...registry.py rollback & ...s444356.py dir test
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@ -4,7 +4,7 @@ import json
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model = mlflow.pyfunc.load_model(
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model = mlflow.pyfunc.load_model(
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'/mlruns/13/da5c6167bb45403fa35569849a1fbc13/artifacts/model')
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'mlruns/1/4b83e774512444188fb587288818c298/artifacts/model')
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with open('input_example.json') as f:
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with open('input_example.json') as f:
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data = np.array([json.load(f)['inputs'][0]], dtype=np.float32)
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data = np.array([json.load(f)['inputs'][0]], dtype=np.float32)
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print(f"Predicted values: {model.predict(data.reshape(-1, 2))}")
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print(f"Predicted values: {model.predict(data.reshape(-1, 2))}")
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@ -6,7 +6,7 @@ import os
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print('################\n\n', os.listdir(), "\n\n###############")
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print('################\n\n', os.listdir(), "\n\n###############")
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model = mlflow.pyfunc.load_model(
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model = mlflow.pyfunc.load_model(
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'mlruns/1/4b83e774512444188fb587288818c298/artifacts/model')
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'mlruns/13/da5c6167bb45403fa35569849a1fbc13/artifacts/model')
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with open('mlruns/1/4b83e774512444188fb587288818c298/artifacts/model/input_example.json') as f:
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with open('mlruns/13/da5c6167bb45403fa35569849a1fbc13/artifacts/model/input_example.json') as f:
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data = np.array([json.load(f)['inputs'][0]], dtype=np.float32)
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data = np.array([json.load(f)['inputs'][0]], dtype=np.float32)
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print(f"Predicted values: {model.predict(data.reshape(-1, 2))}")
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print(f"Predicted values: {model.predict(data.reshape(-1, 2))}")
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