Add warning_cache.deprecation and set warning stacklevel [1/2] (#8005)

Co-authored-by: Carlos Mocholi <[email protected]>

Author: awaelchli

pytorch_lightning/callbacks/model_checkpoint.py

@@ -607,10 +607,10 @@ def _add_backward_monitor_support(self, trainer: 'pl.Trainer') -> None:
             self.save_top_k = 1
 
         if deprecation_warning:
-            warning_cache.warn(
+            warning_cache.deprecation(
                 "Relying on `self.log('val_loss', ...)` to set the ModelCheckpoint monitor is deprecated in v1.2"
                 " and will be removed in v1.4. Please, create your own `mc = ModelCheckpoint(monitor='your_monitor')`"
-                " and use it as `Trainer(callbacks=[mc])`.", DeprecationWarning
+                " and use it as `Trainer(callbacks=[mc])`.",
             )
 
     def _validate_monitor_key(self, trainer: 'pl.Trainer') -> None:

pytorch_lightning/core/lightning.py

@@ -165,10 +165,6 @@ def example_input_array(self, example: Any) -> None:
 
     @property
     def datamodule(self) -> Any:
-        rank_zero_deprecation(
-            "The `LightningModule.datamodule` property is deprecated in v1.3 and will be removed in v1.5."
-            " Access the datamodule through using `self.trainer.datamodule` instead."
-        )
         return self._datamodule
 
     @datamodule.setter

pytorch_lightning/loggers/wandb.py

@@ -115,9 +115,9 @@ def __init__(
             )
 
         if sync_step is not None:
-            warning_cache.warn(
+            warning_cache.deprecation(
                 "`WandbLogger(sync_step=(True|False))` is deprecated in v1.2.1 and will be removed in v1.5."
-                " Metrics are now logged separately and automatically synchronized.", DeprecationWarning
+                " Metrics are now logged separately and automatically synchronized."
             )
 
         super().__init__()

pytorch_lightning/plugins/training_type/deepspeed.py

@@ -30,7 +30,7 @@
 from pytorch_lightning.trainer.optimizers import _get_default_scheduler_config
 from pytorch_lightning.utilities import AMPType
 from pytorch_lightning.utilities.apply_func import apply_to_collection
-from pytorch_lightning.utilities.distributed import rank_zero_info, rank_zero_only
+from pytorch_lightning.utilities.distributed import _warn, rank_zero_info, rank_zero_only
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.imports import _DEEPSPEED_AVAILABLE
 

pytorch_lightning/profiler/pytorch.py

@@ -23,8 +23,8 @@
 from torch import nn, Tensor
 from torch.autograd.profiler import record_function
 
-from pytorch_lightning.profiler.profilers import BaseProfiler
-from pytorch_lightning.utilities.distributed import rank_zero_warn
+from pytorch_lightning.profiler import BaseProfiler
+from pytorch_lightning.utilities.distributed import rank_zero_deprecation, rank_zero_warn
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.imports import _KINETO_AVAILABLE
 
@@ -349,9 +349,9 @@ def __deprecation_check(
             record_functions = set()
 
         if profiled_functions is not None:
-            rank_zero_warn(
+            rank_zero_deprecation(
                 "`PyTorchProfiler.profiled_functions` has been renamed to"
-                " `record_functions` in v1.3 and will be removed in v1.5", DeprecationWarning
+                " `record_functions` in v1.3 and will be removed in v1.5",
             )
             if not record_functions:
                 record_functions |= set(profiled_functions)

pytorch_lightning/trainer/callback_hook.py

@@ -97,10 +97,10 @@ def on_train_epoch_end(self, outputs: EPOCH_OUTPUT):
         """
         for callback in self.callbacks:
             if is_param_in_hook_signature(callback.on_train_epoch_end, "outputs"):
-                warning_cache.warn(
+                warning_cache.deprecation(
                     "The signature of `Callback.on_train_epoch_end` has changed in v1.3."
                     " `outputs` parameter has been removed."
-                    " Support for the old signature will be removed in v1.5", DeprecationWarning
+                    " Support for the old signature will be removed in v1.5"
                 )
                 callback.on_train_epoch_end(self, self.lightning_module, outputs)
             else:

