Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- crowdsourced
+languages:
+- en
+licenses:
+- cc-by-nc-4-0
+multilinguality:
+- monolingual
+size_categories:
+  evaluation_dataset:
+  - n<1K
+  search_corpus:
+  - n>1M
+source_datasets:
+- original
+task_categories:
+- question-answering
+task_ids:
+  evaluation_dataset:
+  - extractive-qa
+  search_corpus:
+  - extractive-qa
+---
+
+# Dataset Card for Neural Code Search
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:**
+[facebookresearch
+/
+Neural-Code-Search-Evaluation-Dataset](https://github.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset/tree/master/data)
+- **Repository:**
+[Github](https://github.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset.git)
+- **Paper:**
+[arXiv](https://arxiv.org/pdf/1908.09804.pdf)
+
+### Dataset Summary
+
+Neural-Code-Search-Evaluation-Dataset presents an evaluation dataset consisting of natural language query and code snippet pairs, with the hope that future work in this area can use this dataset as a common benchmark. We also provide the results of two code search models (NCS, UNIF) from recent work.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+EN - English
+
+## Dataset Structure
+
+### Data Instances
+
+#### Search Corpus
+The search corpus is indexed using all method bodies parsed from the 24,549 GitHub repositories. In total, there are 4,716,814 methods in this corpus. The code search model will find relevant code snippets (i.e. method bodies) from this corpus given a natural language query. In this data release, we will provide the following information for each method in the corpus:
+
+#### Evaluation Dataset
+The evaluation dataset is composed of 287 Stack Overflow question and answer pairs
+
+### Data Fields
+
+#### Search Corpus
+- id: Each method in the corpus has a unique numeric identifier. This ID number will also be referenced in our evaluation dataset.
+- filepath: The file path is in the format of :owner/:repo/relative-file-path-to-the-repo
+method_name
+- start_line: Starting line number of the method in the file.
+- end_line: Ending line number of the method in the file.
+- url: GitHub link to the method body with commit ID and line numbers encoded.
+
+#### Evaluation Dataset
+- stackoverflow_id: Stack Overflow post ID.
+- question: Title fo the Stack Overflow post.
+- question_url: URL of the Stack Overflow post.
+- answer: Code snippet answer to the question.
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The most popular Android repositories on GitHub (ranked by the number of stars) is used to create the search corpus. For each repository that we indexed, we provide the link, specific to the commit that was used.5 In total, there are 24,549 repositories.
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+Hongyu Li, Seohyun Kim and Satish Chandra
+
+### Licensing Information
+
+CC-BY-NC 4.0 (Attr Non-Commercial Inter.)
+
+### Citation Information
+
+arXiv:1908.09804 [cs.SE]

dataset_infos.json

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+{"evaluation_dataset": {"description": "Neural-Code-Search-Evaluation-Dataset presents an evaluation dataset consisting of natural language query and code snippet pairs and a search corpus consisting of code snippets collected from the most popular Android repositories on GitHub.\n", "citation": "@InProceedings{huggingface:dataset,\ntitle         = {Neural Code Search Evaluation Dataset},\nauthors       = {Hongyu Li, Seohyun Kim and Satish Chandra},\njournal       = {arXiv e-prints},\nyear          = 2018,\neid           = {arXiv:1908.09804 [cs.SE]},\npages         = {arXiv:1908.09804 [cs.SE]},\narchivePrefix = {arXiv},\neprint        = {1908.09804},\n}\n", "homepage": "https://github.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset/tree/master/data", "license": "CC-BY-NC 4.0 (Attr Non-Commercial Inter.)", "features": {"stackoverflow_id": {"dtype": "int32", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "question_url": {"dtype": "string", "id": null, "_type": "Value"}, "question_author": {"dtype": "string", "id": null, "_type": "Value"}, "question_author_url": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "answer_url": {"dtype": "string", "id": null, "_type": "Value"}, "answer_author": {"dtype": "string", "id": null, "_type": "Value"}, "answer_author_url": {"dtype": "string", "id": null, "_type": "Value"}, "examples": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "examples_url": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "neural_code_search", "config_name": "evaluation_dataset", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 296848, "num_examples": 287, "dataset_name": "neural_code_search"}}, "download_checksums": {"https://raw.githubusercontent.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset/master/data/287_android_questions.json": {"num_bytes": 383625, "checksum": "23117c7ee244ad7eddd863d1a92ea2d21d2c5f4e3d577d0d809bb3d88f797561"}}, "download_size": 383625, "post_processing_size": null, "dataset_size": 296848, "size_in_bytes": 680473}, "search_corpus": {"description": "Neural-Code-Search-Evaluation-Dataset presents an evaluation dataset consisting of natural language query and code snippet pairs and a search corpus consisting of code snippets collected from the most popular Android repositories on GitHub.\n", "citation": "@InProceedings{huggingface:dataset,\ntitle         = {Neural Code Search Evaluation Dataset},\nauthors       = {Hongyu Li, Seohyun Kim and Satish Chandra},\njournal       = {arXiv e-prints},\nyear          = 2018,\neid           = {arXiv:1908.09804 [cs.SE]},\npages         = {arXiv:1908.09804 [cs.SE]},\narchivePrefix = {arXiv},\neprint        = {1908.09804},\n}\n", "homepage": "https://github.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset/tree/master/data", "license": "CC-BY-NC 4.0 (Attr Non-Commercial Inter.)", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "filepath": {"dtype": "string", "id": null, "_type": "Value"}, "method_name": {"dtype": "string", "id": null, "_type": "Value"}, "start_line": {"dtype": "int32", "id": null, "_type": "Value"}, "end_line": {"dtype": "int32", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "neural_code_search", "config_name": "search_corpus", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1452630278, "num_examples": 4716814, "dataset_name": "neural_code_search"}}, "download_checksums": {"https://raw.githubusercontent.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset/master/data/search_corpus_1.tar.gz": {"num_bytes": 50756713, "checksum": "ba6c96b949bd283d1935e58c99d9159896601c2eeff24c5787e61dd1da1ecd4f"}, "https://raw.githubusercontent.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset/master/data/search_corpus_2.tar.gz": {"num_bytes": 70355830, "checksum": "a3cb354476a60ee45c29fe6629f5462d52965b082381340002882dd2192eddeb"}}, "download_size": 121112543, "post_processing_size": null, "dataset_size": 1452630278, "size_in_bytes": 1573742821}}

