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Add `cho_factor` and `cho_solve` to `dpnp.scipy.linalg` (#3116)

Add SciPy-compatible `dpnp.scipy.linalg.cho_factor` and
`dpnp.scipy.linalg.cho_solve`, including batched input as in SciPy 1.18
(#3096).

### Implementation

- `cho_factor` uses the existing `potrf` and `potrf_batch` bindings.
Only the referenced triangle is copied, in one pass, into a zeroed
C-order buffer, which matches the SciPy 1.18 output. With
`overwrite_a=True`, a 2-D, writable input of the result dtype that is C-
or F-contiguous is factored in place. As in SciPy, a 0-D or 1-D input is
viewed as a matrix.
- `cho_solve` uses a new LAPACK `potrs` binding for a 2-D factor. For a
batch of factors it calls a new BLAS `trsm_batch` binding twice, since
oneMKL `potrs_batch` is much slower (MKLD-20341).
- A single factor (2-D, or with size-1 batch dimensions) is not
broadcast to a batched right-hand side: the batch is folded into the
columns of one `potrs` call. For a real type on GPU with more than 16
folded columns and a batch of at most 32, the factor is shared by the
batch in `trsm_batch` (stride 0) instead, because double-precision
`trsm` on Xe GPUs slows down by up to 3.6x above 16 columns.
- Batch dimensions broadcast as in `lu_solve`, and a broadcast
right-hand side is copied without being materialized first.
- `lower` can also be the batch-shaped array SciPy 1.18 returns, or a
sequence, if all its values are equal. An empty `lower` raises
`ValueError`, as in SciPy, except in `cho_solve` for a zero-size batch
of factors.
- With `overwrite_b=True`, `cho_solve` solves in a copy when `b`
overlaps the factor (SciPy overwrites the factor).
- With `check_finite=True`, both finiteness checks of `cho_solve` are
submitted before the first host sync.

### Differences from SciPy

Documented in the docstrings and covered by tests:
- `cho_factor` returns `lower` as a Python bool; SciPy 1.18 returns an
array tiled to the batch shape.
- `cho_solve` supports a zero-size batch; SciPy raises.
- `low... (continued)

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