| import toml |
| from collections import Counter |
| import srsly |
| import typer |
| from sklearn.model_selection import train_test_split |
| from pathlib import Path |
|
|
| def count_labels(data): |
| label_counter = Counter() |
| for annotation in data: |
| labels = [span['label'] for span in annotation['spans']] |
| label_counter.update(labels) |
| return label_counter |
|
|
| def split_data(input_file: Path, train_ratio: float = 0.7, dev_ratio: float = 0.15, |
| train_output: Path = Path("assets/train.jsonl"), |
| dev_output: Path = Path("assets/dev.jsonl"), |
| test_output: Path = Path("assets/test.jsonl"), |
| random_state: int = 1): |
| |
| data = list(srsly.read_jsonl(input_file)) |
|
|
| |
| test_ratio = 1 - train_ratio - dev_ratio |
| train_data, temp_data = train_test_split(data, test_size=(dev_ratio + test_ratio), random_state=random_state) |
| dev_data, test_data = train_test_split(temp_data, test_size=test_ratio/(dev_ratio + test_ratio), random_state=random_state) |
|
|
| |
| train_labels = count_labels(train_data) |
| dev_labels = count_labels(dev_data) |
| test_labels = count_labels(test_data) |
|
|
| |
| srsly.write_jsonl(train_output, train_data) |
| srsly.write_jsonl(dev_output, dev_data) |
| srsly.write_jsonl(test_output, test_data) |
|
|
| |
| all_labels = sorted(set(train_labels.keys()) | set(dev_labels.keys()) | set(test_labels.keys())) |
| annotations_data = {label: {'Train': train_labels.get(label, 0), 'Dev': dev_labels.get(label, 0), 'Test': test_labels.get(label, 0)} for label in all_labels} |
|
|
| |
| print(f"{'Label':<20}{'Train':<10}{'Dev':<10}{'Test':<10}") |
| for label in all_labels: |
| print(f"{label:<20}{train_labels.get(label, 0):<10}{dev_labels.get(label, 0):<10}{test_labels.get(label, 0):<10}") |
|
|
| |
| with open("annotations.toml", "w") as toml_file: |
| toml.dump(annotations_data, toml_file) |
|
|
| print("Annotations data saved in annotations.toml") |
|
|
| if __name__ == "__main__": |
| typer.run(split_data) |
|
|