Unable to get the ObjectDetector_SSD sample to work?

Autonomous Machines Jetson & Embedded Systems Jetson Nano
1

I have followed the README instructions to get the objectdetectorSSD to run but I’m failing on the UFF conversion step.

I’m testing with Jetpack 4.4 dp on a Xavier NX.

I have installed Tensorflow 2 as per these instructions: Jetson Zoo - eLinux.org.

When I run:

python3 /usr/lib/python3.6/dist-packages/uff/bin/convert_to_uff.py frozen_inference_graph.pb -O NMS -p /usr/src/tensorrt/samples/sampleUffSSD/config.py -o sample_ssd_relu6.uff

I get this error:

2020-06-07 11:48:33.930004: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.2
2020-06-07 11:48:36.009453: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libnvinfer.so.7
2020-06-07 11:48:36.012461: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libnvinfer_plugin.so.7
Loading frozen_inference_graph.pb
WARNING:tensorflow:From /usr/lib/python3.6/dist-packages/uff/bin/../../uff/converters/tensorflow/conversion_helpers.py:227: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.

Traceback (most recent call last):
  File "/usr/lib/python3.6/dist-packages/uff/bin/convert_to_uff.py", line 96, in <module>
    main()
  File "/usr/lib/python3.6/dist-packages/uff/bin/convert_to_uff.py", line 92, in main
    debug_mode=args.debug
  File "/usr/lib/python3.6/dist-packages/uff/bin/../../uff/converters/tensorflow/conversion_helpers.py", line 229, in from_tensorflow_frozen_model
    return from_tensorflow(graphdef, output_nodes, preprocessor, **kwargs)
  File "/usr/lib/python3.6/dist-packages/uff/bin/../../uff/converters/tensorflow/conversion_helpers.py", line 83, in from_tensorflow
    if tf.__version__ != tf_supported_ver:
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/util/module_wrapper.py", line 192, in __getattr__
    attr = getattr(self._tfmw_wrapped_module, name)
AttributeError: module 'tensorflow' has no attribute '__version__'

As a test I can execute:

$ python3
Python 3.6.9 (default, Apr 18 2020, 01:56:04)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.

>>> import tensorflow as tf
2020-06-07 11:52:09.195625: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.2
2020-06-07 11:52:11.859123: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libnvinfer.so.7
2020-06-07 11:52:11.862051: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libnvinfer_plugin.so.7

>>> exit()

So tensorflow seems to be installed ok.

I have looked at the dockerfile used to builld the nvcr.io/nvidia/l4t-tensorflow:r32.4.2-tf1.15-py3 image and it seems to use tensorflow version 1.15. ??

Is version 1.15 an un-documented requirement and is that why the UFF converter is failing?

3

Hi,

This is a known issue in tensorflow-2.1.0+nv20.4-cp36-cp36m-linux_aarch64.whl.
A workaround is to comment out the version checker in uff parser dierctly.

/usr/lib/python3.6/dist-packages/uff/converters/tensorflow/conversion_helpers.py

...
#    if tf.__version__ != tf_supported_ver:
#        print("NOTE: UFF has been tested with TensorFlow " + str(tf_supported_ver) + ".")
#        print("WARNING: The version of TensorFlow installed on this system is not guaranteed to work with UFF.")
...

Thanks.

4

That did the job. Thank you. Would be good to get it added to the README or fixed in time for 5.0GA. ;-)

5

Hi,

This issue is fixed in our next TensorFlow package.
So you don’t need to do this once the new release is available.

Sorry for the inconvenience.
Thanks.