Add pygrep-hooks in .pre-commit-config.yaml to catch common mistakes in .rst files

.pre-commit-config.yaml

@@ -30,7 +30,7 @@ repos:
         language: python
         additional_dependencies:
           - https://files.pythonhosted.org/packages/cc/20/ff623b09d963f88bfde16306a54e12ee5ea43e9b597108672ff3a408aad6/pathspec-0.12.1-py3-none-any.whl
-      
+
       - id: no-markdown-in-docs-source
         name: Prevent markdown files in docs/source directories
         entry: bash -c
@@ -39,6 +39,14 @@ repos:
         pass_filenames: false
         always_run: true
 
+  # Checking for common mistakes
+  - repo: https://github.com/pre-commit/pygrep-hooks
+    rev: "v1.10.0"
+    hooks:
+    - id: rst-backticks
+    - id: rst-directive-colons
+    - id: rst-inline-touching-normal
+
   - repo: https://github.com/PyCQA/bandit
     rev: 2d0b675b04c80ae42277e10500db06a0a37bae17  # frozen: 1.8.6
     hooks:

cuda_core/DESCRIPTION.rst

@@ -12,7 +12,7 @@ cuda-core: Pythonic access to CUDA core functionalities
 * `Examples <https://github.com/NVIDIA/cuda-python/tree/main/cuda_core/examples>`_
 * `Issue tracker <https://github.com/NVIDIA/cuda-python/issues/>`_
 
-`cuda.core` is currently under active development. Any feedbacks or suggestions are welcomed!
+``cuda.core`` is currently under active development. Feedback and suggestions are welcome!
 
 
 Installation
@@ -22,4 +22,4 @@ Installation
 
    pip install cuda-core[cu12]
 
-Please refer to the `installation instructions <https://nvidia.github.io/cuda-python/cuda-core/latest/install.html>`_ for different ways of installing `cuda.core`, including building from source.
+Please refer to the `installation instructions <https://nvidia.github.io/cuda-python/cuda-core/latest/install.html>`_ for different ways of installing ``cuda.core``, including building from source.

cuda_core/docs/source/interoperability.rst

@@ -38,7 +38,7 @@ exposing their own stream types.
 To address this issue, we propose the :attr:`~_stream.IsStreamT.__cuda_stream__` protocol
 (currently version 0) as follows: For any Python objects that are meant to be interpreted
 as a stream, they should add a ``__cuda_stream__`` *method* that returns a 2-tuple: The
-version number (``0``) and the address of ``cudaStream_t`` (both as Python `int`):
+version number (``0``) and the address of ``cudaStream_t`` (both as Python ``int``):
 
 .. code-block:: python
 

cuda_core/docs/source/release/0.1.0-notes.rst

@@ -20,5 +20,5 @@ Limitations
 
 - All APIs are currently *experimental* and subject to change without deprecation notice.
   Please kindly share your feedback with us so that we can make ``cuda.core`` better!
-- Source code release only; `pip`/`conda` support is coming in a future release
+- Source code release only; ``pip``/``conda`` support is coming in a future release
 - Windows TCC mode is `not yet supported <https://github.com/NVIDIA/cuda-python/issues/206>`_

cuda_core/docs/source/release/0.1.1-notes.rst

@@ -45,10 +45,10 @@ Limitations
 
 - All APIs are currently *experimental* and subject to change without deprecation notice.
   Please kindly share your feedback with us so that we can make ``cuda.core`` better!
-- Using ``cuda.core`` with NVRTC or nvJitLink installed from PyPI via `pip install` is currently
+- Using ``cuda.core`` with NVRTC or nvJitLink installed from PyPI via ``pip install`` is currently
   not supported. This will be fixed in a future release.
 - Some :class:`~LinkerOptions` are only available when using a modern version of CUDA. When using CUDA <12,
   the backend is the cuLink API which supports only a subset of the options that nvjitlink does.
   Further, some options aren't available on CUDA versions <12.6.
 - To use ``cuda.core`` with Python 3.13, it currently requires building ``cuda-python`` from source
-  prior to `pip install`. This extra step will be fixed soon.
+  prior to ``pip install``. This extra step will be fixed soon.

