def softmax_neg_loss( outputs, targets, derivative=False, epsilon=1e-11 ):
    outputs = np.clip(outputs, epsilon, 1 - epsilon)
    
    if derivative:
        return outputs - targets
    else:
        return -np.sum(targets * np.log( outputs ))
#end cost function
Parse an attribute query
dataset/ETHPy150Open jorgenkg/python-neural-network/src/cost_functions.py/softmax_neg_loss--crossover with--dataset/ETHPy150Open cloudera/hue/desktop/core/ext-py/pysaml2-2.4.0/src/saml2/server.py/Server.parse_attribute_query