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There is a newer version: 4.23.0.17664

This rule raises an issue when the input_shape is specified in a tensorflow.keras.Model subclass.
Why is this an issue?
Keras provides a full-featured model class called tensorflow.keras.Model. It inherits from tensorflow.keras.layers.Layer,
so a Keras model can be used and nested in the same way as Keras layers. Keras models come with extra functionality that makes them easy to train,
evaluate, load, save, and even train on multiple machines.
As the tensorflow.keras.Model class inherits from the 'tensorflow.keras.layers' you do not need to specify input_shape in
a subclassed model; this argument will be ignored.
How to fix it
Do not specify input_shape in a tf.keras.Model subclasses
Code examples
Noncompliant code example
import tensorflow as tf

class MyModel(tf.keras.Model):
    def __init__(self):
        super(MyModel, self).__init__(input_shape=...)  # Noncompliant: this parameter will be ignored

Compliant solution
import tensorflow as tf

class MyModel(tf.keras.Model):
    def __init__(self):
        super(MyModel, self).__init__()  # OK

Resources
Documentation

   Tensorflow documentation - Keras models