Delete loading script

compguesswhat.py

@@ -1,254 +0,0 @@
-import gzip
-import json
-import os
-
-import datasets
-
-
-class CompguesswhatConfig(datasets.BuilderConfig):
-    """BuilderConfig for CompGuessWhat?!"""
-
-    def __init__(self, data_url, splits, gameplay_scenario, **kwargs):
-        """
-
-        Args:
-            gameplay_scenario: to specify if we want to load original CompGuessWhat?! split ('original') or
-            the zero-shot reference games based on NOCAPS images ('zero_shot')
-            **kwargs: keyword arguments forwarded to super.
-        """
-        super(CompguesswhatConfig, self).__init__(
-            version=datasets.Version("0.2.0", "Second CompGuessWhat?! release"), **kwargs
-        )
-        assert gameplay_scenario in (
-            "original",
-            "zero_shot",
-        ), "Invalid choice for parameter 'gameplay_scenario': {gameplay_scenario}. Valid values are ('original', 'zero_shot')."
-
-        self.gameplay_scenario = gameplay_scenario
-        self.splits = splits
-        self.data_url = data_url
-
-
-class Compguesswhat(datasets.GeneratorBasedBuilder):
-    _CITATION = """\
-        @inproceedings{suglia2020compguesswhat,
-          title={CompGuessWhat?!: a Multi-task Evaluation Framework for Grounded Language Learning},
-          author={Suglia, Alessandro, Konstas, Ioannis, Vanzo, Andrea, Bastianelli, Emanuele, Desmond Elliott, Stella Frank and Oliver Lemon},
-          booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
-          year={2020}
-        }
-    """
-
-    _DESCRIPTION = """
-        CompGuessWhat?! is an instance of a multi-task framework for evaluating the quality of learned neural representations,
-        in particular concerning attribute grounding. Use this dataset if you want to use the set of games whose reference
-        scene is an image in VisualGenome. Visit the website for more details: https://compguesswhat.github.io
-    """
-
-    BUILDER_CONFIGS = [
-        CompguesswhatConfig(
-            name="compguesswhat-original",
-            gameplay_scenario="original",
-            description="CompGuessWhat?! subset of games from the original GuessWhat?! dataset",
-            data_url="https://www.dropbox.com/s/qd9wlydpkpmq8rr/compguesswhat-original.zip?dl=1",
-            splits={
-                "train": "compguesswhat.train.jsonl.gz",
-                "valid": "compguesswhat.valid.jsonl.gz",
-                "test": "compguesswhat.test.jsonl.gz",
-            },
-        ),
-        CompguesswhatConfig(
-            name="compguesswhat-zero_shot",
-            gameplay_scenario="zero_shot",
-            description="CompGuessWhat?! reference set of games for zero-shot evaluation using NOCAPS images",
-            data_url="https://www.dropbox.com/s/f5o2t7aiok7kpcm/compguesswhat-zero_shot.zip?dl=1",
-            splits={
-                "nd_valid": "compguesswhat.nd_valid.jsonl.gz",
-                "nd_test": "compguesswhat.nd_test.jsonl.gz",
-                "od_valid": "compguesswhat.od_valid.jsonl.gz",
-                "od_test": "compguesswhat.od_test.jsonl.gz",
-            },
-        ),
-    ]
-
-    VERSION = datasets.Version("0.2.0")
-
-    def _info(self):
-        if self.config.gameplay_scenario == "original":
-            return datasets.DatasetInfo(
-                # This is the description that will appear on the datasets page.
-                description=self._DESCRIPTION,
-                # datasets.features.FeatureConnectors
-                features=datasets.Features(
-                    {
-                        "id": datasets.Value("int32"),
-                        "target_id": datasets.Value("int32"),
-                        "timestamp": datasets.Value("string"),
-                        "status": datasets.Value("string"),
-                        "image": {
-                            # this is the image ID in GuessWhat?! which corresponds to the MSCOCO id
-                            "id": datasets.Value("int32"),
-                            "file_name": datasets.Value("string"),
-                            "flickr_url": datasets.Value("string"),
-                            "coco_url": datasets.Value("string"),
-                            "height": datasets.Value("int32"),
-                            "width": datasets.Value("int32"),
-                            # this field represents the corresponding image metadata that can be found in VisualGenome
-                            # in the file image_data.json
-                            # We copy it over so that we avoid any confusion or possible wrong URL
-                            # Please use the original image files to resolve photos
-                            "visual_genome": {
-                                "width": datasets.Value("int32"),
-                                "height": datasets.Value("int32"),
-                                "url": datasets.Value("string"),
-                                "coco_id": datasets.Value("int32"),
-                                # this is the actual VisualGenome image ID
-                                # because we can't rely store it as an integer we same it as string
-                                "flickr_id": datasets.Value("string"),
-                                "image_id": datasets.Value("string"),
-                            },
-                        },
-                        "qas": datasets.features.Sequence(
-                            {
-                                "question": datasets.Value("string"),
-                                "answer": datasets.Value("string"),
-                                "id": datasets.Value("int32"),
-                            }
-                        ),
-                        "objects": datasets.features.Sequence(
-                            {
-                                "id": datasets.Value("int32"),
-                                "bbox": datasets.Sequence(datasets.Value("float32"), length=4),
-                                "category": datasets.Value("string"),
-                                "area": datasets.Value("float32"),
-                                "category_id": datasets.Value("int32"),
-                                "segment": datasets.features.Sequence(
-                                    datasets.features.Sequence(datasets.Value("float32"))
-                                ),
-                            }
-                        ),
-                    }
-                ),
-                # If there's a common (input, target) tuple from the features,
-                # specify them here. They'll be used if as_supervised=True in
-                # builder.as_dataset.
