions ep_options;
ortso.AppendExecutionProvider_MIGraphX(ep_options);
} else if (provider_name == "openvino") {
OrtOpenVINOProviderOptions ep_options;
ortso.AppendExecutionProvider_OpenVINO(ep_options);
}
#ifdef USE_NNAPI
else if (provider_name == "nnapi") {
ASSERT_ORT_STATUS_OK(OrtSessionOptionsAppendExecutionProvider_Nnapi(ortso, 0));
}
#endif
#ifdef USE_VSINPU
else if (provider_name == "vsinpu") {
ASSERT_ORT_STATUS_OK(OrtSessionOptionsAppendExecutionProvider_VSINPU(ortso));
}
#endif
#ifdef USE_RKNPU
else if (provider_name == "rknpu") {
ASSERT_ORT_STATUS_OK(OrtSessionOptionsAppendExecutionProvider_Rknpu(ortso));
}
#endif
#ifdef USE_ACL
else if (provider_name == "acl") {
ASSERT_ORT_STATUS_OK(OrtSessionOptionsAppendExecutionProvider_ACL(ortso, false));
}
#endif
#ifdef USE_ARMNN
else if (provider_name == "armnn") {
ASSERT_ORT_STATUS_OK(OrtSessionOptionsAppendExecutionProvider_ArmNN(ortso));
}
#endif
#ifdef USE_XNNPACK
else if (provider_name == "xnnpack") {
ortso.AppendExecutionProvider("XNNPACK");
}
#endif
OrtSession* ort_session;
OrtStatus* ort_st = OrtApis::CreateSession(*ort_env, model_path.c_str(), ortso, &ort_session);
if (ort_st != nullptr) {
OrtErrorCode error_code = OrtApis::GetErrorCode(ort_st);
if (error_code == ORT_NOT_IMPLEMENTED) {
OrtApis::ReleaseStatus(ort_st);
continue;
}
FAIL() << OrtApis::GetErrorMessage(ort_st);
}
std::unique_ptr<OrtSession, decltype(&OrtApis::ReleaseSession)> rel_ort_session(ort_session,
&OrtApis::ReleaseSession);
const size_t data_count = l->GetDataCount();
#ifndef USE_DNNL // potential crash for DNNL pipeline
if (data_count > 1 && tests_run_parallel.find(l->GetTestCaseName()) != tests_run_parallel.end()) {
LOGS_DEFAULT(ERROR) << "Parallel test for " << l->GetTestCaseName(); // TODO(leca): change level to INFO or even delete the log once verified parallel test working
std::shared_ptr<TestCaseResult> results = TestCaseRequestContext::Run(tp.get(), *l, *ort_env, ortso, data_count, 1 /*repeat_count*/);
for (EXECUTE_RESULT res : results->GetExcutionResult()) {
EXPECT_EQ(res, EXECUTE_RESULT::SUCCESS) << "is_single_thread:" << is_single_thread << ", execution_mode:" << execution_mode << ", provider_name:"
<< provider_name << ", test name:" << results->GetName() << ", result: " << res;
}
continue;
}
#endif // !USE_DNNL
// TODO(leca): leverage TestCaseRequestContext::Run() to make it short
auto default_allocator = std::make_unique<MockedOrtAllocator>();
for (size_t task_id = 0; task_id != data_count; ++task_id) {
onnxruntime::test::HeapBuffer holder;
std::unordered_map<std::string, Ort::Value> feeds;
l->LoadTestData(task_id, holder, feeds, true);
size_t output_count;
ASSERT_ORT_STATUS_OK(OrtApis::SessionGetOutputCount(ort_session, &output_count));
// Create output feed
std::vector<char*> output_names(output_count);
for (size_t i = 0; i != output_count; ++i) {
