jscore2023 commited on
Commit
7544111
1 Parent(s): 9b73c50

Create handler.py

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  1. handler.py +33 -0
handler.py ADDED
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+ import torch
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+
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+ from typing import Any, Dict
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+
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+ class EndpointHandler:
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+ def __init__(self, path=""):
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+ # load model and tokenizer from path
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+ self.tokenizer = AutoTokenizer.from_pretrained(path)
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+ self.model = AutoModelForCausalLM.from_pretrained(
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+ path, device_map="auto", torch_dtype=torch.float16, trust_remote_code=True
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+ )
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+ self.device = "cuda" if torch.cuda.is_available() else "cpu"
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+
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+ def __call__(self, data: Dict[str, Any]) -> Dict[str, str]:
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+ # process input
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+ inputs = data.pop("inputs", data)
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+ parameters = data.pop("parameters", None)
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+
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+ # preprocess
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+ inputs = self.tokenizer(inputs, return_tensors="pt").to(self.device)
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+
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+ # pass inputs with all kwargs in data
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+ if parameters is not None:
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+ outputs = self.model.generate(**inputs, **parameters)
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+ else:
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+ outputs = self.model.generate(**inputs)
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+
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+ # postprocess the prediction
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+ prediction = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
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+
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+ return [{"generated_text": prediction}]