From 8105b0924b6ab85a9ef1ec96c2f562961b4a8894 Mon Sep 17 00:00:00 2001 From: Daniel Dale Date: Wed, 2 Feb 2022 15:24:08 -0800 Subject: [PATCH 1/6] create read-only property set when checkpoints loaded via Trainer.{fit,validate,test,predict}, deprecate Trainer.{validated,tested,predicted}_ckpt_path --- pytorch_lightning/trainer/trainer.py | 103 +++++++++++++++++++++--- tests/deprecated_api/test_remove_1-8.py | 10 +++ tests/trainer/test_trainer.py | 22 +++-- 3 files changed, 112 insertions(+), 23 deletions(-) diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py index 7e9f4d18801f0..c34efaebb7a91 100644 --- a/pytorch_lightning/trainer/trainer.py +++ b/pytorch_lightning/trainer/trainer.py @@ -480,10 +480,14 @@ def __init__( # default .predict() loop self.predict_loop = PredictionLoop() - # .validate() and .test() set this when they load a checkpoint - self.validated_ckpt_path: Optional[str] = None - self.tested_ckpt_path: Optional[str] = None - self.predicted_ckpt_path: Optional[str] = None + # set when a checkpoint is loaded via `Trainer.{fit,validate,test,predict}`. + self._ckpt_path: Optional[str] = None + + # .validate(), predict() and .test() set these when they load a checkpoint. They will be removed in favor of + # the unified read-only `Trainer.ckpt_path` attribute in v1.8 + self._validated_ckpt_path: Optional[str] = None # TODO: remove in v1.8 + self._tested_ckpt_path: Optional[str] = None # TODO: remove in v1.8 + self._predicted_ckpt_path: Optional[str] = None # TODO: remove in v1.8 # todo: remove in v1.7 self._weights_summary: Optional[str] = None @@ -758,7 +762,10 @@ def _fit_impl( # TODO: ckpt_path only in v2.0 ckpt_path = ckpt_path or self.resume_from_checkpoint - results = self._run(model, ckpt_path=ckpt_path) + self._ckpt_path = self.__set_ckpt_path( + ckpt_path, model_provided=model, model_connected=self.lightning_module is not None + ) + results = self._run(model, ckpt_path=self.ckpt_path) assert self.state.stopped self.training = False @@ -837,12 +844,14 @@ def _validate_impl( # links data to the trainer self._data_connector.attach_data(model, val_dataloaders=dataloaders, datamodule=datamodule) - self.validated_ckpt_path = self.__set_ckpt_path( + self._ckpt_path = self.__set_ckpt_path( ckpt_path, model_provided=model_provided, model_connected=self.lightning_module is not None ) + self._validated_ckpt_path = self.ckpt_path # TODO: remove in v1.8 + # run validate - results = self._run(model, ckpt_path=self.validated_ckpt_path) + results = self._run(model, ckpt_path=self.ckpt_path) assert self.state.stopped self.validating = False @@ -923,12 +932,14 @@ def _test_impl( # links data to the trainer self._data_connector.attach_data(model, test_dataloaders=dataloaders, datamodule=datamodule) - self.tested_ckpt_path = self.__set_ckpt_path( + self._ckpt_path = self.__set_ckpt_path( ckpt_path, model_provided=model_provided, model_connected=self.lightning_module is not None ) + self._tested_ckpt_path = self.ckpt_path # TODO: remove in v1.8 + # run test - results = self._run(model, ckpt_path=self.tested_ckpt_path) + results = self._run(model, ckpt_path=self.ckpt_path) assert self.state.stopped self.testing = False @@ -1009,11 +1020,13 @@ def _predict_impl( # links data to the trainer self._data_connector.attach_data(model, predict_dataloaders=dataloaders, datamodule=datamodule) - self.predicted_ckpt_path = self.__set_ckpt_path( + self._ckpt_path = self.