update

open-license-corpus.py

@@ -60,17 +60,16 @@ N_SHARDS_PER_SPLIT = {
 DATA_URL = 'https://huggingface.co/datasets/kernelmachine/open-license-corpus/resolve/main/data/{name}/{split}-{index:05d}-of-{n_shards:05d}.jsonl.gz'
 
 class OpenLicenseCorpusConfig(datasets.BuilderConfig):
-    def __init__(self, *args, subsets, **kwargs):
-        super(OpenLicenseCorpusConfig, self).__init__(**kwargs)
-        self.subsets = subsets
+    def __init__(self, features, citation, **kwargs):
+        super().__init__(**kwargs)
 
 
 class OpenLicenseCorpus(datasets.GeneratorBasedBuilder):
 
     BUILDER_CONFIGS = [
-        OpenLicenseCorpusConfig(name=name, subsets=[name], version=datasets.Version("1.0.0", ""), description=f"OpenLicenseCorpus {name} subset")
+        datasets.BuilderConfig(name=name)
         for name in OLC_SUBSET_NAMES
-    ]   
+    ]
 
     def _info(self):
         return datasets.DatasetInfo(
@@ -88,27 +87,24 @@ class OpenLicenseCorpus(datasets.GeneratorBasedBuilder):
     def _split_generators(self, dl_manager):
         data_urls = {}
         for split in ["train"]:
-            for subset in self.config.subsets:
-                n_shards = N_SHARDS_PER_SPLIT[subset][split] - 1
-                data_urls[split] = {subset: [
-                    DATA_URL.format(name=self.config.name, split=split, index=index, n_shards=n_shards)
-                    for index in range(n_shards)
-                ]
-                }
+            n_shards = N_SHARDS_PER_SPLIT[self.config.name][split] - 1
+            data_urls[split] = [
+                DATA_URL.format(name=self.config.name, split=split, index=index, n_shards=n_shards)
+                for index in range(n_shards)
+            ]
 
-        train_downloaded_files = {subset: dl_manager.download(data_urls["train"]) for subset in self.config.subsets}
+        train_downloaded_files = dl_manager.download(data_urls["train"])
         
-        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": { subset : train_downloaded_files[subset] for subset in self.config.subsets}})]
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files})]
 
     def _generate_examples(self, filepaths):
         """This function returns the examples in the raw (text) form by iterating on all the files."""
         id_ = 0
-        for subset in filepaths:
-            for path in filepaths[subset]:
-                logger.info("generating examples from = %s", path)
-                with gzip.open(open(path, "rb"), "rt", encoding="utf-8") as f:
-                    for line in f:
-                        if line:
-                            example = json.loads(line)
-                            yield id_, example
-                            id_ += 1
+        for filepath in filepaths:
+            logger.info("generating examples from = %s", filepath)
+            with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
+                for line in f:
+                    if line:
+                        example = json.loads(line)
+                        yield id_, example
+                        id_ += 1