| from typing import Any, Dict | |
| from transformers import ViltProcessor, ViltForQuestionAnswering | |
| class EndpointHandler: | |
| def __init__(self, path=""): | |
| # load model and processor from path | |
| self.processor = AutoTokenizer.from_pretrained(path) | |
| self.model = ViltForQuestionAnswering.from_pretrained(path) | |
| self.device = "cuda" if torch.cuda.is_available() else "cpu" | |
| def __call__(self, data: Dict[str, Any]) -> Dict[str, str]: | |
| # process input | |
| image = data.pop("image", data) | |
| text = data.pop("text", data) | |
| parameters = data.pop("parameters", None) | |
| # preprocess | |
| encoding = processor(image, text, return_tensors="pt") | |
| outputs = model(**encoding) | |
| # postprocess the prediction | |
| logits = outputs.logits | |
| idx = logits.argmax(-1).item() | |
| return [{"answer": model.config.id2label[idx]}] |