17 lines
459 B
Python
17 lines
459 B
Python
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import json
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import mlflow
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import numpy as np
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import torch
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from torch.autograd import Variable
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logged_model = 'mlruns/1/d5b6f9c1784a4d2dbb8592cd4ad364d7/artifacts/model'
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loaded_model = mlflow.pyfunc.load_model(logged_model)
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with open(f'{logged_model}/input_example.json') as f:
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data = json.load(f)
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input_example = np.array(data['inputs'][0])
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input_example = Variable(torch.from_numpy(input_example)).float()
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loaded_model.predict(input_example)
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