Update Docker Readme to include instructions for Low Disk Storage problem

docker/readme.md

@@ -47,3 +47,122 @@ pnpm test
 sh ./scripts/run_tests.sh unzip
 sh ./scripts/run_tests.sh simple vision-classification
 ```
+
+
+## Troubleshooting
+
+### Low Disk Space on Windows
+
+**Issue:** Faced the Issue of Low Space on C Drive, since this is where all the Docker and Linux Distributions of WSL are stored.
+
+**Solution:**
+- To shift WSL to D Drive, Followed the instructions: [Is there any way to install WSL on non-C drive?](https://superuser.com/a/1572837)
+- To shift Docker and Docker Desktop over to D Drive, Followed the instructions: [How can I change the location of docker images when using Docker Desktop on WSL2 with Windows 10 Home?](https://stackoverflow.com/a/63752264/17397774)
+
+---
+After setting up Docker and whatever the issue with space and docker is:
+
+Enable wsl integration with Ububtu in Settings -> Resources -> WSL Integration [Image Here](https://imgur.com/a/t07UovC)
+
+In the WSL Ubuntu terminal, Create a container from the image that we created using:
+```bash
+docker run -p 3000:3000 -p 5000:5000 --name=codegen-dev -it -v $PWD:/code -w /code -v /path/to/data:/data --ipc=host pytorchignite/codegenerator:dev /bin/bash
+```
+
+For Terminal beautification and git branch parsing:
+```bash
+apt-get upgrade && apt-get update
+apt-get install vim
+cd
+vi .bashrc
+```
+
+Insert the script at the end of the `.bashrc`
+```bash
+parse_git_branch() {
+     git branch 2> /dev/null | sed -e '/^[^*]/d' -e 's/* \(.*\)/ (\1)/'
+}
+export PS1="\[\033[0;32m\]\u@\h \[\033[0;33m\]\w\[\033[0;36m\]\$(parse_git_branch)\[\033[0;37m\]\n$ \[\033[0;37m\]"
+```
+
+```bash
+source .bashrc
+```
+
+**The data is stored in `/root/data`**
+
+## Instruction for Debugging:
+
+Inside the container we can install all other project dependencies:
+
+```bash
+git config --global --add safe.directory /code
+
+pnpm i --frozen-lockfile --color
+pnpm build
+
+bash scripts/run_code_style.sh install
+```
+
+Local app deployment, to work in Windows through the layers of docker, wsl and windows, use `--host`
+
+```bash
+pnpm dev --host
+```
+
+In Project Directory:
+```bash
+pnpm test:ci
+
+sh ./scripts/run_tests.sh unzip
+```
+
+Run sample tests:
+```bash
+sh ./scripts/run_tests.sh simple vision-classification
+```
+
+`pnpm test:ci` would have created the actual code which we can debug! What this does is actually simple in the project directory there exists a directory `__tests__` which contains the `js` code to download the actual code!
+What happens is that `pnpm` server is started at `http://localhost:5000` and the scripts accordingly are downloaded using `js` 
+
+>If we want the live changes to be reflected, then we will have to change the line:
+>`await page.goto(http://localhost:5000/create)` to `await page.goto(http://localhost:3000/create)`
+>Before running this, we will first have to run `pnpm dev` so that the local server is started at port `3000` which will be reflecting the live changes, so as mentioned above, since the `js` at `__tests__` are downloading the actual code hosted at the website, it will download the live changes.
+
+**For Debugging:**
+In the file: `.vscode/launch.json`
+```json
+{
+	"version": "0.2.0",
+	"configurations": [
+		{
+			"name": "Python: Remote Attach",
+			"type": "python",
+			"request": "attach",
+			"connect": {
+				"host": "localhost",
+				"port": 3000
+			},
+			"pathMappings": [
+				{
+					"localRoot": "${workspaceFolder}/",
+					"remoteRoot": "/code"
+				}
+			],
+			"justMyCode": false
+		}
+	]
+}
+```
+
+```bash
+pip install debugpy
+```
+
+Go to the template and the test you want to run, in the `dist-tests/` directory, from there we can debug using the command: (Modify according to your needs, this is for the simple tests)
+```bash
+cd dist-tests/vision-segmentation-simple/
+python -m debugpy --listen 0.0.0.0:3000 --wait-for-client main.py --data_path /root/data --train_batch_size 2 --eval_batch_size 2 --num_workers 2 --max_epochs 2 --train_epoch_length 4 --eval_epoch_length 4
+```
+
+>For vision segmentation, we will first have to download the datasets in the `root/data/` folder