diff --git a/docs/source-pytorch/common/lightning_module.rst b/docs/source-pytorch/common/lightning_module.rst index 636777ec7e..bf774b02a2 100644 --- a/docs/source-pytorch/common/lightning_module.rst +++ b/docs/source-pytorch/common/lightning_module.rst @@ -1626,15 +1626,3 @@ on_after_batch_transfer .. automethod:: pytorch_lightning.core.module.LightningModule.on_after_batch_transfer :noindex: - -add_to_queue -~~~~~~~~~~~~ - -.. automethod:: pytorch_lightning.core.module.LightningModule.add_to_queue - :noindex: - -get_from_queue -~~~~~~~~~~~~~~ - -.. automethod:: pytorch_lightning.core.module.LightningModule.get_from_queue - :noindex: diff --git a/src/pytorch_lightning/CHANGELOG.md b/src/pytorch_lightning/CHANGELOG.md index 0d42f819d9..a4bec3f0ad 100644 --- a/src/pytorch_lightning/CHANGELOG.md +++ b/src/pytorch_lightning/CHANGELOG.md @@ -174,6 +174,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). ### Removed +- Removed the deprecated `LightningModule.add_to_queue` and `LightningModule.get_from_queue` method ([#13600](https://github.com/PyTorchLightning/pytorch-lightning/pull/13600)) + + - Removed deprecated `pytorch_lightning.core.decorators.parameter_validation` from `decorators` ([#13514](https://github.com/Lightning-AI/lightning/pull/13514)) diff --git a/src/pytorch_lightning/core/module.py b/src/pytorch_lightning/core/module.py index ef4a869b3c..022f7ab678 100644 --- a/src/pytorch_lightning/core/module.py +++ b/src/pytorch_lightning/core/module.py @@ -1955,28 +1955,6 @@ class LightningModule( ) self._use_amp = use_amp - def add_to_queue(self, queue: pl.strategies.launchers.spawn._FakeQueue) -> None: - """Appends the :attr:`trainer.callback_metrics` dictionary to the given queue. To avoid issues with memory - sharing, we cast the data to numpy. - - Args: - queue: the instance of the queue to append the data. - - .. deprecated:: v1.5 - This method was deprecated in v1.5 and will be removed in v1.7. - """ - - def get_from_queue(self, queue: pl.strategies.launchers.spawn._FakeQueue) -> None: - """Retrieve the :attr:`trainer.callback_metrics` dictionary from the given queue. To preserve consistency, - we cast back the data to ``torch.Tensor``. - - Args: - queue: the instance of the queue from where to get the data. - - .. deprecated:: v1.5 - This method was deprecated in v1.5 and will be removed in v1.7. - """ - @contextmanager def _prevent_trainer_and_dataloaders_deepcopy(self) -> None: self._should_prevent_trainer_and_dataloaders_deepcopy = True diff --git a/src/pytorch_lightning/strategies/launchers/spawn.py b/src/pytorch_lightning/strategies/launchers/spawn.py index d94909b778..0a92ceee5a 100644 --- a/src/pytorch_lightning/strategies/launchers/spawn.py +++ b/src/pytorch_lightning/strategies/launchers/spawn.py @@ -26,7 +26,6 @@ from pytorch_lightning.strategies.launchers.base import _Launcher from pytorch_lightning.strategies.strategy import Strategy from pytorch_lightning.trainer.states import TrainerFn, TrainerState from pytorch_lightning.utilities.apply_func import apply_to_collection, move_data_to_device -from pytorch_lightning.utilities.model_helpers import is_overridden from pytorch_lightning.utilities.rank_zero import rank_zero_debug from pytorch_lightning.utilities.types import _PATH @@ -122,10 +121,6 @@ class _SpawnLauncher(_Launcher): trainer.state = spawn_output.trainer_state # get the `callback_metrics` and set it to the trainer - if is_overridden("get_from_queue", trainer.lightning_module): - # only in case the user does not override it. - # TODO: Remove the if in v1.7 - trainer.lightning_module.get_from_queue(spawn_output.extra) self.get_from_queue(trainer, spawn_output.extra) def _collect_rank_zero_results(self, trainer: "pl.Trainer", results: Any) -> Optional["_SpawnOutput"]: @@ -151,9 +146,6 @@ class _SpawnLauncher(_Launcher): # adds the `callback_metrics` to the queue extra = _FakeQueue() - if is_overridden("add_to_queue", trainer.lightning_module): - # TODO: Remove the if in v1.7 - trainer.lightning_module.add_to_queue(extra) self.add_to_queue(trainer, extra) return _SpawnOutput(best_model_path, weights_path, trainer.state, results, extra) diff --git a/src/pytorch_lightning/strategies/launchers/xla_spawn.py b/src/pytorch_lightning/strategies/launchers/xla_spawn.py index 13c948577c..9c47e3b325 100644 --- a/src/pytorch_lightning/strategies/launchers/xla_spawn.py +++ b/src/pytorch_lightning/strategies/launchers/xla_spawn.py @@ -23,7 +23,6 @@ from pytorch_lightning.strategies.launchers.spawn import _FakeQueue, _SpawnLaunc from pytorch_lightning.trainer.states import TrainerFn from pytorch_lightning.utilities import _TPU_AVAILABLE from pytorch_lightning.utilities.apply_func import move_data_to_device -from pytorch_lightning.utilities.model_helpers import is_overridden from pytorch_lightning.utilities.rank_zero import rank_zero_debug if _TPU_AVAILABLE: @@ -136,9 +135,6 @@ class _XLASpawnLauncher(_SpawnLauncher): # adds the `callback_metrics` to the queue extra = _FakeQueue() - if is_overridden("add_to_queue", trainer.lightning_module): - # TODO: