Fix spelling errors (#18773)

fix spelling errors

docs/source-app/workflows/mount_cloud_object_store.rst

@@ -115,7 +115,7 @@ See the Full Example
 
 .. note::
 
-    When running a Lighting App on your local machine, any :class:`~lightning.app.utilities.packaging.cloud_compute.CloudCompute`
+    When running a Lightning App on your local machine, any :class:`~lightning.app.utilities.packaging.cloud_compute.CloudCompute`
     configuration (including a :class:`~lightning.app.storage.mount.Mount`) is ignored at runtime. If you need access to
     these files on your local disk, you should download a copy of them to your machine.
 

docs/source-pytorch/cli/lightning_cli_advanced.rst

@@ -186,7 +186,7 @@ configuration files and automatic creation of objects, so you don't need to do i
 
 .. note::
 
-    Lighting automatically registers all subclasses of :class:`~lightning.pytorch.core.LightningModule`,
+    Lightning automatically registers all subclasses of :class:`~lightning.pytorch.core.LightningModule`,
     so the complete import path is not required for them and can be replaced by the class name.
 
 .. note::

docs/source-pytorch/expertise_levels.rst

@@ -175,7 +175,7 @@ Configure all aspects of Lightning for advanced usecases.
 
 .. displayitem::
    :header: Level 16: Own the training loop
-   :description: Learn all the ways of owning your raw PyTorch loops with Lighting.
+   :description: Learn all the ways of owning your raw PyTorch loops with Lightning.
    :col_css: col-md-6
    :button_link: levels/advanced_level_17.html
    :height: 150

docs/source-pytorch/levels/advanced.rst

@@ -31,7 +31,7 @@ Configure all aspects of Lightning for advanced usecases.
 
 .. displayitem::
    :header: Level 16: Own the training loop
-   :description: Learn all the ways of owning your raw PyTorch loops with Lighting.
+   :description: Learn all the ways of owning your raw PyTorch loops with Lightning.
    :col_css: col-md-6
    :button_link: advanced_level_17.html
    :height: 150

docs/source-pytorch/upgrade/sections/1_7_devel.rst

@@ -74,7 +74,7 @@
      - rely on Torch native AMP
      - `PR12312`_
 
-   * - used ``LightingModule.use_amp`` attribute
+   * - used ``LightningModule.use_amp`` attribute
      - rely on Torch native AMP
      - `PR12315`_
 

examples/fabric/reinforcement_learning/README.md

@@ -29,7 +29,7 @@ The main architecture is the following:
   <img src="https://pl-public-data.s3.amazonaws.com/assets_lightning/examples/fabric/reinforcement-learning/fabric_coupled.png">
 </p>
 
-where `N+1` processes (labelled *rank-0*, ..., *rank-N* in the figure above) will be spawned by Fabric/PyTorch, each of them running `M+1` independent copies of the environment (*Env-0*, ..., *Env-M*). Every rank has its own copy of the agent, represented by a [LightningModule](https://lightning.ai/docs/pytorch/stable/common/lightning_module.html)/[Pytorch Module](https://pytorch.org/docs/stable/generated/torch.nn.Module.html), which will be updated through distributed training.
+where `N+1` processes (labelled *rank-0*, ..., *rank-N* in the figure above) will be spawned by Fabric/PyTorch, each of them running `M+1` independent copies of the environment (*Env-0*, ..., *Env-M*). Every rank has its own copy of the agent, represented by a [LightningModule](https://lightning.ai/docs/pytorch/stable/common/lightning_module.html)/[PyTorch Module](https://pytorch.org/docs/stable/generated/torch.nn.Module.html), which will be updated through distributed training.
 
 ### Raw PyTorch:
 

src/lightning/pytorch/utilities/compile.py

@@ -46,7 +46,7 @@ def from_compiled(model: "torch._dynamo.OptimizedModule") -> "pl.LightningModule
     if not isinstance(orig_module, pl.LightningModule):
         _check_mixed_imports(model)
         raise ValueError(
-            f"`model` is expected to be a compiled LightingModule. Found a `{type(orig_module).__name__}` instead"
+            f"`model` is expected to be a compiled LightningModule. Found a `{type(orig_module).__name__}` instead"
         )
 
     orig_module._compiler_ctx = {