temp_africaNLP_keyword_spotting_for_african_languages
/
temp_africaNLP_keyword_spotting_for_african_languages.py
| # Testing how to load rarfile from Zenodo, specifically https://zenodo.org/record/4661645. | |
| # https://github.com/huggingface/datasets/blob/dfdd2f949c1840926c02ae47f0f0c43083ef0b1f/datasets/common_voice/common_voice.py#L661 provided some inspiration | |
| # also https://huggingface.co/docs/datasets/master/dataset_script.html | |
| # 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 pandas as pd | |
| import rarfile | |
| # TODO: Add BibTeX citation | |
| # Find for instance the citation on arxiv or on the dataset repo/website | |
| _CITATION = """\ | |
| @InProceedings{huggingface:dataset, | |
| title = {A great new dataset}, | |
| author={huggingface, Inc. | |
| }, | |
| year={2020} | |
| } | |
| """ | |
| # 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. | |
| """ | |
| _HOMEPAGE = "https://zenodo.org/record/466164" | |
| # 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) | |
| _URLs = { | |
| "first_domain": "https://zenodo.org/record/4661645/files/Keyword_spotting_dataset_v0.01_17042021.rar", | |
| } | |
| class TempAfricaNLPKeywordSpottingForAfricanLanguages(datasets.GeneratorBasedBuilder): | |
| """TODO: Short description of my dataset.""" | |
| VERSION = datasets.Version("1.1.0") | |
| # This is an example of a dataset with multiple configurations. | |
| # If you don't want/need to define several sub-sets in your dataset, | |
| # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. | |
| # If you need to make complex sub-parts in the datasets with configurable options | |
| # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig | |
| # BUILDER_CONFIG_CLASS = MyBuilderConfig | |
| # You will be able to load one or the other configurations in the following list with | |
| # data = datasets.load_dataset('my_dataset', 'first_domain') | |
| # data = datasets.load_dataset('my_dataset', 'second_domain') | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="first_domain", | |
| version=VERSION, | |
| description="This part of my dataset covers a first domain", | |
| ), | |
| ] | |
| DEFAULT_CONFIG_NAME = "first_domain" # It's not mandatory to have a default configuration. Just use one if it make sense. | |
| def _info(self): | |
| # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset | |
| if ( | |
| self.config.name == "first_domain" | |
| ): # This is the name of the configuration selected in BUILDER_CONFIGS above | |
| features = datasets.Features( | |
| { | |
| "sentence": datasets.Value("string"), | |
| "path": datasets.Value("string"), | |
| "audio": datasets.features.Audio() # TODO: sampling rate? https://huggingface.co/docs/datasets/master/package_reference/main_classes.html#datasets.Audio | |
| # TODO: 'id', 'client_id', 'path', 'sentence', 'original_sentence_id', 'created_at', 'bucket', 'locale_id' | |
| } | |
| ) | |
| else: # This is an example to show how to have different features for "first_domain" and "second_domain" | |
| features = datasets.Features( | |
| { | |
| "sentence": datasets.Value("string"), | |
| "option2": datasets.Value("string"), | |
| "second_domain_answer": datasets.Value("string") | |
| # These are the features of your dataset like images, labels ... | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| # This is the description that will appear on the datasets page. | |
| description=_DESCRIPTION, | |
| # This defines the different columns of the dataset and their types | |
| features=features, # Here we define them above because they are different between the two configurations | |
| # 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=_HOMEPAGE, | |
| # License for the dataset if available | |
| license=_LICENSE, | |
| # Citation for the dataset | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration | |
| # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name | |
| # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs | |
| # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. | |
| # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive | |
| my_urls = _URLs[self.config.name] | |
| data_dir = dl_manager.download_and_extract(my_urls) | |
| data_dir = os.path.join( | |
| data_dir, "data_17042021" | |
| ) # the rar file has a subfolder. | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, "clips.xlsx"), | |
| "split": "train", | |
| "data_dir": data_dir, | |
| }, | |
| ), | |
| # | |
| # datasets.SplitGenerator( | |
| # name=datasets.Split.TEST, | |
| # # These kwargs will be passed to _generate_examples | |
| # gen_kwargs={ | |
| # "filepath": os.path.join(data_dir, "test.jsonl"), | |
| # "split": "test" | |
| # }, | |
| # ), | |
| # datasets.SplitGenerator( | |
| # name=datasets.Split.VALIDATION, | |
| # # These kwargs will be passed to _generate_examples | |
| # gen_kwargs={ | |
| # "filepath": os.path.join(data_dir, "dev.jsonl"), | |
| # "split": "dev", | |
| # }, | |
| # ), | |
| # | |
| ] | |
| def _generate_examples( | |
| self, | |
| filepath, | |
| split, | |
| data_dir, # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
| ): | |
| """Yields examples as (key, example) tuples.""" | |
| # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. | |
| # The `key` is here for legacy reason (tfds) and is not important in itself. | |
| clips_df = pd.read_excel(filepath) | |
| with open(filepath, encoding="utf-8") as f: | |
| for id_, row in clips_df.iterrows(): | |
| data = row | |
| bucket = row["bucket"] | |
| if bucket == split: | |
| yield id_, { | |
| "sentence": data["sentence"], | |
| "path": data["path"], | |
| "audio": os.path.join( | |
| data_dir, data["path"] | |
| ), # set the audio feature, should be able to handle things automatically? | |
| } | |