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Model Optimizer does not process .pb file correctly due to tensorflow upgrade

Tsin__Ross
New Contributor I
‎03-18-2019 07:58 AM
723 Views

Recently I upgrade tensorflow to v1.13.1,

and try to convert tiny-yolov3 weights to IE model,  I got warnings and erros.

 

E:\AI\OpenVINO\COCO>python ..\tensorflow-yolo-v3\convert_weights_pb.py --class_names coco.names --data_format NHWC --weights_file yolov3-tiny.weights --tiny

WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.

WARNING:tensorflow:From C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
2019-03-18 22:37:12.201250: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
WARNING:tensorflow:From E:\AI\OpenVINO\tensorflow-yolo-v3\utils.py:53: convert_variables_to_constants (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.compat.v1.graph_util.convert_variables_to_constants
WARNING:tensorflow:From C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\framework\graph_util_impl.py:245: extract_sub_graph (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.compat.v1.graph_util.extract_sub_graph
299 ops written to frozen_darknet_yolov3_model.pb.

E:\AI\OpenVINO\COCO>python C:\Intel\computer_vision_sdk\deployment_tools\model_optimizer\mo_tf.py --input_model frozen_darknet_yolov3_model.pb --tensorflow_use_custom_operations_config tiny-yolov3.json --batch 1
Model Optimizer arguments:
Common parameters:
        - Path to the Input Model:      E:\AI\OpenVINO\COCO\frozen_darknet_yolov3_model.pb
        - Path for generated IR:        E:\AI\OpenVINO\COCO\.
        - IR output name:       frozen_darknet_yolov3_model
        - Log level:    ERROR
        - Batch:        1
        - Input layers:         Not specified, inherited from the model
        - Output layers:        Not specified, inherited from the model
        - Input shapes:         Not specified, inherited from the model
        - Mean values:  Not specified
        - Scale values:         Not specified
        - Scale factor:         Not specified
        - Precision of IR:      FP32
        - Enable fusing:        True
        - Enable grouped convolutions fusing:   True
        - Move mean values to preprocess section:       False
        - Reverse input channels:       False
TensorFlow specific parameters:
        - Input model in text protobuf format:  False
        - Offload unsupported operations:       False
        - Path to model dump for TensorBoard:   None
        - List of shared libraries with TensorFlow custom layers implementation:        None
        - Update the configuration file with input/output node names:   None
        - Use configuration file used to generate the model with Object Detection API:  None
        - Operations to offload:        None
        - Patterns to offload:  None
        - Use the config file:  E:\AI\OpenVINO\COCO\tiny-yolov3.json
Model Optimizer version:        1.5.12.49d067a0
[ ERROR ]  List of operations that cannot be converted to IE IR:
[ ERROR ]      LeakyRelu (11)
[ ERROR ]          detector/yolo-v3-tiny/Conv/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_1/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_2/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_3/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_4/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_5/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_6/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_7/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_10/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_11/LeakyRelu
[ ERROR ]          detector/yolo-v3-tiny/Conv_8/LeakyRelu
[ ERROR ]  Part of the nodes was not translated to IE. Stopped.
 For more information please refer to Model Optimizer FAQ (<INSTALL_DIR>/deployment_tools/documentation/docs/MO_FAQ.html), question #24.

 

 

I compared the newly generated .pb file and the old one which works, differences as followsdiff.jpg

 

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Shubha_R_Intel
Employee
‎03-18-2019 08:45 AM
723 Views

Dear Ross, you seem to have stumbled upon a known bug. I will file a bug on this issue. Meanwhile, please look at this related post :

https://software.intel.com/en-us/forums/computer-vision/topic/805882

Meanwhile, please stick with a slightly older Tensorflow version, 1.12.0 which seems to work fine.

Thanks for using OpenVino !

Shubha

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Tsin__Ross
New Contributor I
‎03-18-2019 08:52 AM
723 Views

Shubha R. (Intel) wrote:

Dear Ross, you seem to have stumbled upon a known bug. I will file a bug on this issue. Meanwhile, please look at this related post :

https://software.intel.com/en-us/forums/computer-vision/topic/805882

Meanwhile, please stick with a slightly older Tensorflow version, 1.12.0 which seems to work fine.

Thanks for using OpenVino !

Shubha

 

Hi Shubha,

 

Thank you very much for the reply.

P.S.

I just reverted to Python 3.6.7 and Tensorflow 1.9.0, it works.

 

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Shubha_R_Intel
Employee
‎03-18-2019 08:57 AM
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Ross you are welcome ! Please continue using OpenVino and post here if you have issues !

Sincerely,

Shubha

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Tsin__Ross
New Contributor I
‎03-18-2019 05:52 PM
723 Views

Shubha R. (Intel) wrote:

Ross you are welcome ! Please continue using OpenVino and post here if you have issues !

