tf.keras.layers.AlphaDropout | TensorFlow v2.0.0 (original) (raw)
tf.keras.layers.AlphaDropout
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Applies Alpha Dropout to the input.
Inherits From: Layer
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Compat aliases for migration
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tf.compat.v1.keras.layers.AlphaDropout
tf.keras.layers.AlphaDropout(
rate, noise_shape=None, seed=None, **kwargs
)
Alpha Dropout is a Dropout that keeps mean and variance of inputs to their original values, in order to ensure the self-normalizing property even after this dropout. Alpha Dropout fits well to Scaled Exponential Linear Units by randomly setting activations to the negative saturation value.
| Arguments | |
|---|---|
| rate | float, drop probability (as with Dropout). The multiplicative noise will have standard deviation sqrt(rate / (1 - rate)). |
| 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).
Input shape:
Arbitrary. Use the keyword argument input_shape(tuple of integers, does not include the samples axis) when using this layer as the first layer in a model.
Output shape:
Same shape as input.
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Last updated 2020-10-01 UTC.