MXNET ISSUE

[Batra__Dhruv]

Hey...I tried running the model optimizer on ssd_inceptionv3_512_voc0712trainval downloaded from the link which was provided in the documentation. 
This is the Error I have got:
 

dhruv@dhruv:/opt/intel/computer_vision_sdk/deployment_tools/model_optimizer$ sudo pyt

hon3 mo_mxnet.py --input_model /home/dhruv/Downloads/ssd_inceptionv3_512_voc0712train

val/ssd_inceptionv3_512-0215.params --input_shape [1,3,300,300]

Model Optimizer arguments:

Common parameters:

- Path to the Input Model: /home/dhruv/Downloads/ssd_inceptionv3_512_voc

0712trainval/ssd_inceptionv3_512-0215.params

- Path for generated IR: /opt/intel/computer_vision_sdk_2018.5.445/dep

loyment_tools/model_optimizer/.

- IR output name: ssd_inceptionv3_512-0215

- 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: [1,3,300,300]

- 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

MXNet specific parameters:

- Deploy-ready symbol file: None

- Enable MXNet loader for models trained with MXNet version lower than 1.0.0:

False

- Prefix name for args.nd and argx.nd files: None

- Pretrained model to be merged with the .nd files: None

- Enable saving built parameters file from .nd files: False

Model Optimizer version: 1.5.12.49d067a0

[ ERROR ]  Unexpected exception happened during extracting attributes for node mixed_

1_tower_1_conv_2_batchnorm_moving_mean.

Original exception message: Operation '_contrib_MultiBoxTarget' not supported. Please

register it as custom op.

For more information please refer to Model Optimizer FAQ (<INSTALL_DIR>/deployment_t

ools/documentation/docs/MO_FAQ.html), question #86.

dhruv@dhruv:/opt/intel/computer_vision_sdk/deployment_tools/model_optimizer$