Merge branch 'master' into bugfix/logger-attributeerror

.github/workflows/ci-pytorch-test-conda.yml

@@ -27,7 +27,7 @@ jobs:
           - {python-version: "3.8", pytorch-version: "1.10"}
           - {python-version: "3.9", pytorch-version: "1.11"}
           - {python-version: "3.9", pytorch-version: "1.12"}
-    timeout-minutes: 30
+    timeout-minutes: 40
 
     steps:
     - name: Workaround for https://github.com/actions/checkout/issues/760

.github/workflows/docs-deploy.yml

@@ -1,7 +1,7 @@
 name: "Deploy Docs"
 on:
   push:
-    branches: [master]
+    branches: ["release/app"]
 
 jobs:
   # https://github.com/marketplace/actions/deploy-to-github-pages

docs/source-app/workflows/build_lightning_app/from_scratch_content.rst

@@ -58,64 +58,3 @@ Run the Lightning App on the cloud:
 .. code:: bash
 
     lightning run app app.py --cloud
-
-----
-
-*************************************
-Build a Lightning App from a template
-*************************************
-If you didn't find an Lightning App similar to the one you need (in the `Lightning App gallery <https://lightning.ai/apps>`_), another option is to start from a template.
-The Lightning CLI can generate a template with built-in testing that can be easily published to the
-Lightning App Gallery.
-
-Generate a Lightning App with our template generator:
-
-.. code:: bash
-
-    lightning init app your-app-name
-
-You'll see a print-out like this:
-
-.. code:: bash
-
-    ➜ lightning init app your-app-name
-
-    /Users/Your/Current/dir/your-app-name
-    INFO: laying out app template at /Users/Your/Current/dir/your-app-name
-    INFO:
-        Lightning app template created!
-        /Users/Your/Current/dir/your-app-name
-
-    run your app with:
-        lightning run app your-app-name/app.py
-
-    run it on the cloud to share with your collaborators:
-        lightning run app your-app-name/app.py --cloud
-
-----
-
-Modify the Lightning App template
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-The command above generates a Lightning App file like this:
-
-.. code:: python
-
-    from your_app_name import ComponentA, ComponentB
-
-    import lightning as L
-
-
-    class LitApp(L.LightningFlow):
-        def __init__(self) -> None:
-            super().__init__()
-            self.component_a = ComponentA()
-            self.component_b = ComponentB()
-
-        def run(self):
-            self.component_a.run()
-            self.component_b.run()
-
-
-    app = L.LightningApp(LitApp())
-
-Now you can add your own components as you wish!

docs/source-app/workflows/build_lightning_component/from_scratch_component_content.rst

@@ -151,50 +151,3 @@ run the app
 .. code:: bash
 
     lightning run app app.py
-
-----
-
-*******************************************
-Build a Lightning component from a template
-*******************************************
-If you'd prefer a component template with built-in testing that can be easily published to the
-Lightning component gallery, generate it with our template generator:
-
-.. code:: bash
-
-    lightning init component your-component-name
-
-You'll see a print-out like this:
-
-.. code:: bash
-
-    ➜ lightning init component your-component-name
-    INFO: laying out component template at /Users/williamfalcon/Developer/opensource/_/lightning/scratch/hello-world
-    INFO:
-    ⚡ Lightning component template created! ⚡
-    /Users/williamfalcon/Developer/opensource/_/lightning/scratch/hello-world
-
-    ...
-
-----
-
-Modify the component template
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-The command above generates a component file like this:
-
-.. code:: python
-
-    import lightning as L
-
-
-    class TemplateComponent(L.LightningWork):
-        def __init__(self) -> None:
-            super().__init__()
-            self.value = 0
-
-        def run(self):
-            self.value += 1
-            print("welcome to your work component")
-            print("this is running inside a work")
-
-Now you can modify the component as you wish!

