Delete _charttotext-s.py

_charttotext-s.py

@@ -1,117 +0,0 @@
-#!/usr/bin/env python3
-
-"""
-The script used to load the dataset from the original source.
-"""
-
-import json
-import datasets
-import os
-import csv 
-
-_CITATION = """\
-@inproceedings{kantharaj2022chart,
-  title={Chart-to-Text: A Large-Scale Benchmark for Chart Summarization},
-  author={Kantharaj, Shankar and Leong, Rixie Tiffany and Lin, Xiang and Masry, Ahmed and Thakkar, Megh and Hoque, Enamul and Joty, Shafiq},
-  booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
-  pages={4005--4023},
-  year={2022}
-}
-"""
-_DESCRIPTION = """\
-Chart-to-Text is a large-scale benchmark with two datasets and a total of 44,096 charts covering a wide range of topics and chart types.
-This dataset CONTAINS ONLY the Statista subset from the benchmark. 
-Statista (statista.com) is an online platform that regularly publishes charts on a wide range of topics including economics, market and opinion research.
-
-Statistics:
-Total charts: 27868
-
-=== Chart Type Information ===
-Number of charts of each chart type
-column: 16319
-bar: 8272
-line: 2646
-pie: 408
-table: 223
-
-=== Token Information ===
-Average token count per summary: 53.65027989091431
-Total tokens: 1495126
-Total types (unique tokens): 39598
-=== Sentence Information ===
-Average sentence count per summary: 2.5596741782689825
-"""
-
-_URL = "https://github.com/vis-nlp/Chart-to-text/tree/main/statista_dataset/dataset"
-_LICENSE = "GNU General Public License v3.0"
-
-class ChartToTextS(datasets.GeneratorBasedBuilder):
-    VERSION = "1.0.0"
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features({
-                'title' : datasets.Value(dtype='string'),
-                'ref' : datasets.Value(dtype='string'),
-                'content' : datasets.Value(dtype='large_string'),
-            }),
-            supervised_keys=None,
-            homepage=_URL,
-            citation=_CITATION,
-            license=_LICENSE,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": "dataset", "split" : "train"}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": "dataset", "split" : "dev"}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": "dataset", "split" : "test"}),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        data = []
-        mapping_file = split if split != "dev" else "val"
-
-        with open(
-            os.path.join(
-                filepath, "dataset_split", f"{mapping_file}_index_mapping.csv"
-            )
-        ) as f:
-            next(f)
-            for i, line in enumerate(f):
-                subdir = "." if line.startswith("two_col") else "multiColumn"
-                filename = line.split("-")[1].split(".")[0]
-
-                with open(
-                    os.path.join(filepath, subdir, "data", filename + ".csv")
-                ) as g:
-                    content = []
-                    reader = csv.reader(g, delimiter=",", quotechar='"')
-                    for row in reader:
-                        content.append(row)
-
-                with open(
-                    os.path.join(filepath, subdir, "captions", filename + ".txt")
-                ) as g:
-                    ref = g.read().rstrip("\n")
-
-                with open(
-                    os.path.join(filepath, subdir, "titles", filename + ".txt")
-                ) as g:
-                    title = g.read().rstrip("\n")
-
-                data.append(
-                    {"content": content, "ref": ref, "title": title}
-                )
-
-                if i % 1000 == 0:
-                    print(f"Loaded {i} items")
-
-        for example_idx, entry in enumerate(data):
-            yield example_idx, {key: str(value) for key, value in entry.items()}
-
-if __name__ == '__main__':
-    dataset = datasets.load_dataset(__file__)
-    dataset.push_to_hub("kasnerz/charttotext-s")