notebooks/escience_series/mnist.py [136:151]:
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def neo_postprocess(result):
    import logging
    import numpy as np
    import json

    logging.info('Invoking user-defined post-processing function')

    # Softmax (assumes batch size 1)
    result = np.squeeze(result)
    result_exp = np.exp(result - np.max(result))
    result = result_exp / np.sum(result_exp)

    response_body = json.dumps(result.tolist())
    content_type = 'application/json'

    return response_body, content_type
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notebooks/ml_tensorflow/mnist.py [145:160]:
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def neo_postprocess(result):
    import logging
    import numpy as np
    import json

    logging.info('Invoking user-defined post-processing function')
    
    # Softmax (assumes batch size 1)
    result = np.squeeze(result)
    result_exp = np.exp(result - np.max(result))
    result = result_exp / np.sum(result_exp)

    response_body = json.dumps(result.tolist())
    content_type = 'application/json'

    return response_body, content_type
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