tensor_forest.py 文件源码

def _variance(self, sums, squares):
    """Calculate the variance for each row of the input tensors.

    Variance is V = E[x^2] - (E[x])^2.

    Args:
      sums: A tensor containing output sums, usually a slice from
        variables.node_sums.  Should contain the number of examples seen
        in index 0 so we can calculate expected value.
      squares: Same as sums, but sums of squares.

    Returns:
      A 1-D tensor of the variances for each row in the input.
    """
    total_count = array_ops.slice(sums, [0, 0], [-1, 1])
    e_x = sums / total_count
    e_x2 = squares / total_count

    return math_ops.reduce_sum(e_x2 - math_ops.square(e_x), 1)