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How to generate Debug Dump Binaries (DDB)

The DDB contains useful information for functional debugging of the RBLN NPU, such as the input of the RBLN Compiler, the error log of each compile pass, and the progress status of the compilation. Note that all DDB files are securely encrypted.

You can generate the DDB by setting the environment variable RBLN_DEBUG_LEVEL:

  • RBLN_DEBUG_LEVEL=1: DDB generation, without model parameters
  • RBLN_DEBUG_LEVEL=2: DDB generation, including model parameters

Setting RBLN_DEBUG_LEVEL=2 is better for debugging, but if it is not possible to share the model parameters, setting RBLN_DEBUG_LEVEL=1 is a suitable option.

Here is an example of how to generate the DDB for the PyTorch ResNet50 model in the RBLN Model Zoo:

$ cd rbln_model_zoo/pytorch/torchvisions
$ RBLN_DEBUG_LEVEL=2 python3 --model_name resnet50
$ ls ./debug_mm_dd_yyyy_hh_mm_ss/

You can see:

0_graph.json.gz.enc  100_graph.json.gz.enc  error_log.txt.enc  progress.txt.enc

We recommend that you create a tar ball containing all DDB files and submit it via RBLN portal > Technical Supports with detailed descriptions for further assistance:

$ tar -zcvf debug_mm_dd_yyyy_hh_mm_ss.tar.gz debug_mm_dd_yyyy_hh_mm_ss/