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| """Preprocessing — pure transforms on captions and images. | |
| Functions in this package take inputs and return outputs with no hidden state | |
| and no disk I/O. That makes them trivially unit-testable and lets us share the | |
| same logic across the training pipeline (where they're composed into tf.data | |
| maps) and the inference path (where they're called once per request). | |
| Modules: | |
| caption.py ``preprocess_caption(text)`` — lower/strip/wrap with [start]/[end] | |
| image.py ``preprocess_image_tensor(img)``, ``load_and_preprocess_image(path)`` | |
| tokenizer.py ``CaptionTokenizer`` — wraps tf.keras TextVectorization | |
| augmentation.py ``default_image_augmentation()`` — Keras Sequential | |
| """ | |
| from captioning.preprocessing.augmentation import default_image_augmentation | |
| from captioning.preprocessing.caption import ( | |
| END_TOKEN, | |
| START_TOKEN, | |
| preprocess_caption, | |
| ) | |
| from captioning.preprocessing.image import ( | |
| load_and_preprocess_image, | |
| preprocess_image_tensor, | |
| ) | |
| from captioning.preprocessing.tokenizer import CaptionTokenizer | |
| __all__ = [ | |
| "END_TOKEN", | |
| "START_TOKEN", | |
| "CaptionTokenizer", | |
| "default_image_augmentation", | |
| "load_and_preprocess_image", | |
| "preprocess_caption", | |
| "preprocess_image_tensor", | |
| ] | |