tf.keras.layers激活函数

In TensorFlow's Keras API, the `tanh` activation function can be applied to a layer using the `tf.keras.layers.Activation` layer or by specifying it directly within the desired layer.

Here's an example of using the `tanh` activation function in a Keras model:

import tensorflow as tf

model = tf.keras.models.Sequential([
    tf.keras.layers.Dense(64, activation='tanh'),
    ...
])

In this example, a `Dense` layer with 64 units is used, and the `tanh` activation function is specified as the activation argument. This will apply the hyperbolic tangent activation function element-wise to the output of this layer.

Alternatively, you can use the `tf.keras.layers.Activation` layer to apply the `tanh` activation function as follows:

import tensorflow as tf

model = tf.keras.models.Sequential([
    tf.keras.layers.Dense(64),
    tf.keras.layers.Activation('tanh'),
    ...
])

Both approaches will achieve the same result of applying the `tanh` activation function to the output of the layer.