BUG: torch: accept Python scalars in binary elementwise functions

[raashish1601]

Closes #271 (also covers #410).

torch.maximum, minimum, atan2, hypot, logaddexp, nextafter and logical_and/or/xor reject Python scalars, and equal, not_equal, less, less_equal, greater, greater_equal and copysign reject a scalar as the first argument. The 2024.12 standard allows a scalar in either position.

Following the idea in the issue, _two_arg now takes scalar_x1 / scalar_x2 flags. When set, a Python scalar in that position is converted to a 0-D tensor with result_type(scalar, other) on the other argument's device. The flags are only set where torch rejects the scalar, so calls that already work (e.g. add(x, 1)) take the same path as before. nextafter and the logical functions are now wrapped too and added to __all__.

from array_api_compat import torch as xp
xp.maximum(xp.asarray([1., 2.]), 1.5)   # was TypeError
xp.less(1.5, xp.asarray([1, 2]))        # was TypeError

Testing: removed the matching test_binary_with_scalars_* entries from torch-xfails.txt; those 28 tests pass locally against array-api-tests, along with the rest of test_operators_and_elementwise_functions.py and test_signatures.py. Added tests to tests/test_torch.py; they fail on main and pass with this change. ruff check . passes.