AI::MXNet::Gluon::NN::Activation
Applies an activation function to input. Parameters ---------- activation : str Name of activation function to use. See mxnet.ndarray.Activation for available choices. Input shape: Arbitrary. Output shape: Same shape as input.
AI::MXNet::Gluon::NN::LeakyReLU - Leaky version of a Rectified Linear Unit.
Leaky version of a Rectified Linear Unit. It allows a small gradient when the unit is not active Parameters ---------- alpha : float slope coefficient for the negative half axis. Must be >= 0.
AI::MXNet::Gluon::NN::PReLU - Parametric leaky version of a Rectified Linear Unit.
Parametric leaky version of a Rectified Linear Unit. https://arxiv.org/abs/1502.01852 It learns a gradient when the unit is not active Parameters ---------- alpha_initializer : Initializer Initializer for the embeddings matrix.
AI::MXNet::Gluon::NN::ELU - Exponential Linear Unit (ELU)
Exponential Linear Unit (ELU) "Fast and Accurate Deep Network Learning by Exponential Linear Units", Clevert et al, 2016 https://arxiv.org/abs/1511.07289 Published as a conference paper at ICLR 2016 Parameters ---------- alpha : float The alpha parameter as described by Clevert et al, 2016
AI::MXNet::Gluon::NN::SELU - Scaled Exponential Linear Unit (SELU)
Scaled Exponential Linear Unit (SELU) "Self-Normalizing Neural Networks", Klambauer et al, 2017 https://arxiv.org/abs/1706.02515
AI::MXNet::Gluon::NN::Swish - Swish Activation function
Swish Activation function https://arxiv.org/pdf/1710.05941.pdf Parameters ---------- beta : float swish(x) = x * sigmoid(beta*x)
To install AI::MXNet, copy and paste the appropriate command in to your terminal.
cpanm
cpanm AI::MXNet
CPAN shell
perl -MCPAN -e shell install AI::MXNet
For more information on module installation, please visit the detailed CPAN module installation guide.