refactor: Use jax.numpy for JAX backend tensorlib.tolist

[matthewfeickert]

Description

Resolves #1137

In more recent releases of JAX the jax.numpy module is more filled out and it now supports jax.numpy.tolist, which was the only thing NumPy was used for previously.

NumPy must still be kept as JAX relies on numpy itself to convert from JAX DeviceArray to NumPy

pyhf/src/pyhf/tensor/jax_backend.py

Lines 568 to 593 in 2b2b281

	def to_numpy(self, tensor_in):
	"""
	Convert the JAX tensor to a :class:`numpy.ndarray`.
	Example:
	>>> import pyhf
	>>> pyhf.set_backend("jax")
	>>> tensor = pyhf.tensorlib.astensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
	>>> tensor
	DeviceArray([[1., 2., 3.],
	[4., 5., 6.]], dtype=float64)
	>>> numpy_ndarray = pyhf.tensorlib.to_numpy(tensor)
	>>> numpy_ndarray
	array([[1., 2., 3.],
	[4., 5., 6.]])
	>>> type(numpy_ndarray)
	<class 'numpy.ndarray'>
	Args:
	tensor_in (:obj:`tensor`): The input tensor object.
	Returns:
	:class:`numpy.ndarray`: The tensor converted to a NumPy ``ndarray``.
	"""
	return np.asarray(tensor_in, dtype=tensor_in.dtype)

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* Use jax.numpy.tolist to provide the tolist method for the JAX backend
   - Note that NumPy dependency can never be removed as JAX depends on
     NumPy for JAX to NumPy conversion

[matthewfeickert]

I was hoping to remove NumPy entirely, but turns out that's not possible with JAX as JAX needs NumPy to convert to NumPy.

[codecov]

Codecov Report

Merging #1138 (a786908) into master (2b2b281) will increase coverage by 0.04%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master    #1138      +/-   ##
==========================================
+ Coverage   98.06%   98.10%   +0.04%     
==========================================
  Files          64       64              
  Lines        4228     4228              
  Branches      587      587              
==========================================
+ Hits         4146     4148       +2     
+ Misses         49       46       -3     
- Partials       33       34       +1     

Flag	Coverage Δ
contrib	25.40% <0.00%> (ø)
doctest	61.21% <0.00%> (ø)
unittests	96.42% <100.00%> (+0.04%)	⬆️

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Impacted Files	Coverage Δ
src/pyhf/tensor/jax_backend.py	98.58% <100.00%> (+1.41%)	⬆️

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