ASSERT_ORT_STATUS_OK(
OrtApis::SessionGetOutputName(ort_session, i, default_allocator.get(), &output_names[i]));
}
std::vector<const char*> input_names;
std::vector<OrtValue*> input_values;
std::vector<OrtValue*> output_values(output_count);
{
for (auto& p : feeds) {
input_names.push_back(p.first.c_str());
input_values.push_back(p.second);
}
ort_st = OrtApis::Run(ort_session, nullptr, input_names.data(), input_values.data(), input_values.size(),
output_names.data(), output_names.size(), output_values.data());
if (ort_st != nullptr) {
OrtErrorCode error_code = OrtApis::GetErrorCode(ort_st);
if (error_code == ORT_NOT_IMPLEMENTED) {
OrtApis::ReleaseStatus(ort_st);
for (char* p : output_names) {
default_allocator->Free(p);
}
for (OrtValue* v : output_values) {
OrtApis::ReleaseValue(v);
}
}
FAIL() << OrtApis::GetErrorMessage(ort_st);
}
}
bool post_procesing = false;
Status status;
l->GetPerSampleTolerance(&per_sample_tolerance);
l->GetRelativePerSampleTolerance(&relative_per_sample_tolerance);
l->GetPostProcessing(&post_procesing);
// TODO: if there are no output value files, just skip the validation
std::unordered_map<std::string, Ort::Value> expected_output_values;
l->LoadTestData(task_id, holder, expected_output_values, false);
std::unordered_map<std::string, OrtValue*> name_fetch_output_map;
std::unordered_map<std::string, const ONNX_NAMESPACE::ValueInfoProto*> name_output_value_info_proto;
size_t i = 0;
for (auto& output_name : output_names) {
// p_fetches is filled in the order of output_names.
name_fetch_output_map[output_name] = output_values[i];
const ONNX_NAMESPACE::ValueInfoProto* infoProto = l->GetOutputInfoFromModel(i);
if (infoProto != nullptr)
name_output_value_info_proto.insert(std::make_pair(infoProto->name(), infoProto));
i++;
}
for (auto& output : expected_output_values) {
const OrtValue* expected_output_value = output.second;
const std::string& output_name = output.first;
auto iter = name_fetch_output_map.find(output_name);
ASSERT_NE(iter, name_fetch_output_map.end());
OrtValue* actual_output_value = iter->second;
std::pair<COMPARE_RESULT, std::string> ret =
CompareOrtValue(*actual_output_value, *expected_output_value, per_sample_tolerance,
relative_per_sample_tolerance, post_procesing);
COMPARE_RESULT compare_result = ret.first;
ASSERT_EQ(COMPARE_RESULT::SUCCESS, ret.first) << ret.second;
const ONNX_NAMESPACE::ValueInfoProto* v = name_output_value_info_proto[output_name];
if (v == nullptr)
continue;
ret = VerifyValueInfo(*v, actual_output_value);
compare_result = ret.first;
ASSERT_EQ(COMPARE_RESULT::SUCCESS, ret.first) << ret.second;
if (compare_result != COMPARE_RESULT::SUCCESS) {
break;
}
}
for (char* p : output_names) {
default_allocator->Free(p);
}
for (OrtValue* v : output_values) {
OrtApis::ReleaseValue(v);
}
}
}
}
}
