uff_batchnorm.txt

Hi, I am unable to convert many mainstream deep neural network architectures in Keras / Tensorflow from .pb to .uff because the conversion tool "convert_to_uff.py" throws an error about how parts of the Batch Normalization layer are not supported.

This effects bog standard CNN architectures such as GoogleNet / Inception_V3 which are obviously supported in Caffe.

Here is the .pb I used for conversion: https://www.dropbox.com/s/pu98bi9q87lz9mq/inception_v3.pb?dl=0
Here is the way I am exporting the graph: https://gist.github.com/csvance/a1728337d273c8a1536fd80852857337

I have no problems importing networks from Caffe trained by nVidia DIGITS which use Batchnorm. I also have no problem importing networks which do not use the Batchnorm layer.

--Log--
root@4f42b39d20e9:/usr/lib/python2.7/dist-packages/uff/bin# python convert_to_uff.py tensorflow -o /Git/inception_v3.uff --input-file /Git/inception_v3.pb -O predictions/Softmax --input-file /Git/inception_v3.pb -O pr 
Loading /Git/inception_v3.pb
Using output node predictions/Softmax
Converting to UFF graph
Warning: No conversion function registered for layer: Merge yet.
Converting as custom op Merge batch_normalization_94/cond/Merge
name: "batch_normalization_94/cond/Merge"
op: "Merge"
input: "batch_normalization_94/cond/batchnorm/add_1"
input: "batch_normalization_94/cond/Switch_1:1"
attr {
  key: "N"
  value {
    i: 2
  }
}
attr {
  key: "T"
  value {
    type: DT_FLOAT
  }
}

Warning: No conversion function registered for layer: Switch yet.
Converting as custom op Switch batch_normalization_94/cond/Switch_1
name: "batch_normalization_94/cond/Switch_1"
op: "Switch"
input: "batch_normalization_94/FusedBatchNorm"
input: "batch_normalization_94/cond/pred_id"
attr {
  key: "T"
  value {
    type: DT_FLOAT
  }
}
attr {
  key: "_class"
  value {
    list {
      s: "loc:@batch_normalization_94/FusedBatchNorm"
    }
  }
}

Warning: No conversion function registered for layer: PlaceholderWithDefault yet.
Converting as custom op PlaceholderWithDefault batch_normalization_1/keras_learning_phase
name: "batch_normalization_1/keras_learning_phase"
op: "PlaceholderWithDefault"
input: "batch_normalization_1/keras_learning_phase/input"
attr {
  key: "dtype"
  value {
    type: DT_BOOL
  }
}
attr {
  key: "shape"
  value {
    shape {
    }
  }
}

Traceback (most recent call last):
  File "convert_to_uff.py", line 109, in <module>
    main()
  File "convert_to_uff.py", line 104, in main
    output_filename=args.output
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 103, in from_tensorflow_frozen_model
    return from_tensorflow(graphdef, output_nodes, **kwargs)
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 75, in from_tensorflow
    name="main")
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 64, in convert_tf2uff_graph
    uff_graph, input_replacements)
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 51, in convert_tf2uff_node
    op, name, tf_node, inputs, uff_graph, tf_nodes=tf_nodes)
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 28, in convert_layer
    fields = cls.parse_tf_attrs(tf_node.attr)
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in parse_tf_attrs
    for key, val in attrs.items()}
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in <dictcomp>
    for key, val in attrs.items()}
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 172, in parse_tf_attr_value
    return cls.convert_tf2uff_field(code, val)
  File "/usr/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 161, in convert_tf2uff_field
    if shp.unknown_rank:
AttributeError: 'google.protobuf.pyext._message.RepeatedCompositeCo' object has no attribute 'unknown_rank'
root@4f42b39d20e9:/usr/lib/python2.7/dist-packages/uff/bin# 


--Operating System Info--

docker pull chybhao666/cuda9_cudnn7_tensorrt3.0:latest

root@4f42b39d20e9:~# lsb_release -a
No LSB modules are available.
Distributor ID:	Ubuntu
Description:	Ubuntu 16.04.3 LTS
Release:	16.04
Codename:	xenial

root@4f42b39d20e9:~# dpkg -l | grep -i tensor
ii  libnvinfer-dev                                         4.0.1-1+cuda9.0                          amd64        TensorRT development libraries and headers
ii  libnvinfer-samples                                     4.0.1-1+cuda9.0                          amd64        TensorRT samples and documentation
ii  libnvinfer4                                            4.0.1-1+cuda9.0                          amd64        TensorRT runtime libraries
ii  nv-tensorrt-repo-ubuntu1604-ga-cuda9.0-trt3.0-20171128 1-1                                      amd64        nv-tensorrt repository configuration files
iU  python-libnvinfer                                      4.0.1-1+cuda9.0                          amd64        Python bindings for TensorRT
iU  python-libnvinfer-dev                                  4.0.1-1+cuda9.0                          amd64        Python development package for TensorRT
ii  tensorrt                                               3.0.1-1+cuda9.0                          amd64        Meta package of TensorRT
ii  uff-converter-tf                                       4.0.1-1+cuda9.0                          amd64        UFF converter for TensorRT package