# DISS

## Setup
### Python environment
I use conda and python 3.12. After creating python virtual environment, run `./setup.sh` to install dependencies.
```console
$ conda create -n diss python=3.12
$ conda activate diss
$ ./setup.sh
```

## Usage
### To do quick prototype
Use the interactive python files located under notebooks/diss_ipynb or notebooks/modiste_ipynb.

### To check progress
I use tensorboard to log experiments metrics. You don't necessary have to change directory to the experiment folder though. You should be able to see the result with your favorite browser.

```console
$ tensorboard --port 6006 --logdir outputs/$HYDRA_JOB_NAME/sweep/$HYDRA_SWEEP_DIR/
TensorFlow installation not found - running with reduced feature set.

NOTE: Using experimental fast data loading logic. To disable, pass
    "--load_fast=false" and report issues on GitHub. More details:
    https://github.com/tensorflow/tensorboard/issues/4784

Serving TensorBoard on localhost; to expose to the network, use a proxy or pass --bind_all
TensorBoard 2.17.1 at http://localhost:6006/ (Press CTRL+C to quit)
```