using ORT_STRING_VIEW = std::basic_string_view<ORTCHAR_T>;
static constexpr ORT_STRING_VIEW opset7 = ORT_TSTR("opset7");
static constexpr ORT_STRING_VIEW opset8 = ORT_TSTR("opset8");
static constexpr ORT_STRING_VIEW opset9 = ORT_TSTR("opset9");
static constexpr ORT_STRING_VIEW opset10 = ORT_TSTR("opset10");
static constexpr ORT_STRING_VIEW opset11 = ORT_TSTR("opset11");
static constexpr ORT_STRING_VIEW opset12 = ORT_TSTR("opset12");
static constexpr ORT_STRING_VIEW opset13 = ORT_TSTR("opset13");
static constexpr ORT_STRING_VIEW opset14 = ORT_TSTR("opset14");
static constexpr ORT_STRING_VIEW opset15 = ORT_TSTR("opset15");
static constexpr ORT_STRING_VIEW opset16 = ORT_TSTR("opset16");
static constexpr ORT_STRING_VIEW opset17 = ORT_TSTR("opset17");
static constexpr ORT_STRING_VIEW opset18 = ORT_TSTR("opset18");
// TODO: enable opset19 tests
// static constexpr ORT_STRING_VIEW opset19 = ORT_TSTR("opset19");
static constexpr ORT_STRING_VIEW provider_name_cpu = ORT_TSTR("cpu");
static constexpr ORT_STRING_VIEW provider_name_tensorrt = ORT_TSTR("tensorrt");
#ifdef USE_MIGRAPHX
static constexpr ORT_STRING_VIEW provider_name_migraphx = ORT_TSTR("migraphx");
#endif
static constexpr ORT_STRING_VIEW provider_name_openvino = ORT_TSTR("openvino");
static constexpr ORT_STRING_VIEW provider_name_cuda = ORT_TSTR("cuda");
static constexpr ORT_STRING_VIEW provider_name_rocm = ORT_TSTR("rocm");
static constexpr ORT_STRING_VIEW provider_name_dnnl = ORT_TSTR("dnnl");
// For any non-Android system, NNAPI will only be used for ort model converter
#if defined(USE_NNAPI) && defined(__ANDROID__)
static constexpr ORT_STRING_VIEW provider_name_nnapi = ORT_TSTR("nnapi");
#endif
#ifdef USE_VSINPU
static ORT_STRING_VIEW provider_name_vsinpu = ORT_TSTR("vsinpu");
#endif
#ifdef USE_RKNPU
static constexpr ORT_STRING_VIEW provider_name_rknpu = ORT_TSTR("rknpu");
#endif
#ifdef USE_ACL
static constexpr ORT_STRING_VIEW provider_name_acl = ORT_TSTR("acl");
#endif
#ifdef USE_ARMNN
static constexpr ORT_STRING_VIEW provider_name_armnn = ORT_TSTR("armnn");
#endif
#ifdef USE_XNNPACK
static constexpr ORT_STRING_VIEW provider_name_xnnpack = ORT_TSTR("xnnpack");
#endif
static constexpr ORT_STRING_VIEW provider_name_dml = ORT_TSTR("dml");
::std::vector<::std::basic_string<ORTCHAR_T>> GetParameterStrings() {
// Map key is provider name(CPU, CUDA, etc). Value is the ONNX node tests' opsets to run.
std::map<ORT_STRING_VIEW, std::vector<ORT_STRING_VIEW>> provider_names;
// The default CPU provider always supports all opsets, and must maintain backwards compatibility.
provider_names[provider_name_cpu] = {opset7, opset8, opset9, opset10, opset11, opset12, opset13, opset14, opset15, opset16, opset17, opset18};
// The other EPs can choose which opsets to test.
// If an EP doesn't have any CI build pipeline, then there is no need to specify any opset.
