OpenVINO Model Optimizer Error of tensorflow model

[park__kyungja]

Hi,

I'm trying to convert custom tensorflow  model to IR with Model Optimizer.

But, I've got error!

here are my command and error message.

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C:\Program Files (x86)\IntelSWTools\openvino_2019.1.133\deployment_tools\model_optimizer>python mo_tf.py --input_model d:\openVINO\frozen_model_tf_1.14.pb --input keep_probabilty,input_image --input_shape (1),(1,40,40,1) --output inference/prediction --output_dir d:\openVINO
Model Optimizer arguments:
Common parameters:
        - Path to the Input Model:      d:\openVINO\frozen_model_tf_1.14.pb
        - Path for generated IR:        d:\openVINO
        - IR output name:       frozen_model_tf_1.14
        - Log level:    ERROR
        - Batch:        Not specified, inherited from the model
        - Input layers:         keep_probabilty,input_image
        - Output layers:        inference/prediction
        - Input shapes:         (1),(1,40,40,1)
        - 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
        - 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:  None
Model Optimizer version:        2019.1.0-341-gc9b66a2
[ ERROR ]  Can't permute attrs for node EltwiseReshapeNormalization. Error message: only integer scalar arrays can be converted to a scalar index

/////////////////////////////////

Please, help me!!

[Shubha_R_Intel]

Dear park, kyungja,

I'm seeing  frozen_model_tf_1.14 everywhere but Model Optimizer only supports up to Tensorflow 1.12 today. 

Thanks,

shubha

[park__kyungja]

Dear, shubha,

Thank you for your quick reply.

Actually, I produced a frozen model on tensorflow 1.9 first

It gave me a same error message.

So, I upgraded tensorflow 1.14 and produced a frozen model on it.

Is any possible other reason?

Thanks anyway 

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// my model info

C:\Program Files (x86)\IntelSWTools\openvino_2019.1.133\deployment_tools\model_optimizer\mo\utils>python summarize_graph.py --input_model "d:\openVINO\frozen_model_tf_1.9.pb"
2 input(s) detected:
Name: keep_probabilty, type: float32, shape: <unknown>
Name: input_image, type: float32, shape: (-1,40,40,1)
1 output(s) detected:
inference/prediction

/////////////////////////

[Shubha_R_Intel]

Dear park, kyungja,

Can you tell me the kind of Tensorflow model you're having issues with ? Is it an Object Detection API model ? SSD ? Faster RCNN ? If it's a Tensorflow Object Detection API model, then you must follow the below instructions:

http://docs.openvinotoolkit.org/latest/_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_Object_Detection_API_Models.html

Please report back here with your results.

Thanks,

Shubha

[park__kyungja]

Dear, Shubha

My model is a kind of semantic segmentation.

It's a modified model of FCN.

It works fine in Ubuntu system with NVIDIA GPU.

Thanks.

Kyungja

[Shubha_R_Intel]

Dear park, kyungja,

Please run downloader.py under C:\Program Files (x86)\IntelSWTools\openvino_2019.1.148\deployment_tools\tools\model_downloader . Do python3 downloader.py --all . After completing that you will see a few semantic segmentation models that we also support, cascaded_unet, deeplab, dilation. Is the model you're trying one of these ?

If it's not, please give me a link to your model (I assume that it's a public model).

Thanks,

Shubha

[park__kyungja]

Dear Shubha,

I've already tested public semantic segmentation models.

There are no problem.

I want to have application specific model.

I designed my network and learned the model with my own image sets.

I can't give you my model publicly.

But, I can send it to you by email.

Please, let me know your email address.

Thanks.

Kyungja

[Shubha_R_Intel]

Dear park, kyungja,

I have PM'd you so that you may send me the model privately.

Appreciate your cooperation.

Thanks !

Shubha