mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-07-29 20:14:01 +00:00
Update UT
This commit is contained in:
Jingyan Wang
parent
7ef865cc35
commit
253a59903e
1 changed files with 43 additions and 29 deletions
|
|
@ -134,21 +134,22 @@ void CreateBaseModel(const PathString& model_name,
|
|||
* All three inputs have the same dimensions.
|
||||
* output: "M"
|
||||
*
|
||||
* "X" "Y"
|
||||
* "X" "Y"
|
||||
* \ /
|
||||
* "Z" Add
|
||||
* "Z" Add
|
||||
* \ /
|
||||
* Add
|
||||
* /
|
||||
* "A" NonZero (This node will be placed on CUDA EP)
|
||||
* \ |
|
||||
* Add
|
||||
* /
|
||||
* "A" NonZero (This node will be placed on CUDA EP)
|
||||
* \ /
|
||||
* Add
|
||||
* |
|
||||
* "M"
|
||||
*/
|
||||
void CreateParititionedModel(const PathString& model_name,
|
||||
std::string graph_name,
|
||||
std::vector<int> dims) {
|
||||
std::vector<int> dims,
|
||||
std::vector<int> dims2) {
|
||||
onnxruntime::Model model(graph_name, false, DefaultLoggingManager().DefaultLogger());
|
||||
auto& graph = model.MainGraph();
|
||||
std::vector<onnxruntime::NodeArg*> inputs;
|
||||
|
|
@ -162,6 +163,13 @@ void CreateParititionedModel(const PathString& model_name,
|
|||
float_tensor.mutable_tensor_type()->mutable_shape()->add_dim()->set_dim_value(dim);
|
||||
}
|
||||
|
||||
// INT tensor
|
||||
ONNX_NAMESPACE::TypeProto int_tensor;
|
||||
int_tensor.mutable_tensor_type()->set_elem_type(ONNX_NAMESPACE::TensorProto_DataType_INT64);
|
||||
for (auto dim : dims2) {
|
||||
int_tensor.mutable_tensor_type()->mutable_shape()->add_dim()->set_dim_value(dim);
|
||||
}
|
||||
|
||||
auto& input_arg_1 = graph.GetOrCreateNodeArg("X", &float_tensor);
|
||||
auto& input_arg_2 = graph.GetOrCreateNodeArg("Y", &float_tensor);
|
||||
inputs.push_back(&input_arg_1);
|
||||
|
|
@ -182,8 +190,6 @@ void CreateParititionedModel(const PathString& model_name,
|
|||
|
||||
inputs.clear();
|
||||
inputs.push_back(&output_arg_2);
|
||||
ONNX_NAMESPACE::TypeProto int_tensor;
|
||||
int_tensor.mutable_tensor_type()->set_elem_type(ONNX_NAMESPACE::TensorProto_DataType_INT64);
|
||||
auto& output_arg_3 = graph.GetOrCreateNodeArg("node_3_out_1", &int_tensor);
|
||||
outputs.clear();
|
||||
outputs.push_back(&output_arg_3);
|
||||
|
|
@ -203,6 +209,7 @@ void CreateParititionedModel(const PathString& model_name,
|
|||
status = onnxruntime::Model::Save(model, model_name);
|
||||
}
|
||||
|
||||
|
||||
std::vector<char> ReadFileFromDisk(const PathString& path) {
|
||||
std::fstream file(path.c_str(), std::fstream::binary | std::fstream::in | std::fstream::ate);
|
||||
std::vector<char> file_bytes;
|
||||
|
|
@ -465,8 +472,11 @@ TEST(TensorrtExecutionProviderTest, EPContextNode) {
|
|||
std::string model_name_str = "EPContextNode_test.onnx";
|
||||
PathString model_name = ToPathString(model_name_str);
|
||||
std::string graph_name = "EPContextNode_test";
|
||||
std::string ctx_model_path = "EP_Context_model.onnx";
|
||||
std::string sess_log_id = "EPContextNode_test";
|
||||
std::vector<int> dims = {1, 3, 2};
|
||||
|
||||
remove(ctx_model_path.c_str()); // remove the context model file generated by previous test
|
||||
CreateBaseModel(model_name, graph_name, dims);
|
||||
|
||||
SessionOptions so;
|
||||
|
|
@ -513,14 +523,14 @@ TEST(TensorrtExecutionProviderTest, EPContextNode) {
|
|||
* context model "EP_Context_model.onnx" should be created in current directory
