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Project Repository

This repository contains code and scripts for training and validating TGVNs to replicate https://arxiv.org/abs/2501.03021. Below is an overview of the files and their purposes. As the repository was built on fastMRI, the requirements can be found on /~https://github.com/facebookresearch/fastMRI

File Descriptions

Data and Splits

  • fastmri_split: Contains the data split for the fastMRI knee dataset. Note that the csv files contain absolute paths, so the user should modify them depending on the dataset location.
  • m4raw_split: Contains the data split for the M4Raw dataset. Note that the csv files contain absolute paths, so the user should modify them depending on the dataset location.

SLURM Batch Scripts

  • Set_I.sbatch: SLURM script for running the first set of experiments using TGVN.
  • Set_II.sbatch: SLURM script for running the second set of experiments using TGVN.
  • Set_III.sbatch: SLURM script for running the third set of experiments using TGVN.

Core Code Files

  • custom_losses.py: Implements the custom loss function for training models.
  • data.py: Contains data loading and preprocessing logic for fastMRI knee and M4Raw datasets.
  • distributed.py: Handles distributed training setup and utilities.
  • main_fastmri.py: Main script for training and evaluating models on the fastMRI dataset.
  • main_m4.py: Main script for training and evaluating models on the M4Raw dataset.
  • models.py: Defines TGVN architecture used in the project.

Running Experiments

  1. Update the SLURM batch scripts (Set_I.sbatch, Set_II.sbatch, Set_III.sbatch) with the appropriate parameters for your environment.
  2. Submit jobs using: 
    sbatch Set_I.sbatch
sbatch Set_II.sbatch
sbatch Set_III.sbatch

Questions

For any questions or issues, feel free to reach out or open an issue in this repository.