Enable sphinx-lint pre-commit hook

.pre-commit-config.yaml

@@ -21,6 +21,11 @@ repos:
               pytensor/tensor/variable\.py|
           )$
       - id: check-merge-conflict
+  - repo: https://github.com/sphinx-contrib/sphinx-lint                                  
+    rev: v1.0.0                                                                          
+    hooks:                                                                               
+    - id: sphinx-lint 
+      args: ["."]
   - repo: https://github.com/astral-sh/ruff-pre-commit
     rev: v0.6.5
     hooks:

doc/extending/creating_a_c_op.rst

@@ -152,7 +152,7 @@ This distance between consecutive elements of an array over a given dimension,
 is called the stride of that dimension.
 
 
-Accessing NumPy :class`ndarray`\s' data and properties
+Accessing NumPy :class:`ndarray`'s data and properties
 ------------------------------------------------------
 
 The following macros serve to access various attributes of NumPy :class:`ndarray`\s.

doc/extending/creating_a_numba_jax_op.rst

@@ -60,7 +60,7 @@ could also have any data type (e.g. floats, ints), so our implementation
 must be able to handle all the possible data types.
 
 It also tells us that there's only one return value, that it has a data type
-determined by :meth:`x.type()` i.e., the data type of the original tensor.
+determined by :meth:`x.type` i.e., the data type of the original tensor.
 This implies that the result is necessarily a matrix.
 
 Some class may have a more complex behavior. For example, the :class:`CumOp`\ :class:`Op`

doc/extending/type.rst

@@ -333,7 +333,7 @@ returns eitehr a new transferred variable (which can be the same as
 the input if no transfer is necessary) or returns None if the transfer
 can't be done.
 
-Then register that function by calling :func:`register_transfer()`
+Then register that function by calling :func:`register_transfer`
 with it as argument.
 
 An example

doc/library/compile/io.rst

@@ -36,7 +36,7 @@ The ``inputs`` argument to ``pytensor.function`` is a list, containing the ``Var
       ``self.<name>``. The default value is ``None``.
 
       ``value``: literal or ``Container``. The initial/default value for this
-        input. If update is`` None``, this input acts just like
+        input. If update is ``None``, this input acts just like
         an argument with a default value in Python. If update is not ``None``,
         changes to this
         value will "stick around", whether due to an update or a user's

doc/library/config.rst

@@ -226,7 +226,7 @@ import ``pytensor`` and print the config variable, as in:
     in the future.
 
     The ``'numpy+floatX'`` setting attempts to mimic NumPy casting rules,
-    although it prefers to use ``float32` `numbers instead of ``float64`` when
+    although it prefers to use ``float32`` numbers instead of ``float64`` when
     ``config.floatX`` is set to ``'float32'`` and the associated data is not
     explicitly typed as ``float64`` (e.g. regular Python floats).  Note that
     ``'numpy+floatX'`` is not currently behaving exactly as planned (it is a

doc/library/tensor/basic.rst

@@ -1064,7 +1064,7 @@ Reductions
         inner summation. This will not necessarily be the dtype of the
         output (in particular if it is a discrete (int/uint) dtype, the
         output will be in a float type).  If None, then we use the same
-        rules as :func:`sum()`.
+        rules as :func:`sum`.
     :Returns: mean value of *x* along *axis*
 
     `axis` can be: