Merge branch 'master' into ci/upgrade-eager

Author: Borda

.actions/pull_legacy_checkpoints.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+# Run this script from the project root.
+URL="https://pl-public-data.s3.amazonaws.com/legacy/checkpoints.zip"
+mkdir -p legacy
+# wget is simpler but does not work on Windows
+python -c "from urllib.request import urlretrieve; urlretrieve('$URL', 'legacy/checkpoints.zip')"
+ls -l legacy/
+unzip -o legacy/checkpoints.zip -d legacy/
+ls -l legacy/checkpoints/

.azure-pipelines/gpu-tests.yml

@@ -69,10 +69,7 @@ jobs:
         python requirements/check-avail-extras.py
       displayName: 'Env details'
 
-    - bash: |
-        wget https://pl-public-data.s3.amazonaws.com/legacy/checkpoints.zip -P legacy/
-        unzip -o legacy/checkpoints.zip -d legacy/
-        ls -l legacy/checkpoints/
+    - bash: bash .actions/pull_legacy_checkpoints.sh
       displayName: 'Get legacy checkpoints'
 
     - bash: |

.github/workflows/ci_test-conda.yml

@@ -55,13 +55,8 @@ jobs:
         # sanity check
         python requirements/check-avail-extras.py
 
-    - name: Pull checkpoints from S3
-      working-directory: ./legacy
-      run: |
-        # enter legacy and update checkpoints from S3
-        curl https://pl-public-data.s3.amazonaws.com/legacy/checkpoints.zip --output checkpoints.zip
-        unzip -o checkpoints.zip
-        ls -l checkpoints/
+    - name: Pull legacy checkpoints
+      run: bash .actions/pull_legacy_checkpoints.sh
 
     - name: Tests
       run: |

.github/workflows/ci_test-full.yml

@@ -76,14 +76,8 @@ jobs:
         restore-keys: |
           ${{ runner.os }}-pip-td${{ env.TIME_PERIOD }}-py${{ matrix.python-version }}-${{ matrix.release }}-${{ matrix.requires }}-
 
-    - name: Pull checkpoints from S3
-      working-directory: ./legacy
-      run: |
-        # wget is simpler but does not work on Windows
-        python -c "from urllib.request import urlretrieve ; urlretrieve('https://pl-public-data.s3.amazonaws.com/legacy/checkpoints.zip', 'checkpoints.zip')"
-        ls -l .
-        unzip -o checkpoints.zip
-        ls -l checkpoints/
+    - name: Pull legacy checkpoints
+      run: bash .actions/pull_legacy_checkpoints.sh
 
     - name: Install dependencies
       run: |

CHANGELOG.md

@@ -96,9 +96,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Raise an error if there are insufficient training batches when using a float value of `limit_train_batches` ([#12885](https://github.com/PyTorchLightning/pytorch-lightning/pull/12885))
 
-
-- Changed `pytorch_lightning.core.lightning` to `pytorch_lightning.core.module` ([#12740](https://github.com/PyTorchLightning/pytorch-lightning/pull/12740))
-
 ### Deprecated
 
 - Deprecated `pytorch_lightning.loggers.base.LightningLoggerBase` in favor of `pytorch_lightning.loggers.logger.Logger`, and deprecated `pytorch_lightning.loggers.base` in favor of `pytorch_lightning.loggers.logger` ([#120148](https://github.com/PyTorchLightning/pytorch-lightning/pull/12014))
@@ -116,6 +113,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `pytorch_lightning.core.lightning.LightningModule` in favor of `pytorch_lightning.core.module.LightningModule` ([#12740](https://github.com/PyTorchLightning/pytorch-lightning/pull/12740))
 
 
+- Deprecated `pytorch_lightning.loops.base.Loop` in favor of `pytorch_lightning.loops.loop.Loop` ([#13043](https://github.com/PyTorchLightning/pytorch-lightning/pull/13043))
+
+
 - Deprecated `Trainer.reset_train_val_dataloaders()` in favor of `Trainer.reset_{train,val}_dataloader` ([#12184](https://github.com/PyTorchLightning/pytorch-lightning/pull/12184))
 
