torch.nn.functional. nll_loss (input, target, weight = None, size_average = None, ignore_index =-100, reduce = None, reduction = 'mean') [source] [source] ¶ Compute the negative log likelihood loss. See NLLLoss for details.

The negative log likelihood loss. It is useful to train a classification problem with C classes. If provided, the optional argument weight should be a 1D Tensor assigning weight to each of the classes. This is particularly useful when you have an unbalanced training set.

torch.nn.NLLLOSS通常不被独立当作损失函数，而需要和softmax、 log 等运算组合当作损失函数。 torch.nn.NLLLOSS官方链接： NLLLoss - PyTorch 1.9.0 documentation. 在使用nllloss时，需要有两个张量，一个是预测向量，一个是label. # output: tensor(-3.) nllloss对两个向量的操作为， 将predict中的向量，在label中对应的index取出，并取负号输出。 label中为1，则取2，3，1中的 …

2017年8月13日 · Negative Log-Likelihood (NLL) In practice, the softmax function is used in tandem with the negative log-likelihood (NLL). This loss function is very interesting if we interpret it in relation to the behavior of softmax. First, let’s write down our loss function: \[L(\mathbf{y}) = -\log(\mathbf{y})\] This is summed for all the correct classes.

2019年8月13日 · NLL: -ln(0.5) = 0.69. Take a breath and look at the values obtained by using the logarithm and multiplying by -1. You see? The better the prediction the lower the NLL loss, exactly what we...

2024年1月15日 · NLLLoss全名叫做Negative Log Likelihood Loss，顾名思义，输入就是log likelihood，对输入的对应部分取负号就是这个loss的输出了，公式可以表示为： 其中 是每个类别的权重，默认的全为1， 表示对应target那一类的概率。 更简单一点来说，就是将对应类别的x输出取负值。 比如说x= [-2, -3, -0.5]，y= [0, 0, 1]，那么 NLL loss 就为对应target那类的输出值的 …

The following are 30 code examples of torch.nn.functional.nll_loss(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.

2020年8月14日 · CrossEntropyLoss applies LogSoftmax to the output before passing it to NLLLoss. Is there a difference in terms of running time or accuracy of using CrossEntropyLoss vs. LogSoftmax + NLLLoss (on CPU or GPU)? Which option is considered more conventional / …

2023年6月7日 · When defining the loss function, Negative Log Likelihood loss (NLL loss) are highly involved no matter which method for BNN. I see some people would directly use a MSE loss as the NLL loss, some people would define there own NLL loss.

2022年3月5日 · nll_loss = nn. NLLLoss xx = torch. tensor ([[0.1, 0.1, 0.1, 0.2, 0.5], [0.1, 0.1, 0.1, 0.2, 0.5]]) yy = torch. tensor ([4, 1]) nll_loss (xx, yy) # 出力 # tensor(-0.3000)