Applies Dropout to the input.
Compat aliases for migration
See Migration guide for more details.
tf.layers.Dropout( rate=0.5, noise_shape=None, seed=None, name=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. The units that are kept are scaled by
1 / (1 - rate), so that their sum is unchanged at training time and inference time.
| || The dropout rate, between 0 and 1. E.g. |
| || 1D tensor of type |
| || A Python integer. Used to create random seeds. See |
| ||The name of the layer (string).|
| ||DEPRECATED FUNCTION|
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Code samples licensed under the Apache 2.0 License.