cuda_core/docs/source/release/0.3.0-notes.rst

@@ -32,7 +32,7 @@ New features
 
 - :class:`~_module.Kernel` adds :attr:`~_module.Kernel.num_arguments` and :attr:`~_module.Kernel.arguments_info` for introspection of kernel arguments. (#612)
 - Add pythonic access to kernel occupancy calculation functions via :attr:`Kernel.occupancy`. (#648)
-- Support launching cooperative kernels by setting :attr:`LaunchConfig.cooperative_launch` to `True`.
+- Support launching cooperative kernels by setting :attr:`LaunchConfig.cooperative_launch` to ``True``.
 - A name can be assigned to :class:`ObjectCode` instances generated by both :class:`Program` and :class:`Linker` through their respective options.
 - Expose :class:`Buffer`, :class:`DeviceMemoryResource`, :class:`LegacyPinnedMemoryResource`, and :class:`MemoryResource` to the top namespace.
    - Before this release, the internal :class:`Buffer` class had an ``__init__()`` constructor. To align with the design of cuda.core objects,

cuda_core/docs/source/release/0.X.Y-notes.rst

@@ -19,7 +19,7 @@ Breaking Changes
 ----------------
 
 - **LaunchConfig grid parameter interpretation**: When :attr:`LaunchConfig.cluster` is specified, the :attr:`LaunchConfig.grid` parameter now correctly represents the number of clusters instead of blocks. Previously, the grid parameter was incorrectly interpreted as blocks, causing a mismatch with the expected C++ behavior. This change ensures that ``LaunchConfig(grid=4, cluster=2, block=32)`` correctly produces 4 clusters × 2 blocks/cluster = 8 total blocks, matching the C++ equivalent ``cudax::make_hierarchy(cudax::grid_dims(4), cudax::cluster_dims(2), cudax::block_dims(32))``.
-- When :class:`Buffer` is closed, :attr:`Buffer.handle` is now set to `None`. It was previously set to ``0`` by accident.
+- When :class:`Buffer` is closed, :attr:`Buffer.handle` is now set to ``None``. It was previously set to ``0`` by accident.
 
 
 New features

cuda_python/DESCRIPTION.rst

@@ -10,22 +10,22 @@ CUDA Python is the home for accessing NVIDIA's CUDA platform from Python. It con
 * `cuda.core <https://nvidia.github.io/cuda-python/cuda-core/latest>`_: Pythonic access to CUDA Runtime and other core functionalities
 * `cuda.bindings <https://nvidia.github.io/cuda-python/cuda-bindings/latest>`_: Low-level Python bindings to CUDA C APIs
 * `cuda.cooperative <https://nvidia.github.io/cccl/python/cooperative>`_: A Python package providing CCCL's reusable block-wide and warp-wide *device* primitives for use within Numba CUDA kernels
-* `cuda.parallel <https://nvidia.github.io/cccl/python/parallel>`_: A Python package for easy access to CCCL's highly efficient and customizable parallel algorithms, like `sort`, `scan`, `reduce`, `transform`, etc, that are callable on the *host*
+* `cuda.parallel <https://nvidia.github.io/cccl/python/parallel>`_: A Python package for easy access to CCCL's highly efficient and customizable parallel algorithms, like ``sort``, ``scan``, ``reduce``, ``transform``, etc, that are callable on the *host*
 * `numba.cuda <https://nvidia.github.io/numba-cuda/>`_: Numba's target for CUDA GPU programming by directly compiling a restricted subset of Python code into CUDA kernels and device functions following the CUDA execution model.
 
 For access to NVIDIA CPU & GPU Math Libraries, please refer to `nvmath-python <https://docs.nvidia.com/cuda/nvmath-python/latest>`_.
 
-CUDA Python is currently undergoing an overhaul to improve existing and bring up new components. All of the previously available functionalities from the `cuda-python` package will continue to be available, please refer to the `cuda.bindings <https://nvidia.github.io/cuda-python/cuda-bindings/latest>`_ documentation for installation guide and further detail.
+CUDA Python is currently undergoing an overhaul to improve existing and bring up new components. All of the previously available functionalities from the ``cuda-python`` package will continue to be available, please refer to the `cuda.bindings <https://nvidia.github.io/cuda-python/cuda-bindings/latest>`_ documentation for installation guide and further detail.
 
 cuda-python as a metapackage
 ============================
 
-`cuda-python` is now a metapackage that contains a collection of subpackages. Each subpackage is versioned independently, allowing installation of each component as needed.
+``cuda-python`` is now a metapackage that contains a collection of subpackages. Each subpackage is versioned independently, allowing installation of each component as needed.
 
 Subpackage: cuda.core
 ---------------------
 
-The `cuda.core` package offers idiomatic, pythonic access to CUDA Runtime and other functionalities.
+The ``cuda.core`` package offers idiomatic, pythonic access to CUDA Runtime and other functionalities.
 
 The goals are to
 
@@ -38,7 +38,7 @@ The goals are to
 Subpackage: cuda.bindings
 -------------------------
 
-The `cuda.bindings` package is a standard set of low-level interfaces, providing full coverage of and access to the CUDA host APIs from Python.
+The ``cuda.bindings`` package is a standard set of low-level interfaces, providing full coverage of and access to the CUDA host APIs from Python.
 
 The list of available interfaces are: