Accelerating TensorFlow 1.12.0 With TensorRT 5.0.2 Using The 18.12 Or 19.01 Container

These release notes are for accelerating TensorFlow 1.12.0 with TensorRT version 5.0.2 using using either the TensorFlow 18.12 or TensorFlow 19.01 container. For specific details about TensorRT, see the TensorRT 5.0.2 Release Notes.

Compatibility

Using TensorFlow 1.12.0 With TensorRT 5.0.2

Deprecated Features

  • Support for accelerating TensorFlow with TensorRT 3.x will be removed in a future release (likely TensorFlow 1.13). The generated plan files are not portable across platforms or TensorRT versions. Plans are specific to the exact GPU model they were built on (in addition to platforms and the TensorRT version) and must be retargeted to the specific GPU in case you want to run them on a different GPU. Therefore, models that were accelerated using TensorRT 3.x will no longer run. If you have a production model that was accelerated with TensorRT 3.x, you will need to convert your model with TensorRT 4.x or later again.

    For more information, see the Note in Serializing A Model In C++ or Serializing A Model In Python.

  • The check_accuracy.py script, used to check whether the accuracy generated by the example matches with the expectation, was removed from the example. Refer to the published accuracy numbers to verify whether your generated accuracy numbers match with the expectation.