#ifdef USE_TENSORRT
// tensorrt: only enable opset 14 to 17 of onnx tests
provider_names[provider_name_tensorrt] = {opset14, opset15, opset16, opset17};
#endif
#ifdef USE_MIGRAPHX
provider_names[provider_name_migraphx] = {opset7, opset8, opset9, opset10, opset11, opset12, opset13, opset14, opset15, opset16, opset17, opset18};
#endif
#ifdef USE_OPENVINO
provider_names[provider_name_openvino] = {};
#endif
#ifdef USE_CUDA
provider_names[provider_name_cuda] = {opset7, opset8, opset9, opset10, opset11, opset12, opset13, opset14, opset15, opset16, opset17, opset18};
#endif
#ifdef USE_ROCM
provider_names[provider_name_rocm] = {opset7, opset8, opset9, opset10, opset11, opset12, opset13, opset14, opset15, opset16, opset17, opset18};
#endif
#ifdef USE_DNNL
provider_names[provider_name_dnnl] = {opset10};
#endif
// For any non-Android system, NNAPI will only be used for ort model converter
#if defined(USE_NNAPI) && defined(__ANDROID__)
provider_names[provider_name_nnapi] = {opset7, opset8, opset9, opset10, opset11, opset12, opset13, opset14, opset15, opset16, opset17, opset18};
#endif
#ifdef USE_VSINPU
provider_names[provider_name_vsinpu] = {};
#endif
#ifdef USE_RKNPU
provider_names[provider_name_rknpu] = {};
#endif
#ifdef USE_ACL
provider_names[provider_name_acl] = {};
#endif
#ifdef USE_ARMNN
provider_names[provider_name_armnn] = {};
#endif
#ifdef USE_DML
provider_names[provider_name_dml] = {opset7, opset8, opset9, opset10, opset11, opset12, opset13, opset14, opset15, opset16, opset17, opset18};
#endif
#ifdef USE_XNNPACK
provider_names[provider_name_xnnpack] = {opset12, opset13, opset14, opset15, opset16, opset17, opset18};
#endif
#if defined(ENABLE_TRAINING_CORE) && defined(USE_CUDA)
// Removing the CPU EP tests from CUDA build for training as these tests are already run in the CPU pipelines.
// Note: These are inference tests, we run these in training builds as an extra check. Therefore reducing
// the number of times these are run to reduce the CI time.
provider_names.erase(provider_name_cpu);
#endif
std::vector<std::basic_string<ORTCHAR_T>> v;
// Permanently exclude following tests because ORT support only opset starting from 7,
// Please make no more changes to the list
static const ORTCHAR_T* immutable_broken_tests[] = {
ORT_TSTR("AvgPool1d"),
ORT_TSTR("AvgPool1d_stride"),
ORT_TSTR("AvgPool2d"),
ORT_TSTR("AvgPool2d_stride"),
ORT_TSTR("AvgPool3d"),
ORT_TSTR("AvgPool3d_stride"),
ORT_TSTR("AvgPool3d_stride1_pad0_gpu_input"),
ORT_TSTR("BatchNorm1d_3d_input_eval"),
ORT_TSTR("BatchNorm2d_eval"),
ORT_TSTR("BatchNorm2d_momentum_eval"),
ORT_TSTR("BatchNorm3d_eval"),
ORT_TSTR("BatchNorm3d_momentum_eval"),
ORT_TSTR("GLU"),
ORT_TSTR("GLU_dim"),
ORT_TSTR("Linear"),
ORT_TSTR("PReLU_1d"),
ORT_TSTR("PReLU_1d_multiparam"),
ORT_TSTR("PReLU_2d"),
ORT_TSTR("PReLU_2d_multiparam"),
ORT_TSTR("PReLU_3d"),
ORT_TSTR("PReLU_3d_multiparam"),
ORT_TSTR("PoissonNLLLLoss_no_reduce"),
ORT_TSTR("Softsign"),
ORT_TSTR("operator_add_broadcast"),
ORT_TSTR("operator_add_size1_broadcast"),
ORT_TSTR("operator_add_size1_right_broadcast"),
ORT_TSTR("operator_add_size1_singleton_broadcast"),
ORT_TSTR("operator_addconstant"),
ORT_TSTR("operator_addmm"),
ORT_TSTR("operator_basic"),
ORT_TSTR("operator_mm"),
ORT_TSTR("operator_non_float_params"),
ORT_TSTR("operator_params"),
ORT_TSTR("operator_pow"),
};
static const ORTCHAR_T* cuda_rocm_flaky_tests[] = {ORT_TSTR("fp16_inception_v1"),
ORT_TSTR("fp16_shufflenet"),
ORT_TSTR("fp16_tiny_yolov2"),
ORT_TSTR("candy"),
ORT_TSTR("tinyyolov3"),
ORT_TSTR("mlperf_ssd_mobilenet_300"),
ORT_TSTR("mlperf_ssd_resnet34_1200"),
ORT_TSTR("tf_inception_v1"),
ORT_TSTR("faster_rcnn"),
ORT_TSTR("split_zero_size_splits"),
ORT_TSTR("convtranspose_3d"),
ORT_TSTR("fp16_test_tiny_yolov2-Candy"),
ORT_TSTR("fp16_coreml_FNS-Candy"),
ORT_TSTR("fp16_test_tiny_yolov2"),
ORT_TSTR("fp16_test_shufflenet"),
ORT_TSTR("keras2coreml_SimpleRNN_ImageNet")};
// For ROCm EP, also disable the following tests due to flakiness,
// mainly with precision issue and random memory access fault.
