|TensorFlow 2 version||View source on GitHub|
Applies Dropout to the input.
Compat aliases for migration
See Migration guide for more details.
tf.keras.layers.Dropout( rate, noise_shape=None, seed=None, **kwargs )
Dropout consists in randomly setting
rate of input units to 0 at each update during training time,
which helps prevent overfitting.
||Float between 0 and 1. Fraction of the input units to drop.|
1D integer tensor representing the shape of the
binary dropout mask that will be multiplied with the input.
For instance, if your inputs have shape
||A Python integer to use as random seed.|
inputs: Input tensor (of any rank).
training: Python boolean indicating whether the layer should behave in training mode (adding dropout) or in inference mode (doing nothing).