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On a few recent images (including gcr.io/kaggle-gpu-images/python latest 311277776c9b 7 days ago 47.2GB) I see very different linked and loaded TensorRT libs, namely 8.4 vs 8.6.
importtensorflow.compilerastf_cclinked_trt_ver=tf_cc.tf2tensorrt._pywrap_py_utils.get_linked_tensorrt_version()
print(f"Linked TRT ver: {linked_trt_ver}")
loaded_trt_ver=tf_cc.tf2tensorrt._pywrap_py_utils.get_loaded_tensorrt_version()
print(f"Loaded TRT ver: {loaded_trt_ver}")
# Linked TRT ver: (8, 4, 3)# Loaded TRT ver: (8, 6, 1)
This has been Python. Now, the system inference libraries are indeed at 8.6:
"Loaded TensorRT %s but linked TensorFlow against TensorRT %s. A few ""requirements must be met:\n""\t-It is required to use the same major version of TensorRT during ""compilation and runtime.\n""\t-TensorRT does not support forward compatibility. The loaded ""version has to be equal or more recent than the linked version.",
The text was updated successfully, but these errors were encountered:
🐛 Bug
Tensorflow TensorRT seems to be wrongly linked.
To Reproduce
On a few recent images (including
gcr.io/kaggle-gpu-images/python latest 311277776c9b 7 days ago 47.2GB
) I see very different linked and loaded TensorRT libs, namely 8.4 vs 8.6.This has been Python. Now, the system inference libraries are indeed at 8.6:
Now, minimal compatibility rules are fulfilled - the loaded version more recent.
However, the linking doesn't work properly. Under these recent containers, minimal TensorRT samples crash:
Expected behavior
Align versions and make the sample code runnable.
Additional context
See the NVIDIA installation guidelines
Conditions from `tensorrt
The text was updated successfully, but these errors were encountered: