tensorflow_backend.py 文件源码

def logsumexp(x, axis=None, keepdims=False):
    """Computes log(sum(exp(elements across dimensions of a tensor))).

    This function is more numerically stable than log(sum(exp(x))).
    It avoids overflows caused by taking the exp of large inputs and
    underflows caused by taking the log of small inputs.

    # Arguments
        x: A tensor or variable.
        axis: An integer, the axis to reduce over.
        keepdims: A boolean, whether to keep the dimensions or not.
            If `keepdims` is `False`, the rank of the tensor is reduced
            by 1. If `keepdims` is `True`, the reduced dimension is
            retained with length 1.

    # Returns
        The reduced tensor.
    """
    axis = _normalize_axis(axis, ndim(x))
    return tf.reduce_logsumexp(x, reduction_indices=axis, keep_dims=keepdims)