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Plot of the ReLU (blue) and GELU (green) functions near x = 0. In the context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function [1] [2] is an activation function defined as the non-negative part of its argument, i.e., the ramp function:
The convex conjugate (specifically, the Legendre transform) of the softplus function is the negative binary entropy (with base e).This is because (following the definition of the Legendre transform: the derivatives are inverse functions) the derivative of softplus is the logistic function, whose inverse function is the logit, which is the derivative of negative binary entropy.
Modern activation functions include the logistic function used in the 2012 speech recognition model developed by Hinton et al; [2] the ReLU used in the 2012 AlexNet computer vision model [3] [4] and in the 2015 ResNet model; and the smooth version of the ReLU, the GELU, which was used in the 2018 BERT model. [5]
ReLU is the abbreviation of rectified linear unit. It was proposed by Alston Householder in 1941, [82] and used in CNN by Kunihiko Fukushima in 1969. [38] ReLU applies the non-saturating activation function = (,). [68] It effectively removes negative values from an activation map by setting them to zero. [83]
The swish function is a family of mathematical function defined as follows: . The swish function = = +. [1]. where can be constant (usually set to 1) or trainable.. The swish family was designed to smoothly interpolate between a linear function and the ReLU function.
PyTorch is a machine learning library based on the Torch library, [4] [5] [6] used for applications such as computer vision and natural language processing, [7] originally developed by Meta AI and now part of the Linux Foundation umbrella.
In mathematics, the ramp function is also known as the positive part. In machine learning, it is commonly known as a ReLU activation function [1] [2] or a rectifier in analogy to half-wave rectification in electrical engineering. In statistics (when used as a likelihood function) it is known as a tobit model.
The torch package also simplifies object-oriented programming and serialization by providing various convenience functions which are used throughout its packages. The torch.class(classname, parentclass) function can be used to create object factories ().