Applies Dropout to the input.

Inherits From: Layer

Used in the notebooks

Used in the guide Used in the tutorials

The Dropout layer randomly sets input units to 0 with a frequency of rate at each step during training time, which helps prevent overfitting. Inputs not set to 0 are scaled up by 1/(1 - rate) such that the sum over all inputs is unchange