Dropout Layers

Regularization through stochastic neuron dropping during training. Includes standard dropout, spatial dropout variants (1D-3D), alpha dropout for self-normalizing networks, and fixed dropout with deterministic masking. Prevents overfitting by encouraging robust feature learning.

Dropout	A layer that stochastically ignores a subset of inputs each training step.
Dropout1d	Randomly zero out entire channels (a channel is a 1D feature map).
Dropout2d	Randomly zero out entire channels (a channel is a 2D feature map).
Dropout3d	Randomly zero out entire channels (a channel is a 3D feature map).
AlphaDropout	Applies Alpha Dropout over the input.
FeatureAlphaDropout	Randomly masks out entire channels with Alpha Dropout properties.
DropoutFixed	A dropout layer with a fixed dropout mask along the time axis.