Remove the if in v1.7 - trainer.lightning_module.add_to_queue(extra) self.add_to_queue(trainer, extra) return _SpawnOutput(best_model_path, weights_path, trainer.state, results, extra) diff --git a/src/pytorch_lightning/trainer/configuration_validator.py b/src/pytorch_lightning/trainer/configuration_validator.py index ceeec9f7fc..c53e22ea74 100644 --- a/src/pytorch_lightning/trainer/configuration_validator.py +++ b/src/pytorch_lightning/trainer/configuration_validator.py @@ -46,7 +46,6 @@ def verify_loop_configurations(trainer: "pl.Trainer") -> None: __verify_eval_loop_configuration(trainer, model, "predict") __verify_dp_batch_transfer_support(trainer, model) - _check_add_get_queue(model) # TODO: Delete _check_on_post_move_to_device in v1.7 _check_on_post_move_to_device(model) _check_deprecated_callback_hooks(trainer) @@ -218,23 +217,6 @@ def __check_training_step_requires_dataloader_iter(model: "pl.LightningModule") ) -def _check_add_get_queue(model: "pl.LightningModule") -> None: - r""" - Checks if add_to_queue or get_from_queue is overridden and sends a deprecation warning. - - Args: - model: The lightning module - """ - if is_overridden("add_to_queue", model): - rank_zero_deprecation( - "The `LightningModule.add_to_queue` method was deprecated in v1.5 and will be removed in v1.7." - ) - if is_overridden("get_from_queue", model): - rank_zero_deprecation( - "The `LightningModule.get_from_queue` method was deprecated in v1.5 and will be removed in v1.7." - ) - - # TODO: Delete _check_on_hpc_hooks in v1.8 def _check_on_hpc_hooks(model: "pl.LightningModule") -> None: if is_overridden("on_hpc_save", model): diff --git a/tests/tests_pytorch/deprecated_api/test_remove_1-7.py b/tests/tests_pytorch/deprecated_api/test_remove_1-7.py index 17cccbfa80..629bb9f913 100644 --- a/tests/tests_pytorch/deprecated_api/test_remove_1-7.py +++ b/tests/tests_pytorch/deprecated_api/test_remove_1-7.py @@ -34,25 +34,6 @@ from pytorch_lightning.strategies import SingleDeviceStrategy from tests_pytorch.plugins.environments.test_lsf_environment import _make_rankfile -class BoringCallbackDDPSpawnModel(BoringModel): - def add_to_queue(self, queue): - ... - - def get_from_queue(self, queue): - ... - - -def test_v1_7_0_deprecate_add_get_queue(tmpdir): - model = BoringCallbackDDPSpawnModel() - trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True) - - with pytest.deprecated_call(match=r"`LightningModule.add_to_queue` method was deprecated in v1.5"): - trainer.fit(model) - - with pytest.deprecated_call(match=r"`LightningModule.get_from_queue` method was deprecated in v1.5"): - trainer.fit(model) - - def test_v1_7_0_deprecate_lightning_distributed(tmpdir): with pytest.deprecated_call(match="LightningDistributed is deprecated in v1.5 and will be removed in v1.7."): from pytorch_lightning.distributed.dist import LightningDistributed diff --git a/tests/tests_pytorch/strategies/test_ddp_spawn_strategy.py b/tests/tests_pytorch/strategies/test_ddp_spawn_strategy.py index 9a072368b0..5af3df4613 100644 --- a/tests/tests_pytorch/strategies/test_ddp_spawn_strategy.py +++ b/tests/tests_pytorch/strategies/test_ddp_spawn_strategy.py @@ -44,14 +44,6 @@ class BoringCallbackDDPSpawnModel(BoringModel): self.log(self.name, self.val) return super().validation_step(batch, batch_idx) - def add_to_queue(self, queue) -> None: - queue.put("test_val") - return super().add_to_queue(queue) - - def get_from_queue(self, queue) -> None: - self.test_val = queue.get() - return super().get_from_queue(queue) - @RunIf(skip_windows=True) def test_ddp_cpu(): @@ -67,31 +59,13 @@ def test_ddp_cpu(): trainer.fit(model) -@RunIf(min_cuda_gpus=2) -def test_ddp_spawn_extra_parameters(tmpdir): - """Tests if device is set correctly when training for DDPSpawnStrategy and tests add_to_queue/get_from_queue - with Lightning Module (deprecated way).""" - trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True, accelerator="gpu", devices=2, strategy="ddp_spawn") - - assert isinstance(trainer.strategy, DDPSpawnStrategy) - assert trainer.strategy.root_device == torch.device("cuda:0") - - val: float = 1.0 - val_name: str = "val_acc" - model = BoringCallbackDDPSpawnModel(val_name, val) - dm = BoringDataModule() - trainer.fit(model, datamodule=dm) - assert trainer.callback_metrics[val_name] == torch.tensor(val) - assert model.test_val == "test_val" - - class CustomSpawnLauncher(_SpawnLauncher): def add_to_queue(self, trainer, queue) -> None: - queue.put("new_test_val") + queue.put("test_val") return super().add_to_queue(trainer, queue) def get_from_queue(self, trainer: Trainer, queue) -> None: - trainer.strategy.new_test_val = queue.get() + trainer.strategy.test_val = queue.get() return super().get_from_queue(trainer, queue) @@ -115,7 +89,7 @@ def test_ddp_spawn_add_get_queue(tmpdir): dm = BoringDataModule() trainer.fit(model, datamodule=dm) assert trainer.callback_metrics[val_name] == torch.tensor(val) - assert ddp_spawn_strategy.new_test_val == "new_test_val" + assert ddp_spawn_strategy.test_val == "test_val" class BoringModelDDP(BoringModel):