[s2s] Script to save wmt data to disk (#6403)

examples/seq2seq/download_wmt.py

+from pathlib import Path
+
+import fire
+from tqdm import tqdm
+
+
+def download_wmt_dataset(src_lang, tgt_lang, dataset="wmt19", save_dir=None) -> None:
+    """Download a dataset using the nlp package and save it to the format expected by finetune.py
+    Format of save_dir: train.source, train.target, val.source, val.target, test.source, test.target.
+
+    Args:
+        src_lang: <str> source language
+        tgt_lang: <str> target language
+        dataset: <str> like wmt19 (if you don't know, try wmt19).
+        save_dir: <str>, where to save the datasets, defaults to f'{dataset}-{src_lang}-{tgt_lang}'
+
+    Usage:
+        >>> download_wmt_dataset('en', 'ru', dataset='wmt19') # saves to wmt19_en_ru
+    """
+    try:
+        import nlp
+    except (ModuleNotFoundError, ImportError):
+        raise ImportError("run pip install nlp")
+    pair = f"{src_lang}-{tgt_lang}"
+    ds = nlp.load_dataset(dataset, pair)
+    if save_dir is None:
+        save_dir = f"{dataset}-{pair}"
+    save_dir = Path(save_dir)
+    save_dir.mkdir(exist_ok=True)
+
+    for split in tqdm(ds.keys()):
+        tr_list = list(ds[split])
+        data = [x["translation"] for x in tr_list]
+        src, tgt = [], []
+        for example in data:
+            src.append(example[src_lang])
+            tgt.append(example[tgt_lang])
+        if split == "validation":
+            split = "val"  # to save to val.source, val.target like summary datasets
+        src_path = save_dir.joinpath(f"{split}.source")
+        src_path.open("w+").write("\n".join(src))
+        tgt_path = save_dir.joinpath(f"{split}.target")
+        tgt_path.open("w+").write("\n".join(tgt))
+    print(f"saved dataset to {save_dir}")
+
+
+if __name__ == "__main__":
+    fire.Fire(download_wmt_dataset)