Possible caching bug

The following code with `test1.txt` containing just "🤗🤗🤗":
```
dataset = datasets.load_dataset('text', data_files=['test1.txt'], split="train", encoding="latin_1")
print(dataset[0])
dataset = datasets.load_dataset('text', data_files=['test1.txt'], split="train", encoding="utf-8")
print(dataset[0])
``` 
produces this output:
```
Downloading and preparing dataset text/default-15600e4d83254059 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /home/arne/.cache/huggingface/datasets/text/default-15600e4d83254059/0.0.0/52cefbb2b82b015d4253f1aeb1e6ee5591124a6491e834acfe1751f765925155...
Dataset text downloaded and prepared to /home/arne/.cache/huggingface/datasets/text/default-15600e4d83254059/0.0.0/52cefbb2b82b015d4253f1aeb1e6ee5591124a6491e834acfe1751f765925155. Subsequent calls will reuse this data.
{'text': 'ð\x9f¤\x97ð\x9f¤\x97ð\x9f¤\x97'}
Using custom data configuration default
Reusing dataset text (/home/arne/.cache/huggingface/datasets/text/default-15600e4d83254059/0.0.0/52cefbb2b82b015d4253f1aeb1e6ee5591124a6491e834acfe1751f765925155)
{'text': 'ð\x9f¤\x97ð\x9f¤\x97ð\x9f¤\x97'}
```
Just changing the order (and deleting the temp files):
```
dataset = datasets.load_dataset('text', data_files=['test1.txt'], split="train", encoding="utf-8")
print(dataset[0])
dataset = datasets.load_dataset('text', data_files=['test1.txt'], split="train", encoding="latin_1")
print(dataset[0])
```
produces this:
```
Using custom data configuration default
Downloading and preparing dataset text/default-15600e4d83254059 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /home/arne/.cache/huggingface/datasets/text/default-15600e4d83254059/0.0.0/52cefbb2b82b015d4253f1aeb1e6ee5591124a6491e834acfe1751f765925155...
Dataset text downloaded and prepared to /home/arne/.cache/huggingface/datasets/text/default-15600e4d83254059/0.0.0/52cefbb2b82b015d4253f1aeb1e6ee5591124a6491e834acfe1751f765925155. Subsequent calls will reuse this data.
{'text': '🤗🤗🤗'}
Using custom data configuration default
Reusing dataset text (/home/arne/.cache/huggingface/datasets/text/default-15600e4d83254059/0.0.0/52cefbb2b82b015d4253f1aeb1e6ee5591124a6491e834acfe1751f765925155)
{'text': '🤗🤗🤗'}
```

Is it intended that the cache path does not depend on the config entries?

tested with datasets==1.1.2 and python==3.8.5

Thanks for reporting. That's a bug indeed.
Apparently only the `data_files` parameter is taken into account right now in `DatasetBuilder._create_builder_config` but it should also be the case for `config_kwargs` (or at least the instantiated `builder_config`)

Hi, does this bug be fixed? when I load JSON files, I get the same errors by the command 
`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`

change the dateset to load json by refering to https://huggingface.co/docs/datasets/loading.html
`dataset = datasets.load_dataset('json', data_files=args.dataset)`

Errors:
`Downloading and preparing dataset json/default (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/json/default-c1e124ad488911b8/0.0.0/45636811569ec4a6630521c18235dfbbab83b7ab572e3393c5ba68ccabe98264...
`

```ds = load_dataset("csv", data_files={'train': 'train.csv', 'test': 'test.csv'})```

Gives the output
```Using custom data configuration default-5c8ae7c208631aca```

and the code hangs there.

> `ds = load_dataset("csv", data_files={'train': 'train.csv', 'test': 'test.csv'})`
> 
> Gives the output `Using custom data configuration default-5c8ae7c208631aca`
> 
> and the code hangs there.

Have you solved it? I met this problem too!

Can you Ctrl+C to kill the process and share the stacktrace here ? It should show at which location in the code it was hanging

I had the same issue and solved it by downgrading the datasets version from 2.7.0 -> 2.6.1
pip install -q datasets==2.6.1

> I had the same issue and solved it by downgrading the datasets version from 2.7.0 -> 2.6.1 pip install -q datasets==2.6.1

Thanks, it works for me