alexshtf

import torch

class BatchIter:
    """
    tensors: feature tensors (each with shape: num_instances x *)
    """

    def __init__(self, *tensors, batch_size, shuffle=True):
        self.tensors = tensors

alexshtf

import torch
import torch.nn.functional as F
import copy
import math


def ipw_crossentropy(weights, scores, label):
    propensities = torch.reciprocal(weights)
    return (
            -label * (scores + torch.log(propensities))

alexshtf

#include <limits>	
	
namespace Detail
{
	double constexpr sqrtNewtonRaphson(double x, double curr, double prev)
	{
		return curr == prev
			? curr
			: sqrtNewtonRaphson(x, 0.5 * (curr + x / curr), curr);
	}