Refactor PL examples to examples/pytorch/ (#16925)

Co-authored-by: awaelchli <[email protected]>

Author: aniketmaurya

.azure/gpu-tests-pytorch.yml

@@ -23,8 +23,8 @@ pr:
       - ".actions/**"
       - ".azure/gpu-tests-pytorch.yml"
       - "examples/run_pl_examples.sh"
-      - "examples/pl_basics/backbone_image_classifier.py"
-      - "examples/pl_basics/autoencoder.py"
+      - "examples/pytorch/basics/backbone_image_classifier.py"
+      - "examples/pytorch/basics/autoencoder.py"
       - "requirements/pytorch/**"
       - "src/lightning/__about__.py"
       - "src/lightning/__init__.py"
@@ -158,7 +158,7 @@ jobs:
         python .actions/assistant.py copy_replace_imports --source_dir="./tests/tests_pytorch" \
           --source_import="lightning.fabric,lightning.pytorch" \
           --target_import="lightning_fabric,pytorch_lightning"
-        python .actions/assistant.py copy_replace_imports --source_dir="./examples/pl_basics" \
+        python .actions/assistant.py copy_replace_imports --source_dir="./examples/pytorch/basics" \
           --source_import="lightning.fabric,lightning.pytorch" \
           --target_import="lightning_fabric,pytorch_lightning"
       condition: eq(variables['PACKAGE_NAME'], 'pytorch')

.azure/hpu-tests.yml

@@ -19,7 +19,7 @@ pr:
     include:
       - ".actions/**"
       - ".azure/hpu-tests.yml"
-      - "examples/pl_hpu/mnist_sample.py"
+      - "examples/pytorch/hpu/mnist_sample.py"
       - "requirements/fabric/**"
       - "src/lightning/__about__.py"
       - "src/lightning/__init__.py"
@@ -92,7 +92,7 @@ jobs:
         python .actions/assistant.py copy_replace_imports --source_dir="./tests/tests_pytorch" \
           --source_import="lightning.fabric,lightning.pytorch" \
           --target_import="lightning_fabric,pytorch_lightning"
-        python .actions/assistant.py copy_replace_imports --source_dir="./examples/pl_hpu" \
+        python .actions/assistant.py copy_replace_imports --source_dir="./examples/pytorch/hpu" \
           --source_import="lightning.fabric,lightning.pytorch" \
           --target_import="lightning_fabric,pytorch_lightning"
       displayName: 'Adjust tests & examples'
@@ -117,7 +117,7 @@ jobs:
 
     - bash: |
         export PYTHONPATH="${PYTHONPATH}:$(pwd)"
-        python "pl_hpu/mnist_sample.py"
+        python "pytorch/hpu/mnist_sample.py"
       workingDirectory: examples
       displayName: 'Testing: HPU examples'
 

.github/ISSUE_TEMPLATE/1_bug_report.yaml

@@ -35,7 +35,7 @@ body:
       label: How to reproduce the bug
       description: >
         Provide steps and example code here.
-        You can also paste a link to Google Colab (see our [Colab bug report template](https://colab.research.google.com/github/Lightning-AI/lightning/blob/master/examples/pl_bug_report/bug_report_model.ipynb)) or adapt this minimal [snippet](https://github.com/Lightning-AI/lightning/blob/master/examples/pl_bug_report/bug_report_model.py).
+        You can also paste a link to Google Colab (see our [Colab bug report template](https://colab.research.google.com/github/Lightning-AI/lightning/blob/master/examples/pytorch/bug_report/bug_report_model.ipynb)) or adapt this minimal [snippet](https://github.com/Lightning-AI/lightning/blob/master/examples/pytorch/bug_report/bug_report_model.py).
       placeholder: |
         ```python
         # Sample code to reproduce the problem

