b8a255e1b5
* Initial update of readme * Readme updates * Review of consolidated README (#3930) * Proposed updates for readme (#3953) I found some of the information was duplicated within the doc, so attempted to streamline * Fix links * More updates - fix build instructions - nodejs doc reorganization - roadmap update - version fixes * Update ORT Server build instructions * More doc cleanup * fix python dev notes name * Update nodejs and some links * sync eigen version back to master * Minor fixes * add nodsjs to sample table of content * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * address PR feedback * address PR feedback * nodejs build instruction * Update Java instructions to include gradle * Roadmap refresh Reformat some data, fix link, minor rewording * Clarify Visual C++ runtime req Co-authored-by: Nat Kershaw (MSFT) <nakersha@microsoft.com> Co-authored-by: Prasanth Pulavarthi <prasantp@microsoft.com> Co-authored-by: manashgoswami <magoswam@microsoft.com>
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Versioning
API
ONNX Runtime follows Semantic Versioning 2.0 for its public API. Each release has the form MAJOR.MINOR.PATCH, adhering to the definitions from the linked semantic versioning doc.
Current stable release version
The version number of the current stable release can be found here.
Release cadence
Compatibility
Backwards compatibility
All versions of ONNX Runtime will support ONNX opsets all the way back to (and including) opset version 7. In other words if an ONNX Runtime release implements ONNX opset ver 9, it'll be able to run all models that are stamped with ONNX opset versions in the range [7-9].
Version matrix
Following table summarizes the relationship between the ONNX Runtime version and the ONNX opset version implemented in that release. Please note the Backwards and Forward compatibility notes above. For more details on ONNX Release versions, see this page.
| ONNX Runtime release version | ONNX release version | ONNX opset version | ONNX ML opset version | Supported ONNX IR version | WinML compatibility |
|---|---|---|---|---|---|
| 1.3.0 | 1.7 down to 1.2 | 12 | 2 | 6 | -- |
| 1.2.0 1.1.2 1.1.1 1.1.0 |
1.6 down to 1.2 | 11 | 2 | 6 | -- |
| 1.0.0 | 1.6 down to 1.2 | 11 | 2 | 6 | -- |
| 0.5.0 | 1.5 down to 1.2 | 10 | 1 | 5 | -- |
| 0.4.0 | 1.5 down to 1.2 | 10 | 1 | 5 | -- |
| 0.3.1 0.3.0 |
1.4 down to 1.2 | 9 | 1 | 3 | -- |
| 0.2.1 0.2.0 |
1.3 down to 1.2 | 8 | 1 | 3 | 1903 (19H1)+ |
| 0.1.5 0.1.4 |
1.3 down to 1.2 | 8 | 1 | 3 | 1809 (RS5)+ |
Tool Compatibility
A variety of tools can be used to create ONNX models. Unless otherwise noted, please use the latest released version of the tools to convert/export the ONNX model. Most tools are backwards compatible and support multiple ONNX versions. Join this with the table above to evaluate ONNX Runtime compatibility.
| Tool | Recommended Version | Supported ONNX version(s) |
|---|---|---|
| PyTorch | Latest stable | 1.2-1.6 |
| ONNXMLTools CoreML, LightGBM, XGBoost, LibSVM |
Latest stable | 1.2-1.6 |
| ONNXMLTools SparkML |
Latest stable | 1.4-1.5 |
| SKLearn-ONNX | Latest stable | 1.2-1.6 |
| Keras-ONNX | Latest stable | 1.2-1.6 |
| Tensorflow-ONNX | Latest stable | 1.2-1.6 |
| WinMLTools | Latest stable | 1.2-1.6 |
| AutoML | 1.0.39+ | 1.5 |
| 1.0.33 | 1.4 |