Unable to save model checkpoint on Tensorflow Recommender's subclass model

Hi,
I have used Tensorflow Recommender's tutorial of Movielens to train the recommender model. But when I try to use callback mdel checkpoint in model.fit(). It raises following error:

the input shape is not available or because the forward pass of the model is not defined.To define a forward pass, please override `Model.call()`. To specify an input shape, either call `build(input_shape)` directly, or call the model on actual data using `Model()`, `Model.fit()`, or `Model.predict()`. If you have a custom training step, please make sure to invoke the forward pass in train step through `Model.__call__`, i.e. `model(inputs)`, as opposed to `model.call()`.

Also, I am unable to model.summary() Please help me to resolve the issue. What are the changes I need to do in the subclass models to save best model checkpoint?

Here is the tutorial link that I am using for training: https://www.tensorflow.org/recommenders/examples/deep_recommenders

Start with the TensorFlow Recommenders deep recommenders tutorial linked in the issue and reproduce the failure using model.fit(), ModelCheckpoint, and model.summary() on the subclass model. Investigate the reported input-shape and forward-pass error; done means identifying the required model setup and confirming that summary generation and best-checkpoint saving work.