__set_ckpt_path( ckpt_path, model_provided=model_provided, model_connected=self.lightning_module is not None ) - results = self._run(model, ckpt_path=self.predicted_ckpt_path) + self._predicted_ckpt_path = self.ckpt_path # TODO: remove in v1.8 + + results = self._run(model, ckpt_path=self.ckpt_path) assert self.state.stopped self.predicting = False @@ -2217,6 +2230,74 @@ def resume_from_checkpoint(self) -> Optional[Union[str, Path]]: return resume_from_checkpoint + @property + def ckpt_path(self) -> Optional[str]: + """Set to the path/URL of checkpoints loaded via :meth:`~pytorch_lightning.trainer.trainer.Trainer.fit`, + :meth:`~pytorch_lightning.trainer.trainer.Trainer.validate`, + :meth:`~pytorch_lightning.trainer.trainer.Trainer.test`, or + :meth:`~pytorch_lightning.trainer.trainer.Trainer.predict`. ``None`` otherwise.""" + return self._ckpt_path + + @property + def validated_ckpt_path(self) -> Optional[str]: + rank_zero_deprecation( + "The `Trainer.validated_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" + " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" + " `Trainer.ckpt_path` instead.", + stacklevel=5, + ) + return self._validated_ckpt_path + + @validated_ckpt_path.setter + def validated_ckpt_path(self, ckpt_path: Optional[str]) -> None: + rank_zero_deprecation( + "The `Trainer.validated_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" + " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the read-only" + " `Trainer.ckpt_path`.", + stacklevel=5, + ) + self._validated_ckpt_path = ckpt_path + + @property + def tested_ckpt_path(self) -> Optional[str]: + rank_zero_deprecation( + "The `Trainer.tested_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" + " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" + " `Trainer.ckpt_path` instead.", + stacklevel=5, + ) + return self._tested_ckpt_path + + @tested_ckpt_path.setter + def tested_ckpt_path(self, ckpt_path: Optional[str]) -> None: + rank_zero_deprecation( + "The `Trainer.tested_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" + " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the read-only" + " `Trainer.ckpt_path` instead.", + stacklevel=5, + ) + self._tested_ckpt_path = ckpt_path + + @property + def predicted_ckpt_path(self) -> Optional[str]: + rank_zero_deprecation( + "The `Trainer.predicted_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" + " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" + " `Trainer.ckpt_path` instead.", + stacklevel=5, + ) + return self._predicted_ckpt_path + + @predicted_ckpt_path.setter + def predicted_ckpt_path(self, ckpt_path: Optional[str]) -> None: + rank_zero_deprecation( + "The `Trainer.predicted_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" + " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the read-only" + " `Trainer.ckpt_path` instead.", + stacklevel=5, + ) + self._predicted_ckpt_path = ckpt_path + def save_checkpoint(self, filepath: _PATH, weights_only: bool = False) -> None: r""" Runs routine to create a checkpoint. diff --git a/tests/deprecated_api/test_remove_1-8.py b/tests/deprecated_api/test_remove_1-8.py index fa0d982478759..60a18b526e26f 100644 --- a/tests/deprecated_api/test_remove_1-8.py +++ b/tests/deprecated_api/test_remove_1-8.py @@ -146,6 +146,16 @@ def test_v1_8_0_trainer_verbose_evaluate(): trainer.verbose_evaluate = False +@pytest.mark.parametrize("fn_prefix", ["validated", "tested", "predicted"], ids=["validated", "tested", "predicted"]) +def test_v1_8_0_trainer_ckpt_path_attributes(fn_prefix: str): + test_attr = f"{fn_prefix}_ckpt_path" + trainer = Trainer() + with pytest.deprecated_call(match=f"{test_attr}` attribute was deprecated in v1.6 and will be removed in v1.8"): + _ = getattr(trainer, test_attr) + with pytest.deprecated_call(match=f"{test_attr}` attribute was deprecated in v1.6 and will be removed in v1.8"): + setattr(trainer, test_attr, "v") + + def test_v1_8_0_deprecated_trainer_should_rank_save_checkpoint(tmpdir): trainer = Trainer() with