Sincerely,

Shubha

 

I am thinking about creating .pb file directly from darknet instead of using TF to convert .weights to .pb

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Tsin__Ross
New Contributor I
‎03-19-2019 01:44 AM
723 Views

Hi guys, 

I wrote a protobuf parser to parse the tiny-yolov3.pb base on COCO dataset,

I got this

<graphdef from="E:\AI\OpenVINO\COCO\tiny_yolov3.pb" >
	<nodedef index="0" name="inputs" op="Placeholder">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="shape"  type="Shape" dim-size="4" dims= "-1,416,416,3" />
		</attributes>
	</nodedef>
	<nodedef index="1" name="detector/truediv/y" op="Const">
		<inputs />
		<attributes>
			<attr name="value"  type="Tensor" type="Float"  dims="0" size="0" />
			<attr name="dtype"  type="Type" value="Float" />
		</attributes>
	</nodedef>
	<nodedef index="2" name="detector/truediv" op="RealDiv">
		<inputs>
			<input node="inputs" />
			<input node="detector/truediv/y" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
		</attributes>
	</nodedef>
	<nodedef index="3" name="detector/yolo-v3-tiny/Conv/weights" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="4" size="1728" />
		</attributes>
	</nodedef>
	<nodedef index="4" name="detector/yolo-v3-tiny/Conv/weights/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/weights" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv/weights" />
		</attributes>
	</nodedef>
	<nodedef index="5" name="detector/yolo-v3-tiny/Conv/Conv2D" op="Conv2D">
		<inputs>
			<input node="detector/truediv" />
			<input node="detector/yolo-v3-tiny/Conv/weights/read" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="strides"  type="List" int-size="4" int-vals="1,1,1,1" />
			<attr name="padding"  type="String" value="SAME" />
			<attr name="dilations"  type="List" int-size="4" int-vals="1,1,1,1" />
			<attr name="data_format"  type="String" value="NHWC" />
			<attr name="use_cudnn_on_gpu"  type="Bool" value="True" />
		</attributes>
	</nodedef>
	<nodedef index="6" name="detector/yolo-v3-tiny/Conv/BatchNorm/gamma" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="1" size="64" />
		</attributes>
	</nodedef>
	<nodedef index="7" name="detector/yolo-v3-tiny/Conv/BatchNorm/gamma/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/gamma" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv/BatchNorm/gamma" />
		</attributes>
	</nodedef>
	<nodedef index="8" name="detector/yolo-v3-tiny/Conv/BatchNorm/beta" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="1" size="64" />
		</attributes>
	</nodedef>
	<nodedef index="9" name="detector/yolo-v3-tiny/Conv/BatchNorm/beta/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/beta" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv/BatchNorm/beta" />
		</attributes>
	</nodedef>
	<nodedef index="10" name="detector/yolo-v3-tiny/Conv/BatchNorm/moving_mean" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="1" size="64" />
		</attributes>
	</nodedef>
	<nodedef index="11" name="detector/yolo-v3-tiny/Conv/BatchNorm/moving_mean/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/moving_mean" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv/BatchNorm/moving_mean" />
		</attributes>
	</nodedef>
	<nodedef index="12" name="detector/yolo-v3-tiny/Conv/BatchNorm/moving_variance" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="1" size="64" />
		</attributes>
	</nodedef>
	<nodedef index="13" name="detector/yolo-v3-tiny/Conv/BatchNorm/moving_variance/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/moving_variance" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv/BatchNorm/moving_variance" />
		</attributes>
	</nodedef>
	<nodedef index="14" name="detector/yolo-v3-tiny/Conv/BatchNorm/FusedBatchNorm" op="FusedBatchNorm">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/Conv2D" />
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/gamma/read" />
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/beta/read" />
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/moving_mean/read" />
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/moving_variance/read" />
		</inputs>
		<attributes>
			<attr name="is_training"  type="Bool" value="False" />
			<attr name="T"  type="Type" value="Float" />
			<attr name="data_format"  type="String" value="NHWC" />
			<attr name="epsilon"  type="Float" value="1.001e-05" />
		</attributes>
	</nodedef>
	<nodedef index="15" name="detector/yolo-v3-tiny/Conv/LeakyRelu/alpha" op="Const">
		<inputs />
		<attributes>
			<attr name="value"  type="Tensor" type="Float"  dims="0" size="0" />
			<attr name="dtype"  type="Type" value="Float" />
		</attributes>
	</nodedef>
	<nodedef index="16" name="detector/yolo-v3-tiny/Conv/LeakyRelu/mul" op="Mul">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/LeakyRelu/alpha" />
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/FusedBatchNorm" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
		</attributes>
	</nodedef>
	<nodedef index="17" name="detector/yolo-v3-tiny/Conv/LeakyRelu" op="Maximum">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/LeakyRelu/mul" />
			<input node="detector/yolo-v3-tiny/Conv/BatchNorm/FusedBatchNorm" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
		</attributes>
	</nodedef>
	<nodedef index="18" name="detector/yolo-v3-tiny/pool2/MaxPool" op="MaxPool">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv/LeakyRelu" />
		</inputs>
		<attributes>
			<attr name="strides"  type="List" int-size="4" int-vals="1,2,2,1" />
			<attr name="T"  type="Type" value="Float" />
			<attr name="data_format"  type="String" value="NHWC" />
