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Sum output shape is resulting collision

Genc__Sahika
Beginner
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I am getting an error on the output shape after Sum layer. It seems like the output is transposed:

 

Model Optimizer arguments:

 

- 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: [1,120,160,2]

- 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: 2019.3.0-408-gac8584cb7

[ ERROR ]  After partial shape inference were found shape collision for node main_level/agent/main/online/network_1/stereo/Sum (old shape: [ 1 13 64], new shape: [ 1 64 13])

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