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Error while convert tensorflow model To IR using Model Optimizer

Vina_Alvionita
Beginner
521 Views

Hello, i want to build mask clasifier model. so i trained tensorflow model using mobile-net v2 archiitecture. i had 2 output, mask and non mask. when i tried this model, it was running well. but i want to use in openvino. when i converted it to IR model using model optimizer i got error like this. 

 

C:\Program Files (x86)\Intel\openvino_2020.2.117\deployment_tools\model_optimizer>python mo.py --input_name "D:\saved_model.pb"
usage: mo.py [options]
mo.py: error: unrecognized arguments: --input_name D:\saved_model.pb

C:\Program Files (x86)\Intel\openvino_2020.2.117\deployment_tools\model_optimizer>python mo.py --input_name saved_model.pb
usage: mo.py [options]
mo.py: error: unrecognized arguments: --input_name saved_model.pb

C:\Program Files (x86)\Intel\openvino_2020.2.117\deployment_tools\model_optimizer>python mo.py --input_model saved_model.pb
Model Optimizer arguments:
Common parameters:
- Path to the Input Model: C:\Program Files (x86)\Intel\openvino_2020.2.117\deployment_tools\model_optimizer\saved_model.pb
- Path for generated IR: C:\Program Files (x86)\Intel\openvino_2020.2.117\deployment_tools\model_optimizer\.
- IR output name: saved_model
- Log level: ERROR
- Batch: Not specified, inherited from the model
- 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
- 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
- Use the config file: None
Model Optimizer version: 2020.2.0-60-g0bc66e26ff
[ FRAMEWORK ERROR ] Cannot load input model: TensorFlow cannot read the model file: "C:\Program Files (x86)\Intel\openvino_2020.2.117\deployment_tools\model_optimizer\saved_model.pb" is incorrect TensorFlow model file.
The file should contain one of the following TensorFlow graphs:
1. frozen graph in text or binary format
2. inference graph for freezing with checkpoint (--input_checkpoint) in text or binary format
3. meta graph

Make sure that --input_model_is_text is provided for a model in text format. By default, a model is interpreted in binary format. Framework error details: Truncated message..
For more information please refer to Model Optimizer FAQ (https://docs.openvinotoolkit.org/latest/_docs_MO_DG_prepare_model_Model_Optimizer_FAQ.html), question #43.

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6 Replies
Peh_Intel
Moderator
494 Views

Hi Vina,


Greetings to you. Firstly, I observed that you’re using an old version of Intel® Distribution of OpenVINO™ toolkit (2020.2). I would recommend you install the latest version of Intel® Distribution of OpenVINO™ toolkit which is 2021.2.


Secondly, I observed that you’re using this command line:

python mo.py --input_model saved_model.pb

This instruction makes the input_model points to the saved_model.pb, but in fact, it should point to the directory. The command line should be:

python mo.py --saved_model_dir <SAVED_MODEL_DIRECTORY>

 

You may refer to the link below under point 3 of the “Loading Non-Frozen Models to the Model Optimizer” section for the steps to store non-frozen TensorFlow models and load them to the Model Optimizer:

https://docs.openvinotoolkit.org/2020.2/_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_T...


For your information, SSD MobileNet V2 COCO is a TensorFlow Object Detection API model which is supported by Model Optimizer. TensorFlow Object Detection API model require more arguments in converting to IR format for example:

·      --reverse_input_channels

·      --tensorflow_object_detection_api_pipeline_config

·      --transformations_config


You may find all the required model_optimizer arguments for this SSD MobileNet V2 COCO in this file:

<path_to_openvino>\deployment_tools\open_model_zoo\models\public\ssd_mobilenet_v2_coco\model.yml

 

These information are also available here:

https://github.com/openvinotoolkit/open_model_zoo/blob/master/models/public/ssd_mobilenet_v2_coco/mo...


For more details, you may refer to the following link:

https://docs.openvinotoolkit.org/2020.2/_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_...




Regards,

Peh


Vina_Alvionita
Beginner
476 Views

I have tried to retrained a simple model and i use tensorflow version 2.4.1. and then i convert to IR model used this command :

python mo.py --saved_model_dir "D:\CP"

but i got different error

[ ERROR ] Exception occurred during running replacer "REPLACEMENT_ID" (<class 'extensions.load.tf.loader.TFLoader'>): Unexpected exception happened during extracting attributes for node Adam/dense_27/bias/v/Read/ReadVariableOp.
Original exception message: 'ascii' codec can't decode byte 0xcc in position 1: ordinal not in range(128)

Vina_Alvionita
Beginner
466 Views

UPDATE 

I am also tried freezing the model, but i got this error. which step i actually wrong? 

Model Optimizer arguments:
Common parameters:
- Path to the Input Model: D:\saved_model_2.pb
- Path for generated IR: C:\Program Files (x86)\Intel\openvino_2020.2.117\deployment_tools\model_optimizer\.
- IR output name: saved_model_2
- Log level: ERROR
- Batch: Not specified, inherited from the model
- Input layers: Not specified, inherited from the model
- Output layers: Not specified, inherited from the model
- Input shapes: [1,3,224,224]
- 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
- Use the config file: None
Model Optimizer version: 2020.2.0-60-g0bc66e26ff
[ ERROR ] Exception occurred during running replacer "REPLACEMENT_ID" (<class 'extensions.middle.BiasAddBroadcasting.BiasAddInputBroadcasting'>): After partial shape inference were found shape collision for node model_1/dense_2/BiasAdd/Add (old shape: [ 0 128], new shape: [ -1 128])

Vina_Alvionita
Beginner
463 Views

Thankyou Peh, i read again carefully all of information you gave above. and i get the solution, it need to add --reverse_input_channels . the IR model succesfully converted

 

Peh_Intel
Moderator
454 Views

Hi Vina,


Greetings to you. I’m glad to hear that you had successfully converted your model into IR format.


Shall we close this thread?



Regards,

Peh


Peh_Intel
Moderator
429 Views

Hi Vina,


This thread will no longer be monitored since this issue has been resolved. If you need any additional information from Intel, please submit a new question.



Regards,

Peh


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