rename org Lightning AI

pl_examples/basic_examples/mnist_datamodule.py

@@ -36,7 +36,7 @@ class _MNIST(Dataset):
     """Carbon copy of ``tests.helpers.datasets.MNIST``.
 
     We cannot import the tests as they are not distributed with the package.
-    See https://github.com/PyTorchLightning/pytorch-lightning/pull/7614#discussion_r671183652 for more context.
+    See https://github.com/Lightning-AI/lightning/pull/7614#discussion_r671183652 for more context.
     """
 
     RESOURCES = (

pl_examples/domain_templates/reinforce_learn_ppo.py

@@ -125,7 +125,7 @@ def get_log_prob(self, pi: Normal, actions: torch.Tensor):
 
 
 class ExperienceSourceDataset(IterableDataset):
-    """Implementation from PyTorch Lightning Bolts: https://github.com/PyTorchLightning/lightning-
+    """Implementation from PyTorch Lightning Bolts: https://github.com/Lightning-AI/lightning-
     bolts/blob/master/pl_bolts/datamodules/experience_source.py.
 
     Basic experience source dataset. Takes a generate_batch function that returns an iterator. The logic for the

pytorch_lightning/loggers/neptune.py

@@ -54,7 +54,7 @@
 
 log = logging.getLogger(__name__)
 
-_INTEGRATION_VERSION_KEY = "source_code/integrations/pytorch-lightning"
+_INTEGRATION_VERSION_KEY = "source_code/integrations/lightning"
 
 # kwargs used in previous NeptuneLogger version, now deprecated
 _LEGACY_NEPTUNE_INIT_KWARGS = [
@@ -113,7 +113,7 @@ class NeptuneLogger(LightningLoggerBase):
 
         neptune_logger = NeptuneLogger(
             api_key="ANONYMOUS",  # replace with your own
-            project="common/pytorch-lightning-integration",  # format "<WORKSPACE/PROJECT>"
+            project="common/lightning-integration",  # format "<WORKSPACE/PROJECT>"
             tags=["training", "resnet"],  # optional
         )
         trainer = Trainer(max_epochs=10, logger=neptune_logger)
@@ -157,7 +157,7 @@ def any_lightning_module_function_or_hook(self):
 
     .. code-block:: python
 
-        neptune_logger = NeptuneLogger(project="common/pytorch-lightning-integration")
+        neptune_logger = NeptuneLogger(project="common/lightning-integration")
 
         trainer = pl.Trainer(logger=neptune_logger)
         model = ...
@@ -182,7 +182,7 @@ def any_lightning_module_function_or_hook(self):
 
     .. code-block:: python
 
-        neptune_logger = NeptuneLogger(project="common/pytorch-lightning-integration", log_model_checkpoints=False)
+        neptune_logger = NeptuneLogger(project="common/lightning-integration", log_model_checkpoints=False)
 
     **Pass additional parameters to the Neptune run**
 
@@ -194,7 +194,7 @@ def any_lightning_module_function_or_hook(self):
         from pytorch_lightning.loggers import NeptuneLogger
 
         neptune_logger = NeptuneLogger(
-            project="common/pytorch-lightning-integration",
+            project="common/lightning-integration",
             name="lightning-run",
             description="mlp quick run with pytorch-lightning",
             tags=["mlp", "quick-run"],
@@ -216,10 +216,10 @@ def any_lightning_module_function_or_hook(self):
     See Also:
         - Read about
           `what object you can log to Neptune <https://docs.neptune.ai/you-should-know/what-can-you-log-and-display>`_.
-        - Check `example run <https://app.neptune.ai/o/common/org/pytorch-lightning-integration/e/PTL-1/all>`_
+        - Check `example run <https://app.neptune.ai/o/common/org/lightning-integration/e/PTL-1/all>`_
           with multiple types of metadata logged.
         - For more detailed info check
-          `user guide <https://docs.neptune.ai/integrations-and-supported-tools/model-training/pytorch-lightning>`_.
+          `user guide <https://docs.neptune.ai/integrations-and-supported-tools/model-training/lightning>`_.
 
