Delete rabbi_kook.py

rabbi_kook.py

@@ -1,99 +0,0 @@
-import json
-import os
-from typing import List
-
-import datasets
-
-_CITATION = ""
-
-_DESCRIPTION = ""
-
-_HOMEPAGE = ""
-
-_LICENSE = ""
-
-# The HuggingFace Datasets library doesn't host the datasets but only points to the original raw_files.
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URL = "https://github.com/LiorLevi15/NLP-MINI-PROJECT/tree/master/DATA/parsed_data_splits"
-_URLS = {
-    "train": _URL + "rabbi_kook_train.json",
-    "test": _URL + "rabbi_kook_test.json",
-    "dev": _URL + "rabbi_kook_dev.json",
-}
-
-
-class RabbiKook(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.1.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "id": datasets.Value("string"),
-                "paragraph": datasets.Value("string"),
-                "summery": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-        )
-
-    # def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-    #     urls_to_download = _URLS
-    #     downloaded_files = dl_manager.download_and_extract(urls_to_download)
-    #
-    #     return [
-    #         datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-    #         datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
-    #         datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-    #     ]
-
-    def _split_generators(self, dl_manager):
-        # This method is tasked with downloading/extracting the data and defining the splits.
-
-        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS It can
-        # accept any type or nested list/dict and will give back the same structure with the url replaced with path
-        # to local raw_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
-        data_dir = dl_manager.download_and_extract(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "rabbi_kook_train.json"),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "rabbi_kook_test.json"),
-                    "split": "test"
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "rabbi_kook_dev.json"),
-                    "split": "dev",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        print(f'generating examples from = {filepath}')
-        with open(filepath, encoding="utf-8") as f:
-            data_list = json.load(f)
-            for data in data_list:
-                yield data["id"], {
-                    "paragraph": data["paragraph"],
-                    "summary": data["summary"],
-                    "id": data["id"],
-                }
-