Update en-as.py

en-as.py

@@ -1,45 +1,168 @@
 import datasets
 
-from .wmt_utils import Wmt, WmtConfig
-
-
-_URL = "http://www.statmt.org/wmt16/translation-task.html"
-_CITATION = """
-@InProceedings{bojar-EtAl:2016:WMT1,
-  author    = {Bojar, Ond\v{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Graham, Yvette  and  Haddow, Barry  and  Huck, Matthias  and  Jimeno Yepes, Antonio  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Neveol, Aurelie  and  Neves, Mariana  and  Popel, Martin  and  Post, Matt  and  Rubino, Raphael  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco  and  Verspoor, Karin  and  Zampieri, Marcos},
-  title     = {Findings of the 2016 Conference on Machine Translation},
-  booktitle = {Proceedings of the First Conference on Machine Translation},
-  month     = {August},
-  year      = {2016},
-  address   = {Berlin, Germany},
-  publisher = {Association for Computational Linguistics},
-  pages     = {131--198},
-  url       = {http://www.aclweb.org/anthology/W/W16/W16-2301}
+
+_CITATION = """\
+@inproceedings{siripragada-etal-2020-multilingual,
+    title = "A Multilingual Parallel Corpora Collection Effort for {I}ndian Languages",
+    author = "Siripragada, Shashank  and
+      Philip, Jerin  and
+      Namboodiri, Vinay P.  and
+      Jawahar, C V",
+    booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
+    month = may,
+    year = "2020",
+    address = "Marseille, France",
+    publisher = "European Language Resources Association",
+    url = "https://aclanthology.org/2020.lrec-1.462",
+    pages = "3743--3751",
+    language = "English",
+    ISBN = "979-10-95546-34-4",
+}
+@article{2020,
+   title={Revisiting Low Resource Status of Indian Languages in Machine Translation},
+   url={http://dx.doi.org/10.1145/3430984.3431026},
+   DOI={10.1145/3430984.3431026},
+   journal={8th ACM IKDD CODS and 26th COMAD},
+   publisher={ACM},
+   author={Philip, Jerin and Siripragada, Shashank and Namboodiri, Vinay P. and Jawahar, C. V.},
+   year={2020},
+   month={Dec}
 }
 """
 
-_LANGUAGE_PAIRS = [(lang, "as") for lang in ["or"]]
+_DESCRIPTION = """\
+Sentence aligned parallel corpus between 11 Indian Languages, crawled and extracted from the press information bureau
+website.
+"""
+
+_HOMEPAGE = "http://preon.iiit.ac.in/~jerin/bhasha/"
+
+_LICENSE = "Creative Commons Attribution-ShareAlike 4.0 International"
+
+_URL = {
+    "0.0.0": "http://preon.iiit.ac.in/~jerin/resources/datasets/pib-v0.tar",
+    "1.3.0": "http://preon.iiit.ac.in/~jerin/resources/datasets/pib_v1.3.tar.gz",
+}
+_ROOT_DIR = {
+    "0.0.0": "pib",
+    "1.3.0": "pib-v1.3",
+}
 
+_LanguagePairs = [
+    "or-ur",
+    "ml-or",
+    "bn-ta",
+    "gu-mr",
+    "hi-or",
+    "en-or",
+    "mr-ur",
+    "en-ta",
+    "hi-ta",
+    "bn-en",
+    "bn-or",
+    "ml-ta",
+    "gu-ur",
+    "bn-ml",
+    "ml-pa",
+    "en-pa",
+    "bn-hi",
+    "hi-pa",
+    "gu-te",
+    "pa-ta",
+    "hi-ml",
+    "or-te",
+    "en-ml",
+    "en-hi",
+    "bn-pa",
+    "mr-te",
+    "mr-pa",
+    "bn-te",
+    "gu-hi",
+    "ta-ur",
+    "te-ur",
+    "or-pa",
+    "gu-ml",
+    "gu-pa",
+    "hi-te",
+    "en-te",
+    "ml-te",
+    "pa-ur",
+    "hi-ur",
+    "mr-or",
+    "en-ur",
+    "ml-ur",
+    "bn-mr",
+    "gu-ta",
+    "pa-te",
+    "bn-gu",
+    "bn-ur",
+    "ml-mr",
+    "or-ta",
+    "ta-te",
+    "gu-or",
+    "en-gu",
+    "hi-mr",
+    "mr-ta",
+    "en-mr"
+    "as-or",
+]
 
-class Wmt16(Wmt):
-    """WMT 16 translation datasets for all {xx, "en"} language pairs."""
 
-    BUILDER_CONFIGS = [
-        WmtConfig(  # pylint:disable=g-complex-comprehension
-            description="WMT 2016 %s-%s translation task dataset." % (l1, l2),
-            url=_URL,
+class PibConfig(datasets.BuilderConfig):
+    """BuilderConfig for PIB"""
+
+    def __init__(self, language_pair, version=datasets.Version("1.3.0"), **kwargs):
+        super().__init__(version=version, **kwargs)
+        """
+        Args:
+            language_pair: language pair, you want to load
+            **kwargs: keyword arguments forwarded to super.
+        """
+        self.src, self.tgt = language_pair.split("-")
+
+
+class Pib(datasets.GeneratorBasedBuilder):
+    """This new dataset is the large scale sentence aligned corpus in 11 Indian languages, viz.
+    CVIT-PIB corpus that is the largest multilingual corpus available for Indian languages.
+    """
+
+    BUILDER_CONFIG_CLASS = PibConfig
+    BUILDER_CONFIGS = [PibConfig(name=pair, description=_DESCRIPTION, language_pair=pair) for pair in _LanguagePairs]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {"translation": datasets.features.Translation(languages=[self.config.src, self.config.tgt])}
+            ),
+            supervised_keys=(self.config.src, self.config.tgt),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
             citation=_CITATION,
-            language_pair=(l1, l2),
-            version=datasets.Version("1.0.0"),
         )
-        for l1, l2 in _LANGUAGE_PAIRS
-    ]
-
-    @property
-    def _subsets(self):
-        return {
-            datasets.Split.TRAIN: [
-                "as-or"              
-            ],
-            
-        }
+
+    def _split_generators(self, dl_manager):
+        archive = dl_manager.download(_URL[str(self.config.version)])
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "archive": dl_manager.iter_archive(archive),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, archive):
+        root_dir = _ROOT_DIR[str(self.config.version)]
+        data_dir = f"{root_dir}/{self.config.src}-{self.config.tgt}"
+        src = tgt = None
+        for path, file in archive:
+            if data_dir in path:
+                if f"{data_dir}/train.{self.config.src}" in path:
+                    src = file.read().decode("utf-8").split("\n")[:-1]
+                if f"{data_dir}/train.{self.config.tgt}" in path:
+                    tgt = file.read().decode("utf-8").split("\n")[:-1]
+            if src and tgt:
+                break
+        for idx, (s, t) in enumerate(zip(src, tgt)):
+            yield idx, {"translation": {self.config.src: s, self.config.tgt: t}}