How to use keras layers in custom keras layer

Question

I am trying to write my own keras layer. In this layer, I want to use some other keras layers. Is there any way to do something like this:

class MyDenseLayer(tf.         


        

Answer 1

This works for me and is clean, concise, and readable.

import tensorflow as tf


class MyDense(tf.keras.layers.Layer):
    def __init__(self, **kwargs):
        super(MyDense, self).__init__(kwargs)
        self.dense = tf.keras.layers.Dense(2, tf.keras.activations.relu)

    def call(self, inputs, training=None):
        return self.dense(inputs)


inputs = tf.keras.Input(shape=10)
outputs = MyDense(trainable=True)(inputs)
model = tf.keras.Model(inputs=inputs, outputs=outputs, name='test')
model.compile(loss=tf.keras.losses.MeanSquaredError())
model.summary()

Output:

Model: "test"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_1 (InputLayer)         [(None, 10)]              0         
_________________________________________________________________
my_dense (MyDense)           (None, 2)                 22        
=================================================================
Total params: 22
Trainable params: 22
Non-trainable params: 0
_________________________________________________________________

Note that trainable=True is needed. I have posted a questions about it here.