Create nli_zh.py

nli_zh.py

@@ -0,0 +1,65 @@
+"""Natural Language Inference (NLI) Chinese Corpus.(nli_zh)"""
+
+
+import csv
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+常见中文语义匹配数据集，包含ATEC、BQ、LCQMC、PAWSX、STS-B共5个任务。
+"""
+
+
+class Nli_zh(datasets.GeneratorBasedBuilder):
+    """The Natural Language Inference Chinese(NLI_zh) Corpus."""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="ATEC",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of NLI_zh",
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "sentence1": datasets.Value("string"),
+                    "sentence2": datasets.Value("string"),
+                    "label": datasets.Value("int32"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/shibing624/text2vec",
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(_DATA_URL)
+        data_dir = os.path.join(dl_dir, "nli_zh")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(data_dir, "snli_1.0_test.txt")}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(data_dir, "snli_1.0_dev.txt")}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(data_dir, "snli_1.0_train.txt")}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+            for idx, row in enumerate(reader):
+                label = -1 if row["gold_label"] == "-" else row["gold_label"]
+                yield idx, {
+                    "premise": row["sentence1"],
+                    "hypothesis": row["sentence2"],
+                    "label": label,
+                }