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from typing import Dict, List, Any |
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import numpy as np |
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from concrete.ml.deployment import FHEModelServer |
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def from_json(python_object): |
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if "__class__" in python_object: |
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return bytes(python_object["__value__"]) |
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def to_json(python_object): |
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if isinstance(python_object, bytes): |
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return {"__class__": "bytes", "__value__": list(python_object)} |
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raise TypeError(repr(python_object) + " is not JSON serializable") |
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class EndpointHandler: |
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def __init__(self, path=""): |
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self.fhemodel_server = FHEModelServer(path + "/compiled_model") |
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self.key_database = {} |
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def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: |
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""" |
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data args: |
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inputs (:obj: `str`) |
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date (:obj: `str`) |
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Return: |
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A :obj:`list` | `dict`: will be serialized and returned |
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""" |
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method = data.pop("method", data) |
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if method is "save_key": |
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evaluation_keys = from_json(data.pop("evaluation_keys", data)) |
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uid = np.random.randint(2**32) |
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while uid in self.key_database.keys(): |
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uid = np.random.randint(2**32) |
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uid = 42 |
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self.key_database[uid] = evaluation_keys |
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return {"uid": uid} |
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elif method == "inference": |
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uid = data.pop("uid", data) |
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uid = 42 |
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assert uid in self.key_database.keys(), f"{uid} not in DB" |
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encrypted_inputs = from_json(data.pop("encrypted_inputs", data)) |
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evaluation_keys = self.key_database[uid] |
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encrypted_prediction = self.fhemodel_server.run(encrypted_inputs, evaluation_keys) |
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return to_json(encrypted_prediction) |
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else: |
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return |
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