saymrwulf/onnxruntime
1
0
Fork 0
mirror of https://github.com/saymrwulf/onnxruntime.git synced 2026-07-20 19:12:24 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Remove old UT carried from old branch

Browse source
This commit is contained in:
Jingyan Wang 2025-01-29 22:23:49 +00:00
parent 2d8b2ba6d1
commit 3a56834acf
1 changed files with 0 additions and 60 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

60
onnxruntime/test/providers/tensorrt/tensorrt_basic_test.cc
View file

@ -842,66 +842,6 @@ TEST(TensorrtExecutionProviderTest, EPContextNodeMulti) {
RunSession(session_object2, run_options, feeds, output_names, expected_dims_mul_m, expected_values_mul_m);
}
// TEST(TensorrtExecutionProviderTest, ExcludeOpsTest) {
// /* The mnist.onnx looks like this:
// * Conv
// * |
// * Add
// * .
// * .
// * |
// * MaxPool
// * |
// * .
// * .
// * MaxPool
// * |
// * Reshape
// * |
// * MatMul
// * .
// * .
// *
// */
// PathString model_name = ORT_TSTR("testdata/mnist.onnx");
// SessionOptions so;
// so.session_logid = "TensorrtExecutionProviderExcludeOpsTest";
// RunOptions run_options;
// run_options.run_tag = so.session_logid;
// InferenceSession session_object{so, GetEnvironment()};
// auto cuda_provider = DefaultCudaExecutionProvider();
// auto cpu_allocator = cuda_provider->CreatePreferredAllocators()[1];
// std::vector<int64_t> dims_op_x = {1, 1, 28, 28};
// std::vector<float> values_op_x(784, 1.0f); // 784=1*1*28*28
// OrtValue ml_value_x;
// CreateMLValue<float>(cpu_allocator, dims_op_x, values_op_x, &ml_value_x);
// NameMLValMap feeds;
// feeds.insert(std::make_pair("Input3", ml_value_x));
// // prepare outputs
// std::vector<std::string> output_names;
// output_names.push_back("Plus214_Output_0");
// std::vector<OrtValue> fetches;
// RemoveCachesByType("./", ".engine");
// OrtTensorRTProviderOptionsV2 params;
// params.trt_engine_cache_enable = 1;
// params.trt_op_types_to_exclude = "MaxPool";
// std::unique_ptr<IExecutionProvider> execution_provider = TensorrtExecutionProviderWithOptions(&params);
// EXPECT_TRUE(session_object.RegisterExecutionProvider(std::move(execution_provider)).IsOK());
// auto status = session_object.Load(model_name);
// ASSERT_TRUE(status.IsOK());
// status = session_object.Initialize();
// ASSERT_TRUE(status.IsOK());
// status = session_object.Run(run_options, feeds, output_names, &fetches);
// ASSERT_TRUE(status.IsOK());
// std::vector<fs::path> engine_files;
// engine_files = GetCachesByType("./", ".engine");
// // The whole graph should be partitioned into 3 TRT subgraphs and 2 cpu nodes
// ASSERT_EQ(engine_files.size(), 3);
// }
TEST(TensorrtExecutionProviderTest, TRTPluginsCustomOpTest) {
PathString model_name = ORT_TSTR("testdata/trt_plugin_custom_op_test.onnx");
SessionOptions so;