Warnings during conversion of frozen_inference_graph.pb to .uff

I trained SSD_Mobilenet_V2_coco model with my own data set then i want to run my custom model on jetson nano. I converted frozen_inference_graph.pb to .uff as:

sudo python3 /usr/lib/python3.6/dist-packages/uff/bin/convert_to_uff.py ./frozen_inference_graph.pb -o ssd_mobilenet_v2.uff -O NMS -p ./config.py

Output of above command:

2020-02-13 22:54:07.807469: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
Loading ./frozen_inference_graph.pb
WARNING:tensorflow:From /usr/lib/python3.6/dist-packages/uff/converters/tensorflow/conversion_helpers.py:231: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.

NOTE: UFF has been tested with TensorFlow 1.12.0. Other versions are not guaranteed to work
WARNING: The version of TensorFlow installed on this system is not guaranteed to work with UFF.
WARNING: To create TensorRT plugin nodes, please use the create_plugin_node function instead.
WARNING: To create TensorRT plugin nodes, please use the create_plugin_node function instead.
UFF Version 0.6.3
=== Automatically deduced input nodes ===
[name: “Input”
op: “Placeholder”
input: “Cast”
attr {
key: “dtype”
value {
type: DT_FLOAT
}
}
attr {
key: “shape”
value {
shape {
dim {
size: 1
}
dim {
size: 3
}
dim {
size: 300
}
dim {
size: 300
}
}
}
}
]

Using output node NMS
Converting to UFF graph
Warning: No conversion function registered for layer: NMS_TRT yet.
Converting NMS as custom op: NMS_TRT
WARNING:tensorflow:From /usr/lib/python3.6/dist-packages/uff/converters/tensorflow/converter.py:179: The name tf.AttrValue is deprecated. Please use tf.compat.v1.AttrValue instead.

Warning: No conversion function registered for layer: FlattenConcat_TRT yet.
Converting concat_box_conf as custom op: FlattenConcat_TRT
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_5_3x3_s2_128/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_1_Conv2d_5_1x1_64/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_4_3x3_s2_256/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_1_Conv2d_4_1x1_128/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_3_3x3_s2_256/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_1_Conv2d_3_1x1_128/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_2_3x3_s2_512/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_1_Conv2d_2_1x1_256/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/Conv_1/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_15/add as custom op: AddV2
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_14/add as custom op: AddV2
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_12/add as custom op: AddV2
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_11/add as custom op: AddV2
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_10/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_9/add as custom op: AddV2
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_8/add as custom op: AddV2
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_7/add as custom op: AddV2
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_6/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_5/add as custom op: AddV2
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_4/add as custom op: AddV2
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_3/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_2/add as custom op: AddV2
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_1/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/Conv/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: Cast yet.
Converting Cast as custom op: Cast
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_2/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_2/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_4/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_4/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_5/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_5/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_7/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_7/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_8/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_8/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_9/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_9/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_11/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_11/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_12/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_12/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_14/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_14/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_15/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_15/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: GridAnchor_TRT yet.
Converting GridAnchor as custom op: GridAnchor_TRT
Warning: No conversion function registered for layer: FlattenConcat_TRT yet.
Converting concat_box_loc as custom op: FlattenConcat_TRT
No. nodes: 644
UFF Output written to ssd_mobilenet_v2.uff

what about these WARNINGS?

Here is config.py:

import graphsurgeon as gs
import tensorflow as tf

Input = gs.create_node(“Input”,
op=“Placeholder”,
dtype=tf.float32,
shape=[1, 3, 300, 300])
PriorBox = gs.create_plugin_node(name=“GridAnchor”, op=“GridAnchor_TRT”,
numLayers=6,
minSize=0.2,
maxSize=0.95,
aspectRatios=[1.0, 2.0, 0.5, 3.0, 0.33],
variance=[0.1,0.1,0.2,0.2],
featureMapShapes=[19, 10, 5, 3, 2, 1])
NMS = gs.create_plugin_node(name=“NMS”, op=“NMS_TRT”,
shareLocation=1,
varianceEncodedInTarget=0,
backgroundLabelId=0,
confidenceThreshold=1e-8,
nmsThreshold=0.6,
topK=100,
keepTopK=100,
numClasses=4,
###########################################
#inputOrder=[0, 2, 1],
inputOrder=[1, 0, 2],
###########################################
confSigmoid=1,
isNormalized=1,
scoreConverter=“SIGMOID”)
concat_priorbox = gs.create_node(name=“concat_priorbox”, op=“ConcatV2”, dtype=tf.float32, axis=2)
concat_box_loc = gs.create_plugin_node(“concat_box_loc”, op=“FlattenConcat_TRT”, dtype=tf.float32, axis=1, ignoreBatch=0)
concat_box_conf = gs.create_plugin_node(“concat_box_conf”, op=“FlattenConcat_TRT”, dtype=tf.float32, axis=1, ignoreBatch=0)

namespace_plugin_map = {
“MultipleGridAnchorGenerator”: PriorBox,
“Postprocessor”: NMS,
“Preprocessor”: Input,
“ToFloat”: Input,
“image_tensor”: Input,

