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Computes the log-leave-one-out-sum of exp(logx).

    logx, axis=None, keepdims=False, name=None


  • logx: Floating-type Tensor representing log(x) where x is some positive value.
  • axis: The dimensions to sum across. If None (the default), reduces all dimensions. Must be in the range [-rank(logx), rank(logx)]. Default value: None (i.e., reduce over all dims).
  • keepdims: If true, retains reduced dimensions with length 1. Default value: False (i.e., keep all dims in log_sum_x).
  • name: Python str name prefixed to Ops created by this function. Default value: None (i.e., "log_loosum_exp").


  • log_loosum_exp: Tensor with same shape and dtype as logx representing the natural-log of the sum of exp(logx) except that the element logx[i] is removed.
  • log_sum_x: logx.dtype Tensor corresponding to the natural-log of the sum of exp(logx). Has reduced shape of logx (per axis and keepdims).