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Sigmoid Linear Units, or SiLUs, are activation functions for neural networks. The activation of the SiLU is computed by the sigmoid function multiplied by its input.
Applies the Sigmoid Linear Unit (SiLU) function, element-wise. The SiLU function is also known as the swish function.
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Jul 20, 2022 · SiLU vs ReLU. SiLU is proposed as an activation function for neural network function approximation in reinforcement learning.
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tf.nn.silu ... Computes the SiLU or Swish activation function: x * sigmoid(beta * x) . View aliases.
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Nov 6, 2022 · The implementation through the functional library (F.silu()) gives me different result than from the torch library -- written as x * sigmoid(x).