“MultipleGridAnchorGenerator/Concatenate”: concat_priorbox,

"Concatenate": concat_priorbox,
"concat": concat_box_loc,
"concat_1": concat_box_conf

}

def preprocess(dynamic_graph):
all_assert_nodes = dynamic_graph.find_nodes_by_op(“Assert”)
dynamic_graph.remove(all_assert_nodes, remove_exclusive_dependencies=True)

all_identity_nodes = dynamic_graph.find_nodes_by_op("Identity")
dynamic_graph.forward_inputs(all_identity_nodes)

dynamic_graph.collapse_namespaces(namespace_plugin_map)
dynamic_graph.remove(dynamic_graph.graph_outputs, remove_exclusive_dependencies=False)
dynamic_graph.find_nodes_by_op("NMS_TRT")[0].input.remove("Input")

Hi,

It’s recommended to create a TensorRT engine with your uff file directly.
Some layers are not supported in the uff parser but already implemented in the TensorRT library.

Based on your log, it looks like your SSD_Mobilenet_V2_coco use FusedBatchNormV3 layer, which is not supported in current TensorRT.
A possible solution is to use older TensorFlow version(ex. 1.14.0) for serializing a .pb file, which won’t use FusedBatchNormV3 layer.

Thanks.

i installed tensorflow version 1.13.1 but receive same WARNINGS.

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:526 : FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated ; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)typ e’.
_np_qint8 = np.dtype([(“qint8”, np.int8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:527 : FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated ; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)typ e’.
_np_quint8 = np.dtype([(“quint8”, np.uint8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:528 : FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated ; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)typ e’.
_np_qint16 = np.dtype([(“qint16”, np.int16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:529 : FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated ; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)typ e’.
_np_quint16 = np.dtype([(“quint16”, np.uint16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:530 : FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated ; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)typ e’.
_np_qint32 = np.dtype([(“qint32”, np.int32, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:535 : FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated ; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)typ e’.
np_resource = np.dtype([(“resource”, np.ubyte, 1)])
Loading ./frozen_inference_graph.pb
NOTE: UFF has been tested with TensorFlow 1.12.0. Other versions are not guaranteed to work
WARNING: The version of TensorFlow installed on this system is not guaranteed to work with UFF.
WARNING: To create TensorRT plugin nodes, please use the create_plugin_node function instead.
WARNING: To create TensorRT plugin nodes, please use the create_plugin_node function instead.
UFF Version 0.6.3
=== Automatically deduced input nodes ===
[name: “Input”
op: “Placeholder”
input: “Cast”
attr {
key: “dtype”
value {
type: DT_FLOAT
}
}
attr {
key: “shape”
value {
shape {
dim {
size: 1
}
dim {
size: 3
}
dim {
size: 300
}
dim {
size: 300
}
}
}
}
]

Using output node NMS
Converting to UFF graph
Warning: No conversion function registered for layer: NMS_TRT yet.
Converting NMS as custom op: NMS_TRT
Warning: No conversion function registered for layer: FlattenConcat_TRT yet.
Converting concat_box_conf as custom op: FlattenConcat_TRT
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_5_3x3_s2_128/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_1_Conv2d_5_1x1_64/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_4_3x3_s2_256/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_1_Conv2d_4_1x1_128/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_3_3x3_s2_256/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_1_Conv2d_3_1x1_128/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_2_3x3_s2_512/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/layer_19_1_Conv2d_2_1x1_256/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/Conv_1/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_15/add as custom op: AddV2
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_14/add as custom op: AddV2
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: FusedBatchNormV3 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNormV3 as custom op: FusedBatchNormV3
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_12/add as custom op: AddV2
Warning: No conversion function registered for layer: AddV2 yet.
Converting FeatureExtractor/MobilenetV2/expanded_conv_11/add as custom op: AddV2
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No. nodes: 644
UFF Output written to updated.uff

Hi,

Do you train the model with TensorFlow v1.13?
Please noticed that you will need to use older version for serializing.

Thanks.

Hi AastaLLL,

Can you please tell me that what does ‘serializing’ mean?

I have trained my model on colab with tensorflow version 1.14.0 and tensorflow version 1.13.1 is installed on Jetson nano.

I have came to know that TF version 1.12.0 is must for training the model, is that so?

duplicate to topic 1071722:
https://devtalk.nvidia.com/default/topic/1071722/jetson-nano/how-to-run-custom-model-on-jteson-nano/