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from datasets import load_dataset |
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load_dataset("path/to/my_dataset") |
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datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"context": datasets.Value("string"), |
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"question": datasets.Value("string"), |
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"answers": datasets.Sequence( |
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{ |
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"text": datasets.Value("string"), |
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"answer_start": datasets.Value("int32"), |
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} |
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), |
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} |
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) |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"context": datasets.Value("string"), |
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"question": datasets.Value("string"), |
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"answers": datasets.features.Sequence( |
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{"text": datasets.Value("string"), "answer_start": datasets.Value("int32"),} |
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), |
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} |
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), |
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|
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|
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supervised_keys=None, |
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homepage="https://rajpurkar.github.io/SQuAD-explorer/", |
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citation=_CITATION, |
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) |
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class SuperGlueConfig(datasets.BuilderConfig): |
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"""BuilderConfig for SuperGLUE.""" |
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|
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def __init__(self, features, data_url, citation, url, label_classes=("False", "True"), **kwargs): |
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"""BuilderConfig for SuperGLUE. |
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|
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Args: |
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features: *list[string]*, list of the features that will appear in the |
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feature dict. Should not include "label". |
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data_url: *string*, url to download the zip file from. |
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citation: *string*, citation for the data set. |
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url: *string*, url for information about the data set. |
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label_classes: *list[string]*, the list of classes for the label if the |
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label is present as a string. Non-string labels will be cast to either |
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'False' or 'True'. |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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|
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|
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super(SuperGlueConfig, self).__init__(version=datasets.Version("1.0.2"), **kwargs) |
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self.features = features |
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self.label_classes = label_classes |
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self.data_url = data_url |
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self.citation = citation |
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self.url = url |
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class SuperGlue(datasets.GeneratorBasedBuilder): |
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"""The SuperGLUE benchmark.""" |
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|
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BUILDER_CONFIGS = [ |
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SuperGlueConfig( |
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name="boolq", |
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description=_BOOLQ_DESCRIPTION, |
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features=["question", "passage"], |
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data_url="https://dl.fbaipublicfiles.com/glue/superglue/data/v2/BoolQ.zip", |
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citation=_BOOLQ_CITATION, |
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url="https://github.com/google-research-datasets/boolean-questions", |
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), |
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... |
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... |
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SuperGlueConfig( |
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name="axg", |
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description=_AXG_DESCRIPTION, |
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features=["premise", "hypothesis"], |
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label_classes=["entailment", "not_entailment"], |
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data_url="https://dl.fbaipublicfiles.com/glue/superglue/data/v2/AX-g.zip", |
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citation=_AXG_CITATION, |
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url="https://github.com/rudinger/winogender-schemas", |
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), |
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from datasets import load_dataset |
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dataset = load_dataset('super_glue', 'boolq') |
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class NewDataset(datasets.GeneratorBasedBuilder): |
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|
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VERSION = datasets.Version("1.1.0") |
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|
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="first_domain", version=VERSION, description="This part of my dataset covers a first domain"), |
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datasets.BuilderConfig(name="second_domain", version=VERSION, description="This part of my dataset covers a second domain"), |
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] |
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|
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DEFAULT_CONFIG_NAME = "first_domain" |
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_URL = "https://rajpurkar.github.io/SQuAD-explorer/dataset/" |
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_URLS = { |
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"train": _URL + "train-v1.1.json", |
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"dev": _URL + "dev-v1.1.json", |
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} |
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
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urls_to_download = self._URLS |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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|
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), |
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] |
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def _generate_examples(self, filepath): |
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"""This function returns the examples in the raw (text) form.""" |
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logger.info("generating examples from = %s", filepath) |
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with open(filepath) as f: |
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squad = json.load(f) |
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for article in squad["data"]: |
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title = article.get("title", "").strip() |
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for paragraph in article["paragraphs"]: |
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context = paragraph["context"].strip() |
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for qa in paragraph["qas"]: |
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question = qa["question"].strip() |
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id_ = qa["id"] |
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|
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answer_starts = [answer["answer_start"] for answer in qa["answers"]] |
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answers = [answer["text"].strip() for answer in qa["answers"]] |
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|
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|
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yield id_, { |
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"title": title, |
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"context": context, |
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"question": question, |
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"id": id_, |
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"answers": {"answer_start": answer_starts, "text": answers,}, |
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} |
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datasets-cli test datasets/<your-dataset-folder> --save_infos --all_configs |
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datasets-cli dummy_data datasets/<your-dataset-folder> --auto_generate |
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datasets-cli dummy_data datasets/<your-dataset-folder> |
|
|
|
==============================DUMMY DATA INSTRUCTIONS============================== |
|
- In order to create the dummy data for my-dataset, please go into the folder './datasets/my-dataset/dummy/1.1.0' with *cd ./datasets/my-dataset/dummy/1.1.0* . |
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|
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- Please create the following dummy data files 'dummy_data/TREC_10.label, dummy_data/train_5500.label' from the folder './datasets/my-dataset/dummy/1.1.0' |
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|
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- For each of the splits 'train, test', make sure that one or more of the dummy data files provide at least one example |
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|
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- If the method *_generate_examples(...)* includes multiple *open()* statements, you might have to create other files in addition to 'dummy_data/TREC_10.label, dummy_data/train_5500.label'. In this case please refer to the *_generate_examples(...)* method |
|
|
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- After all dummy data files are created, they should be zipped recursively to 'dummy_data.zip' with the command *zip -r dummy_data.zip dummy_data/* |
|
|
|
- You can now delete the folder 'dummy_data' with the command *rm -r dummy_data* |
|
|
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- To get the folder 'dummy_data' back for further changes to the dummy data, simply unzip dummy_data.zip with the command *unzip dummy_data.zip* |
|
|
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- Make sure you have created the file 'dummy_data.zip' in './datasets/my-dataset/dummy/1.1.0' |
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=================================================================================== |
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RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_<your_dataset_name> |
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RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_<your_dataset_name> |
