Week 3: Community Bonding cont.

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Update :

In this week, I did the following tasks.

  1. Prepared Dockerfile to send a merge request. This needed to be integrated with the previous Dockerfile. 
  2. Implemented sample quantization and pruning methods on Densenet201 model. Quantization turned out to be fine but pruning made me run into Out-Of-Memory (OOM) errors multiple times.
  3. Prepared my system for the project by installing all the required packages. I had to uninstall my Ubuntu system and dual boot my PC again with an increased partition size so that it could accommodate the size of the project as well as the Docker images.
  4. Finalized model performance methods and packages for it. I found the psutil python library the could help me perform model evaluation.
  5. Read about Knowledge Distillation and it’s related papers. This concept took time to understand and I found more interesting methods for model compression.
Following are my goals for next week. These are urgent tasks and need to be done asap.
  1. Finalize datasets, models and compression methods to implement after discussing with my mentors.
  2. Finalize the system architecture and the plan of implementation.
I feel that I need to strengthen my communication with my mentors as I have a lot of things to discuss in the following week. Looking forward to the next week!

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