predict() cloned the whole model on every call and then used
model.predict(). When predict() runs once per solution inside a fitness
function, this is slow. It now sets the solution as the model weights,
restores the original weights at the end, and calls the model directly
when no batching is asked for. The output is the same and it runs much
faster. model.predict() is still used when batch_size or steps is given.