wehub-resource-sync
24 lines
666 B
Python
24 lines
666 B
Python
from typing import Any
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from custom_code import iris_classes
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import mlflow
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class CustomPredict(mlflow.pyfunc.PythonModel):
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"""Custom pyfunc class used to create customized mlflow models"""
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def predict(self, context, model_input, params: dict[str, Any] | None = None):
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prediction = [x % 3 for x in model_input]
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return iris_classes(prediction)
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with mlflow.start_run(run_name="test_custom_model_with_inferred_code_paths"):
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# log a custom model
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model_info = mlflow.pyfunc.log_model(
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name="artifacts",
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infer_code_paths=True,
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python_model=CustomPredict(),
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)
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print(f"Model URI: {model_info.model_uri}")
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