| import csv |
| import datasets |
|
|
| _DOWNLOAD_URL = "https://huggingface.co/datasets/mrojas/task1a/resolve/main/data.csv" |
|
|
| class Task1a(datasets.GeneratorBasedBuilder): |
| """Task1a classification dataset.""" |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| features=datasets.Features( |
| { |
| "text": datasets.Value("string"), |
| "label": datasets.ClassLabel(names = ["0", "1"]), |
| } |
| ) |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| path = dl_manager.download_and_extract(_DOWNLOAD_URL) |
| return [ |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": path, "is_test": False}), |
| datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": path, "is_test": True}), |
| ] |
|
|
| def _generate_examples(self, filepath, is_test, test_size = 0.3): |
| """Generate examples.""" |
| with open(filepath, encoding="utf-8") as csv_file: |
| train_threshold = 122 |
| csv_reader = csv.reader( |
| csv_file |
| ) |
| |
| for id_, row in enumerate(csv_reader): |
| if id_ > 0: |
| print(row) |
| text, label = row |
| current_row = id_, {"text": text, "label": int(label)} |
| if (id_ < train_threshold) & (not is_test): |
| yield current_row |
| if (id_ >= train_threshold) & (is_test): |
| yield current_row |