			<attr name="padding"  type="String" value="VALID" />
			<attr name="ksize"  type="List" int-size="4" int-vals="1,2,2,1" />
		</attributes>
	</nodedef>
	<nodedef index="19" name="detector/yolo-v3-tiny/Conv_1/weights" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="4" size="18432" />
		</attributes>
	</nodedef>
	<nodedef index="20" name="detector/yolo-v3-tiny/Conv_1/weights/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/weights" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv_1/weights" />
		</attributes>
	</nodedef>
	<nodedef index="21" name="detector/yolo-v3-tiny/Conv_1/Conv2D" op="Conv2D">
		<inputs>
			<input node="detector/yolo-v3-tiny/pool2/MaxPool" />
			<input node="detector/yolo-v3-tiny/Conv_1/weights/read" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="strides"  type="List" int-size="4" int-vals="1,1,1,1" />
			<attr name="padding"  type="String" value="SAME" />
			<attr name="dilations"  type="List" int-size="4" int-vals="1,1,1,1" />
			<attr name="data_format"  type="String" value="NHWC" />
			<attr name="use_cudnn_on_gpu"  type="Bool" value="True" />
		</attributes>
	</nodedef>
	<nodedef index="22" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/gamma" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="1" size="128" />
		</attributes>
	</nodedef>
	<nodedef index="23" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/gamma/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/gamma" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv_1/BatchNorm/gamma" />
		</attributes>
	</nodedef>
	<nodedef index="24" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/beta" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="1" size="128" />
		</attributes>
	</nodedef>
	<nodedef index="25" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/beta/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/beta" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv_1/BatchNorm/beta" />
		</attributes>
	</nodedef>
	<nodedef index="26" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_mean" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="1" size="128" />
		</attributes>
	</nodedef>
	<nodedef index="27" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_mean/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_mean" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_mean" />
		</attributes>
	</nodedef>
	<nodedef index="28" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_variance" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="1" size="128" />
		</attributes>
	</nodedef>
	<nodedef index="29" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_variance/read" op="Identity">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_variance" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
			<attr name="_class"  type="List" string-size="1" strings="loc:@detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_variance" />
		</attributes>
	</nodedef>
	<nodedef index="30" name="detector/yolo-v3-tiny/Conv_1/BatchNorm/FusedBatchNorm" op="FusedBatchNorm">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/Conv2D" />
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/gamma/read" />
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/beta/read" />
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_mean/read" />
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/moving_variance/read" />
		</inputs>
		<attributes>
			<attr name="is_training"  type="Bool" value="False" />
			<attr name="T"  type="Type" value="Float" />
			<attr name="data_format"  type="String" value="NHWC" />
			<attr name="epsilon"  type="Float" value="1.001e-05" />
		</attributes>
	</nodedef>
	<nodedef index="31" name="detector/yolo-v3-tiny/Conv_1/LeakyRelu/alpha" op="Const">
		<inputs />
		<attributes>
			<attr name="value"  type="Tensor" type="Float"  dims="0" size="0" />
			<attr name="dtype"  type="Type" value="Float" />
		</attributes>
	</nodedef>
	<nodedef index="32" name="detector/yolo-v3-tiny/Conv_1/LeakyRelu/mul" op="Mul">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/LeakyRelu/alpha" />
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/FusedBatchNorm" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
		</attributes>
	</nodedef>
	<nodedef index="33" name="detector/yolo-v3-tiny/Conv_1/LeakyRelu" op="Maximum">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/LeakyRelu/mul" />
			<input node="detector/yolo-v3-tiny/Conv_1/BatchNorm/FusedBatchNorm" />
		</inputs>
		<attributes>
			<attr name="T"  type="Type" value="Float" />
		</attributes>
	</nodedef>
	<nodedef index="34" name="detector/yolo-v3-tiny/pool2_1/MaxPool" op="MaxPool">
		<inputs>
			<input node="detector/yolo-v3-tiny/Conv_1/LeakyRelu" />
		</inputs>
		<attributes>
			<attr name="strides"  type="List" int-size="4" int-vals="1,2,2,1" />
			<attr name="T"  type="Type" value="Float" />
			<attr name="data_format"  type="String" value="NHWC" />
			<attr name="padding"  type="String" value="VALID" />
			<attr name="ksize"  type="List" int-size="4" int-vals="1,2,2,1" />
		</attributes>
	</nodedef>
	<nodedef index="35" name="detector/yolo-v3-tiny/Conv_2/weights" op="Const">
		<inputs />
		<attributes>
			<attr name="dtype"  type="Type" value="Float" />
			<attr name="value"  type="Tensor" type="Float"  dims="4" size="73728" />
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Tsin__Ross
New Contributor I
‎03-19-2019 02:14 AM
723 Views

My question:

We see some tensors with "0" dimension, from the context, we know those are for constants, how does Tensorflow store constants in .pb file?

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