update

open-license-corpus.py

@@ -0,0 +1,110 @@
+import datasets
+import os
+from datasets import load_dataset
+import gzip
+import json
+
+logger = datasets.logging.get_logger(__name__)
+
+
+CITATION = """
+"""
+
+DESCRIPTION = """
+The Open License Corpus
+"""
+
+OLC_SUBSET_NAMES = [
+    "ccby_law",
+    "ccby_s2orc",
+    "ccby_stackexchange",
+    "ccby_stackoverflow",
+    "ccby_wikinews",
+    "ccby_wikipedia",
+    "pd_arxiv_abstracts",
+    "pd_books",
+    "pd_law",
+    "pd_news",
+    "pd_s2orc",
+    "sw_amps_math",
+    "sw_dm_math",
+    "sw_github",
+    "sw_hackernews",
+    "sw_ubuntu_irc"
+] 
+
+URL = "https://huggingface.co/datasets/kernelmachine/open-license-corpus/"
+
+
+
+N_SHARDS_PER_SPLIT = {
+    "ccby_s2orc": {"train": 5000},
+    "ccby_law": {"train": 50},
+    "ccby_stackexchange": {"train": 1500},
+    "ccby_stackoverflow": {"train": 750},
+    "ccby_wikinews": {"train": 42},
+    "ccby_wikipedia": {"train": 3000},
+    "pd_arxiv_abstracts": {"train": 1},
+    "pd_books": {"train": 150},
+    "pd_law": {"train": 2000},
+    "pd_news": {"train": 10},
+    "pd_s2orc": {"train": 30},
+    "sw_amps_math": {"train": 2},
+    "sw_dm_math": {"train": 239},
+    "sw_github": {"train": 2500},
+    "sw_hackernews": {"train": 16},
+    "sw_ubuntu_irc": {"train": 27}
+}
+
+#DATA_URL = 'https://huggingface.co/datasets/kernelmachine/open-license-corpus/blob/main/data/{name}/{split}-{index:05d}-of-{n_shards:05d}.jsonl.gz'
+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, features, citation, **kwargs):
+        super().__init__(**kwargs)
+
+
+class OpenLicenseCorpus(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name=name)
+        for name in OLC_SUBSET_NAMES
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage=URL,
+            citation=CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_urls = {}
+        for split in ["train"]:
+            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 = dl_manager.download(data_urls["train"])
+        
+        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 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