Problems with WMT dataset
Hi! Yes, the docs are outdated. Expect this to be fixed soon. 

In the meantime, you can try to fix the issue yourself.

These are the configs/language pairs supported by `wmt15` from which you can choose:
* `cs-en` (Czech - English)
* `de-en` (German - English)
* `fi-en` (Finnish- English)
* `fr-en` (French - English)
* `ru-en` (Russian - English)

And the current implementation always uses all the subsets available for a language, so to define custom subsets, you'll have to clone the repo from the Hub and replace the line https://huggingface.co/datasets/wmt15/blob/main/wmt_utils.py#L688 with:
`for split, ss_names in (self._subsets if self.config.subsets is None else self.config.subsets).items()`

Then, you can load the dataset as follows:
```python
from datasets import load_dataset
dset = load_dataset("path/to/local/wmt15_folder", "<one of 5 available configs>", subsets=...) @mariosasko thanks a lot for the suggested fix!  Hi @mariosasko 

Are the docs updated? If not, I would like to get on it. I am new around here, would we helpful, if you can guide.

Thanks Hi @khushmeeet! The docs haven't been updated, so feel free to work on this issue. This is a tricky issue, so I'll give the steps you can follow to fix this:

First, this code:
https://github.com/huggingface/datasets/blob/7cff5b9726a223509dbd6224de3f5f452c8d924f/src/datasets/load.py#L113-L118

needs to be replaced with (makes the dataset builder search more robust and allows us to remove the ABC stuff from `wmt_utils.py`):
```python
    for name, obj in module.__dict__.items():
        if inspect.isclass(obj) and issubclass(obj, main_cls_type):
            if inspect.isabstract(obj):
                continue
            module_main_cls = obj
            obj_module = inspect.getmodule(obj)
            if obj_module is not None and module == obj_module:
               break
```

Then, all the `wmt_utils.py` scripts need to be updated as follows (these are the diffs with the requiered changes):
````diff
 import os
 import re
 import xml.etree.cElementTree as ElementTree
-from abc import ABC, abstractmethod

 import datasets
````

````diff
logger = datasets.logging.get_logger(__name__)


 _DESCRIPTION = """\
-Translate dataset based on the data from statmt.org.
+Translation dataset based on the data from statmt.org.

-Versions exists for the different years using a combination of multiple data
-sources. The base `wmt_translate` allows you to create your own config to choose
-your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.
+Versions exist for different years using a combination of data
+sources. The base `wmt` allows you to create a custom dataset by choosing
+your own data/language pair. This can be done as follows:

 ```
-config = datasets.wmt.WmtConfig(
-    version="0.0.1",
+from datasets import inspect_dataset, load_dataset_builder
+
+inspect_dataset("<insert the dataset name", "path/to/scripts")
+builder = load_dataset_builder(
+    "path/to/scripts/wmt_utils.py",
     language_pair=("fr", "de"),
     subsets={
         datasets.Split.TRAIN: ["commoncrawl_frde"],
         datasets.Split.VALIDATION: ["euelections_dev2019"],
     },
 )
-builder = datasets.builder("wmt_translate", config=config)
-```

+# Standard version
+builder.download_and_prepare()
+ds = builder.as_dataset()
+
+# Streamable version
+ds = builder.as_streaming_dataset()
+```
 """
````

````diff
+class Wmt(datasets.GeneratorBasedBuilder):
     """WMT translation dataset."""
+
+    BUILDER_CONFIG_CLASS = WmtConfig

     def __init__(self, *args, **kwargs):
-        if type(self) == Wmt and "config" not in kwargs:  # pylint: disable=unidiomatic-typecheck
-            raise ValueError(
-                "The raw `wmt_translate` can only be instantiated with the config "
-                "kwargs. You may want to use one of the `wmtYY_translate` "
-                "implementation instead to get the WMT dataset for a specific year."
-            )
         super(Wmt, self).__init__(*args, **kwargs)

     @property
-    @abstractmethod
     def _subsets(self):
         """Subsets that make up each split of the dataset."""
````
```diff
         """Subsets that make up each split of the dataset for the language pair."""
         source, target = self.config.language_pair
         filtered_subsets = {}
-        for split, ss_names in self._subsets.items():
+        subsets = self._subsets if self.config.subsets is None else self.config.subsets
+        for split, ss_names in subsets.items():
             filtered_subsets[split] = []
             for ss_name in ss_names:
                 dataset = DATASET_MAP[ss_name]
```

`wmt14`, `wmt15`, `wmt16`, `wmt17`, `wmt18`, `wmt19` and `wmt_t2t` have this script, so all of them need to be updated. Also, the dataset summaries from the READMEs of these datasets need to be updated to match the new `_DESCRIPTION` string. And that's it! Let me know if you need additional help. Hi @mariosasko ,

I have made the changes as suggested by you and have opened a PR #4537.

Thanks Resolved via #4554 
## Describe the bug
I am trying to load WMT15 dataset and to define which data-sources to use for train/validation/test splits, but unfortunately it seems that the official documentation at [https://huggingface.co/datasets/wmt15#:~:text=Versions%20exists%20for,wmt_translate%22%2C%20config%3Dconfig)](https://huggingface.co/datasets/wmt15#:~:text=Versions%20exists%20for,wmt_translate%22%2C%20config%3Dconfig)) doesn't work anymore.

## Steps to reproduce the bug
```shell
>>> import datasets
>>> a = datasets.translate.wmt.WmtConfig()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'datasets' has no attribute 'translate'
>>> a = datasets.wmt.WmtConfig()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'datasets' has no attribute 'wmt'
```

## Expected results
To load WMT15 with given data-sources.

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.0
- Platform: Linux-5.10.0-10-amd64-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 7.0.0
- Pandas version: 1.4.1