dummy/evaluation_dataset/1.1.0/dummy_data.zip

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dummy/search_corpus/1.1.0/dummy_data.zip

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neural_code_search.py

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+# 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.
+"""Neural-Code-Search-Evaluation-Dataset presents an evaluation dataset consisting of natural language query and code snippet pairs"""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title         = {Neural Code Search Evaluation Dataset},
+authors       = {Hongyu Li, Seohyun Kim and Satish Chandra},
+journal       = {arXiv e-prints},
+year          = 2018,
+eid           = {arXiv:1908.09804 [cs.SE]},
+pages         = {arXiv:1908.09804 [cs.SE]},
+archivePrefix = {arXiv},
+eprint        = {1908.09804},
+}
+"""
+
+_DESCRIPTION = """\
+Neural-Code-Search-Evaluation-Dataset presents an evaluation dataset \
+consisting of natural language query and code snippet pairs and a search corpus \
+consisting of code snippets collected from the most popular Android repositories \
+on GitHub.
+"""
+
+_HOMEPAGE = "https://github.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset/tree/master/data"
+
+_LICENSE = "CC-BY-NC 4.0 (Attr Non-Commercial Inter.)"
+
+_BASE_URL = "https://raw.githubusercontent.com/facebookresearch/Neural-Code-Search-Evaluation-Dataset/master/data/"
+_URLs = {
+    "evaluation_dataset": _BASE_URL + "287_android_questions.json",
+    "search_corpus_1": _BASE_URL + "search_corpus_1.tar.gz",
+    "search_corpus_2": _BASE_URL + "search_corpus_2.tar.gz",
+}
+
+
+class NeuralCodeSearch(datasets.GeneratorBasedBuilder):
+    """Neural Code Search Evaluation Dataset"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="evaluation_dataset",
+            version=VERSION,
+            description="The evaluation dataset is composed of \
+            287 Stack Overflow question and answer pairs",
+        ),
+        datasets.BuilderConfig(
+            name="search_corpus",
+            version=VERSION,
+            description="The search corpus is indexed using all \
+            method bodies parsed from the 24,549 GitHub repositories.",
+        ),
+    ]
+
+    FILENAME_MAP = {
+        "evaluation_dataset": "287_android_questions.json",
+        "search_corpus": "search_corpus_1.jsonl",
+    }
+
+    def _info(self):
+        if self.config.name == "evaluation_dataset":
+            features = datasets.Features(
+                {
+                    "stackoverflow_id": datasets.Value("int32"),
+                    "question": datasets.Value("string"),
+                    "question_url": datasets.Value("string"),
+                    "question_author": datasets.Value("string"),
+                    "question_author_url": datasets.Value("string"),
+                    "answer": datasets.Value("string"),
+                    "answer_url": datasets.Value("string"),
+                    "answer_author": datasets.Value("string"),
+                    "answer_author_url": datasets.Value("string"),
+                    "examples": datasets.features.Sequence(datasets.Value("int32")),
+                    "examples_url": datasets.features.Sequence(datasets.Value("string")),
+                }
+            )
+        else:
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "filepath": datasets.Value("string"),
+                    "method_name": datasets.Value("string"),
+                    "start_line": datasets.Value("int32"),
+                    "end_line": datasets.Value("int32"),
+                    "url": 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."""
+        my_urls = [url for config, url in _URLs.items() if config.startswith(self.config.name)]
+        data_dir = dl_manager.download_and_extract(my_urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "datapath": data_dir,
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, datapath, split):
+        """ Yields examples. """
+        id_ = 0
+        for dp in datapath:
+            if self.config.name == "evaluation_dataset":
+                with open(dp, encoding="utf-8") as f:
+                    data = json.load(f)
+                    for row in data:
+                        yield id_, {
+                            "stackoverflow_id": row["stackoverflow_id"],
+                            "question": row["question"],
+                            "question_url": row["question_url"],
+                            "question_author": row["question_author"],
+                            "question_author_url": row["question_author_url"],
+                            "answer": row["answer"],
+                            "answer_url": row["answer_url"],
+                            "answer_author": row["answer_author"],
+                            "answer_author_url": row["answer_author_url"],
+                            "examples": row["examples"],
+                            "examples_url": row["examples_url"],
+                        }
+                        id_ += 1
+            else:
+                for dirpath, _, fnames in sorted(os.walk(dp)):
+                    for fname in sorted(fnames):
+                        with open(os.path.join(dirpath, fname), encoding="utf-8") as f:
+                            for row in f:
+                                data_dict = json.loads(row)
+                                yield id_, {
+                                    "id": data_dict["id"],
+                                    "filepath": data_dict["filepath"],
+                                    "method_name": data_dict["method_name"],
+                                    "start_line": data_dict["start_line"],
+                                    "end_line": data_dict["end_line"],
+                                    "url": data_dict["url"],
+                                }
+                                id_ += 1