 ### Removed

dockers/nvidia/Dockerfile

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-ARG PYTORCH_VERSION=21.11
+ARG PYTORCH_VERSION=22.04
 
 # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes
 FROM nvcr.io/nvidia/pytorch:${PYTORCH_VERSION}-py3
@@ -37,21 +37,20 @@ RUN \
         cd .. ; \
     fi && \
 # save the examples
-    mv pytorch-lightning/_notebooks notebooks && \
+    mv pytorch-lightning/_notebooks/.notebooks/ notebooks && \
     mv pytorch-lightning/pl_examples . && \
 
 # Installations \
     pip install -q fire && \
-    python ./pytorch-lightning/.actions/assistant.py requirements_prune_pkgs horovod --req_files ./pytorch-lightning/requirements/extra.txt  && \
-    pip install "Pillow>=8.2, !=8.3.0" "cryptography>=3.4" "py>=1.10" "protobuf>=3.15.6" --no-cache-dir -U --upgrade-strategy eager && \
-    pip install -r ./pytorch-lightning/requirements/extra.txt --no-cache-dir -U --upgrade-strategy eager && \
+    pip install "Pillow>=8.2, !=8.3.0" "cryptography>=3.4" "py>=1.10" --no-cache-dir -U --upgrade-strategy eager && \
+    pip install ./pytorch-lightning["extra","loggers","strategies"] --no-cache-dir -U --upgrade-strategy eager && \
     pip install -r ./pytorch-lightning/requirements/examples.txt --no-cache-dir -U --upgrade-strategy eager && \
-    pip install ./pytorch-lightning --no-cache-dir -U --upgrade-strategy eager && \
     rm -rf pytorch-lightning && \
-    pip install jupyterlab[all] -U && \
     pip list
 
-RUN pip install lightning-grid -U
+RUN pip install jupyterlab[all] -U && \
+    pip install lightning-grid -U
+#    pip install "py>=1.10" "protobuf>=3.15.6" --upgrade-strategy only-if-needed
 
 ENV PYTHONPATH="/workspace"
 

dockers/release/Dockerfile

@@ -36,7 +36,7 @@ RUN \
         mv pytorch-lightning-*/ pytorch-lightning ; \
         rm *.zip ; \
     fi && \
-    pip install ./pytorch-lightning["extra"] --no-cache-dir -U --upgrade-strategy eager && \
+    pip install ./pytorch-lightning["extra","loggers","strategies"] --no-cache-dir -U --upgrade-strategy eager && \
     rm -rf pytorch-lightning
 
 RUN python --version && \

dockers/tpu-tests/Dockerfile

@@ -22,10 +22,7 @@ LABEL maintainer="PyTorchLightning <https://github.com/PyTorchLightning>"
 COPY ./ ./pytorch-lightning/
 
 # Pull the legacy checkpoints
-RUN cd pytorch-lightning && \
-    wget https://pl-public-data.s3.amazonaws.com/legacy/checkpoints.zip -P legacy/ && \
-    unzip -o legacy/checkpoints.zip -d legacy/ && \
-    ls -l legacy/checkpoints/
+RUN cd pytorch-lightning && bash .actions/pull_legacy_checkpoints.sh
 
 RUN \
     pip install -q fire && \

docs/source/common/trainer.rst

@@ -850,6 +850,9 @@ Useful when debugging or testing something that happens at the end of an epoch.
     # run for only 10 batches
     trainer = Trainer(limit_val_batches=10)
 
+    # disable validation
+    trainer = Trainer(limit_val_batches=0)
+
 In the case of multiple validation dataloaders, the limit applies to each dataloader individually.
 
 log_every_n_steps

docs/source/extensions/loops.rst

@@ -81,7 +81,7 @@ The core research logic is simply shifted to the :class:`~pytorch_lightning.core
         loss.backward()
         optimizer.step()
 
