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ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
81fa28bc56
* Enabling ov-ep for 2022.1 Release ->Added ov-ep 2022.1 flow ->Validated CPU Unit tests with OV Master using onnxruntime_test_all unit tests. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fix for output mismatch b/w OpenVINO and ONNX Refer: https://jira.devtools.intel.com/browse/CVS-60310 Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enabling Adobe ops ->Enable Resize op for iGPU ->Enable Add op for iGPU Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Removing irrelevant conditions ->Removing some conditions from GetCapability() which are now not required. (Removed conditions for OV version support less than 2021.2) Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enable upsample op Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enable Adobe proxy-e model Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Removing any extra conditions for Opset13 ops * Opset13 changes Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Exception handling for devices * Added comments * Implement GPU Throttling feature *Added GPU Throttling feature for iGPU's. when user enables it as a runtime option, it helps in reducing overall CPU usage of the application *Added changes to exercise this option using onnxruntime_perf_test application. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Renaming the runtime config option Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Added the user to video and users group * Handling_GPU.0_GPU.1 * Handling special conditions ->Handling corner cases for device_type checks Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Modification to include new api 2.0 changes in the code * Added opset13 changes ->Enabled Few ops ->Added Debug info for case 3b in getcapability() Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enabling ov-ep for 2022.1 Release ->Added ov-ep 2022.1 flow ->Validated CPU Unit tests with OV Master using onnxruntime_test_all unit tests. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fix for output mismatch b/w OpenVINO and ONNX Refer: https://jira.devtools.intel.com/browse/CVS-60310 Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enabling Adobe ops ->Enable Resize op for iGPU ->Enable Add op for iGPU Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Removing irrelevant conditions ->Removing some conditions from GetCapability() which are now not required. (Removed conditions for OV version support less than 2021.2) Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enable upsample op Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enable Adobe proxy-e model Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Removing any extra conditions for Opset13 ops * Opset13 changes Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Exception handling for devices * Added comments * Implement GPU Throttling feature *Added GPU Throttling feature for iGPU's. when user enables it as a runtime option, it helps in reducing overall CPU usage of the application *Added changes to exercise this option using onnxruntime_perf_test application. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Renaming the runtime config option Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Added the user to video and users group * Handling_GPU.0_GPU.1 * Handling special conditions ->Handling corner cases for device_type checks Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Added opset13 changes ->Enabled Few ops ->Added Debug info for case 3b in getcapability() Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Log comments updated * Changes to enable 2.0 api * Enabling ov-ep for 2022.1 Release ->Added ov-ep 2022.1 flow ->Validated CPU Unit tests with OV Master using onnxruntime_test_all unit tests. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fix for output mismatch b/w OpenVINO and ONNX Refer: https://jira.devtools.intel.com/browse/CVS-60310 Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enabling Adobe ops ->Enable Resize op for iGPU ->Enable Add op for iGPU Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Removing irrelevant conditions ->Removing some conditions from GetCapability() which are now not required. (Removed conditions for OV version support less than 2021.2) Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enable upsample op Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Enable Adobe proxy-e model Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Removing any extra conditions for Opset13 ops * Opset13 changes Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Exception handling for devices * Added comments * Implement GPU Throttling feature *Added GPU Throttling feature for iGPU's. when user enables it as a runtime option, it helps in reducing overall CPU usage of the application *Added changes to exercise this option using onnxruntime_perf_test application. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Renaming the runtime config option Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Added the user to video and users group * Handling_GPU.0_GPU.1 * Handling special conditions ->Handling corner cases for device_type checks Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Added opset13 changes ->Enabled Few ops ->Added Debug info for case 3b in getcapability() Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fix build issue Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fixes issues *Fixes compiler warnings c4458 on windows. *Fixes the bug in device_type check logic *Adds print info for enable_opencl_throttling option in onnxruntime_perf_test Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * commit to make openvino_2021.4 compatible * Fixed IO Buffer Optimization * Fix output names issue * Fix 2021.3 branch * Bug Fix for Multiple inputs/outputs - Assigns the right output_name and input_name for the graph when returned by CompiledModel::inputs() OV function. - Also takex care of output mismatch issue b/w openvino output and onnx output Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Add comments for the changes made Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * IO Buffer Changes * Commit for Disabling GPU Throttling for 2021.4 * Updated branch * Fix windows build ->Fixed windows build in debug mode ->Disabled scatternd3_tensor_int64 Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fixed CPP Unit tests for CPU -Fixed shrink, MVN, ReduceL2, Maxpool, upsample, scatter, slice, reshape, unsqueeze. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fixed first set of GPU Tests Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fixed additional failing tests on GPU ->Added conditions to disable certain ops under certain conditions ->Disabled certain tests ->Added some op supports for no_dimension supported Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Added Expand op support for CPU Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Added condition for squeeze op ->Shape can't have empty axes attribute Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Add support for LessOrEqual op function Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * OV Interface wait for replaced by indefinite wait call * use names from ONNX model to access OV tensors This chnage is to use the input/output names retrieved from original onnx model to access OV tensors and to check if there's any input or output names mismatch b/w ONNX naming and OV naming. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fixes Myriad unit tests and other issues ->Fixes Myriad CPP unit tests ->Fixes output mismatch issue with models with sub graph partitioning Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fix segfault issue ->Fixed case 3b condition in get_capability() which was causing the segfault issue Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fixed build isuse with ov 2021.4 with I/O buffer Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Disables performance counters for I/O Buffer Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fixed inputs/outputs mismatch for HDDL with 2022.1 Signed-off-by: Mohammad Amir Aqeel <mohammadx.amir.aqeel@intel.com> * Fix to enable GPU FP16 * Enabled mlperf_ssd_mobilenet_300 model fully on CPU Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Added ov version specific dll packaging for nuget * Fixed conditions for few ops Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Dockerfile updates * Updated License Info -Updated the copyrights License Info -modified FP16 transformations with OV 2022.1 Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Disabling mlperf_ssd_mobilenet_300 model ->Disabled this model for openvino. The test is failing in Internal_CI pipelines. Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Disabling failing python CPU Tests Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> * Fixed flake8 python errors Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com> Co-authored-by: hdgx <harinix.d.g@intel.com> Co-authored-by: mayavijx <mayax.vijayan@intel.com> Co-authored-by: sfatimar <sahar.fatima@intel.com> Co-authored-by: mohsinmx <mohsinx.mohammad@intel.com> Co-authored-by: Mohammad Amir Aqeel <mohammadx.amir.aqeel@intel.com> |
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ONNX Runtime is a cross-platform inference and training machine-learning accelerator.
ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →
ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →
Get Started
General Information: onnxruntime.ai
Usage documention and tutorials: onnxruntime.ai/docs
Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
Build Pipeline Status
| System | CPU | GPU | EPs |
|---|---|---|---|
| Windows | |||
| Linux | |||
| Mac | |||
| Android | |||
| iOS | |||
| WebAssembly |
Data/Telemetry
Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.
Contributions and Feedback
We welcome contributions! Please see the contribution guidelines.
For feature requests or bug reports, please file a GitHub Issue.
For general discussion or questions, please use GitHub Discussions.
Code of Conduct
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
License
This project is licensed under the MIT License.