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from typing import Dict, List, Any
from transformers import CLIPTokenizer, CLIPModel
class EndpointHandler:
def __init__(self, path=""):
# self.model= load_model(path)
hf_model_path = "openai/clip-vit-large-patch14"
self.model = CLIPModel.from_pretrained(hf_model_path)
self.tokenizer = CLIPTokenizer.from_pretrained(hf_model_path)
def __call__(self, data: Dict[str, Any]) -> List[float]:
"""
data args:
inputs (:obj: `str` | `PIL.Image` | `np.array`)
kwargs
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
print("doesn this even get updated:", data)
token_inputs = self.tokenizer([data["inputs"]], padding=True, return_tensors="pt")
query_embed = self.model.get_text_features(**token_inputs)
np_query_embed = query_embed.detach().cpu().numpy()[0].tolist()
return np_query_embed
if __name__ == "__main__":
eh = EndpointHandler()
print(eh({"inputs": "a dog"}))
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