mirror of
https://github.com/clearml/clearml-serving
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24 lines
1011 B
Python
24 lines
1011 B
Python
from typing import Any
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import numpy as np
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# Notice Preprocess class Must be named "Preprocess"
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class Preprocess(object):
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def __init__(self):
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# set internal state, this will be called only once. (i.e. not per request)
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pass
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def preprocess(self, body: dict, state: dict, collect_custom_statistics_fn=None) -> Any:
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# we expect to get four valid numbers on the dict: x0, x1, x2, x3
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return np.array(
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[[body.get("x0", None), body.get("x1", None), body.get("x2", None), body.get("x3", None)], ],
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dtype=np.float32
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)
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def postprocess(self, data: Any, state: dict, collect_custom_statistics_fn=None) -> dict:
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# post process the data returned from the model inference engine
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# data is the return value from model.predict we will put is inside a return value as Y
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# we pick the most probably class and return the class index (argmax)
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return dict(y=int(np.argmax(data)) if isinstance(data, np.ndarray) else data)
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