Sparse sigmoid activation function.

It is defined as

f(x) = 0 for x <= -1, f(x) = 0.5 * (x + 1) for -1 < x < 1, f(x) = 1 for x >= 1.

Usage

activation_sparse_sigmoid(x)

Arguments

x

Input tensor.

Value

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

Reference

• M. Blondel, A. F. T. Martins, V. Niculae, 2019

See also

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_mish()
activation_relu()
activation_relu6()
activation_selu()
activation_sigmoid()
activation_silu()
activation_soft_shrink()
activation_softmax()
activation_softplus()
activation_softsign()
activation_sparse_plus()
activation_sparsemax()
activation_squareplus()
activation_tanh()
activation_tanh_shrink()
activation_threshold()