.github/checkgroup.yml

@@ -46,8 +46,8 @@ subprojects:
       # only the azure GPU workflow runs the examples
       # all examples don't need to be added because they aren't used in CI, but these are
       - "examples/run_pl_examples.sh"
-      - "examples/pl_basics/backbone_image_classifier.py"
-      - "examples/pl_basics/autoencoder.py"
+      - "examples/pytorch/basics/backbone_image_classifier.py"
+      - "examples/pytorch/basics/autoencoder.py"
       - "requirements/pytorch/**"
       - "src/lightning/__about__.py"
       - "src/lightning/__init__.py"
@@ -83,7 +83,7 @@ subprojects:
     paths:
       - ".actions/**"
       - ".azure/hpu-tests.yml"
-      - "examples/pl_hpu/mnist_sample.py"
+      - "examples/pytorch/hpu/mnist_sample.py"
       - "requirements/fabric/**"
       - "src/lightning/__about__.py"
       - "src/lightning/__init__.py"

docs/source-pytorch/accelerators/hpu_intermediate.rst

@@ -45,7 +45,7 @@ This enables advanced users to provide their own BF16 and FP32 operator list ins
         accelerator="hpu",
         devices=1,
         # Optional Habana mixed precision params to be set
-        # Checkout `examples/pl_hpu/ops_bf16_mnist.txt` for the format
+        # Checkout `examples/pytorch/hpu/ops_bf16_mnist.txt` for the format
         plugins=[
             HPUPrecisionPlugin(
                 precision=16,

docs/source-pytorch/accelerators/ipu_basic.rst

@@ -63,7 +63,7 @@ Known limitations
 
 Currently there are some known limitations that are being addressed in the near future to make the experience seamless when moving from different devices.
 
-Please see the `MNIST example <https://github.com/Lightning-AI/lightning/blob/master/examples/pl_ipu/mnist_sample.py>`__ which displays most of the limitations and how to overcome them till they are resolved.
+Please see the `MNIST example <https://github.com/Lightning-AI/lightning/blob/master/examples/pytorch/ipu/mnist_sample.py>`__ which displays most of the limitations and how to overcome them till they are resolved.
 
 * ``self.log`` is not supported in the ``training_step``, ``validation_step``, ``test_step`` or ``predict_step``. This is due to the step function being traced and sent to the IPU devices. We're actively working on fixing this.
 * Multiple optimizers are not supported. ``training_step`` only supports returning one loss from the ``training_step`` function as a result.

docs/source-pytorch/deploy/production_advanced.rst

@@ -73,4 +73,4 @@ In order to do so, your LightningModule needs to subclass the :class:`~lightning
 
 Below you can find an example of how the serving of a resnet18 can be validated.
 
-.. literalinclude:: ../../../examples/pl_servable_module/production.py
+.. literalinclude:: ../../../examples/pytorch/servable_module/production.py

examples/README.md

@@ -25,8 +25,8 @@ ______________________________________________________________________
 
 In this folder, we have 2 simple examples that showcase the power of the Lightning Trainer.
 
-- [Image Classifier](pl_basics/backbone_image_classifier.py) (trains arbitrary datasets with arbitrary backbones).
-- [Autoencoder](pl_basics/autoencoder.py)
+- [Image Classifier](pytorch/basics/backbone_image_classifier.py) (trains arbitrary datasets with arbitrary backbones).
+- [Autoencoder](pytorch/basics/autoencoder.py)
 
 ______________________________________________________________________
 

examples/pl_basics/README.md examples/pytorch/basics/README.md

@@ -26,11 +26,11 @@ args="
   --optimizer=Adam
 "
 
-python "${dir_path}/pl_basics/backbone_image_classifier.py" ${args} "$@"
-python "${dir_path}/pl_basics/autoencoder.py" ${args} "$@"
+python "${dir_path}/pytorch/basics/backbone_image_classifier.py" ${args} "$@"
+python "${dir_path}/pytorch/basics/autoencoder.py" ${args} "$@"
 
 
 # test that a user can manually launch individual processes
 args="--trainer.devices 2 --trainer.strategy ddp --trainer.max_epochs=1 --trainer.limit_train_batches=1 --trainer.limit_val_batches=1 --trainer.limit_test_batches=1"
-MASTER_ADDR="localhost" MASTER_PORT=1234 LOCAL_RANK=1 python "${dir_path}/pl_basics/autoencoder.py" ${args} &
-MASTER_ADDR="localhost" MASTER_PORT=1234 LOCAL_RANK=0 python "${dir_path}/pl_basics/autoencoder.py" ${args}
+MASTER_ADDR="localhost" MASTER_PORT=1234 LOCAL_RANK=1 python "${dir_path}/pytorch/basics/autoencoder.py" ${args} &
+MASTER_ADDR="localhost" MASTER_PORT=1234 LOCAL_RANK=0 python "${dir_path}/pytorch/basics/autoencoder.py" ${args}