Hi,
I’ve followed the examples from this post : https://devblogs.nvidia.com/tensorrt-integration-speeds-tensorflow-inference/ and from there : https://github.com/tensorflow/models/tree/6ff0a53f81439d807a78f8ba828deaea3aaaf269/research/tensorrt
I was able to run the scripts, but then I don’t know how to use the converted graphs.
When I try to display the graph with Tensorboard, I get this error:
Traceback (most recent call last):
File "/usr/lib/python3.5/runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/tools/import_pb_to_tensorboard.py", line 76, in <module>
app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/tools/import_pb_to_tensorboard.py", line 58, in main
import_to_tensorboard(FLAGS.model_dir, FLAGS.log_dir)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/tools/import_pb_to_tensorboard.py", line 49, in import_to_tensorboard
importer.import_graph_def(graph_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/util/deprecation.py", line 432, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/importer.py", line 418, in import_graph_def
graph._c_graph, serialized, options) # pylint: disable=protected-access
tensorflow.python.framework.errors_impl.NotFoundError: Op type not registered 'TRTEngineOp' in binary running on 425785a3e963. Make sure the Op and Kernel are registered
in the binary running in this process. Note that if you are loading a saved graph which used ops from tf.contrib, accessing (e.g.) `tf.contrib.resampler` should be done b
efore importing the graph, as contrib ops are lazily registered when the module is first accessed.
When I try to load the graph in a notebook, I get a similar error.
It’s happening with the ResNet models provided in with the codes and also with a custom MobileNet-based model.
I’m using Tensorflow 1.9 built from source (also tried with Tensorflow 1.7 and 1.8), TensorRT4 (also tried TensorRT3), Python3.5, CUDA9.0 with Cudnn 7.0 and within a Docker container.
Does anyone have an idea how to solve this issue? Is it ok to use a converted graph with Tensorflow tools or can we only use it with TensorRT tools thereafter?
I also have another unrelated question: can we use TensorRT with models that don’t have a fixed shape? For now, I have not been able to use TensorRT with a model which doesn’t have a fixed shape.
Thank you in advance.