tf.keras.layers.Dropout | TensorFlow v2.0.0 (original) (raw)
tf.keras.layers.Dropout
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Applies Dropout to the input.
Inherits From: Layer
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Compat aliases for migration
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tf.compat.v1.keras.layers.Dropout
tf.keras.layers.Dropout(
rate, noise_shape=None, seed=None, **kwargs
)
Dropout consists in randomly setting a fraction rate of input units to 0 at each update during training time, which helps prevent overfitting.
| Arguments | |
|---|---|
| rate | Float between 0 and 1. Fraction of the input units to drop. |
| noise_shape | 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(batch_size, timesteps, features) and you want the dropout mask to be the same for all timesteps, you can use noise_shape=(batch_size, 1, features). |
| seed | A Python integer to use as random seed. |
Call arguments:
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).
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Last updated 2020-10-01 UTC.