Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

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+{"default": {"description": "A large crowd-sourced dataset for developing natural language interfaces for relational databases\n", "citation": "@article{zhongSeq2SQL2017,\n  author    = {Victor Zhong and\n               Caiming Xiong and\n               Richard Socher},\n  title     = {Seq2SQL: Generating Structured Queries from Natural Language using\n               Reinforcement Learning},\n  journal   = {CoRR},\n  volume    = {abs/1709.00103},\n  year      = {2017}\n}\n", "homepage": "https://github.com/salesforce/WikiSQL", "license": "", "features": {"phase": {"dtype": "int32", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "table": {"header": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "page_title": {"dtype": "string", "id": null, "_type": "Value"}, "page_id": {"dtype": "string", "id": null, "_type": "Value"}, "types": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "id": {"dtype": "string", "id": null, "_type": "Value"}, "section_title": {"dtype": "string", "id": null, "_type": "Value"}, "caption": {"dtype": "string", "id": null, "_type": "Value"}, "rows": {"feature": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "name": {"dtype": "string", "id": null, "_type": "Value"}}, "sql": {"human_readable": {"dtype": "string", "id": null, "_type": "Value"}, "sel": {"dtype": "int32", "id": null, "_type": "Value"}, "agg": {"dtype": "int32", "id": null, "_type": "Value"}, "conds": {"feature": {"column_index": {"dtype": "int32", "id": null, "_type": "Value"}, "operator_index": {"dtype": "int32", "id": null, "_type": "Value"}, "condition": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}}, "supervised_keys": null, "builder_name": "wiki_sql", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 32234761, "num_examples": 15878, "dataset_name": "wiki_sql"}, "validation": {"name": "validation", "num_bytes": 15159314, "num_examples": 8421, "dataset_name": "wiki_sql"}, "train": {"name": "train", "num_bytes": 107345917, "num_examples": 56355, "dataset_name": "wiki_sql"}}, "download_checksums": {"https://github.com/salesforce/WikiSQL/raw/master/data.tar.bz2": {"num_bytes": 26164664, "checksum": "755c728ab188e364575705c8641f3fafd86fb089cb8b08e8c03f01832aae0881"}}, "download_size": 26164664, "dataset_size": 154739992, "size_in_bytes": 180904656}}

dummy/0.1.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d01b228943cc6f1a5e76b73ee8d493c69692377f946fbf30fb984610a1610644
+size 2426

wikisql.py

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+"""A large crowd-sourced dataset for developing natural language interfaces for relational databases"""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+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://github.com/salesforce/WikiSQL/raw/master/data.tar.bz2"
+
+_AGG_OPS = ["", "MAX", "MIN", "COUNT", "SUM", "AVG"]
+_COND_OPS = ["=", ">", "<", "OP"]
+
+
+class WikiSQL(datasets.GeneratorBasedBuilder):
+    """WikiSQL: A large crowd-sourced dataset for developing natural language interfaces for relational databases"""
+
+    VERSION = datasets.Version("0.1.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            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"),
+                            }
+                        ),
+                    },
+                }
+            ),
+            # 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, "test.jsonl"),
+                    "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, "dev.jsonl"),
+                    "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, "train.jsonl"),
+                    "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 = "SELECT {agg} {sel} FROM table".format(
+            agg=_AGG_OPS[agg], sel=columns[sel] if columns is not None else "col{}".format(sel)
+        )
+
+        if conditions:
+            rep += " WHERE " + " AND ".join(["{} {} {}".format(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