Adding training sets

opusparcus.py

@@ -19,6 +19,7 @@ import csv
 import json
 import os
 import datasets
+import bz2
 
 # Add BibTeX citation
 
@@ -105,7 +106,7 @@ class Opusparcus(datasets.GeneratorBasedBuilder):
                 "sent2": datasets.Value("string"),
                 "annot_score": datasets.Value("float"),
                 "gem_id": datasets.Value("string"),
-#                "quality": datasets.Value("int")
+                "quality": datasets.Value("uint8")
             }
         )
 
@@ -190,16 +191,35 @@ class Opusparcus(datasets.GeneratorBasedBuilder):
         """ Yields examples as (key, example) tuples. """
         # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
         # The `key` is here for legacy reason (tfds) and is not important in itself.
-        if split == datasets.Split.TEST:
+        if split == datasets.Split.TRAIN:
+            with bz2.open(filepath, "rt", encoding="utf-8") as f:
+                # We know that this file only contains the desired language,
+                # because for the training sets the languages are in separate
+                # files, and only the desired language has been downloaded 
+                for id_, row in enumerate(f):
+                    data = json.loads(row)
+                    if data["quality"] < self.quality:
+                        # The rest of this file contains too low quality data
+                        break
+                    yield id_, {
+                        "lang": data["lang"],
+                        "sent1": data["sent1"],
+                        "sent2": data["sent2"],
+                        "annot_score": None,
+                        "gem_id": data["gem_id"],
+                        "quality": data["quality"],
+                    }
+        else:
             with open(filepath, encoding="utf-8") as f:
                 for id_, row in enumerate(f):
                     data = json.loads(row)
                     if data["lang"] == lang:
                         yield id_, {
-                            "lang": data["lang"] + "-quality-" + str(quality),
+                            "lang": data["lang"],
                             "sent1": data["sent1"],
                             "sent2": data["sent2"],
                             "annot_score": data["annot_score"],
                             "gem_id": data["gem_id"],
+                            "quality": 100,
                         }