requirements/pytorch/base.txt

@@ -6,7 +6,7 @@ torch>=1.9.*, <=1.12.0
 tqdm>=4.57.0, <4.65.0
 PyYAML>=5.4, <=6.0
 fsspec[http]>=2021.05.0, !=2021.06.0, <2022.6.0
-tensorboard>=2.9.1, <2.10.0
+tensorboard>=2.9.1, <2.11.0
 torchmetrics>=0.7.0, <0.9.3  # needed for using fixed compare_version
 pyDeprecate>=0.3.1, <=0.3.2
 packaging>=17.0, <=21.3

src/pytorch_lightning/CHANGELOG.md

@@ -8,15 +8,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Added
 
-- Added `FullyShardedNativeNativeMixedPrecisionPlugin` to handle precision for `DDPFullyShardedNativeStrategy` ([#14092](https://github.com/Lightning-AI/lightning/pull/14092))
-
 
 - Added prefix to log message in `seed_everything` with rank info ([#13290](https://github.com/Lightning-AI/lightning/issues/13290))
 
 
-- Added profiling to these hooks: `on_before_batch_transfer`, `transfer_batch_to_device`, `on_after_batch_transfer`, `configure_gradient_clipping`, `clip_gradients` ([#14069](https://github.com/Lightning-AI/lightning/pull/14069))
-
-
 -
 
 
@@ -28,17 +23,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Raised a `MisconfigurationException` if batch transfer hooks are overriden with `IPUAccelerator` ([#13961](https://github.com/Lightning-AI/lightning/pull/13961))
 
 
-- Updated compatibility for LightningLite to run with the latest DeepSpeed 0.7.0 ([13967](https://github.com/Lightning-AI/lightning/pull/13967))
-
-
 - Replaced the unwrapping logic in strategies with direct access to unwrapped `LightningModule` ([#13738](https://github.com/Lightning-AI/lightning/pull/13738))
 
 
-- The `WandbLogger.name` property no longer returns the name of the experiment, and instead returns the project's name ([#14145](https://github.com/Lightning-AI/lightning/pull/14145))
-
-
-- The default project name in `WandbLogger` is now "lightning_logs" ([#14145](https://github.com/Lightning-AI/lightning/pull/14145))
-
 
 ### Deprecated
 
@@ -77,46 +64,41 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Fixed
 
-- Fixed a bug that caused spurious `AttributeError` when multiple `DataLoader` classes are imported ([#14117](https://github.com/Lightning-AI/lightning/pull/14117))
+- Fixed an assertion error when using a `ReduceOnPlateau` scheduler with the Horovod strategy ([#14215](https://github.com/Lightning-AI/lightning/pull/14215))
 
 
-- Fixed epoch-end logging results not being reset after the end of the epoch ([#14061](https://github.com/Lightning-AI/lightning/pull/14061))
+- Fixed an `AttributeError` when accessing `LightningModule.logger` and the Trainer has multiple loggers ([#14234](https://github.com/Lightning-AI/lightning/pull/14234))
 
 
-- Fixed resuming from a checkpoint when using Stochastic Weight Averaging (SWA) ([#9938](https://github.com/Lightning-AI/lightning/pull/9938))
+## [1.7.2] - 2022-08-17
 
+### Added
 
-- Fixed the device placement when `LightningModule.cuda()` gets called without specifying a device index and the current cuda device was not 0 ([#14128](https://github.com/Lightning-AI/lightning/pull/14128))
+- Added `FullyShardedNativeNativeMixedPrecisionPlugin` to handle precision for `DDPFullyShardedNativeStrategy` ([#14092](https://github.com/Lightning-AI/lightning/pull/14092))
+- Added profiling to these hooks: `on_before_batch_transfer`, `transfer_batch_to_device`, `on_after_batch_transfer`, `configure_gradient_clipping`, `clip_gradients` ([#14069](https://github.com/Lightning-AI/lightning/pull/14069))
 
+### Changed
 
-- Avoided false positive warning about using `sync_dist` when using torchmetrics ([#14143](https://github.com/Lightning-AI/lightning/pull/14143))
+- The `WandbLogger.name` property no longer returns the name of the experiment, and instead returns the project's name ([#14145](https://github.com/Lightning-AI/lightning/pull/14145))
+- The default project name in `WandbLogger` is now "lightning_logs" ([#14145](https://github.com/Lightning-AI/lightning/pull/14145))
+- Updated compatibility for LightningLite to run with the latest DeepSpeed 0.7.0 ([13967](https://github.com/Lightning-AI/lightning/pull/13967))
 
