Data loader handles new training set files

opusparcus.py

@@ -41,15 +41,14 @@ _HOMEPAGE = ""
 
 _LICENSE = ""
 
-# The HuggingFace dataset library don't host the datasets but only point to the original files
+# The HuggingFace dataset library doesn't host the datasets but only point to the original files
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 
 _URLs = {
-
-    "train": None,      # actual value set in the `_split_generators` method
     "validation": "validation.jsonl",
     "test": "test.jsonl"
 
+    # NB: the "train" split file is defined dynamically inside the `_split_generators` method
 }
 
 _VERSION = datasets.Version("1.0.0", "")
@@ -136,12 +135,18 @@ class Opusparcus(datasets.GeneratorBasedBuilder):
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
 
-        if self.config.quality > 95:
-            # No training data matches this quality criterion
-            del _URLs["train"]
-        else:
-            _URLs["train"] = "train_{0}.jsonl.bz2".format(self.config.lang)
-
+        if self.config.quality < 70:
+            # We need to retrieve the largest training set file
+            # containing the full training set for the desired language
+            _URLs["train"] = "train_{0}.60.jsonl.bz2".format(self.config.lang)
+        elif self.config.quality <= 95:
+            # We can do with a smaller version of the training set
+            # for the desired language
+            _URLs["train"] = "train_{0}.70.jsonl.bz2".format(self.config.lang)
+
+        # Otherwise, if the desired quality is above 95, we do not
+        # download any training data, because there is no matching data
+            
         data_dir = dl_manager.download_and_extract(_URLs)
 
         splits = [
@@ -176,7 +181,7 @@ class Opusparcus(datasets.GeneratorBasedBuilder):
                     gen_kwargs={
                         "lang": self.config.lang,
                         "quality": self.config.quality,
-                        "filepath": [data_dir["train"], data_dir["train"], data_dir["train"]],
+                        "filepath": data_dir["train"],
                         "split": "train",
                     },
                 )
@@ -192,7 +197,7 @@ class Opusparcus(datasets.GeneratorBasedBuilder):
         # 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.TRAIN:
-            with bz2.open(filepath[0], "rt", encoding="utf-8") as f:
+            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