     Args:
         api_key: Optional.
@@ -350,7 +350,7 @@ def _verify_input_arguments(
             "  - https://docs-legacy.neptune.ai/integrations/pytorch_lightning.html\n"
             "The NeptuneLogger was re-written to use the neptune.new Python API\n"
             "  - https://neptune.ai/blog/neptune-new\n"
-            "  - https://docs.neptune.ai/integrations-and-supported-tools/model-training/pytorch-lightning\n"
+            "  - https://docs.neptune.ai/integrations-and-supported-tools/model-training/lightning\n"
             "You should use arguments accepted by either NeptuneLogger.init() or neptune.init()"
         )
 
@@ -377,7 +377,7 @@ def _verify_input_arguments(
                 "  - https://docs-legacy.neptune.ai/integrations/pytorch_lightning.html\n"
                 "The NeptuneLogger was re-written to use the neptune.new Python API\n"
                 "  - https://neptune.ai/blog/neptune-new\n"
-                "  - https://docs.neptune.ai/integrations-and-supported-tools/model-training/pytorch-lightning\n"
+                "  - https://docs.neptune.ai/integrations-and-supported-tools/model-training/lightning\n"
             )
 
         # check if user passed redundant neptune.init arguments when passed run
@@ -477,7 +477,7 @@ def log_hyperparams(self, params: Union[Dict[str, Any], Namespace]) -> None:  #
 
             neptune_logger = NeptuneLogger(
                 api_key="ANONYMOUS",
-                project="common/pytorch-lightning-integration"
+                project="common/lightning-integration"
             )
 
             neptune_logger.log_hyperparams(PARAMS)
@@ -627,7 +627,7 @@ def _signal_deprecated_api_usage(f_name, sample_code, raise_exception=False):
             f"  - https://docs-legacy.neptune.ai/integrations/pytorch_lightning.html\n"
             f"The NeptuneLogger was re-written to use the neptune.new Python API\n"
             f"  - https://neptune.ai/blog/neptune-new\n"
-            f"  - https://docs.neptune.ai/integrations-and-supported-tools/model-training/pytorch-lightning\n"
+            f"  - https://docs.neptune.ai/integrations-and-supported-tools/model-training/lightning\n"
             f"Instead of `logger.{f_name}` you can use:\n"
             f"\t{sample_code}"
         )

pytorch_lightning/loops/epoch/evaluation_epoch_loop.py

@@ -195,7 +195,7 @@ def _reload_dataloader_state_dict(self, data_fetcher: AbstractDataFetcher) -> No
         if isinstance(dataloader, CombinedLoader):
             raise MisconfigurationException(
                 "Reloading support hasn't been implemented for `CombinedLoader`. You can request it by opening an issue"
-                " in `https://github.com/PyTorchLightning/pytorch-lightning/issues`."
+                " in `https://github.com/Lightning-AI/lightning/issues`."
             )
         assert isinstance(dataloader, DataLoader)
         _reload_dataloader_state_dict(dataloader, self._dataloader_state_dict)

pytorch_lightning/plugins/io/torch_plugin.py

@@ -54,7 +54,7 @@ def save_checkpoint(self, checkpoint: Dict[str, Any], path: _PATH, storage_optio
             atomic_save(checkpoint, path)
         except AttributeError as err:
             # todo (sean): is this try catch necessary still?
-            # https://github.com/PyTorchLightning/pytorch-lightning/pull/431
+            # https://github.com/Lightning-AI/lightning/pull/431
             key = pl.LightningModule.CHECKPOINT_HYPER_PARAMS_KEY
             checkpoint.pop(key, None)
             rank_zero_warn(f"Warning, `{key}` dropped from checkpoint. An attribute is not picklable: {err}")

pytorch_lightning/plugins/precision/ipu.py

@@ -72,7 +72,7 @@ def optimizer_step(
             # we lack coverage here and IPUs are (currently) limited - something to explore if there's demand
             raise MisconfigurationException(
                 "Skipping backward by returning `None` from your `training_step` is not implemented for IPUs."
-                " Please, open an issue in `https://github.com/PyTorchLightning/pytorch-lightning/issues`"
+                " Please, open an issue in `https://github.com/Lightning-AI/lightning/issues`"
                 " requesting this feature."
             )
         return closure_result

