when I followed “TensorFlow->TensorRT Image Classification” instruction in this website https://github.com/NVIDIA-AI-IOT/tf_to_trt_image_classification#models
and run the following:
python scripts/convert_plan.py data/frozen_graphs/inception_v1.pb data/plans/inception_v1.plan input 224 224 InceptionV1/Logits/SpatialSqueeze 1 0 float
I got this error messages
sudo python scripts/convert_plan.py data/frozen_graphs/inception_v1.pb data/plans/inception_v1.plan input 224 224 InceptionV1/Logits/SpatialSqueeze 1 0 float
Using output node InceptionV1/Logits/SpatialSqueeze
Converting to UFF graph
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting as custom op FusedBatchNormV3 InceptionV1/InceptionV1/Mixed_5c/Branch_3/Conv2d_0b_1x1/BatchNorm/FusedBatchNormV3
name: "InceptionV1/InceptionV1/Mixed_5c/Branch_3/Conv2d_0b_1x1/BatchNorm/FusedBatchNormV3"
op: "FusedBatchNormV3"
input: "InceptionV1/InceptionV1/Mixed_5c/Branch_3/Conv2d_0b_1x1/Conv2D"
input: "InceptionV1/InceptionV1/Mixed_5c/Branch_3/Conv2d_0b_1x1/BatchNorm/Const"
input: "InceptionV1/Mixed_5c/Branch_3/Conv2d_0b_1x1/BatchNorm/beta/read"
input: "InceptionV1/Mixed_5c/Branch_3/Conv2d_0b_1x1/BatchNorm/moving_mean/read"
input: "InceptionV1/Mixed_5c/Branch_3/Conv2d_0b_1x1/BatchNorm/moving_variance/read"
attr {
key: "T"
value {
type: DT_FLOAT
}
}
attr {
key: "U"
value {
type: DT_FLOAT
}
}
attr {
key: "data_format"
value {
s: "NHWC"
}
}
attr {
key: "epsilon"
value {
f: 0.001
}
}
attr {
key: "is_training"
value {
b: false
}
}
Traceback (most recent call last):
File "scripts/convert_plan.py", line 71, in <module>
data_type
File "scripts/convert_plan.py", line 22, in frozenToPlan
text=False,
File "/usr/local/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/local/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 75, in from_tensorflow
name="main")
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 64, in convert_tf2uff_graph
uff_graph, input_replacements)
File "/usr/local/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/local/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/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in parse_tf_attrs
for key, val in attrs.items()}
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in <dictcomp>
for key, val in attrs.items()}
File "/usr/local/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/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 140, in convert_tf2uff_field
return float(val)
TypeError: float() argument must be a string or a number
But if I activate my virtual env and run again I got this kind of error messages
No. nodes: 486
UFF Output written to data/tmp.uff
UffParser: Validator error: InceptionV1/InceptionV1/Mixed_5c/Branch_0/Conv2d_0a_1x1/BatchNorm/FusedBatchNormV3: Unsupported operation _FusedBatchNormV3
Failed to parse UFF
Does anyone can tell me how to solve this error?
thanks