Remove gsl subodule and replace with a local copy of gsl-lite Refactor for onnxruntime::make_unique gsl::span size and index are now size_t Remove lambda auto argument type detection. Remove constexpr from fail_fast in gsl due to Linux not being happy. Comment out std::stream support due to MacOS std lib broken. Move make_unique into include/core/common so it is accessible for server builds. Relax requirements for onnxruntime/test/providers/cpu/ml/write_scores_test.cc due to x86 build. Add ONNXRUNTIME_ROOT to Server Lib includes so gsl is recognized |
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| .. | ||
| posix | ||
| windows | ||
| command_args_parser.cc | ||
| command_args_parser.h | ||
| main.cc | ||
| ort_test_session.cc | ||
| ort_test_session.h | ||
| performance_runner.cc | ||
| performance_runner.h | ||
| README.md | ||
| ReadMe.txt | ||
| test_configuration.h | ||
| test_session.h | ||
| tf_test_session.h | ||
| TFModelInfo.cc | ||
| TFModelInfo.h | ||
| utils.h | ||
ONNXRuntime Performance Test
onnxruntime_perf_test [options...] model_path result_file Options: -m [test_mode]: Specifies the test mode. Value coulde be 'duration' or 'times'. Provide 'duration' to run the test for a fix duration, and 'times' to repeated for a certain times. Default:'duration'. -e [cpu|cuda|mkldnn|tensorrt|ngraph|nuphar]: Specifies the provider 'cpu','cuda','mkldnn','tensorrt','ngraph' or 'nuphar'. Default:'cpu'. -r [repeated_times]: Specifies the repeated times if running in 'times' test mode.Default:1000. -t [seconds_to_run]: Specifies the seconds to run for 'duration' mode. Default:600. -p [profile_file]: Specifies the profile name to enable profiling and dump the profile data to the file. -s: Show statistics result, like P75, P90. -v: Show verbose information. -x: Use parallel executor, default (without -x): sequential executor. -h: help
Model path and input data dependency: Performance test uses the same input structure as onnx_test_runner. It requrires the directory trees as below:
--ModelName
--test_data_set_0
--input0.pb
--test_data_set_2
--input0.pb
--model.onnx
The path of model.onnx needs to be provided as <model_path> argument.