pytest.deprecated_call( diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py index 3c3dc80e252d1..a30bf9e127ebd 100644 --- a/tests/trainer/test_trainer.py +++ b/tests/trainer/test_trainer.py @@ -686,8 +686,7 @@ def predict_step(self, batch, *_): trainer.fit(model) trainer_fn = getattr(trainer, fn) - path_attr = f"{fn}{'d' if fn == 'validate' else 'ed'}_ckpt_path" - assert getattr(trainer, path_attr) is None + assert getattr(trainer, "ckpt_path") is None if ckpt_path == "best": # ckpt_path is 'best', meaning we load the best weights @@ -698,20 +697,20 @@ def predict_step(self, batch, *_): trainer_fn(model, ckpt_path=ckpt_path) else: trainer_fn(ckpt_path=ckpt_path) - assert getattr(trainer, path_attr) == trainer.checkpoint_callback.best_model_path + assert getattr(trainer, "ckpt_path") == trainer.checkpoint_callback.best_model_path trainer_fn(model, ckpt_path=ckpt_path) - assert getattr(trainer, path_attr) == trainer.checkpoint_callback.best_model_path + assert getattr(trainer, "ckpt_path") == trainer.checkpoint_callback.best_model_path elif ckpt_path is None: # ckpt_path is None, meaning we don't load any checkpoints and use the provided model trainer_fn(model, ckpt_path=ckpt_path) - assert getattr(trainer, path_attr) is None + assert getattr(trainer, "ckpt_path") is None if save_top_k > 0: # ckpt_path is None with no model provided means load the best weights with pytest.warns(UserWarning, match="The best model of the previous `fit` call will be used"): trainer_fn(ckpt_path=ckpt_path) - assert getattr(trainer, path_attr) == trainer.checkpoint_callback.best_model_path + assert getattr(trainer, "ckpt_path") == trainer.checkpoint_callback.best_model_path else: # specific checkpoint, pick one from saved ones if save_top_k == 0: @@ -724,10 +723,10 @@ def predict_step(self, batch, *_): ].absolute() ) trainer_fn(ckpt_path=ckpt_path) - assert getattr(trainer, path_attr) == ckpt_path + assert getattr(trainer, "ckpt_path") == ckpt_path trainer_fn(model, ckpt_path=ckpt_path) - assert getattr(trainer, path_attr) == ckpt_path + assert getattr(trainer, "ckpt_path") == ckpt_path @pytest.mark.parametrize("enable_checkpointing", (False, True)) @@ -758,15 +757,14 @@ def predict_step(self, batch, *_): trainer.fit(model) trainer_fn = getattr(trainer, fn) - path_attr = f"{fn}{'d' if fn == 'validate' else 'ed'}_ckpt_path" - assert getattr(trainer, path_attr) is None + assert getattr(trainer, "ckpt_path") is None if enable_checkpointing: trainer_fn(ckpt_path="best") - assert getattr(trainer, path_attr) == trainer.checkpoint_callback.best_model_path + assert getattr(trainer, "ckpt_path") == trainer.checkpoint_callback.best_model_path trainer_fn(model, ckpt_path="best") - assert getattr(trainer, path_attr) == trainer.checkpoint_callback.best_model_path + assert getattr(trainer, "ckpt_path") == trainer.checkpoint_callback.best_model_path else: with pytest.raises(MisconfigurationException, match="`ModelCheckpoint` is not configured."): trainer_fn(ckpt_path="best") From ff405eb788ef08c50bbe9427fafceab06b44c59e Mon Sep 17 00:00:00 2001 From: Daniel Dale Date: Wed, 2 Feb 2022 15:38:12 -0800 Subject: [PATCH 2/6] change `BaseFinetuning.__apply_mapping_to_param_groups` to protected instead of private and minor refactor of finetuning_callback test --- pytorch_lightning/callbacks/finetuning.py | 8 ++-- tests/callbacks/test_finetuning_callback.py | 50 +++++++++++---------- 2 files changed, 30 insertions(+), 28 deletions(-) diff --git a/pytorch_lightning/callbacks/finetuning.py b/pytorch_lightning/callbacks/finetuning.py index 4a2ff06ef2767..36a16b69523de 100644 --- a/pytorch_lightning/callbacks/finetuning.py +++ b/pytorch_lightning/callbacks/finetuning.py @@ -98,7 +98,7 @@ def on_fit_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") - if self._restarting: named_parameters = dict(pl_module.named_parameters()) for opt_idx, optimizer in enumerate(trainer.optimizers): - param_groups = self.