Training a new PLC model

[dariadiatlova]

Hello,

I am trying to train a new PLC model with train_plc.py and and several things have caused me difficulties:

1. Can I follow the same data preprocessing set up with ./dump_data -train input.s16 features.f32 data.s16 to get input features.f32 for PLC model training?
2. How should lost_file for training look like? Is it a single .txt file - a concatenation of smaller .txt files with one entry per 20ms packet, where 1 means "packet lost" and 0 means "packet not lost"? How to create a single file if original data was augmented after running ./dump_data? Is there any script for it?
3. To close the above questions with lost_file preprocessing, can I just uncomment the line and train the model with random packets marked as lost? Have you noticed any significant degradation in how this works?
4. Following test_plc.py, the output is: features + (1-lost)*out, but the shapes:

• features: [bs, seq_len, nb_used_features+nb_burg_features]
• lost: [bs, seq_len, 1]
• out: [bs, seq_len, nb_used_features]

Did I think of the wrong shapes? What should be the shape of a correct output for writing to output.f32?

Thank you for sharing your code and supporting this repository!

[Janne-byti]

@dariadiatlova Hello, could you please retrain the PLC model? May I ask how to prepare training data?

[felixshing]

Hello, I am also interested in training a new PLC model with a combination of audio features and visual features. I would like to ask how to do that? Any insights are truly appreciated!