DRAFT: Support non-numpy array backends

[ColmTalbot]

I've been working on this PR on and off for a few months, it isn't ready yet, but I wanted to share it in case other people had early opinions.

The goal is to make it easier to interface with models/samplers implemented in e.g., JAX, that support GPU/TPU acceleration and JIT compilation.

The general guiding principles are:

• when possible maintain existing behaviour with numpy/builtin arguments
• work introspectively so users don't need to specify the target backend, but use input types
• write as little backend specific code as possible, mostly through using the array-api specification and scipy interoperability

The primary changes so far are:

• making most priors backend independent, there are a few holdouts where the underlying scipy functionality isn't compatible yet
• core likelihoods mostly work with data from any backend
• GW likelihoods work with any backend supported by the source function
• the GW detector objects don't work via introspection, they need to be manually set
• GW geometry (currently in bilby_cython) is handled via multiple-dispatch and added back into bilby

Changed behaviour:

• prior sampling/rescale shapes - related to Conserve rescale shape #863
• some priors won't return floats on float input

Remaining issues:

• Saving/loading nun-numpy arrays in result files may not work
• I added some additional parameter conversions that I will remove
• the bilby.gw.jaxstuff file should be removed and relevant functionality be moved elsewhere, it's currently just used for testing
• the ROQ likelihood hasn't been ported
• add more testing with JAX
• translate some of the hyperparameter functionality, c.f., GWPopulation