Upload pclue.py

pclue.py

@@ -0,0 +1,95 @@
+# 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.
+"""Pclue dataset."""
+
+
+import json
+
+import py7zr
+
+import datasets
+
+
+_CITATION = """https://github.com/CLUEbenchmark/pCLUE"""
+
+_DESCRIPTION = """https://github.com/CLUEbenchmark/pCLUE"""
+
+_HOMEPAGE = "https://github.com/CLUEbenchmark/pCLUE"
+
+_LICENSE = "apache-2.0"
+
+
+_URL = "https://huggingface.co/datasets/wbbbbb/pclue/resolve/main/pclue.7z"
+
+
+class Pclue(datasets.GeneratorBasedBuilder):
+    """Pclue Corpus dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="pclue"),
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "input": datasets.Value("string"),
+                "target": datasets.Value("string"),
+                "type": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        path = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": path+"train.json",
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": path+"test.json",
+                    "split": "test",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": path+"dev.json",
+                    "split": "val",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """Yields examples."""
+         with open(filepath, encoding="utf-8") as f:
+            for idx, row in enumerate(f):
+                 yield idx, json.load(row)
+