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--- |
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language: |
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- en |
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--- |
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copy of [data-of-multimodal-sarcasm-detection](https://github.com/headacheboy/data-of-multimodal-sarcasm-detection) |
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```python |
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# usage |
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from datasets import load_dataset |
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from transformers import CLIPImageProcessor, CLIPTokenizer |
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from torch.utils.data import DataLoader |
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image_processor = CLIPImageProcessor.from_pretrained(clip_path) |
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tokenizer = CLIPTokenizer.from_pretrained(clip_path) |
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def tokenization(example): |
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text_inputs = tokenizer(example["text"], truncation=True, padding=True, return_tensors="pt") |
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image_inputs = image_processor(example["image"], return_tensors="pt") |
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return {'pixel_values': image_inputs['pixel_values'], |
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'input_ids': text_inputs['input_ids'], |
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'attention_mask': text_inputs['attention_mask'], |
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"label": example["label"]} |
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dataset = load_dataset('quaeast/multimodal_sarcasm_detection') |
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dataset.set_transform(tokenization) |
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# get torch dataloader |
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train_dl = DataLoader(dataset['train'], batch_size=256, shuffle=True) |
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test_dl = DataLoader(dataset['test'], batch_size=256, shuffle=True) |
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val_dl = DataLoader(dataset['validation'], batch_size=256, shuffle=True) |
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``` |
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