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Optimizer that implements the NAdam algorithm.
Inherits From: Optimizer
tf.keras.optimizers.Nadam( learning_rate=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-07, name='Nadam', **kwargs )
Much like Adam is essentially RMSprop with momentum, Nadam is Adam with Nesterov momentum.
Args | |
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learning_rate | A Tensor or a floating point value. The learning rate. |
beta_1 | A float value or a constant float tensor. The exponential decay rate for the 1st moment estimates. |
beta_2 | A float value or a constant float tensor. The exponential decay rate for the exponentially weighted infinity norm. |
epsilon | A small constant for numerical stability. |
name | Optional name for the operations created when applying gradients. Defaults to "Nadam" . |
**kwargs | Keyword arguments. Allowed to be one of "clipnorm" or "clipvalue" . "clipnorm" (float) clips gradients by norm; "clipvalue" (float) clips gradients by value. |
Raises | |
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ValueError | in case of any invalid argument. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/optimizers/Nadam