pytorch_lightning/trainer/training_loop.py

@@ -642,10 +642,10 @@ def _on_train_epoch_end_hook(self, processed_epoch_output) -> None:
             if is_overridden(hook_name, model_ref):
                 hook_fx = getattr(model_ref, hook_name)
                 if is_param_in_hook_signature(hook_fx, "outputs"):
-                    self.warning_cache.warn(
+                    self.warning_cache.deprecation(
                         "The signature of `ModelHooks.on_train_epoch_end` has changed in v1.3."
                         " `outputs` parameter has been deprecated."
-                        " Support for the old signature will be removed in v1.5", DeprecationWarning
+                        " Support for the old signature will be removed in v1.5",
                     )
                     model_ref.on_train_epoch_end(processed_epoch_output)
                 else:
@@ -944,10 +944,10 @@ def build_train_args(self, batch, batch_idx, opt_idx, hiddens):
         if len(self.trainer.optimizers) > 1:
             if self.trainer.has_arg("training_step", "optimizer_idx"):
                 if not self.trainer.lightning_module.automatic_optimization:
-                    self.warning_cache.warn(
+                    self.warning_cache.deprecation(
                         "`training_step` hook signature has changed in v1.3."
                         " `optimizer_idx` argument has been removed in case of manual optimization. Support for"
-                        " the old signature will be removed in v1.5", DeprecationWarning
+                        " the old signature will be removed in v1.5",
                     )
                 args.append(opt_idx)
             elif not self.trainer.has_arg(

pytorch_lightning/utilities/device_parser.py

@@ -16,7 +16,7 @@
 
 import torch
 
-from pytorch_lightning.utilities import _TPU_AVAILABLE, rank_zero_warn
+from pytorch_lightning.utilities import _TPU_AVAILABLE, rank_zero_deprecation
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.imports import _compare_version
 
@@ -121,12 +121,11 @@ def _normalize_parse_gpu_string_input(s: Union[int, str, List[int]]) -> Union[in
     else:
         num_gpus = int(s.strip())
         if _compare_version("pytorch_lightning", operator.lt, "1.5"):
-            rank_zero_warn(
+            rank_zero_deprecation(
                 f"Parsing of the Trainer argument gpus='{s}' (string) will change in the future."
                 " In the current version of Lightning, this will select"
                 f" CUDA device with index {num_gpus}, but from v1.5 it will select gpus"
                 f" {list(range(num_gpus))} (same as gpus={s} (int)).",
-                DeprecationWarning,
             )
             return [num_gpus]
         return num_gpus

pytorch_lightning/utilities/warnings.py

@@ -11,18 +11,23 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from pytorch_lightning.utilities.distributed import rank_zero_warn
+from pytorch_lightning.utilities.distributed import rank_zero_deprecation, rank_zero_warn
 
 
 class WarningCache:
 
     def __init__(self):
         self.warnings = set()
 
+    def clear(self):
+        self.warnings.clear()
+
     def warn(self, m, *args, **kwargs):
         if m not in self.warnings:
             self.warnings.add(m)
             rank_zero_warn(m, *args, **kwargs)
 
-    def clear(self):
-        self.warnings.clear()
+    def deprecation(self, m, *args, **kwargs):
+        if m not in self.warnings:
+            self.warnings.add(m)
+            rank_zero_deprecation(m, *args, **kwargs)

tests/deprecated_api/test_remove_1-5.py

@@ -362,15 +362,6 @@ def test_v1_5_0_trainer_gpus_str_parsing(*_):
         assert gpus == [0]
 
 
-def test_v1_5_0_datamodule_setter():
-    model = BoringModel()
-    datamodule = BoringDataModule()
-    with no_deprecated_call(match="The `LightningModule.datamodule`"):
-        model.datamodule = datamodule
-    with pytest.deprecated_call(match="The `LightningModule.datamodule`"):
-        _ = model.datamodule
-
-
 def test_v1_5_0_trainer_tbptt_steps(tmpdir):
     with pytest.deprecated_call(match="is deprecated in v1.3 and will be removed in v1.5"):
         _ = Trainer(truncated_bptt_steps=1)