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Fix spelling errors (#18773)
fix spelling errors (cherry picked from commit e0ba4d4)
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docs/source-app/workflows/mount_cloud_object_store.rst

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

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

docs/source-pytorch/expertise_levels.rst

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

docs/source-pytorch/levels/advanced.rst

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

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

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- rely on Torch native AMP
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- `PR12312`_
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* - used ``LightingModule.use_amp`` attribute
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* - used ``LightningModule.use_amp`` attribute
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- rely on Torch native AMP
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- `PR12315`_
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examples/fabric/reinforcement_learning/README.md

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@@ -29,7 +29,7 @@ The main architecture is the following:
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<img src="https://pl-public-data.s3.amazonaws.com/assets_lightning/examples/fabric/reinforcement-learning/fabric_coupled.png">
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</p>
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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.
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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.
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### Raw PyTorch:
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src/lightning/pytorch/utilities/compile.py

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if not isinstance(orig_module, pl.LightningModule):
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_check_mixed_imports(model)
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raise ValueError(
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f"`model` is expected to be a compiled LightingModule. Found a `{type(orig_module).__name__}` instead"
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f"`model` is expected to be a compiled LightningModule. Found a `{type(orig_module).__name__}` instead"
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)
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orig_module._compiler_ctx = {

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