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wikisql_VALUE.py

@@ -1,243 +0,0 @@
-"""A large crowd-sourced dataset for developing natural language interfaces for relational databases"""
-
-
-import json
-import os
-import textwrap
-
-import datasets
-
-
-_CITATION = """\
-@article{zhongSeq2SQL2017,
-  author    = {Victor Zhong and
-               Caiming Xiong and
-               Richard Socher},
-  title     = {Seq2SQL: Generating Structured Queries from Natural Language using
-               Reinforcement Learning},
-  journal   = {CoRR},
-  volume    = {abs/1709.00103},
-  year      = {2017}
-}
-"""
-
-_DESCRIPTION = """\
-A large crowd-sourced dataset for developing natural language interfaces for relational databases
-"""
-
-_DATA_URL = "https://huggingface.co/datasets/SALT-NLP/wikisql_VALUE/resolve/main/data.zip"
-
-_AGG_OPS = ["", "MAX", "MIN", "COUNT", "SUM", "AVG"]
-_COND_OPS = ["=", ">", "<", "OP"]
-
-
-class WikiSQLConfig(datasets.BuilderConfig):
-    """BuilderConfig for WikiSQL."""
-
-    def __init__(
-        self,
-        name,
-        description,
-        train_path,
-        dev_path,
-        test_path,
-        **kwargs
-    ):
-        super(WikiSQLConfig, self).__init__(version=datasets.Version("0.1.0", ""), **kwargs)
-        self.features = datasets.Features(
-                {
-                    "phase": datasets.Value("int32"),
-                    "question": datasets.Value("string"),
-                    "table": {
-                        "header": datasets.features.Sequence(datasets.Value("string")),
-                        "page_title": datasets.Value("string"),
-                        "page_id": datasets.Value("string"),
-                        "types": datasets.features.Sequence(datasets.Value("string")),
-                        "id": datasets.Value("string"),
-                        "section_title": datasets.Value("string"),
-                        "caption": datasets.Value("string"),
-                        "rows": datasets.features.Sequence(datasets.features.Sequence(datasets.Value("string"))),
-                        "name": datasets.Value("string"),
-                    },
-                    "sql": {
-                        "human_readable": datasets.Value("string"),
-                        "sel": datasets.Value("int32"),
-                        "agg": datasets.Value("int32"),
-                        "conds": datasets.features.Sequence(
-                            {
-                                "column_index": datasets.Value("int32"),
-                                "operator_index": datasets.Value("int32"),
-                                "condition": datasets.Value("string"),
-                            }
-                        ),
-                    },
-                }
-            )
-        self.name = name
-        self.description = description
-        self.train_path = train_path
-        self.dev_path = dev_path
-        self.test_path = test_path
-
-
-class WikiSQL(datasets.GeneratorBasedBuilder):
-    """WikiSQL: A large crowd-sourced dataset for developing natural language interfaces for relational databases"""
-
-    VERSION = datasets.Version("0.1.0")
-
-    BUILDER_CONFIGS = [
-        WikiSQLConfig(
-            name="AppE",
-            description=textwrap.dedent(
-                """\
-            An Appalachian English variant of the large crowd-sourced dataset for developing natural language interfaces for relational databases"""
-            ),        
-            train_path="train_AppE.jsonl",
-            dev_path="dev_AppE.jsonl",
-            test_path="test_AppE.jsonl"
-        ),
-        WikiSQLConfig(
-            name="ChcE",
-            description=textwrap.dedent(
-                """\
-            A Chicano English variant of the large crowd-sourced dataset for developing natural language interfaces for relational databases"""
-            ),        
-            train_path="train_ChcE.jsonl",
-            dev_path="dev_ChcE.jsonl",
-            test_path="test_ChcE.jsonl"
-        ),
-        WikiSQLConfig(
-            name="CollSgE",
-            description=textwrap.dedent(
-                """\
-            A Singapore English (Singlish) variant of the large crowd-sourced dataset for developing natural language interfaces for relational databases"""
-            ),        
-            train_path="train_CollSgE.jsonl",
-            dev_path="dev_CollSgE.jsonl",
-            test_path="test_CollSgE.jsonl"
-        ),
-        WikiSQLConfig(
-            name="IndE",
-            description=textwrap.dedent(
-                """\