|
||||
*/
|
||||
(void)so.config_options.AddConfigEntry("ep.context_enable", "1");
|
||||
(void)so.config_options.AddConfigEntry("ep.context_file_path", "EP_Context_model.onnx");
|
||||
(void)so.config_options.AddConfigEntry("ep.context_file_path", ctx_model_path.c_str());
|
||||
(void)so.config_options.AddConfigEntry("ep.context_embed_mode", "0");
|
||||
InferenceSession session_object{so, GetEnvironment()};
|
||||
// Need to set corresponding trt params since options merging logic in privider_bridge_ort is not called in unit test
|
||||
OrtTensorRTProviderOptionsV2 params;
|
||||
params.trt_engine_cache_enable = 1;
|
||||
params.trt_dump_ep_context_model = 1;
|
||||
params.trt_ep_context_file_path = "EP_Context_model.onnx";
|
||||
params.trt_ep_context_file_path = ctx_model_path.c_str();
|
||||
params.trt_ep_context_embed_mode = 0;
|
||||
params.trt_engine_cache_prefix = "TRTEP_Cache_Test";
|
||||
std::unique_ptr<IExecutionProvider> execution_provider = TensorrtExecutionProviderWithOptions(¶ms);
|
||||
|
|
@ -532,7 +542,7 @@ TEST(TensorrtExecutionProviderTest, EPContextNode) {
|
|||
// Engine cache with params.trt_engine_cache_prefix prefix should be created
|
||||
ASSERT_TRUE(HasCacheFileWithPrefix(params.trt_engine_cache_prefix));
|
||||
// EP_Context_model.onnx should be created
|
||||
ASSERT_TRUE(HasCacheFileWithPrefix("EP_Context_model.onnx"));
|
||||
ASSERT_TRUE(HasCacheFileWithPrefix(ctx_model_path));
|
||||
|
||||
/*
|
||||
* Test case 1.2: Run the dumped context model, context saved in engine cache
|
||||
|
|
@ -546,7 +556,7 @@ TEST(TensorrtExecutionProviderTest, EPContextNode) {
|
|||
*/
|
||||
InferenceSession session_object2{so, GetEnvironment()};
|
||||
OrtTensorRTProviderOptionsV2 params2;
|
||||
PathString ctx_model_name = ToPathString("EP_Context_model.onnx");
|
||||
PathString ctx_model_name = ToPathString(ctx_model_path);
|
||||
execution_provider = TensorrtExecutionProviderWithOptions(¶ms2);
|
||||
EXPECT_TRUE(session_object2.RegisterExecutionProvider(std::move(execution_provider)).IsOK());
|
||||
status = session_object2.Load(ctx_model_name);
|
||||
|
|
@ -629,12 +639,13 @@ TEST(TensorrtExecutionProviderTest, EPContextNode) {
|
|||
/*
|
||||
* Test case 3.1: Dump context model with embed_model = 1
|
||||
*/
|
||||
(void)so.config_options.AddConfigEntry("ep.context_file_path", "EP_Context_model_emb.onnx");
|
||||
const std::string ctx_model_path_emb = "EP_Context_model_emb.onnx";
|
||||
(void)so.config_options.AddConfigEntry("ep.context_file_path", ctx_model_path_emb.c_str());
|
||||
(void)so.config_options.AddConfigEntry("ep.context_embed_mode", "1");
|
||||
InferenceSession session_object5{so, GetEnvironment()};
|
||||
OrtTensorRTProviderOptionsV2 params5;
|
||||
params5.trt_dump_ep_context_model = 1;
|
||||
params5.trt_ep_context_file_path = "EP_Context_model_emb.onnx";
|
||||
params5.trt_ep_context_file_path = ctx_model_path_emb.c_str();
|
||||
params5.trt_ep_context_embed_mode = 1;
|
||||
execution_provider = TensorrtExecutionProviderWithOptions(¶ms5);
|
||||
EXPECT_TRUE(session_object5.RegisterExecutionProvider(std::move(execution_provider)).IsOK());
|
||||
|
|
@ -642,7 +653,7 @@ TEST(TensorrtExecutionProviderTest, EPContextNode) {
|
|||
ASSERT_TRUE(status.IsOK());
|
||||
status = session_object5.Initialize();
|
||||
ASSERT_TRUE(status.IsOK());
|
||||
