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