pytorch_lightning/plugins/precision/tpu.py

@@ -46,7 +46,7 @@ def optimizer_step(
             # we lack coverage here so disable this - something to explore if there's demand
             raise MisconfigurationException(
                 "Skipping backward by returning `None` from your `training_step` is not implemented for TPUs."
-                " Please, open an issue in `https://github.com/PyTorchLightning/pytorch-lightning/issues`"
+                " Please, open an issue in `https://github.com/Lightning-AI/lightning/issues`"
                 " requesting this feature."
             )
         return closure_result

pytorch_lightning/setup_tools.py

@@ -59,7 +59,7 @@ def _load_readme_description(path_dir: str, homepage: str, version: str) -> str:
     # drop images from readme
     text = text.replace("![PT to PL](docs/source/_static/images/general/pl_quick_start_full_compressed.gif)", "")
 
-    # https://github.com/PyTorchLightning/pytorch-lightning/raw/master/docs/source/_static/images/lightning_module/pt_to_pl.png
+    # https://github.com/Lightning-AI/lightning/raw/master/docs/source/_static/images/lightning_module/pt_to_pl.png
     github_source_url = os.path.join(homepage, "raw", version)
     # replace relative repository path to absolute link to the release
     #  do not replace all "docs" as in the readme we reger some other sources with particular path to docs
@@ -81,7 +81,7 @@ def _load_readme_description(path_dir: str, homepage: str, version: str) -> str:
     # todo: wrap content as commented description
     text = re.sub(rf"{skip_begin}.+?{skip_end}", "<!--  -->", text, flags=re.IGNORECASE + re.DOTALL)
 
-    # # https://github.com/Borda/pytorch-lightning/releases/download/1.1.0a6/codecov_badge.png
+    # # https://github.com/Borda/lightning/releases/download/1.1.0a6/codecov_badge.png
     # github_release_url = os.path.join(homepage, "releases", "download", version)
     # # download badge and replace url with local file
     # text = _parse_for_badge(text, github_release_url)

pytorch_lightning/strategies/launchers/spawn.py

@@ -53,7 +53,7 @@ def __init__(self, strategy: Strategy) -> None:
     def is_interactive_compatible(self) -> bool:
         # The start method 'spawn' is currently the only one that works with DDP and CUDA support
         # The start method 'fork' is the only one supported in Jupyter environments but not compatible with CUDA
-        # For more context, see https://github.com/PyTorchLightning/pytorch-lightning/issues/7550
+        # For more context, see https://github.com/Lightning-AI/lightning/issues/7550
         return self._start_method == "fork" and self._strategy.root_device.type != "cuda"
 
     def launch(self, function: Callable, *args: Any, trainer: Optional["pl.Trainer"] = None, **kwargs: Any) -> Any:

pytorch_lightning/trainer/connectors/accelerator_connector.py

@@ -221,7 +221,7 @@ def _init_deterministic(self, deterministic: Optional[bool]) -> None:
         torch.use_deterministic_algorithms(self.deterministic)
         if self.deterministic:
             # fixing non-deterministic part of horovod
-            # https://github.com/PyTorchLightning/pytorch-lightning/pull/1572/files#r420279383
+            # https://github.com/Lightning-AI/lightning/pull/1572/files#r420279383
             os.environ["HOROVOD_FUSION_THRESHOLD"] = "0"
 
             # https://docs.nvidia.com/cuda/cublas/index.html#cublasApi_reproducibility
@@ -605,7 +605,7 @@ def _check_strategy_and_fallback(self) -> None:
             if _TPU_AVAILABLE:
                 raise MisconfigurationException(
                     "`accelerator='ddp_cpu'` is not supported on TPU machines. "
-                    "Learn more: https://github.com/PyTorchLightning/pytorch-lightning/issues/7810"
+                    "Learn more: https://github.com/Lightning-AI/lightning/issues/7810"
                 )
             if self._devices_flag == 1 and self._num_nodes_flag > 1:
                 strategy_flag = DDPStrategy.strategy_name
@@ -725,7 +725,7 @@ def _validate_precision_choice(self) -> None:
             if self._precision_flag == 64:
                 raise MisconfigurationException(
                     "`Trainer(accelerator='tpu', precision=64)` is not implemented."
-                    " Please, open an issue in `https://github.com/PyTorchLightning/pytorch-lightning/issues`"
+                    " Please, open an issue in `https://github.com/Lightning-AI/lightning/issues`"
                     " requesting this feature."
                 )
             if self._precision_plugin_flag and not isinstance(

