[s2s examples] convert existing scripts to run_seq2seq.py from finetune_trainer.py
As `transformers` examples are evolving it seems that the good old `finetune_trainer.py` is going to be moved into unmaintained `examples/legacy/` area, and `run_seq2seq.py` is to be the new king, so let's automate this process

Assuming your cmd script is `process.txt` (and replace with the file names that you have (one or many), let's auto-adjust it:

1. Renames
```
# main name and args rename
perl -pi -e 's|finetune_trainer|run_seq2seq|g; s#--n_(train|val)#--max_$1_samples#g; \
s|--src_lang|--source_lang|g; s|--tgt_lang|--target_lang|g; s|--eval_beams|--num_beams|'  process.txt

# drop no longer supported args
perl -pi -e 's|--freeze_embeds||; s|--test_max_target_length[ =]+\d+||;' process.txt

```

2. t5 auto-adding prefix has been dropped, so you need to add it manually, e.g.:
```
--source_prefix "translate English to Romanian: "
```
otherwise the results would be terrible.

3. Datasets are different

a. need to convert the normal dataset into jsonlines (unless the data is already on datasets hub)
instructions are: https://huggingface.co/docs/datasets/loading_datasets.html#json-files

b. new arguments:

instead of 
```
            --data_dir {data_dir}
```
now you need:
``` 
            --train_file {data_dir}/train.json
            --validation_file {data_dir}/val.json
```

Here's is an example conversion script for the `wmt_en_ro` dataset:

```
# convert.py
import io
import json
import re

src_lang, tgt_lang = ["en", "ro"]

for split in ["train", "val", "test"]:
    recs = []
    fout = f"{split}.json"
    with io.open(fout, "w", encoding="utf-8") as f:
        for type in ["source", "target"]:
            fin = f"{split}.{type}"
            recs.append([line.strip() for line in open(fin)])
        for src, tgt in zip(*recs):
            out = {"translation": { src_lang: src, tgt_lang: tgt } }
            x = json.dumps(out, indent=0, ensure_ascii=False)
            x = re.sub(r'\n', ' ', x, 0, re.M)
            f.write(x + "\n")
```

Or if you find an existing dataset in `datasets`, you can supply it instead of the `--data_dir` arg as following:

```
--dataset_name wmt16 --dataset_config_name ro-en 
```

Here is the full conversion table from the previously recommended 4 datasets in the `examples/seq2seq` folder:
* [x] `--data_dir wmt_en_de` => `--dataset_name wmt14 --dataset_config "de-en"` or if you want the highest score use: `--dataset_name wmt14-en-de-pre-processed`
* [x] `--data_dir wmt_en_ro` => --dataset_name wmt16 --dataset_config "ro-en"` 
* [x] `--data_dir cnn_dm` => `--dataset_name cnn_dailymail --dataset_config "3.0.0"`
* [x] `--data_dir xsum` => `--dataset_name xsum`

You will find more details [here](https://github.com/huggingface/transformers/issues/10044#issuecomment-779555741)

----

t5-specific changes: from https://github.com/huggingface/transformers/pull/10133#issuecomment-778071812

    1. Use the same dataset
    2. if using T5 manually pass the `prefix` argument,
    3. manually copy the `task_specific_parms` to `config`



`run_seq2seq.py` didn't survive for long, it's no more in master, so yet another automatic conversion for translation scripts is:

```
perl -pi -e 's|run_seq2seq.py|run_translation.py|g; s|--task translation_(\w\w)_to_(\w\w)|--source_lang $1 --target_lang $2|;' process.txt
```
<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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