For specific ONNX node support information, refer to the Operators’ support document. Common ONNX Parser Error Messages Error Message Description <X> must be an initializer! These error messages signify that an ONNX node input tensor is expected to be an initializer in TensorRT. A possible ...
Refitting a Weight-Stripped Engine Directly from ONNXWhen working with weight-stripped engines created from ONNX models, the refit process can be done automatically with the IParserRefitter class from the ONNX parser library. The following steps show how to create the class and run the refit ...
TensorRT’s primary means of importing a trained model from a framework is through the ONNX interchange format. TensorRT ships with an ONNX parser library to assist in importing models. Where possible, the parser is backward compatible up to opset 7; the ONNX Model Opset Version Conve...
1.5. ONNX TensorRT's primary means of importing a trained model from a framework is through the ONNX interchange format. TensorRT ships with an ONNX parser library to assist in importing models. Where possible, the parser is backward compatible up to opset 7; the ONNX Model Opset ...
‣ The TensorRT ONNX parser has been tested with ONNX 1.9.0 and supports opset 14. ‣ If the target system has both TensorRT and one or more training frameworks installed on it, the simplest strategy is to use the same version of cuDNN for the training frameworks as the one that ...
ONNX GitHub version Semantic Versioning 2.0.0 MAJOR version when making incompatible API or ABI changes MINOR version when adding functionality in a backward-compatible manner PATCH version when making backward-compatible bug fixes # Deprecation informs developers that some APIs and tools are no longer...
1.5. ONNX TensorRT’s primary means of importing a trained model from a framework is through the ONNX interchange format. TensorRT ships with an ONNX parser library to assist in importing models. Where possible, the parser is backward compatible up to opset 7; the ONNX Model Opset...
1.5. ONNX TensorRT’s primary means of importing a trained model from a framework is through the ONNX interchange format. TensorRT ships with an ONNX parser library to assist in importing models. Where possible, the parser is backward compatible up to opset 7; the ONNX Model Opset ...
Refitting a Weight-Stripped Engine Directly from ONNX# When working with weight-stripped engines created from ONNX models, the refit process can be done automatically with theIParserRefitterclass from the ONNX parser library. The following steps show how to create the class and run the refit ...
‣ The TensorRT ONNX parser has been tested with ONNX 1.8.0 and supports opset 11. ‣ If the target system has both TensorRT and one or more training frameworks installed on it, the simplest strategy is to use the same version of cuDNN for the training frameworks as the one that ...