lambda-spec | Adding λ to your Java Specs | Functional Programming library

This looks like a disastrous mix of NumPy and Keras. Let's look at the 2 main confusion points:

1. Once you are inside a Keras model, example Lambda layer, you are dealing with tensors and not NumPy arrays. Although convinient it would be, you can't use any NumPy operations, external libraries inside models. Having said that, tensor operators are very similar to arrays for good reason. Because it's your first layer, you can pre-process it in NumPy and then pass that into your model, this would work.

2. Why you get prints working? There are 2 main steps in Keras, Tensorflow: 1-> build the computation graph, 2-> actually run it. So you are building the graph and your operations get called yes, but they create symbolic tensors that have no value. So you can print the shape which can be determined when building the graph but not for example the values it holds.

Take away message, don't mix NumPy with Tensorflow inside computation graphs (models) and by all means print the shapes while building the graph to get an idea of what the graph looks like but you won't get anything more out of symbolic tensors at build time.