* Add __index__ to array_api and update __int__, __bool__, and __float__

The spec specifies that they should only work on arrays with corresponding
dtypes. __index__ is new in the spec since the initial PR, and works
identically to np.array.__index__.

* Add the to_device method to the array_api

This method is new since #18585. It does nothing in NumPy since NumPy does not
support non-CPU devices.

* Update transpose methods in the array_api

transpose() was renamed to matrix_transpose() and now operates on stacks of
matrices. A function to permute dimensions will be added once it is finalized
in the spec. The attribute mT was added and the T attribute was updated to
only operate on 2-dimensional arrays as per the spec.

* Restrict input dtypes in the array API statistical functions

* Add the dtype parameter to the array API sum() and prod()

* Add the function permute_dims() to the array_api namespace

permute_dims() is the replacement for transpose(), which was split into
permute_dims() and matrix_transpose().

* Add tril and triu to the array API namespace

* Fix the array_api Array.__repr__ to indent the array properly

* Make the Device type in the array_api just accept the string "cpu"

I've omitted a few changes from black that messed up the readability of some
complicated if statements that were organized logically line-by-line, and some
changes that use unnecessary operator spacing.

asarray() is already called in Array._new.

Instead of the leading underscore, the experimentalness of the module will be
indicated by omitting a warning on import. That we, we do not have to change
the API from underscore to no underscore when the module is no longer
experimental.