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The function is defined as f (x) = αx, where α is a small constant (e.g., 0.01) It was designed to address the dying relu problem, where neurons can become inactive and stop learning during training This gives a slight upward slope for negative inputs, preventing the dying neuron problem
Uses of leaky relu prevents dead neurons by allowing a small gradient for negative inputs Leaky rectified linear unit, or leaky relu, is an activation function used in neural networks (nn) and is a direct improvement upon the standard rectified linear unit (relu) function Improves gradient flow during backpropagation.
Relu vs leakyrelu vs prelu in pytorch
In the realm of deep learning, activation functions play a crucial role in enabling neural networks to learn complex patterns and make accurate predictions One such activation function is leakyrelu (leaky rectified linear unit), which addresses some of the limitations of the traditional relu function 文章浏览阅读2.4w次，点赞24次，收藏93次。文章介绍了PyTorch中LeakyReLU激活函数的原理和作用，它通过允许负轴上的一小部分值通过（乘以一个小的斜率α），解决了ReLU可能出现的死亡神经元问题。此外，文章还提供了代码示例进行LeakyReLU与ReLU的对比，并展示了LeakyReLU的图形表示。
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