static const ORTCHAR_T* rocm_disabled_tests[] = {ORT_TSTR("bvlc_alexnet"),
ORT_TSTR("bvlc_reference_caffenet"),
ORT_TSTR("bvlc_reference_rcnn_ilsvrc13"),
ORT_TSTR("coreml_Resnet50_ImageNet"),
ORT_TSTR("mlperf_resnet"),
ORT_TSTR("mobilenetv2-1.0"),
ORT_TSTR("shufflenet"),
// models from model zoo
ORT_TSTR("AlexNet"),
ORT_TSTR("CaffeNet"),
ORT_TSTR("MobileNet v2-7"),
ORT_TSTR("R-CNN ILSVRC13"),
ORT_TSTR("ShuffleNet-v1"),
ORT_TSTR("version-RFB-320"),
ORT_TSTR("version-RFB-640")};
static const ORTCHAR_T* openvino_disabled_tests[] = {
ORT_TSTR("tf_mobilenet_v1_1.0_224"),
ORT_TSTR("bertsquad"),
ORT_TSTR("yolov3"),
ORT_TSTR("LSTM_Seq_lens_unpacked"),
ORT_TSTR("tinyyolov3"),
// ORT_TSTR("faster_rcnn"),
ORT_TSTR("mask_rcnn"),
ORT_TSTR("coreml_FNS-Candy_ImageNet"),
ORT_TSTR("tf_mobilenet_v2_1.0_224"),
ORT_TSTR("tf_mobilenet_v2_1.4_224"),
ORT_TSTR("operator_permute2"),
ORT_TSTR("operator_repeat"),
ORT_TSTR("operator_repeat_dim_overflow"),
ORT_TSTR("mlperf_ssd_resnet34_1200"),
ORT_TSTR("candy"),
ORT_TSTR("cntk_simple_seg"),
// ORT_TSTR("GPT2_LM_HEAD"),
ORT_TSTR("mlperf_ssd_mobilenet_300"),
ORT_TSTR("fp16_coreml_FNS-Candy"),
ORT_TSTR("fp16_test_tiny_yolov2"),
ORT_TSTR("negative_log_likelihood_loss_input_shape_is_NCd1d2d3d4d5_mean_weight"),
ORT_TSTR("negative_log_likelihood_loss_input_shape_is_NCd1d2d3d4d5_mean_weight_expanded"),
ORT_TSTR("negative_log_likelihood_loss_input_shape_is_NCd1d2d3d4d5_none_no_weight"),
ORT_TSTR("negative_log_likelihood_loss_input_shape_is_NCd1d2d3d4d5_none_no_weight_expanded"),
ORT_TSTR("softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight"),
ORT_TSTR("softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_expanded"),
ORT_TSTR("softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_log_prob"),
ORT_TSTR("softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_log_prob_expanded"),
ORT_TSTR("softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight"),
ORT_TSTR("softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_expanded"),
ORT_TSTR("softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_log_prob"),
ORT_TSTR("softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_log_prob_expanded"),
// models from model zoo
ORT_TSTR("Tiny YOLOv3"),
ORT_TSTR("BERT-Squad"),
ORT_TSTR("YOLOv3"),
ORT_TSTR("Candy"),
ORT_TSTR("SSD"),
ORT_TSTR("ResNet101_DUC_HDC-12"),
ORT_TSTR("YOLOv3-12")};
static const ORTCHAR_T* dml_disabled_tests[] = {ORT_TSTR("mlperf_ssd_resnet34_1200"),
ORT_TSTR("mlperf_ssd_mobilenet_300"),
ORT_TSTR("mask_rcnn"),
ORT_TSTR("faster_rcnn"),
ORT_TSTR("tf_pnasnet_large"),