__apply_mapping_to_param_groups( + param_groups = self._apply_mapping_to_param_groups( self._internal_optimizer_metadata[opt_idx], named_parameters ) optimizer.param_groups = param_groups @@ -244,7 +244,7 @@ def on_before_accelerator_backend_setup(self, trainer: "pl.Trainer", pl_module: self.freeze_before_training(pl_module) @staticmethod - def __apply_mapping_to_param_groups(param_groups: List[Dict[str, Any]], mapping: dict) -> List[Dict[str, Any]]: + def _apply_mapping_to_param_groups(param_groups: List[Dict[str, Any]], mapping: dict) -> List[Dict[str, Any]]: output = [] for g in param_groups: # skip params to save memory @@ -262,13 +262,13 @@ def _store( ) -> None: mapping = {p: n for n, p in pl_module.named_parameters()} if opt_idx not in self._internal_optimizer_metadata: - self._internal_optimizer_metadata[opt_idx] = self.__apply_mapping_to_param_groups( + self._internal_optimizer_metadata[opt_idx] = self._apply_mapping_to_param_groups( current_param_groups, mapping ) elif num_param_groups != len(current_param_groups): # save new param_groups possibly created by the users. self._internal_optimizer_metadata[opt_idx].extend( - self.__apply_mapping_to_param_groups(current_param_groups[num_param_groups:], mapping) + self._apply_mapping_to_param_groups(current_param_groups[num_param_groups:], mapping) ) def on_train_epoch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: diff --git a/tests/callbacks/test_finetuning_callback.py b/tests/callbacks/test_finetuning_callback.py index d282288390b01..d37f5972f18d3 100644 --- a/tests/callbacks/test_finetuning_callback.py +++ b/tests/callbacks/test_finetuning_callback.py @@ -287,34 +287,36 @@ def configure_optimizers(self): trainer.fit(model) -def test_complex_nested_model(): - """Test flattening, freezing, and thawing of models which contain parent (non-leaf) modules with parameters - directly themselves rather than exclusively their submodules containing parameters.""" +class ConvBlock(nn.Module): + def __init__(self, in_channels, out_channels): + super().__init__() + self.conv = nn.Conv2d(in_channels, out_channels, 3) + self.act = nn.ReLU() + self.bn = nn.BatchNorm2d(out_channels) - class ConvBlock(nn.Module): - def __init__(self, in_channels, out_channels): - super().__init__() - self.conv = nn.Conv2d(in_channels, out_channels, 3) - self.act = nn.ReLU() - self.bn = nn.BatchNorm2d(out_channels) + def forward(self, x): + x = self.conv(x) + x = self.act(x) + return self.bn(x) - def forward(self, x): - x = self.conv(x) - x = self.act(x) - return self.bn(x) - class ConvBlockParam(nn.Module): - def __init__(self, in_channels, out_channels): - super().__init__() - self.module_dict = nn.ModuleDict({"conv": nn.Conv2d(in_channels, out_channels, 3), "act": nn.ReLU()}) - # add trivial test parameter to convblock to validate parent (non-leaf) module parameter handling - self.parent_param = nn.Parameter(torch.zeros((1), dtype=torch.float)) - self.bn = nn.BatchNorm2d(out_channels) +class ConvBlockParam(nn.Module): + def __init__(self, in_channels, out_channels): + super().