Mish activation function. — activation_mish • keras3

It is defined as:

mish(x) = x * tanh(softplus(x))

where softplus is defined as:

softplus(x) = log(exp(x) + 1)

Usage

activation_mish(x)

Arguments

x: Input tensor.

Value

A tensor, the result from applying the activation to the input tensor x.

Reference

Misra, 2019

See also

https://keras.io/api/layers/activations#mish-function

Other activations:
activation_celu()
activation_elu()
activation_exponential()
activation_gelu()
activation_glu()
activation_hard_shrink()
activation_hard_sigmoid()
activation_hard_tanh()
activation_leaky_relu()
activation_linear()
activation_log_sigmoid()
activation_log_softmax()
activation_relu()
activation_relu6()
activation_selu()
activation_sigmoid()
activation_silu()
activation_soft_shrink()
activation_softmax()
activation_softplus()
activation_softsign()
activation_sparse_plus()
activation_sparse_sigmoid()
activation_sparsemax()
activation_squareplus()
activation_tanh()
activation_tanh_shrink()
activation_threshold()