ORT_TSTR("zfnet512"),
ORT_TSTR("keras2coreml_Dense_ImageNet")};
static const ORTCHAR_T* dnnl_disabled_tests[] = {ORT_TSTR("densenet121"),
ORT_TSTR("resnet18v2"),
ORT_TSTR("resnet34v2"),
ORT_TSTR("resnet50v2"),
ORT_TSTR("resnet101v2"),
ORT_TSTR("resnet101v2"),
ORT_TSTR("vgg19"),
ORT_TSTR("dequantizelinear"),
ORT_TSTR("tf_inception_resnet_v2"),
ORT_TSTR("tf_inception_v1"),
ORT_TSTR("tf_inception_v3"),
ORT_TSTR("tf_inception_v4"),
ORT_TSTR("tf_mobilenet_v1_1.0_224"),
ORT_TSTR("tf_mobilenet_v2_1.0_224"),
ORT_TSTR("tf_mobilenet_v2_1.4_224"),
ORT_TSTR("tf_nasnet_large"),
ORT_TSTR("tf_pnasnet_large"),
ORT_TSTR("tf_resnet_v1_50"),
ORT_TSTR("tf_resnet_v1_101"),
ORT_TSTR("tf_resnet_v1_101"),
ORT_TSTR("tf_resnet_v2_101"),
ORT_TSTR("tf_resnet_v2_152"),
ORT_TSTR("batchnorm_example_training_mode"),
ORT_TSTR("batchnorm_epsilon_training_mode"),
ORT_TSTR("mobilenetv2-1.0"),
ORT_TSTR("shufflenet"),
ORT_TSTR("candy"),
ORT_TSTR("range_float_type_positive_delta_expanded"),
ORT_TSTR("range_int32_type_negative_delta_expanded"),
ORT_TSTR("averagepool_2d_ceil"),
ORT_TSTR("maxpool_2d_ceil"),
ORT_TSTR("maxpool_2d_dilations"),
ORT_TSTR("mlperf_ssd_resnet34_1200"),
ORT_TSTR("convtranspose_1d"),
ORT_TSTR("convtranspose_3d"),
ORT_TSTR("maxpool_2d_uint8"),
ORT_TSTR("mul_uint8"),
ORT_TSTR("div_uint8")};
static const ORTCHAR_T* tensorrt_disabled_tests[] = {
ORT_TSTR("YOLOv3-12"), // needs to run symbolic shape inference shape first
ORT_TSTR("SSD-MobilenetV1-12"), // symbolic shape inference shape error
ORT_TSTR("SSD"), // needs to run symbolic shape inference shape first
ORT_TSTR("size") // INVALID_ARGUMENT: Cannot find binding of given name: x
};
std::vector<std::filesystem::path> paths;
for (std::pair<ORT_STRING_VIEW, std::vector<ORT_STRING_VIEW>> kvp : provider_names) {
const ORT_STRING_VIEW provider_name = kvp.first;
// Setup ONNX node tests. The test data is preloaded on our CI build machines.
#if !defined(_WIN32)
ORT_STRING_VIEW node_test_root_path = ORT_TSTR("/data/onnx");
#else
ORT_STRING_VIEW node_test_root_path = ORT_TSTR("c:\\local\\data\\onnx");
#endif
for (auto p : kvp.second) {
// tensorrt ep isn't expected to pass all onnx node tests. exclude and run model tests only.
if (provider_name != provider_name_tensorrt) {
paths.push_back(ConcatPathComponent(node_test_root_path, p));
}
}
// Same as the above, except this one is for large models
#if defined(NDEBUG) || defined(RUN_MODELTEST_IN_DEBUG_MODE)
#ifdef _WIN32
ORT_STRING_VIEW model_test_root_path = ORT_TSTR("..\\models");
// thus, only the root path should be mounted.
