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138 Views

IR model does not work in Myriad-2

Hello,

I have trained an model with pytorch toolkit of openvino_training_extensions. Afterwards I successfully converted it to ONNX with the nncf utility existing in the abovementioned toolkit.

Finally I converted the model in the IR representation  (FP16 and FP32 format) with the openvino model optimizer utilities.

The problem that I have encountered is the following.

I tested both of these formats with the benchmark app in my Ubuntu CPU and they are working. When later I try to test them in the MYRIAD-2 NCS stick then an error breaks the benchmark routine.

The error (which I have not found it in the forums) is the following:

[ ERROR ] AssertionFailed: data->numConsumers() > 0

I attach you the models with other related informations.

Thank you in advance for your time.

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9 Replies
Shubha_R_Intel
Employee
138 Views

Dear Katakis, Sofoklis,

Did you try on OpenVino 2019R3 ? It was just released this week. If not please do so, and report back on this forum.

Thanks !

Shubha

 

138 Views

Dear Shubha,

Thank you for your answer.

Yes I tried. The same thing.

Shubha_R_Intel
Employee
138 Views

Dear Katakis, Sofoklis,

Thanks for trying 2019R3 anyway. Let me debug this and get back to you.

Thanks for your patience !

Shubha

 

Sahira_Intel
Moderator
138 Views

Hi Sofoklis,

If you still require assistance on this issue, can you please provide the commands you used to convert your model, and also the full command you used to deploy your model. I see you also provided a smaller file on your Github ticket here

Sincerely,

Sahira 

138 Views

Dear Sahira,

The command that I used to deploy the model is in log files. I copy it from there.

 "./intel64/Debug/benchmark_app  -i ~/test_im -m /path_to_the_model/model_FP16.xml  -d MYRIAD -b 1"

The command that I used to transform the model is via onnx. I tried various combinations but non was working. An example is the following.

python mo_onnx.py -m Onnx_model_path -n Model_name -o Output_path  --data_type FP16 --scale 255 --input_shape [1,3,300,300]

Hope that I helped,

K. Sofoklis

Sahira_Intel
Moderator
138 Views

Hi,

It looks like there was a bug in the VPU plugin. This issue will be fixed in the next OpenVINO release. 

Please let me know if you have any further questions!

Best Regards,

Sahira

赵__明
Beginner
138 Views

Hello!I have a very similar problem to this,my IR model work with CPU but not MYRIAD,and the error message is(using  2019R3 ):

  File "classification_sample_new.py", line 349, in main
    exec_net = ie.load_network(network=net, device_name=args.device)
  File "ie_api.pyx", line 85, in openvino.inference_engine.ie_api.IECore.load_network
  File "ie_api.pyx", line 92, in openvino.inference_engine.ie_api.IECore.load_network
RuntimeError: AssertionFailed: _allocatedIntermData.count(topParent) > 0

 

For more details please see:

https://software.intel.com/zh-cn/node/832716

Thanks for attention!

Sahira_Intel
Moderator
138 Views

Hi, 

This error is caused by a bug in the VPU plugin that will be resolved in the next OpenVINO release.

Best Regards,

Sahira 

138 Views

Hello, I have the same problem with a Myriad V1. My Network works in CPU mode and when I switch to 'MYRIAD' mode I get this error message.

You can find in attach files the optimise Network and the Python file (inferenceV2myriad.py)

I work with openvino 2019.3.334

 

Can you say when the next release is Ok for correct this bug ?

 

Thank's

 

error message :

python3 inferenceV2myriad.py 
Input Layer:  im0
Output Layer:  2848/Split.1
Input Shape:  [1, 3, 256, 512]
Output Shape:  [1, 6, 64, 128]
Available Devices:  ['MYRIAD']
Traceback (most recent call last):
  File "inferenceV2myriad.py", line 65, in <module>
    OpenVinoExecutable = OpenVinoIE.load_network(network=OpenVinoNetwork,device_name='MYRIAD')
  File "ie_api.pyx", line 85, in openvino.inference_engine.ie_api.IECore.load_network
  File "ie_api.pyx", line 92, in openvino.inference_engine.ie_api.IECore.load_network
RuntimeError: AssertionFailed: _allocatedIntermData.count(topParent) > 0
 

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