ASSERT_TRUE(HasCacheFileWithPrefix("EP_Context_model_emb.onnx"));
|
||||
ASSERT_TRUE(HasCacheFileWithPrefix(ctx_model_path_emb));
|
||||
|
||||
/*
|
||||
* Test case 3.2: Run context model with embed_model = 1
|
||||
|
|
@ -724,12 +735,14 @@ TEST(TensorrtExecutionProviderTest, EPContextNode) {
|
|||
}
|
||||
|
||||
TEST(TensorrtExecutionProviderTest, EPContextNodeMulti) {
|
||||
std::string model_name_str = "EPContextNode_test.onnx";
|
||||
std::string model_name_str = "EPContextNode_test_multi.onnx";
|
||||
PathString model_name = ToPathString(model_name_str);
|
||||
std::string graph_name = "EPContextNode_test";
|
||||
std::string ctx_model_path = "EP_Context_model_multi.onnx";
|
||||
std::string sess_log_id = "EPContextNode_test";
|
||||
std::vector<int> dims = {1, 3, 2};
|
||||
CreateParititionedModel(model_name, graph_name, dims);
|
||||
std::vector<int> dims2 = {3, 6};
|
||||
CreateParititionedModel(model_name, graph_name, dims, dims2);
|
||||
|
||||
SessionOptions so;
|
||||
so.session_logid = sess_log_id;
|
||||
|
|
@ -740,7 +753,7 @@ TEST(TensorrtExecutionProviderTest, EPContextNodeMulti) {
|
|||
std::vector<int64_t> dims_mul_x = {1, 3, 2};
|
||||
std::vector<int64_t> dims_mul_a = {3, 6};
|
||||
std::vector<float> values_mul_x = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f};
|
||||
std::vector<int> values_mul_a = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17};
|
||||
std::vector<int64_t> values_mul_a = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17};
|
||||
OrtValue ml_value_x;
|
||||
CreateMLValue<float>(cpu_allocator, dims_mul_x, values_mul_x, &ml_value_x);
|
||||
OrtValue ml_value_y;
|
||||
|
|
@ -748,7 +761,7 @@ TEST(TensorrtExecutionProviderTest, EPContextNodeMulti) {
|
|||
OrtValue ml_value_z;
|
||||
CreateMLValue<float>(cpu_allocator, dims_mul_x, values_mul_x, &ml_value_z);
|
||||
OrtValue ml_value_a;
|
||||
CreateMLValue<int>(cpu_allocator, dims_mul_x, values_mul_a, &ml_value_a);
|
||||
CreateMLValue<int64_t>(cpu_allocator, dims_mul_a, values_mul_a, &ml_value_a);
|
||||
NameMLValMap feeds;
|
||||
feeds.insert(std::make_pair("X", ml_value_x));
|
||||
feeds.insert(std::make_pair("Y", ml_value_y));
|
||||
|
|
@ -780,14 +793,14 @@ TEST(TensorrtExecutionProviderTest, EPContextNodeMulti) {
|
|||
* context model "EP_Context_model.onnx" should be created in current directory
|
||||
*/
|
||||
(void)so.config_options.AddConfigEntry("ep.context_enable", "1");
|
||||
(void)so.config_options.AddConfigEntry("ep.context_file_path", "EP_Context_model.onnx");
|
||||
(void)so.config_options.AddConfigEntry("ep.context_file_path", ctx_model_path.c_str());
|
||||
(void)so.config_options.AddConfigEntry("ep.context_embed_mode", "0");
|
||||
InferenceSession session_object{so, GetEnvironment()};
|
||||
// Need to set corresponding trt params since options merging logic in privider_bridge_ort is not called in unit test
|
||||
OrtTensorRTProviderOptionsV2 params;
|
||||
params.trt_engine_cache_enable = 1;
|
||||
params.trt_dump_ep_context_model = 1;
|
||||
params.trt_ep_context_file_path = "EP_Context_model.onnx";
|
||||
params.trt_ep_context_file_path = ctx_model_path.c_str();
|
||||
params.trt_ep_context_embed_mode = 0;
|
||||
std::unique_ptr<IExecutionProvider> execution_provider = TensorrtExecutionProviderWithOptions(¶ms);
|
||||
EXPECT_TRUE(session_object.RegisterExecutionProvider(std::move(execution_provider)).IsOK());
