Here we pull the outputs from distilbert and use a MaxPooling layer to convert the tensor from 3D to 2D — alternatively,

But before we move forward, notice the replaceMethod function, that’s where all the magic happens. That’s where the new function is created and where we decide when to call our aspect and what to do with its returned value.

If you are wanting to train the transformer parameters further, the final line is not necessary! We choose not to as BERT is already an incredibly well built and fine-tuned model. It would take a very long time to train, so for the likely minuscule performance increase — there’s little justification.

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Pointcut (Where): They reference the place in your target code where you want to inject the aspect. In theory, you could pinpoint anywhere in your target code when you want your code to be executed. In practice, this is not that realistic, but you can potentially specify things such as: “all methods of my object”, or “only this particular method”, or we could even get fancy with something like “all methods starting with get_”.

Re-use aspects across projects. You can think of aspects as components, small and decoupled pieces of code that can run anywhere. If you write your aspects correctly, you can share them across different projects with ease.

Just because I’m a visual learner, I think showing a basic example of how you’d go about implementing a sort of inject method to add AOP-based behavior would come a long way.

In order to formalize a bit the definition above, let’s take the example of the logger and cover these 3 concepts about AOP that are going to help you out if you decide to look further into this paradigm:

With this explanation, you could argue that creating an AOP-based library to add logging logic to existing OOP-based business logic (for example) is relatively easy. All you’d have to do is replace the existing matching methods of the target object, with a custom function that would add the aspect’s logic at the right time and then call the original method.

Nothing too fancy, a basic object with 3 methods. We want to inject two aspects that are generic to all of them. One to log the attributes received and one to analyze their returned value and log their type. Two aspects, two lines of code (instead of the six we would need).

Flexible logic. The logic around your implementation of the advice and pointcuts can give you a lot of flexibility when it comes to injecting your aspects. This in turn can help to dynamically turn on and off different aspects (pun definitely intended) of your logic.

However, it does provide you with the ability to do whatever you want, and that, coupled with a lack of understanding of good programming practices, can cause a really big mess.

Great way to encapsulate cross-cutting concerns. I’m a big fan of encapsulation because it means you get easier to read and easier to maintain code that can be re-used all across your project.

Advice (When): When do you want the aspect to run? They specify some common moments when you want your aspect’s code to be executed, such as “before”, “after”, “around”, “whenThrowing”, and the like. They, in turn, refer to the moment in time-related to the execution of the code. For the ones referring to after the code is executed, the aspects will intercept the returned value and potentially overwrite it if they needed to.

And if you think about it, they’re kind of right, AOP gives you a lot of power to add unrelated behavior into existing methods or even replace their entire logic. Of course, that might not be exactly why this pattern was introduced, and it’s certainly not the intention of the example I provided above.

Aspects (What): These are the “aspects” or behavior you’re looking to inject into your target code. In our context (JavaScript), these will be functions that encapsulate the behavior you’re looking to add.