Added data loader script - totto

totto.py

@@ -0,0 +1,180 @@
+import json
+import os
+
+import datasets
+
+_CITATION = """\@inproceedings{parikh2020totto,
+title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},
+author={Parikh, Ankur P and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},
+booktitle={Proceedings of EMNLP},
+year={2020}
+}
+"""
+
+_DESCRIPTION = """\
+ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description. 
+"""
+
+_URLs = {
+    "totto": {
+        "data": "https://storage.googleapis.com/totto/totto_data.zip",
+        "challenge_set": "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_challenge_sets/totto.zip",
+    },
+}
+
+
+class Mlsum(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            version=datasets.Version("1.0.0"),
+            description=f"GEM benchmark: struct2text task",
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features = datasets.Features(
+                {
+                    "gem_id": datasets.Value("string"),
+                    "gem_parent_id": datasets.Value("string"),
+                    "totto_id": datasets.Value("int32"),
+                    "table_page_title": datasets.Value("string"),
+                    "table_webpage_url": datasets.Value("string"),
+                    "table_section_title": datasets.Value("string"),
+                    "table_section_text": datasets.Value("string"),
+                    "table": [
+                        [
+                            {
+                                "column_span": datasets.Value("int32"),
+                                "is_header": datasets.Value("bool"),
+                                "row_span": datasets.Value("int32"),
+                                "value": datasets.Value("string"),
+                            }
+                        ]
+                    ],
+                    "highlighted_cells": [[datasets.Value("int32")]],
+                    "example_id": datasets.Value("string"),
+                    "sentence_annotations": [
+                        {
+                            "original_sentence": datasets.Value("string"),
+                            "sentence_after_deletion": datasets.Value("string"),
+                            "sentence_after_ambiguity": datasets.Value("string"),
+                            "final_sentence": datasets.Value("string"),
+                        }
+                    ],
+                    "overlap_subset": datasets.Value("string"),
+                    "target": datasets.Value("string"),  # single target for train
+                    "references": [datasets.Value("string")],
+                },
+            ),
+            supervised_keys=None,
+            homepage="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        dl_dir = dl_manager.download_and_extract(_URLs[self.config.name])
+        challenge_sets = [
+                ("challenge_train_sample", "train_totto_RandomSample500.json"),
+                ("challenge_validation_sample", "validation_totto_RandomSample500.json"),
+                ("challenge_test_scramble", "test_totto_ScrambleInputStructure500.json"),
+            ]
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "filepath": os.path.join(dl_dir["data"], "totto_data/totto_train_data.jsonl"),
+                        "split": "train",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    gen_kwargs={
+                        "filepath": os.path.join(dl_dir["data"], "totto_data/totto_dev_data.jsonl"),
+                        "split": "validation",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "filepath": os.path.join(dl_dir["data"], "totto_data/unlabeled_totto_test_data.jsonl"),
+                        "split": "test",
+                    },
+                ),
+            ] + [
+                datasets.SplitGenerator(
+                    name=challenge_split,
+                    gen_kwargs={
+                        "filepath": os.path.join(dl_dir["challenge_set"], self.config.name, filename),
+                        "split": challenge_split,
+                    },
+                )
+                for challenge_split, filename in challenge_sets
+            ]
+
+    def _generate_examples(self, filepath, split, filepaths=None, lang=None):
+        """Yields examples."""
+	if "challenge" in split:
+		exples = json.load(open(filepath, encoding="utf-8"))
+                if isinstance(exples, dict):
+                    assert len(exples) == 1, "multiple entries found"
+                    exples = list(exples.values())[0]
+                for id_, exple in enumerate(exples):
+                    if len(exple) == 0:
+                        continue
+                    exple["gem_parent_id"] = exple["gem_id"]
+                    exple["gem_id"] = f"{self.config.name}-{split}-{id_}"
+                    yield id_, exple
+	else:
+		with open(filepath, "r", encoding="utf-8") as json_file:
+                    json_list = list(json_file)
+                id_ = -1
+                i = -1
+                for json_str in json_list:
+                    result = json.loads(json_str)
+                    if split == "train":
+                        i += 1
+                        for sentence in result["sentence_annotations"]:
+                            id_ += 1
+                            response = {
+                                "gem_id": f"{self.config.name}-{split}-{id_}",
+                                "gem_parent_id": f"{self.config.name}-{split}-{id_}",
+                                "totto_id": i,
+                                "table_page_title": result["table_page_title"],
+                                "table_webpage_url": result["table_webpage_url"],
+                                "table_section_title": result["table_section_title"],
+                                "table_section_text": result["table_section_text"],
+                                "table": result["table"],
+                                "highlighted_cells": result["highlighted_cells"],
+                                "example_id": str(result["example_id"]),
+                                "overlap_subset": "none",
+                                "sentence_annotations": [sentence],
+                                "references": [],
+                                "target": sentence["final_sentence"],
+                            }
+                            yield id_, response
+                    else:
+                        id_ += 1
+                        response = {
+                            "gem_id": f"{self.config.name}-{split}-{id_}",
+                            "gem_parent_id": f"{self.config.name}-{split}-{id_}",
+                            "totto_id": id_,
+                            "table_page_title": result["table_page_title"],
+                            "table_webpage_url": result["table_webpage_url"],
+                            "table_section_title": result["table_section_title"],
+                            "table_section_text": result["table_section_text"],
+                            "table": result["table"],
+                            "highlighted_cells": result["highlighted_cells"],
+                            "example_id": str(result["example_id"]),
+                            "overlap_subset": str(result["overlap_subset"]),
+                        }
+                        response["sentence_annotations"] = [] if split == "test" else result["sentence_annotations"]
+                        response["references"] = [
+                            sentence["final_sentence"] for sentence in response["sentence_annotations"]
+                        ]
+                        response["target"] = response["references"][0] if len(response["references"]) > 0 else ""
+                        yield id_, response
+