+### Fixed
 
+- Fixed a bug that caused spurious `AttributeError` when multiple `DataLoader` classes are imported ([#14117](https://github.com/Lightning-AI/lightning/pull/14117))
+- Fixed epoch-end logging results not being reset after the end of the epoch ([#14061](https://github.com/Lightning-AI/lightning/pull/14061))
+- Fixed resuming from a checkpoint when using Stochastic Weight Averaging (SWA) ([#9938](https://github.com/Lightning-AI/lightning/pull/9938))
+- Fixed the device placement when `LightningModule.cuda()` gets called without specifying a device index and the current cuda device was not 0 ([#14128](https://github.com/Lightning-AI/lightning/pull/14128))
+- Avoided false positive warning about using `sync_dist` when using torchmetrics ([#14143](https://github.com/Lightning-AI/lightning/pull/14143))
 - Avoid `metadata.entry_points` deprecation warning on Python 3.10 ([#14052](https://github.com/Lightning-AI/lightning/pull/14052))
-
-
 - Fixed epoch-end logging results not being reset after the end of the epoch ([#14061](https://github.com/Lightning-AI/lightning/pull/14061))
-
-
 - Avoid raising the sampler warning if num_replicas=1 ([#14097](https://github.com/Lightning-AI/lightning/pull/14097))
-
-
 - Fixed saving hyperparameters in a composition where the parent class is not a `LightningModule` or `LightningDataModule` ([#14151](https://github.com/Lightning-AI/lightning/pull/14151))
-
-
 - Avoided requiring the FairScale package to use precision with the fsdp native strategy ([#14092](https://github.com/Lightning-AI/lightning/pull/14092))
-
-
-- Fixed an `AttributeError` when accessing `LightningModule.logger` and the Trainer has multiple loggers ([#14234](https://github.com/Lightning-AI/lightning/pull/14234))
-
-
 - Fixed an issue in which the default name for a run in `WandbLogger` would be set to the project name instead of a randomly generated string ([#14145](https://github.com/Lightning-AI/lightning/pull/14145))
-
-
 - Fixed not preserving set attributes on `DataLoader` and `BatchSampler` when instantiated inside `*_dataloader` hooks ([#14212](https://github.com/Lightning-AI/lightning/pull/14212))
 
 
-
 ## [1.7.1] - 2022-08-09
 
 ### Fixed

src/pytorch_lightning/serve/servable_module_validator.py

@@ -47,7 +47,7 @@ def __init__(
         server: Literal["fastapi", "ml_server", "torchserve", "sagemaker"] = "fastapi",
         host: str = "127.0.0.1",
         port: int = 8080,
-        timeout: int = 10,
+        timeout: int = 20,
         exit_on_failure: bool = True,
     ):
         super().__init__()
@@ -109,7 +109,8 @@ def on_train_start(self, trainer: "pl.Trainer", servable_module: "pl.LightningMo
             except requests.exceptions.ConnectionError:
                 pass
             if time.time() - t0 > self.timeout:
-                raise Exception(f"The Server didn't start in {self.timeout}")
+                process.kill()
+                raise Exception(f"The server didn't start within {self.timeout} seconds.")
             time.sleep(0.1)
 
         payload = servable_module.configure_payload()

src/pytorch_lightning/strategies/horovod.py

@@ -31,7 +31,6 @@
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.imports import _HOROVOD_AVAILABLE
 from pytorch_lightning.utilities.rank_zero import rank_zero_only
-from pytorch_lightning.utilities.types import _LRScheduler
 
 if _HOROVOD_AVAILABLE:
     import horovod.torch as hvd
@@ -114,8 +113,8 @@ def _unpack_lightning_optimizer(opt: Optimizer) -> Optimizer:
         lr_scheduler_configs = self.lr_scheduler_configs
         for config in lr_scheduler_configs:
             scheduler = config.scheduler
-            assert isinstance(scheduler, _LRScheduler)
-            scheduler.base_lrs = [lr * self.world_size for lr in scheduler.base_lrs]
+            if hasattr(scheduler, "base_lrs"):
+                scheduler.base_lrs = [lr * self.world_size for lr in scheduler.base_lrs]  # type: ignore[union-attr]
 
         assert self.lightning_module is not None
         # Horovod: broadcast parameters & optimizer state to ensure consistent initialization