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func

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func / func.py

Samip Dahal

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e4b5e70 over 2 years ago

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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.
	"""TODO: Add a description here."""


	import csv
	import json
	import os

	import datasets
	import pickle


	# TODO: Add BibTeX citation
	# Find for instance the citation on arxiv or on the dataset repo/website
	_CITATION = """"""

	# TODO: Add description of the dataset here
	# You can copy an official description
	_DESCRIPTION = """\
	This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
	"""

	# TODO: Add a link to an official homepage for the dataset here
	_HOMEPAGE = ""

	# TODO: Add the licence for the dataset here if you can find it
	_LICENSE = ""

	# TODO: Add link to the official dataset URLs here
	# The HuggingFace dataset library don't host the datasets but only point to the original files
	# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
	languages=['python','javascript','java','go']
	_URLs = {lang:f'https://funcdef.s3.amazonaws.com/{lang}.tar.gz' for lang in languages}
	_URLs['all']=_URLs.copy()


	# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
	class FundDefDataset(datasets.GeneratorBasedBuilder):
	VERSION = datasets.Version("1.0.0")
	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="all", version=VERSION, description="All available data"),
	datasets.BuilderConfig(name="python", version=VERSION, description="Python data"),
	datasets.BuilderConfig(name="javascript", version=VERSION, description="Javascript data"),
	datasets.BuilderConfig(name="java", version=VERSION, description="Java data"),
	datasets.BuilderConfig(name="go", version=VERSION, description="Go data"),
	]

	DEFAULT_CONFIG_NAME = "all"

	def _info(self):
	# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset

	features = datasets.Features(
	{
	"repository_name": datasets.Value("string"),
	"function_path": datasets.Value("string"),
	"function_identifier": datasets.Value("string"),
	"language": datasets.Value("string"),
	"function": datasets.Value("string"),
	"docstring": datasets.Value("string"),
	"function_url": datasets.Value("string"),
	"license":datasets.Value("string"),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features, # Here we define them above because they are different between the two configurations
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	my_urls = _URLs[self.config.name]
	if isinstance(my_urls, str):
	my_urls = {self.config.name:my_urls}
	data_dir = [os.path.join(lang_dir,lang) for lang,lang_dir in dl_manager.download_and_extract(my_urls).items()]
	splitpaths={split:[os.path.join(lang_dir,f'{split}.bin') for lang_dir in data_dir] for split in ['train','valid','test']}

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": splitpaths['train'],
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": splitpaths['test'],
	"split": "test"
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": splitpaths['valid'],
	"split": "valid",
	},
	),
	]

	def _generate_examples(
	self, filepath,split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
	):
	""" Yields examples as (key, example) tuples. """
	count=-1
	for i,filepath in enumerate(filepath):
	loaded_f=pickle.load(open(filepath,'rb'))
	for j, func in enumerate(loaded_f):
	count+=1
	yield count,{
	"repository_name": str(func['nwo']),
	"function_path":str(func['path']),
	"function_identifier": str(func['identifier']),
	"language": str(func['language']),
	"function": str(func['function']),
	"docstring": str(func['docstring']),
	"function_url": str(func['url']),
	"license":str(func['license']),
	}