|
||||
|
|
@ -798,7 +811,7 @@ TEST(TensorrtExecutionProviderTest, EPContextNodeMulti) {
|
|||
// Engine cache TensorrtExecutionProvider_*.engine should be created
|
||||
ASSERT_TRUE(HasCacheFileWithPrefix("TensorrtExecutionProvider"));
|
||||
// EP_Context_model.onnx should be created
|
||||
ASSERT_TRUE(HasCacheFileWithPrefix("EP_Context_model.onnx"));
|
||||
ASSERT_TRUE(HasCacheFileWithPrefix(ctx_model_path));
|
||||
|
||||
/*
|
||||
* Test case 1.2: Run the dumped context model, context saved in engine cache
|
||||
|
|
@ -812,10 +825,10 @@ TEST(TensorrtExecutionProviderTest, EPContextNodeMulti) {
|
|||
*/
|
||||
InferenceSession session_object2{so, GetEnvironment()};
|
||||
OrtTensorRTProviderOptionsV2 params2;
|
||||
PathString ctx_model_name = ToPathString("EP_Context_model.onnx");
|
||||
PathString ctx_model_name = ToPathString(ctx_model_path);
|
||||
execution_provider = TensorrtExecutionProviderWithOptions(¶ms2);
|
||||
EXPECT_TRUE(session_object2.RegisterExecutionProvider(std::move(execution_provider)).IsOK());
|
||||
status = session_object2.Load(ctx_model_name);
|
||||
auto status = session_object2.Load(ctx_model_name);
|
||||
ASSERT_TRUE(status.IsOK());
|
||||
status = session_object2.Initialize();
|
||||
ASSERT_TRUE(status.IsOK());
|
||||
|
|
@ -869,7 +882,8 @@ TEST(TensorrtExecutionProviderTest, TRTPluginsCustomOpTest) {
|
|||
}
|
||||
|
||||
TEST_P(TensorrtExecutionProviderCacheTest, Run) {
|
||||
remove("EP_Context_model.onnx"); // remove the context model file if it exists
|
||||
std::string ctx_model_path = "EP_Context_model.onnx";
|
||||
remove(ctx_model_path.c_str()); // remove the context model file generated by previous test
|
||||
// GetParam() returns the parameter of following format:
|
||||
// ##cache type##_##input shape type##
|
||||
std::string param = GetParam();
|
||||
|
|
@ -930,14 +944,14 @@ TEST_P(TensorrtExecutionProviderCacheTest, Run) {
|
|||
*
|
||||
*/
|
||||
(void)so.config_options.AddConfigEntry("ep.context_enable", "1");
|
||||
(void)so.config_options.AddConfigEntry("ep.context_file_path", "EP_Context_model.onnx");
|
||||
(void)so.config_options.AddConfigEntry("ep.context_file_path", ctx_model_path.c_str());
|
||||
(void)so.config_options.AddConfigEntry("ep.context_embed_mode", "0");
|
||||
InferenceSession session_object{so, GetEnvironment()};
|
||||
|
||||
params.trt_engine_cache_enable = 1;
|
||||
params.trt_engine_cache_prefix = "TRTEP_Cache_Test";
|
||||
params.trt_dump_ep_context_model = 1;
|
||||
params.trt_ep_context_file_path = "EP_Context_model.onnx";
|
||||
params.trt_ep_context_file_path = ctx_model_path.c_str();
|
||||
std::unique_ptr<IExecutionProvider> execution_provider = TensorrtExecutionProviderWithOptions(¶ms);
|
||||
EXPECT_TRUE(session_object.RegisterExecutionProvider(std::move(execution_provider)).IsOK());
|
||||
auto status = session_object.Load(model_name);
|
||||
|
|
@ -1039,7 +1053,7 @@ TEST_P(TensorrtExecutionProviderCacheTest, Run) {
|
|||
}
|
||||
}
|
||||
|
||||
remove("EP_Context_model.onnx"); // remove the context model file generated earlier
|
||||
remove(ctx_model_path.c_str()); // remove the context model file generated by previous test
|
||||
|
||||
// Test explicit min/max/opt profile shapes
|
||||
// create another session object with TRT EP provider options:
|
||||
|
|
|
|||
Loading…
Reference in a new issue