update script

aspectemo.py

@@ -1,104 +1,118 @@
-import csv
-from typing import List, Generator, Tuple, Dict
+# coding=utf-8
+# 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.
+import json
+import os
+from typing import Generator, Tuple, Dict, List
 
 import datasets
 from datasets import DownloadManager
 from datasets.info import SupervisedKeysData
 
-_DESCRIPTION = """AspectEmo 1.0 dataset: Multi-Domain Corpus of Consumer Reviews for Aspect-Based 
+_CITATION = """@misc{11321/849,	
+ title = {{AspectEmo} 1.0: Multi-Domain Corpus of Consumer Reviews for Aspect-Based Sentiment Analysis},	
+ author = {Koco{\'n}, Jan and Radom, Jarema and Kaczmarz-Wawryk, Ewa and Wabnic, Kamil and Zaj{\c a}czkowska, Ada and Za{\'s}ko-Zieli{\'n}ska, Monika},	
+ url = {http://hdl.handle.net/11321/849},	
+ note = {{CLARIN}-{PL} digital repository},	
+ copyright = {The {MIT} License},	
+ year = {2021}	
+}"""
+
+_DESCRIPTION = """AspectEmo dataset: Multi-Domain Corpus of Consumer Reviews for Aspect-Based 
                 Sentiment Analysis"""
 
-_CLASSES = ['O',
-            'B-a_plus_m',
-            'B-a_minus_m',
-            'B-a_zero',
-            'B-a_minus_s',
-            'B-a_plus_s',
-            'B-a_amb',
-            'B-a_minus_m:B-a_minus_m',
-            'B-a_minus_m:B-a_minus_m:B-a_minus_m',
-            'B-a_plus_m:B-a_plus_m',
-            'B-a_plus_m:B-a_plus_m:B-a_plus_m',
-            'B-a_zero:B-a_zero:B-a_zero',
-            'B-a_zero:B-a_zero',
-            'I-a_plus_m',
-            'B-a_zero:B-a_plus_m',
-            'B-a_minus_m:B-a_zero',
-            'B-a_minus_s:B-a_minus_s:B-a_minus_s',
-            'B-a_amb:B-a_amb',
-            'I-a_minus_m',
-            'B-a_minus_s:B-a_minus_s',
-            'B-a_plus_s:B-a_plus_s:B-a_plus_s',
-            'B-a_plus_m:B-a_plus_m:B-a_plus_m:B-a_plus_m:B-a_plus_m:B-a_plus_m',
-            'B-a_plus_m:B-a_amb',
-            'B-a_minus_m:B-a_plus_m',
-            'B-a_amb:B-a_amb:B-a_amb',
-            'I-a_zero',
-            'B-a_plus_s:B-a_plus_s',
-            'B-a_plus_m:B-a_plus_s',
-            'B-a_plus_m:B-a_zero',
-            'B-a_zero:B-a_zero:B-a_zero:B-a_zero:B-a_zero:B-a_zero',
-            'B-a_zero:B-a_minus_m',
-            'B-a_amb:B-a_plus_s',
-            'B-a_zero:B-a_minus_s']
+_HOMEPAGE = "https://clarin-pl.eu/dspace/handle/11321/849"
+
+_LICENSE = "The MIT License"
 
-_URLS = {
-    "train": "https://huggingface.co/datasets/clarin-pl/aspectemo/resolve/main/data/train.tsv",
-    "validation": "https://huggingface.co/datasets/clarin-pl/aspectemo/resolve/main/data/val.tsv",
-    "test": "https://huggingface.co/datasets/clarin-pl/aspectemo/resolve/main/data/test.tsv",
+_URLs = {
+    "1.0": "https://huggingface.co/datasets/clarin-pl/aspectemo/resolve/main/data/aspectemo1.zip",
+    # '2.0': "",
 }
 
+_CLASSES = ["a_plus_s", "a_zero", "a_amb", "a_minus_m", "O", "a_minus_s", "a_plus_m"]
+
 
 class AspectEmo(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="1.0",
+            version=VERSION,
+            description="AspectEmo 1.0 Corpus, used in the original paper.",
+        ),
+        # datasets.BuilderConfig(
+        #     name="2.0",
+        #     version=VERSION,
+        #     description="",
+        # ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "1.0"
+
     def _info(self) -> datasets.DatasetInfo:
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=datasets.Features(
                 {
-                    "orth": datasets.Sequence(datasets.Value("string")),
-                    "ctag": datasets.Sequence(datasets.Value("string")),
-                    "sentiment": datasets.Sequence(datasets.features.ClassLabel(
-                        names=_CLASSES,
-                        num_classes=len(_CLASSES)
-                    )),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "labels": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=_CLASSES, num_classes=len(_CLASSES)
+                        )
+                    ),
                 }
             ),
-            supervised_keys=SupervisedKeysData(input="orth", output="sentiment"),
-            homepage="https://clarin-pl.eu/dspace/handle/11321/849",
+            supervised_keys=SupervisedKeysData(input="tokens", output="labels"),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
         )
 
-    def _split_generators(self, dl_manager: DownloadManager) -> List[datasets.SplitGenerator]:
-        urls_to_download = _URLS
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+    def _split_generators(
+        self, dl_manager: DownloadManager
+    ) -> List[datasets.SplitGenerator]:
+        my_urls = _URLs[self.config.name]
+        data_dir = dl_manager.download_and_extract(my_urls)
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": downloaded_files["train"]},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"filepath": downloaded_files["validation"]},
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "data.json"),
+                    "split": "train",
+                },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
-                gen_kwargs={"filepath": downloaded_files["test"]},
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "data.json"),
+                    "split": "test",
+                },
             ),
         ]
 
     def _generate_examples(
-            self, filepath: str
+        self,
+        filepath: str,
+        split: str,
     ) -> Generator[Tuple[int, Dict[str, str]], None, None]:
-        with open(filepath, "r", encoding="utf-8") as f:
-            reader = csv.reader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
-            next(reader, None)  # skip header
-            id_, orth, ctag, sentiment = set(), [], [], []
-            for line in reader:
-                if not line:
-                    assert len(id_) == 1
-                    yield id_.pop(), {"orth": orth, "ctag": ctag, "sentiment": sentiment, }
-                    id_, orth, ctag, sentiment = set(), [], [], []
-                else:
-                    id_.add(line[0])
-                    orth.append(line[1])
-                    ctag.append(line[2])
-                    sentiment.append(line[3])
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)[split]
+            for id_, row in data.items():
+                yield id_, {
+                    "tokens": row["tokens"],
+                    "labels": row["labels"],
+                }