ORT_STRING_VIEW model_zoo_path = ORT_TSTR("..\\models\\zoo");
#else
ORT_STRING_VIEW model_test_root_path = ORT_TSTR("../models");
ORT_STRING_VIEW model_zoo_path = ORT_TSTR("../models/zoo");
#endif
for (auto p : kvp.second) {
paths.push_back(ConcatPathComponent(model_test_root_path, p));
paths.push_back(ConcatPathComponent(model_zoo_path, p));
}
#endif
std::unordered_set<std::basic_string<ORTCHAR_T>> all_disabled_tests(std::begin(immutable_broken_tests),
std::end(immutable_broken_tests));
bool provider_cuda_or_rocm = provider_name == provider_name_cuda;
if (provider_name == provider_name_rocm) {
provider_cuda_or_rocm = true;
all_disabled_tests.insert(std::begin(rocm_disabled_tests), std::end(rocm_disabled_tests));
}
if (provider_cuda_or_rocm) {
all_disabled_tests.insert(std::begin(cuda_rocm_flaky_tests), std::end(cuda_rocm_flaky_tests));
} else if (provider_name == provider_name_dml) {
all_disabled_tests.insert(std::begin(dml_disabled_tests), std::end(dml_disabled_tests));
} else if (provider_name == provider_name_dnnl) {
// these models run but disabled tests to keep memory utilization low
// This will be removed after LRU implementation
all_disabled_tests.insert(std::begin(dnnl_disabled_tests), std::end(dnnl_disabled_tests));
} else if (provider_name == provider_name_tensorrt) {
// these models run but disabled tests to keep memory utilization low
// This will be removed after LRU implementation
all_disabled_tests.insert(std::begin(tensorrt_disabled_tests), std::end(tensorrt_disabled_tests));
} else if (provider_name == provider_name_openvino) {
// these models run but disabled tests to keep memory utilization low
// This will be removed after LRU implementation
all_disabled_tests.insert(std::begin(openvino_disabled_tests), std::end(openvino_disabled_tests));
}
#if !defined(__amd64__) && !defined(_M_AMD64)
// out of memory
static const ORTCHAR_T* x86_disabled_tests[] = {ORT_TSTR("BERT_Squad"),
ORT_TSTR("bvlc_alexnet"),
ORT_TSTR("bvlc_reference_caffenet"),
ORT_TSTR("coreml_VGG16_ImageNet"),
ORT_TSTR("VGG 16-fp32"),
ORT_TSTR("VGG 19-caffe2"),
ORT_TSTR("VGG 19-bn"),
ORT_TSTR("VGG 16-bn"),
ORT_TSTR("VGG 19"),
ORT_TSTR("VGG 16"),
ORT_TSTR("faster_rcnn"),
ORT_TSTR("GPT2"),
ORT_TSTR("GPT2_LM_HEAD"),
ORT_TSTR("keras_lotus_resnet3D"),
ORT_TSTR("mlperf_ssd_resnet34_1200"),
ORT_TSTR("mask_rcnn_keras"),
ORT_TSTR("mask_rcnn"),
ORT_TSTR("ssd"),
ORT_TSTR("vgg19"),
ORT_TSTR("zfnet512"),
ORT_TSTR("ResNet101_DUC_HDC"),
ORT_TSTR("ResNet101_DUC_HDC-12"),
ORT_TSTR("FCN ResNet-101"),
ORT_TSTR("SSD")};
all_disabled_tests.insert(std::begin(x86_disabled_tests), std::end(x86_disabled_tests));
#endif
// fp16 models have different outputs with different kinds of hardware. We need to disable all fp16 models
all_disabled_tests.insert(ORT_TSTR("fp16_shufflenet"));
all_disabled_tests.insert(ORT_TSTR("fp16_inception_v1"));
all_disabled_tests.insert(ORT_TSTR("fp16_tiny_yolov2"));
while (!paths.empty()) {
std::filesystem::path node_data_root_path = paths.back();
paths.pop_back();
if (!std::filesystem::exists(node_data_root_path) || !std::filesystem::is_directory(node_data_root_path)) {
continue;
}
for (auto const& dir_entry : std::filesystem::directory_iterator(node_data_root_path)) {
if (dir_entry.is_directory()) {
paths.push_back(dir_entry.path());
continue;
}
const std::filesystem::path& path = dir_entry.path();
if (!path.has_filename() || path.filename().native().compare(0, 1, ORT_TSTR(".")) == 0) {
// Ignore hidden files.