__init__() + self.module_dict = nn.ModuleDict({"conv": nn.Conv2d(in_channels, out_channels, 3), "act": nn.ReLU()}) + # add trivial test parameter to convblock to validate parent (non-leaf) module parameter handling + self.parent_param = nn.Parameter(torch.zeros((1), dtype=torch.float)) + self.bn = nn.BatchNorm2d(out_channels) - def forward(self, x): - x = self.module_dict["conv"](x) - x = self.module_dict["act"](x) - return self.bn(x) + def forward(self, x): + x = self.module_dict["conv"](x) + x = self.module_dict["act"](x) + return self.bn(x) + + +def test_complex_nested_model(): + """Test flattening, freezing, and thawing of models which contain parent (non-leaf) modules with parameters + directly themselves rather than exclusively their submodules containing parameters.""" model = nn.Sequential( OrderedDict( From 4008b86dfb3e3bcdc915e71d7313e04701fe8a42 Mon Sep 17 00:00:00 2001 From: Daniel Dale Date: Wed, 2 Feb 2022 15:38:48 -0800 Subject: [PATCH 3/6] update changelog --- CHANGELOG.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 7a2b32ac44cdf..9a09184202866 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -77,6 +77,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). ### Changed +- Deprecated `Trainer.{validated,tested,predicted}_ckpt_path` and replaced with read-only property `Trainer.ckpt_path` set when checkpoints loaded via `Trainer.{fit,validate,test,predict}` ([#11696](https://github.com/PyTorchLightning/pytorch-lightning/pull/11696)) + + - Set the `prog_bar` flag to False in `LightningModule.log_grad_norm` ([#11472](https://github.com/PyTorchLightning/pytorch-lightning/pull/11472)) From ac7109d7355160289faf594742e1d485f8862cdf Mon Sep 17 00:00:00 2001 From: Dan Dale Date: Wed, 2 Feb 2022 19:08:25 -0800 Subject: [PATCH 4/6] Update tests/deprecated_api/test_remove_1-8.py MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Carlos Mocholí --- tests/deprecated_api/test_remove_1-8.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/deprecated_api/test_remove_1-8.py b/tests/deprecated_api/test_remove_1-8.py index 60a18b526e26f..168a8bc098b75 100644 --- a/tests/deprecated_api/test_remove_1-8.py +++ b/tests/deprecated_api/test_remove_1-8.py @@ -146,7 +146,7 @@ def test_v1_8_0_trainer_verbose_evaluate(): trainer.verbose_evaluate = False -@pytest.mark.parametrize("fn_prefix", ["validated", "tested", "predicted"], ids=["validated", "tested", "predicted"]) +@pytest.mark.parametrize("fn_prefix", ["validated", "tested", "predicted"]) def test_v1_8_0_trainer_ckpt_path_attributes(fn_prefix: str): test_attr = f"{fn_prefix}_ckpt_path" trainer = Trainer() From 64f46e77680610838fa0b38f5456ba59fdec626b Mon Sep 17 00:00:00 2001 From: Daniel Dale Date: Thu, 3 Feb 2022 10:45:01 -0800 Subject: [PATCH 5/6] move changelog entry to recommended section --- CHANGELOG.md | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 9a09184202866..c57ed42f84d0f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -77,9 +77,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). ### Changed -- Deprecated `Trainer.{validated,tested,predicted}_ckpt_path` and replaced with read-only property `Trainer.ckpt_path` set when checkpoints loaded via `Trainer.{fit,validate,test,predict}` ([#11696](https://github.com/PyTorchLightning/pytorch-lightning/pull/11696)) - - - Set the `prog_bar` flag to False in `LightningModule.log_grad_norm` ([#11472](https://github.com/PyTorchLightning/pytorch-lightning/pull/11472)) @@ -233,6 +230,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). ### Deprecated +- Deprecated `Trainer.{validated,tested,predicted}_ckpt_path` and replaced with read-only property `Trainer.ckpt_path` set when checkpoints loaded via `Trainer.