Add Pedalboard to benchmarks.

[psobot]

(Note: I haven't tested this code locally yet.)

[faroit]

@psobot sorry for being slow. I will have a look this weekend. I thought about making some major changes to better spot the differences... Maybe you have some ideas on the following points?

• For now I test each lib on each framework. In practice not all combinations really make sense. I wonder if its better to just everything on numpy and only use torch and tf for the libs that natively output the respective tensor formats
• all tests are single processed and some libs are known to not work well with multithreading or multiprocessing. Thats why i set all workers in torch and tf to 0. For better real world performance benchmarks, it probably better to evaluate parallelization
• all tests are measuring loading + decoding speed. In ML practice, we can decouple this with some libraries. So, I wonder if we should test decoding speed separately if possible.