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import torch.nn.functional as F
from torch import Tensor
from transformers import AutoTokenizer, AutoModel, AutoProcessor
from torch import cuda
class EndpointHandler():
def __init__(self, path=""):
#self.processor = AutoProcessor.from_pretrained(path)
#self.model = AutoModel.from_pretrained(path, trust_remote_code=True)
#self.device = "cuda" if cuda.is_available() else "cpu"
#self.model.to(self.device)
def __call__(self, data: Dict[str, Any]) -> List[List[int]]:
#image = data.pop("inputs",data)
#processed = self.processor(images=image, return_tensors="pt").to(self.device)
#prediction = self.model(processed["pixel_values"])
return "OK"#prediction.item() |