Add MetaShift dataset
Hi ! Thanks for adding this dataset :) Let me answer your questions:

1. in this case you can put everything in the "train" split
2. Yes you can copy the script (provided you also include the MIT license of the code in the file header for example). Though we ideally try to not create new directories nor files when generating dataset, so if possible this script should be adapted to not create the file structure they mentioned, but instead yield the images one by one in `_generate_examples`. Let me know if you think this is feasible
3. see point 2 haha

> The user has the ability to use default selected classes, get the complete dataset or add more specific additional classes. I think config would be a good option here.

Yup ! We can also define a `selected_classes` parameter such that users can do
```python
load_dataset("metashift", selected_classes=["cat", "dog", ...])
```
## Adding a Dataset
- **Name:** MetaShift
- **Description:**  collection of 12,868 sets of natural images across 410 classes-
- **Paper:** https://arxiv.org/abs/2202.06523v1
- **Data:** https://github.com/weixin-liang/metashift

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

Add MetaShift dataset 
 ## Adding a Dataset
- **Name:** MetaShift
- **Description:**  collection of 12,868 sets of natural images across 410 classes-
- **Paper:** https://arxiv.org/abs/2202.06523v1
- **Data:** https://github.com/weixin-liang/metashift

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
 
 Hi ! Thanks for adding this dataset :) Let me answer your questions:

1. in this case you can put everything in the "train" split
2. Yes you can copy the script (provided you also include the MIT license of the code in the file header for example). Though we ideally try to not create new directories nor files when generating dataset, so if possible this script should be adapted to not create the file structure they mentioned, but instead yield the images one by one in `_generate_examples`. Let me know if you think this is feasible
3. see point 2 haha

> The user has the ability to use default selected classes, get the complete dataset or add more specific additional classes. I think config would be a good option here.

Yup ! We can also define a `selected_classes` parameter such that users can do
```python
load_dataset("metashift", selected_classes=["cat", "dog", ...])
```