-            An Indian English variant of the large crowd-sourced dataset for developing natural language interfaces for relational databases"""
-            ),        
-            train_path="train_IndE.jsonl",
-            dev_path="dev_IndE.jsonl",
-            test_path="test_IndE.jsonl"
-        ),
-        WikiSQLConfig(
-            name="UAAVE",
-            description=textwrap.dedent(
-                """\
-            An Urban African American English variant of the large crowd-sourced dataset for developing natural language interfaces for relational databases"""
-            ),        
-            train_path="train_UAAVE.jsonl",
-            dev_path="dev_UAAVE.jsonl",
-            test_path="test_UAAVE.jsonl"
-        ),
-        WikiSQLConfig(
-            name="MULTI",
-            description=textwrap.dedent(
-                """\
-            A mixed-dialectal variant of the large crowd-sourced dataset for developing natural language interfaces for relational databases"""
-            ),        
-            train_path="train_MULTI.jsonl",
-            dev_path="dev_MULTI.jsonl",
-            test_path="test_MULTI.jsonl"
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=self.config.description,
-            features=self.config.features,
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="https://github.com/salesforce/WikiSQL",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        dl_dir = dl_manager.download_and_extract(_DATA_URL)
-        dl_dir = os.path.join(dl_dir, "data")
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "main_filepath": os.path.join(dl_dir, self.config.test_path),
-                    "tables_filepath": os.path.join(dl_dir, "test.tables.jsonl"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "main_filepath": os.path.join(dl_dir, self.config.dev_path),
-                    "tables_filepath": os.path.join(dl_dir, "dev.tables.jsonl"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "main_filepath": os.path.join(dl_dir, self.config.train_path),
-                    "tables_filepath": os.path.join(dl_dir, "train.tables.jsonl"),
-                },
-            )
-        ]
-
-    def _convert_to_human_readable(self, sel, agg, columns, conditions):
-        """Make SQL query string. Based on https://github.com/salesforce/WikiSQL/blob/c2ed4f9b22db1cc2721805d53e6e76e07e2ccbdc/lib/query.py#L10"""
-
-        rep = f"SELECT {_AGG_OPS[agg]} {columns[sel] if columns is not None else f'col{sel}'} FROM table"
-
-        if conditions:
-            rep += " WHERE " + " AND ".join([f"{columns[i]} {_COND_OPS[o]} {v}" for i, o, v in conditions])
-        return " ".join(rep.split())
-
-    def _generate_examples(self, main_filepath, tables_filepath):
-        """Yields examples."""
-
-        # Build dictionary to table_ids:tables
-        with open(tables_filepath, encoding="utf-8") as f:
-            tables = [json.loads(line) for line in f]
-            id_to_tables = {x["id"]: x for x in tables}
-
-        with open(main_filepath, encoding="utf-8") as f:
-            for idx, line in enumerate(f):
-                row = json.loads(line)
-                row["table"] = id_to_tables[row["table_id"]]
-                del row["table_id"]
-
-                # Handle missing data
-                row["table"]["page_title"] = row["table"].get("page_title", "")
-                row["table"]["section_title"] = row["table"].get("section_title", "")
-                row["table"]["caption"] = row["table"].get("caption", "")
-                row["table"]["name"] = row["table"].get("name", "")
-                row["table"]["page_id"] = str(row["table"].get("page_id", ""))
-
-                # Fix row types
-                row["table"]["rows"] = [[str(e) for e in r] for r in row["table"]["rows"]]
-
-                # Get human-readable version
-                row["sql"]["human_readable"] = self._convert_to_human_readable(
-                    row["sql"]["sel"],
-                    row["sql"]["agg"],
-                    row["table"]["header"],
-                    row["sql"]["conds"],
-                )
-
-                # Restructure sql->conds
-                # - wikiSQL provides a tuple [column_index, operator_index, condition]
-                #   as 'condition' can have 2 types (float or str) we convert to dict
-                for i in range(len(row["sql"]["conds"])):
-                    row["sql"]["conds"][i] = {
-                        "column_index": row["sql"]["conds"][i][0],
-                        "operator_index": row["sql"]["conds"][i][1],
-                        "condition": str(row["sql"]["conds"][i][2]),
-                    }
-                yield idx, row