Module-level Op instances break LSP signatures, Sphinx docs, and source links for expm, det, inv, lstsq

Problem

Several public API symbols in pytensor.tensor.linalg are bare Op instances (or Blockwise(Op()) instances), not functions with real signatures. This causes three issues:

1. LSPs (pyright, mypy, jedi) can only show the generic Op.__call__ signature (*inputs, name=None, return_list=False, **kwargs) — no parameter names, types, or docstrings.
2. Sphinx autodoc renders the same generic signature and pulls the docstring from Blockwise instead of the actual operation.
3. "Source" links in the docs point to pytensor/tensor/blockwise.py rather than the operation's actual home (e.g. products.py, summary.py, inverse.py).

Affected symbols:

Documentation examples:

• https://pytensor.readthedocs.io/en/latest/library/tensor/linalg.html#pytensor.tensor.linalg.expm — shows expm(*inputs, name=None, return_list=False, **kwargs) with the Blockwise docstring, source link goes to blockwise.py
• https://pytensor.readthedocs.io/en/latest/library/tensor/linalg.html#pytensor.tensor.linalg.det — same issue
• https://pytensor.readthedocs.io/en/latest/library/tensor/linalg.html#pytensor.tensor.linalg.inv — same issue

Compare with properly wrapped functions like solve, cholesky, svd, norm, tensorsolve which all show their actual parameter signatures, domain-specific docstrings, and correct source links.

Possible approaches

A) Function wrapper — The codebase already uses this pattern in tensor/math.py:

_matmul = Blockwise(_dot, name="Matmul")      # private Op instance

def matmul(x1, x2, dtype=None):                 # public function with real signature
    """Compute the matrix product of two tensor variables.
    ...
    """
    return _matmul(x1, x2)

For each affected symbol, this would mean keeping the Op instance private and exposing a wrapper function with proper annotations and docstring.

B) .pyi stub files — Add products.pyi, summary.pyi, etc. with typed signatures. Helps LSPs but doesn't fix Sphinx autodoc, and adds maintenance burden keeping stubs in sync.

C) typing.cast with a Callable annotation — Helps LSPs but doesn't fix Sphinx.

D) Instance __doc__ — e.g. a docstring after the assignment. Fixes the rendered description in Sphinx but not the signature, source link, or LSP behavior.

Start by comparing the public wrappers in tensor/math.py with the affected definitions in products.py, summary.py, inverse.py, and solvers/lstsq.py. Inspect how the linalg API is rendered by Sphinx and how its source links are generated. Done means the affected symbols expose operation-specific signatures and docstrings to LSPs and Sphinx, with source links pointing to their defining files.