pytorch_lightning/trainer/connectors/logger_connector/fx_validator.py

@@ -182,7 +182,7 @@ def check_logging(cls, fx_name: str) -> None:
         if fx_name not in cls.functions:
             raise RuntimeError(
                 f"Logging inside `{fx_name}` is not implemented."
-                " Please, open an issue in `https://github.com/PyTorchLightning/pytorch-lightning/issues`."
+                " Please, open an issue in `https://github.com/Lightning-AI/lightning/issues`."
             )
 
         if cls.functions[fx_name] is None:

pytorch_lightning/trainer/connectors/logger_connector/result.py

@@ -125,7 +125,7 @@ def __post_init__(self) -> None:
     def _parse_reduce_fx(self) -> None:
         error = (
             "Only `self.log(..., reduce_fx={min,max,mean,sum})` are currently supported."
-            " Please, open an issue in `https://github.com/PyTorchLightning/pytorch-lightning/issues`."
+            " Please, open an issue in `https://github.com/Lightning-AI/lightning/issues`."
             f" Found: {self.reduce_fx}"
         )
         if isinstance(self.reduce_fx, str):

pytorch_lightning/utilities/migration.py

@@ -28,7 +28,7 @@ class pl_legacy_patch:
     unpickling old checkpoints. The following patches apply.
 
         1. ``pytorch_lightning.utilities.argparse._gpus_arg_default``: Applies to all checkpoints saved prior to
-           version 1.2.8. See: https://github.com/PyTorchLightning/pytorch-lightning/pull/6898
+           version 1.2.8. See: https://github.com/Lightning-AI/lightning/pull/6898
         2. ``pytorch_lightning.utilities.argparse_utils``: A module that was deprecated in 1.2 and removed in 1.4,
            but still needs to be available for import for legacy checkpoints.
 

setup.py

@@ -69,7 +69,7 @@ def _load_py_module(fname, pkg="pytorch_lightning"):
     author=about.__author__,
     author_email=about.__author_email__,
     url=about.__homepage__,
-    download_url="https://github.com/PyTorchLightning/pytorch-lightning",
+    download_url="https://github.com/Lightning-AI/lightning",
     license=about.__license__,
     packages=find_packages(exclude=["tests*", "pl_examples*", "legacy*"]),
     include_package_data=True,
@@ -82,9 +82,9 @@ def _load_py_module(fname, pkg="pytorch_lightning"):
     install_requires=setup_tools._load_requirements(_PATH_REQUIRE),
     extras_require=extras,
     project_urls={
-        "Bug Tracker": "https://github.com/PyTorchLightning/pytorch-lightning/issues",
-        "Documentation": "https://pytorch-lightning.rtfd.io/en/latest/",
-        "Source Code": "https://github.com/PyTorchLightning/pytorch-lightning",
+        "Bug Tracker": "https://github.com/Lightning-AI/lightning/issues",
+        "Documentation": "https://lightning.rtfd.io/en/latest/",
+        "Source Code": "https://github.com/Lightning-AI/lightning",
     },
     classifiers=[
         "Environment :: Console",

tests/loggers/test_neptune.py

@@ -47,7 +47,7 @@ class Run:
 
     def __setitem__(self, key, value):
         # called once
-        assert key == "source_code/integrations/pytorch-lightning"
+        assert key == "source_code/integrations/lightning"
         assert value == __version__
 
     def wait(self):
@@ -89,7 +89,7 @@ def test_neptune_online(self, neptune):
         self.assertEqual(created_run_mock.__getitem__.call_count, 2)
         self.assertEqual(created_run_mock.__setitem__.call_count, 1)
         created_run_mock.__getitem__.assert_has_calls([call("sys/id"), call("sys/name")], any_order=True)
-        created_run_mock.__setitem__.assert_called_once_with("source_code/integrations/pytorch-lightning", __version__)
+        created_run_mock.__setitem__.assert_called_once_with("source_code/integrations/lightning", __version__)
 
     @patch("pytorch_lightning.loggers.neptune.Run", Run)
     def test_online_with_custom_run(self, neptune):