Monday, November 28th, 2022 - Saturday, December 3th, 2022
Refactored the vision transformer for small-size datasets code using pytorch. The code is more comprehensible but the dataset and dataloader part is more difficult. The model part is easier but the training part which shows the training process takes some additional work. I needed to use the tqdm to manually build a process bar and make the training process run.
Similar to the tf_data_constructor, I also build a torch_data_constructor python file to construct the dataset and dataloader. Consequently, only the base_dir needed to be modified.
Read the paper [1] and watch videos about it. Also, I start to learn the code.
Turned the code back to the default graph mode. It seemed to be faster and can handle a bigger batch_size.
After a lockdown for approximately fifteen days, I finally went back to the lab on November 30th.
Everything in the laboratory seemed so unfamiliar to me.
Collect this post as an NFT.