-                supervised_keys=None,
-                # Homepage of the dataset for documentation
-                homepage="https://compguesswhat.github.io/",
-                citation=self._CITATION,
-            )
-        elif self.config.gameplay_scenario == "zero_shot":
-            return datasets.DatasetInfo(
-                # This is the description that will appear on the datasets page.
-                description=self._DESCRIPTION,
-                # datasets.features.FeatureConnectors
-                features=datasets.Features(
-                    {
-                        "id": datasets.Value("int32"),
-                        "target_id": datasets.Value("string"),
-                        "status": datasets.Value("string"),
-                        "image": {
-                            "id": datasets.Value("int32"),
-                            "file_name": datasets.Value("string"),
-                            "coco_url": datasets.Value("string"),
-                            "height": datasets.Value("int32"),
-                            "width": datasets.Value("int32"),
-                            "license": datasets.Value("int32"),
-                            "open_images_id": datasets.Value("string"),
-                            "date_captured": datasets.Value("string"),
-                        },
-                        "objects": datasets.features.Sequence(
-                            {
-                                "id": datasets.Value("string"),
-                                "bbox": datasets.Sequence(datasets.Value("float32"), length=4),
-                                "category": datasets.Value("string"),
-                                "area": datasets.Value("float32"),
-                                "category_id": datasets.Value("int32"),
-                                "IsOccluded": datasets.Value("int32"),
-                                "IsTruncated": datasets.Value("int32"),
-                                "segment": datasets.features.Sequence(
-                                    {
-                                        "MaskPath": datasets.Value("string"),
-                                        "LabelName": datasets.Value("string"),
-                                        "BoxID": datasets.Value("string"),
-                                        "BoxXMin": datasets.Value("string"),
-                                        "BoxXMax": datasets.Value("string"),
-                                        "BoxYMin": datasets.Value("string"),
-                                        "BoxYMax": datasets.Value("string"),
-                                        "PredictedIoU": datasets.Value("string"),
-                                        "Clicks": datasets.Value("string"),
-                                    }
-                                ),
-                            }
-                        ),
-                    }
-                ),
-                # If there's a common (input, target) tuple from the features,
-                # specify them here. They'll be used if as_supervised=True in
-                # builder.as_dataset.
-                supervised_keys=None,
-                # Homepage of the dataset for documentation
-                homepage="https://compguesswhat.github.io/",
-                citation=self._CITATION,
-            )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        dl_dir = dl_manager.download_and_extract(self.config.data_url)
-
-        splits_gen = []
-
-        for split_id, split_filename in self.config.splits.items():
-            if self.config.gameplay_scenario == "original":
-                if "train" in split_id:
-                    split_name = datasets.Split.TRAIN
-                elif "valid" in split_id:
-                    split_name = datasets.Split.VALIDATION
-                elif "test" in split_id:
-                    split_name = datasets.Split.TEST
-            else:
-                split_name = datasets.Split(split_id)
-
-            full_split_name = "-".join(["compguesswhat", self.config.gameplay_scenario])
-            splits_gen.append(
-                datasets.SplitGenerator(
-                    name=split_name,
-                    gen_kwargs={
-                        "filepath": os.path.join(
-                            dl_dir,
-                            full_split_name,
-                            self.VERSION.version_str,
-                            split_filename,
-                        )
-                    },
-                )
-            )
-
-        return splits_gen
-
-    def _generate_examples(self, filepath):
-        def _extract_game_tuple(data):
-            data = data.decode("utf-8")
-            game = json.loads(data.strip("\n"))
-
-            # we refactor the data structure a bit to fit with the new version
-            game["target_id"] = game["object_id"]
-            if "object_id" in game:
-                del game["object_id"]
-
-            if "questioner_id" in game:
-                del game["questioner_id"]
-            ###
-
-            if "visual_genome" in game["image"]:
-                # We need to cast it to string so that we avoid issues with int size
-                game["image"]["visual_genome"]["image_id"] = str(game["image"]["visual_genome"]["image_id"])
-                game["image"]["visual_genome"]["flickr_id"] = str(game["image"]["visual_genome"]["flickr_id"])
-
-            return game["id"], game
-
-        """Yields examples."""
-        with open(filepath, "rb") as gzip_file:
-            with gzip.open(gzip_file) as in_file:
-                for data in in_file:
-                    yield _extract_game_tuple(data)