Apply multiplicative 1-centered Gaussian noise.
Inherits From: Layer, Operation
tf.keras.layers.GaussianDropout(
rate, seed=None, **kwargs
)
As it is a regularization layer, it is only active at training time.
| Args | |
|---|---|
rate | Float, drop probability (as with Dropout). The multiplicative noise will have standard deviation sqrt(rate / (1 - rate)). |
seed | Integer, optional random seed to enable deterministic behavior. |
| 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). |
| Attributes | |
|---|---|
input | Retrieves the input tensor(s) of a symbolic operation. Only returns the tensor(s) corresponding to the first time the operation was called. |
output | Retrieves the output tensor(s) of a layer. Only returns the tensor(s) corresponding to the first time the operation was called. |
from_config@classmethod
from_config(
config
)
Creates a layer from its config.
This method is the reverse of get_config, capable of instantiating the same layer from the config dictionary. It does not handle layer connectivity (handled by Network), nor weights (handled by set_weights).
| Args | |
|---|---|
config | A Python dictionary, typically the output of get_config. |
| Returns | |
|---|---|
| A layer instance. |
symbolic_callsymbolic_call(
*args, **kwargs
)
© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/layers/GaussianDropout