{fit,validate,test,predict}` ([#11696](https://github.com/PyTorchLightning/pytorch-lightning/pull/11696)) + - Deprecated `ClusterEnvironment.master_{address,port}` in favor of `ClusterEnvironment.main_{address,port}` ([#10103](https://github.com/PyTorchLightning/pytorch-lightning/pull/10103)) From 029fd451ae3f4dfa4d50005b9e8b6686691a991e Mon Sep 17 00:00:00 2001 From: Daniel Dale Date: Fri, 4 Feb 2022 19:43:57 -0800 Subject: [PATCH 6/6] clarify docstring language per recommendation --- pytorch_lightning/trainer/trainer.py | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py index c34efaebb7a91..1d3982cd2c960 100644 --- a/pytorch_lightning/trainer/trainer.py +++ b/pytorch_lightning/trainer/trainer.py @@ -2232,7 +2232,7 @@ def resume_from_checkpoint(self) -> Optional[Union[str, Path]]: @property def ckpt_path(self) -> Optional[str]: - """Set to the path/URL of checkpoints loaded via :meth:`~pytorch_lightning.trainer.trainer.Trainer.fit`, + """Set to the path/URL of a checkpoint loaded via :meth:`~pytorch_lightning.trainer.trainer.Trainer.fit`, :meth:`~pytorch_lightning.trainer.trainer.Trainer.validate`, :meth:`~pytorch_lightning.trainer.trainer.Trainer.test`, or :meth:`~pytorch_lightning.trainer.trainer.Trainer.predict`. ``None`` otherwise.""" @@ -2242,7 +2242,7 @@ def ckpt_path(self) -> Optional[str]: def validated_ckpt_path(self) -> Optional[str]: rank_zero_deprecation( "The `Trainer.validated_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" - " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" + " path of a checkpoint loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" " `Trainer.ckpt_path` instead.", stacklevel=5, ) @@ -2252,8 +2252,8 @@ def validated_ckpt_path(self) -> Optional[str]: def validated_ckpt_path(self, ckpt_path: Optional[str]) -> None: rank_zero_deprecation( "The `Trainer.validated_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" - " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the read-only" - " `Trainer.ckpt_path`.", + " path of a checkpoint loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the" + " read-only `Trainer.ckpt_path`.", stacklevel=5, ) self._validated_ckpt_path = ckpt_path @@ -2262,7 +2262,7 @@ def validated_ckpt_path(self, ckpt_path: Optional[str]) -> None: def tested_ckpt_path(self) -> Optional[str]: rank_zero_deprecation( "The `Trainer.tested_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" - " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" + " path of a checkpoint loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" " `Trainer.ckpt_path` instead.", stacklevel=5, ) @@ -2272,8 +2272,8 @@ def tested_ckpt_path(self) -> Optional[str]: def tested_ckpt_path(self, ckpt_path: Optional[str]) -> None: rank_zero_deprecation( "The `Trainer.tested_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" - " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the read-only" - " `Trainer.ckpt_path` instead.", + " path of a checkpoint loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the" + " read-only `Trainer.ckpt_path` instead.", stacklevel=5, ) self._tested_ckpt_path = ckpt_path @@ -2282,7 +2282,7 @@ def tested_ckpt_path(self, ckpt_path: Optional[str]) -> None: def predicted_ckpt_path(self) -> Optional[str]: rank_zero_deprecation( "The `Trainer.predicted_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" - " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" + " path of a checkpoint loaded via `Trainer.{fit,validate,test,predict}` should be accessed via" " `Trainer.ckpt_path` instead.", stacklevel=5, ) @@ -2292,8 +2292,8 @@ def predicted_ckpt_path(self) -> Optional[str]: def predicted_ckpt_path(self, ckpt_path: Optional[str]) -> None: rank_zero_deprecation( "The `Trainer.predicted_ckpt_path` attribute was deprecated in v1.6 and will be removed in v1.8. The" - " path of checkpoints loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the read-only" - " `Trainer.ckpt_path` instead.", + " path of a checkpoint loaded via `Trainer.{fit,validate,test,predict}` should be accessed via the" + " read-only `Trainer.ckpt_path` instead.", stacklevel=5, ) self._predicted_ckpt_path = ckpt_path