nn.Sigmoid()

nn.Sigmoid() is a class in PyTorch's nn module that represents the sigmoid activation function. The sigmoid function is a non-linear activation function that squashes the input values between 0 and 1. It is commonly used in neural networks for binary classification tasks where the output value needs to be between 0 and 1. The sigmoid function is defined as:

$$
\text{sigmoid}(x) = \frac{1}{1+e^{-x}}
$$

where $x$ is the input value. The nn.Sigmoid() class can be used in PyTorch to apply the sigmoid function to the outputs of a neural network layer.

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nn.Sigmoid

nnigmoid()是PyTorch库中的一个类，用于实现Sigmoid激活函数。它将输入值转换为0到1之间的概率值。该类可以通过torch.nn.Sigmoid()来调用。在使用时，首先需要导入torch.nn和torch模块，然后创建一个输入张量a，通过nn.Sigmoid()创建一个Sigmoid对象sigmoid，再通过sigmoid(a)来对输入进行Sigmoid激活。最后可以打印出输入张量a和经过Sigmoid激活后的输出张量b。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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nn.sigmoid

Sigmoid函数是一种常用的激活函数，可以将输入的值映射到0到1之间。它的数学表达式为：

f(x) = 1 / (1 + exp(-x))

其中，x为输入值。Sigmoid函数在神经网络中常用于二分类问题的输出层，可以将输出结果转化为概率形式。它的特点是输出值在接近边界时变化缓慢，而在中间区域变化较快。