add download script

abricot.py

@@ -0,0 +1,115 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# TODO: Address all TODOs and remove all explanatory comments
+
+
+import csv
+import json
+import os
+
+import datasets
+
+
+_CITATION = """"""
+
+_DESCRIPTION = """This new dataset is designed to measure Language Models abstractness and inclusiveness understanding in Italian."""
+
+_HOMEPAGE = ""
+
+_LICENSE = "CC BY 4.0"
+
+
+_URLS = {
+    "abs": "https://github.com/aramelior/ABRICOT-ABstRactness-and-Inclusiveness-in-COntexT"
+}
+
+
+class abricot(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("0.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="abs", version=VERSION, description="Abstraction assessment"),
+        # datasets.BuilderConfig(name="ita", version=VERSION, description="Italian Understanding"),
+    ]
+
+    DEFAULT_CONFIG_NAME = "abs"
+
+    def _info(self):
+        if self.config.name == "abs":
+            features = datasets.Features(
+                # TODO: add after the image col is there "immagine": datasets.Value("string"),
+                {
+                    "ID": datasets.Value("string"),
+                    "domain": datasets.Value("string"),
+                    "begin": datasets.Value("int64"),
+                    "end": datasets.Value("int64"),
+                    "text": datasets.Value("string"),
+                    "target_token": datasets.Value("string"),
+                    "target_lemma": datasets.Value("string"),
+                    "inc_mean": datasets.Value("float"),
+                    "inc_std": datasets.Value("float"),
+                    "abs_mean": datasets.Value("float"),
+                    "abs_std": datasets.Value("float"),
+                    "target_number": datasets.Value("string"),
+                }
+            )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+
+        urls = _URLS[self.config.name]
+        data_dir = dl_manager.extract(urls)
+        if self.config.name == "abs":
+            data_file = "dataset_it.csv"
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, data_file),
+                    "split": "val",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        ds = datasets.load_dataset("csv", data_files=filepath)["train"]
+        for key, row in enumerate(ds):
+            # data = json.loads(row)
+            if self.config.name == "abs":
+                # Yields examples as (key, example) tuples
+                out = {
+                    "ID": row["ID"],
+                    "domain": row["domain"],
+                    "begin": row["begin"],
+                    "end": row["end"],
+                    "text": row["text"],
+                    "target_token": row["target_token"],
+                    "target_lemma": row["target_lemma"],
+                    "inc_mean": row["inc_mean"],
+                    "inc_std": row["inc_std"],
+                    "abs_mean": row["abs_mean"],
+                    "abs_std": row["abs_std"],
+                    "target_number": row["target_number"],
+                }
+
+                yield key, out