Metadata-Version: 2.1
Name: coreml
Version: 0.0.1
Summary: Generic Framework for ML projects
Home-page: https://github.com/dalmia/coreml
Author: Aman Dalmia
Author-email: amandalmia18@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# CoreML

Generic framework for Machine Learning projects.

## Setup

Clone the project:

```bash
$ git clone https://github.com/dalmia/coreml.git
```

### Weights & Biases
We use [`wandb`](http://wandb.com/) for experiment tracking. You'll need to have that set up:
- Install wandb

```bash
$ pip install wandb
```

2. Login to wandb:

```bash
$ wandb login
```

You will be redirected to a link that will show you your WANDB_API_KEY .

3. Set the WANDB_API_KEY by adding this to your ~/.bashrc file:
```bash
export WANDB_API_KEY=YOUR_API_KEY
```

4. Run `source ~/.bashrc`.


### Docker
We use Docker containers to ensure replicability of experiments. You can either fetch the Docker image from DockerHub using the following line:
```bash
$ docker pull adalmia/coreml:v1.0
```
OR

You can build the image using the `DockerFile`:
```bash
$ docker build -t adalmia/coreml:v1.0 .
```

The repository runs inside a Docker container. When creating the container, you need to mount the directory containing data to `/data` and directory where you want to store the ouptuts to `/output` on the container. Make the corresponding changes to `create_container.sh` to mount the respective directories by changing `/path/to/coreml`, `/path/to/data` and `/path/to/outputs` to the appropriate values.

Use the following command to launch a container:

```bash
$ bash create_container.sh
```