continue;
}
if (path.filename().extension().compare(ORT_TSTR(".onnx")) != 0) {
// Ignore the files that are not ONNX models
continue;
}
std::basic_string<PATH_CHAR_TYPE> test_case_name = path.parent_path().filename().native();
if (test_case_name.compare(0, 5, ORT_TSTR("test_")) == 0)
test_case_name = test_case_name.substr(5);
if (all_disabled_tests.find(test_case_name) != all_disabled_tests.end())
continue;
#ifdef DISABLE_ML_OPS
auto starts_with = [](const std::basic_string<PATH_CHAR_TYPE>& find_in,
const std::basic_string<PATH_CHAR_TYPE>& find_what) {
return find_in.compare(0, find_what.size(), find_what) == 0;
};
if (starts_with(test_case_name, ORT_TSTR("XGBoost_")) || starts_with(test_case_name, ORT_TSTR("coreml_")) ||
starts_with(test_case_name, ORT_TSTR("scikit_")) || starts_with(test_case_name, ORT_TSTR("libsvm_"))) {
continue;
}
#endif
std::basic_ostringstream<PATH_CHAR_TYPE> oss;
oss << provider_name << ORT_TSTR("_") << path.native();
v.emplace_back(oss.str());
}
}
}
return v;
}
auto ExpandModelName = [](const ::testing::TestParamInfo<ModelTest::ParamType>& info) {
// use info.param here to generate the test suffix
std::basic_string<ORTCHAR_T> name = info.param;
// the original name here is the combination of provider name and model path name
// remove the trailing 'xxxxxxx/model.onnx' of name
if (name.size() > 11 && name.substr(name.size() - 11) == ORT_TSTR("/model.onnx")) {
name = name.substr(0, info.param.size() - 11);
}
// remove the trailing 'xxxxxx.onnx' of name
else if (name.size() > 5 && name.substr(name.size() - 5) == ORT_TSTR(".onnx")) {
name = name.substr(0, info.param.size() - 5);
}
// Note: test name only accepts '_' and alphanumeric
// replace '/' or '\' with '_'
std::replace(name.begin(), name.end(), '/', '_');
std::replace(name.begin(), name.end(), '\\', '_');
// in case there's whitespace in directory name
std::replace(name.begin(), name.end(), ' ', '_');
// Note: test name only accepts '_' and alphanumeric
// remove '.', '-', ':'
char chars[] = ".-:()";
for (unsigned int i = 0; i < strlen(chars); ++i) {
name.erase(std::remove(name.begin(), name.end(), chars[i]), name.end());
}
#ifdef _WIN32
// Note: The return value of INSTANTIATE_TEST_SUITE_P accepts std::basic_string<char...>.
// Need conversion of wchar_t to char.
return std::wstring_convert<std::codecvt_utf8<wchar_t>>().to_bytes(name);
#else
return name;
#endif
};
// The optional last argument is a function or functor that generates custom test name suffixes based on the test
// parameters. Specify the last argument to make test name more meaningful and clear instead of just the sequential
// number.
INSTANTIATE_TEST_SUITE_P(ModelTests, ModelTest, testing::ValuesIn(GetParameterStrings()), ExpandModelName);
} // namespace test
} // namespace onnxruntime