test_mlx_eigh compares eigenvector signs, which are arbitrary

Description

tests/link/mlx/linalg/test_decomposition.py::test_mlx_eigh fails on main for both lower=True and lower=False, but the backend is not wrong: it compares raw eigenvector arrays, and the sign of an eigenvector is arbitrary.

The eigenvalues agree, and both results satisfy A v = w v; the eigenvectors differ by a per-column sign:

eigenvalues match: True
np  v[:,0]: [-0.94071188 -0.19066783 -0.28054756]
mlx v[:,0]: [ 0.9407117   0.19066775  0.28054756]
per-column sign ratio: [-1.  1. -1.]
residual |A v - w v|:  mlx 3.8e-07   numpy 7.8e-16

Suggested fix: normalise the sign before comparing — e.g. fix the sign of the largest-magnitude entry of each column, or compare |v| — rather than asserting on the raw array. The same consideration applies to test_mlx_svd.

Secondary observation from the residuals above: MLX computed this in float32 even though the input was float64. MLX has no float64 support, so the .astype(dtype=...) calls throughout pytensor/link/mlx/dispatch/linalg/ silently downcast a float64 graph. That may deserve its own issue — an explicit error or a documented warning would be safer than a silent precision loss in a Cholesky or a log-determinant.

Start with tests/link/mlx/linalg/test_decomposition.py::test_mlx_eigh and run the failing cases for both lower=True and lower=False. Update the eigenvector comparison so arbitrary per-column signs do not cause failure, then apply the same consideration to test_mlx_svd and run the relevant decomposition tests.