![]() ImportError: cannot import name 'swish' from '' (C:\Users\FlamePrinz\Anaconda3\lib\site-packages\tensorflow\python\keras\activations. The SiLU was later rediscovered in 2017 as the Sigmoid-weighted Linear Unit. For 1, the function becomes equivalent to the Sigmoid Linear Unit 2 or SiLU, first proposed alongside the GELU in 2016. With default values, this returns the standard ReLU activation: max(x, 0), the element-wise maximum. The swish function is a mathematical function defined as follows: where is either constant or a trainable parameter depending on the model. As an example, here is how I implemented the swish activation function: from keras import backend as K def swish (x, beta1.0): return x K. > 23 from import swishĢ4 from import tanh Applies the rectified linear unit activation function. 3 Answers Sorted by: 16 First you need to define a function using backend functions. According to the paper is new self-gate activation function is more powerful than relu, and can improves neural net's accuarcy by just simple replace relu with swish. ~\Anaconda3\lib\site-packages\tensorflow\keras\activations\_init_.py in Ģ1 from import softplusĢ2 from import softsign Activation-function-swish-in-Keras Google just release a paper to describe a new activation function: SWISH: A SELF-GATED ACTIVATION FUNCTION. ~\Anaconda3\lib\site-packages\tensorflow\keras\_init_.py in > 6 from import SequentialĨ from import Dense, Activation, Dropout tf.( x ) Función de activación de swish que devuelve xsigmoid(x). I get the following error: ImportError Traceback (most recent call last) I am trying to run the import statement: from import Sequential I am running a jupyter notebook from an Anaconda Prompt (Anaconda 3), and I am trying to use tensorflow keras. ![]()
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