-Under the hood, the above loop is implemented using the :class:`~pytorch_lightning.loops.base.Loop` API like so:
+Under the hood, the above loop is implemented using the :class:`~pytorch_lightning.loops.loop.Loop` API like so:
 
 .. code-block:: python
 
@@ -183,7 +183,7 @@ Now your code is FULLY flexible and you can still leverage ALL the best parts of
 Creating a New Loop From Scratch
 --------------------------------
 
-You can also go wild and implement a full loop from scratch by sub-classing the :class:`~pytorch_lightning.loops.base.Loop` base class.
+You can also go wild and implement a full loop from scratch by sub-classing the :class:`~pytorch_lightning.loops.loop.Loop` base class.
 You will need to override a minimum of two things:
 
 .. code-block:: python
@@ -222,7 +222,7 @@ Loop API
 --------
 Here is the full API of methods available in the Loop base class.
 
-The :class:`~pytorch_lightning.loops.base.Loop` class is the base of all loops in the same way as the :class:`~pytorch_lightning.core.module.LightningModule` is the base of all models.
+The :class:`~pytorch_lightning.loops.loop.Loop` class is the base of all loops in the same way as the :class:`~pytorch_lightning.core.module.LightningModule` is the base of all models.
 It defines a public interface that each loop implementation must follow, the key ones are:
 
 Properties
@@ -231,13 +231,13 @@ Properties
 done
 ~~~~
 
-.. autoattribute:: pytorch_lightning.loops.base.Loop.done
+.. autoattribute:: pytorch_lightning.loops.loop.Loop.done
     :noindex:
 
 skip (optional)
 ~~~~~~~~~~~~~~~
 
-.. autoattribute:: pytorch_lightning.loops.base.Loop.skip
+.. autoattribute:: pytorch_lightning.loops.loop.Loop.skip
     :noindex:
 
 Methods
@@ -246,19 +246,19 @@ Methods
 reset (optional)
 ~~~~~~~~~~~~~~~~
 
-.. automethod:: pytorch_lightning.loops.base.Loop.reset
+.. automethod:: pytorch_lightning.loops.loop.Loop.reset
     :noindex:
 
 advance
 ~~~~~~~
 
-.. automethod:: pytorch_lightning.loops.base.Loop.advance
+.. automethod:: pytorch_lightning.loops.loop.Loop.advance
     :noindex:
 
 run (optional)
 ~~~~~~~~~~~~~~
 
-.. automethod:: pytorch_lightning.loops.base.Loop.run
+.. automethod:: pytorch_lightning.loops.loop.Loop.run
     :noindex:
 
 
@@ -267,7 +267,7 @@ run (optional)
 Subloops
 --------
 
-When you want to customize nested loops within loops, use the :meth:`~pytorch_lightning.loops.base.Loop.replace` method:
+When you want to customize nested loops within loops, use the :meth:`~pytorch_lightning.loops.loop.Loop.replace` method:
 
 .. code-block:: python
 
@@ -276,7 +276,7 @@ When you want to customize nested loops within loops, use the :meth:`~pytorch_li
     # Trainer runs the fit loop with your new epoch loop!
     trainer.fit(model)
 
-Alternatively, for more fine-grained control, use the :meth:`~pytorch_lightning.loops.base.Loop.connect` method:
+Alternatively, for more fine-grained control, use the :meth:`~pytorch_lightning.loops.loop.Loop.connect` method:
 
 .. code-block:: python
 
@@ -326,7 +326,7 @@ Here is what the structure would look like in plain Python:
                 ...
 
 
-Each of these :code:`for`-loops represents a class implementing the :class:`~pytorch_lightning.loops.base.Loop` interface.
+Each of these :code:`for`-loops represents a class implementing the :class:`~pytorch_lightning.loops.loop.Loop` interface.
 
 
 .. list-table:: Trainer entry points and associated loops