Upload spider_VALUE.py

spider_VALUE.py

@@ -0,0 +1,175 @@
+# 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.
+"""Spider: A Large-Scale Human-Labeled Dataset for Text-to-SQL Tasks"""
+
+
+import json
+import os
+import textwrap
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """\
+@article{yu2018spider,
+  title={Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task},
+  author={Yu, Tao and Zhang, Rui and Yang, Kai and Yasunaga, Michihiro and Wang, Dongxu and Li, Zifan and Ma, James and Li, Irene and Yao, Qingning and Roman, Shanelle and others},
+  journal={arXiv preprint arXiv:1809.08887},
+  year={2018}
+}
+"""
+
+_DESCRIPTION = """\
+Spider is a large-scale complex and cross-domain semantic parsing and text-toSQL dataset annotated by 11 college students
+"""
+
+_HOMEPAGE = "https://yale-lily.github.io/spider"
+
+_LICENSE = "CC BY-SA 4.0"
+
+_URL = "https://huggingface.co/datasets/spider/resolve/main/data/spider.zip"
+
+class SpiderConfig(datasets.BuilderConfig):
+    """BuilderConfig for Spider."""
+
+    def __init__(
+        self,
+        name,
+        description,
+        train_path,
+        dev_path,
+        **kwargs
+    ):
+        super(SpiderConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        self.features = 
+        self.name = name
+        self.description = description
+        self.train_path = train_path
+        self.dev_path = dev_path
+
+
+class Spider(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        SpiderConfig(
+            name="AppE",
+            description=textwrap.dedent(
+                """\
+            An Appalachian English variant of a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students"""
+            ),        
+            train_path="train_spider_AppE.json",
+            dev_path="dev_AppE.json",
+        ),
+        SpiderConfig(
+            name="ChcE",
+            description=textwrap.dedent(
+                """\
+            A Chicano English variant of a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students"""
+            ),        
+            train_path="train_spider_ChcE.json",
+            dev_path="dev_ChcE.json",
+        ),
+        SpiderConfig(
+            name="CollSgE",
+            description=textwrap.dedent(
+                """\
+            A Singapore English (Singlish) variant of a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students"""
+            ),        
+            train_path="train_spider_CollSgE.json",
+            dev_path="dev_CollSgE.json",
+        ),
+        SpiderConfig(
+            name="IndE",
+            description=textwrap.dedent(
+                """\
+            An Indian English variant of a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students"""
+            ),        
+            train_path="train_spider_IndE.json",
+            dev_path="dev_IndE.json",
+        ),
+        SpiderConfig(
+            name="UAAVE",
+            description=textwrap.dedent(
+                """\
+            An Urban African American English variant of a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students"""
+            ),        
+            train_path="train_spider_UAAVE.json",
+            dev_path="dev_UAAVE.json",
+        ),
+        SpiderConfig(
+            name="MULTI",
+            description=textwrap.dedent(
+                """\
+            A mixed-dialectal variant of a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 college students"""
+            ),        
+            train_path="train_spider_MULTI.json",
+            dev_path="dev_MULTI.json",
+        ),
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "db_id": datasets.Value("string"),
+                "query": datasets.Value("string"),
+                "question": datasets.Value("string"),
+                "query_toks": datasets.features.Sequence(datasets.Value("string")),
+                "query_toks_no_value": datasets.features.Sequence(datasets.Value("string")),
+                "question_toks": datasets.features.Sequence(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):
+        downloaded_filepath = dl_manager.download_and_extract(_URL)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_filepath": os.path.join(downloaded_filepath, self.config.train_path),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "data_filepath": os.path.join(downloaded_filepath, self.config.dev_path),
+                },
+            )
+        ]
+
+    def _generate_examples(self, data_filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", data_filepath)
+        with open(data_filepath, encoding="utf-8") as f:
+            spider = json.load(f)
+            for idx, sample in enumerate(spider):
+                yield idx, {
+                    "db_id": sample["db_id"],
+                    "query": sample["query"],
+                    "question": sample["question"],
+                    "query_toks": sample["query_toks"],
+                    "query_toks_no_value": sample["query_toks_no_value"],
+                    "question_toks": sample["question_toks"],
+                }