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boston_handler.py
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50 lines (40 loc) · 998 Bytes
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from pydantic import BaseModel
import numpy as np
class HousingFeatures(BaseModel):
CRIM: float
ZN: float
INDUS: float
CHAS: float
NOX: float
RM: float
AGE: float
DIS: float
RAD: float
TAX: float
PTRATIO: float
B: float
LSTAT: float
def to_numpy(self):
return np.array(
[
self.CRIM,
self.ZN,
self.INDUS,
self.CHAS,
self.NOX,
self.RM,
self.AGE,
self.DIS,
self.RAD,
self.TAX,
self.PTRATIO,
self.B,
self.LSTAT,
]
).astype(np.float32)
class PredictionResult(BaseModel):
predicted: float
def pre_inference(sample, metadata):
return HousingFeatures(**sample).to_numpy()
def post_inference(prediction, metadata):
return PredictionResult(**{'predicted': prediction[0][0]}).dict()