nnet.py 文件源码

def binary_crossentropy(output, target):
    """
    Compute the crossentropy of binary random variables.

    Output and target are each expectations of binary random
    variables; target may be exactly 0 or 1 but output must
    lie strictly between 0 and 1.

    Notes
    -----
    We could use the x log y op to support output=0 and output=1.
    The gradient would still be undefined though.

    We do not sum, crossentropy is computed by component.
    TODO : Rewrite as a scalar, and then broadcast to tensor.

    """
    return -(target * tensor.log(output) + (1.0 - target) * tensor.log(1.0 - output))