prune warning & deprecation wrapper (#6540)

* docs

* wrapper

* test

* count

* flake8

(cherry picked from commit 555a6fe)

pytorch_lightning/core/step_result.py

@@ -20,8 +20,8 @@
 
 import torch
 from torch import Tensor
+from torchmetrics import Metric
 
-from pytorch_lightning.metrics import Metric
 from pytorch_lightning.utilities.distributed import sync_ddp_if_available
 
 

pytorch_lightning/metrics/classification/accuracy.py

@@ -14,9 +14,9 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.accuracy import _accuracy_compute, _accuracy_update
-from pytorch_lightning.metrics.metric import Metric
 
 
 class Accuracy(Metric):

pytorch_lightning/metrics/classification/auc.py

@@ -14,9 +14,9 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.auc import _auc_compute, _auc_update
-from pytorch_lightning.metrics.metric import Metric
 from pytorch_lightning.utilities import rank_zero_warn
 
 

pytorch_lightning/metrics/classification/auroc.py

@@ -15,9 +15,9 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.auroc import _auroc_compute, _auroc_update
-from pytorch_lightning.metrics.metric import Metric
 from pytorch_lightning.utilities import rank_zero_warn
 
 

pytorch_lightning/metrics/classification/average_precision.py

@@ -14,9 +14,9 @@
 from typing import Any, List, Optional, Union
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.average_precision import _average_precision_compute, _average_precision_update
-from pytorch_lightning.metrics.metric import Metric
 from pytorch_lightning.utilities import rank_zero_warn
 
 

pytorch_lightning/metrics/classification/confusion_matrix.py

@@ -14,9 +14,9 @@
 from typing import Any, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.confusion_matrix import _confusion_matrix_compute, _confusion_matrix_update
-from pytorch_lightning.metrics.metric import Metric
 
 
 class ConfusionMatrix(Metric):

pytorch_lightning/metrics/classification/f_beta.py

@@ -14,9 +14,9 @@
 from typing import Any, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.f_beta import _fbeta_compute, _fbeta_update
-from pytorch_lightning.metrics.metric import Metric
 from pytorch_lightning.utilities import rank_zero_warn
 
 

pytorch_lightning/metrics/classification/hamming_distance.py

@@ -14,9 +14,9 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.hamming_distance import _hamming_distance_compute, _hamming_distance_update
-from pytorch_lightning.metrics.metric import Metric
 
 
 class HammingDistance(Metric):

pytorch_lightning/metrics/classification/precision_recall_curve.py

@@ -14,12 +14,12 @@
 from typing import Any, List, Optional, Tuple, Union
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.precision_recall_curve import (
     _precision_recall_curve_compute,
     _precision_recall_curve_update,
 )
-from pytorch_lightning.metrics.metric import Metric
 from pytorch_lightning.utilities import rank_zero_warn
 
 

pytorch_lightning/metrics/classification/roc.py

@@ -14,9 +14,9 @@
 from typing import Any, List, Optional, Tuple, Union
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.roc import _roc_compute, _roc_update
-from pytorch_lightning.metrics.metric import Metric
 from pytorch_lightning.utilities import rank_zero_warn
 
 

pytorch_lightning/metrics/classification/stat_scores.py

@@ -14,9 +14,9 @@
 from typing import Any, Callable, Optional, Tuple
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.stat_scores import _stat_scores_compute, _stat_scores_update
-from pytorch_lightning.metrics.metric import Metric
 
 
 class StatScores(Metric):

pytorch_lightning/metrics/compositional.py

@@ -21,10 +21,9 @@
 
 
 class CompositionalMetric(__CompositionalMetric):
-    r"""
-    This implementation refers to :class:`~torchmetrics.metric.CompositionalMetric`.
-
-    .. warning:: This metric is deprecated, use ``torchmetrics.metric.CompositionalMetric``. Will be removed in v1.5.0.
+    """
+    .. deprecated::
+        Use :class:`torchmetrics.metric.CompositionalMetric`. Will be removed in v1.5.0.
     """
 
     def __init__(
@@ -34,7 +33,7 @@ def __init__(
         metric_b: Union[Metric, int, float, torch.Tensor, None],
     ):
         rank_zero_warn(
-            "This `Metric` was deprecated since v1.3.0 in favor of `torchmetrics.Metric`."
-            " It will be removed in v1.5.0", DeprecationWarning
+            "This `CompositionalMetric` was deprecated since v1.3.0 in favor of"
+            " `torchmetrics.metric.CompositionalMetric`. It will be removed in v1.5.0", DeprecationWarning
         )
         super().__init__(operator=operator, metric_a=metric_a, metric_b=metric_b)

pytorch_lightning/metrics/metric.py

@@ -13,17 +13,17 @@
 # limitations under the License.
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
-from torchmetrics import Metric as __Metric
-from torchmetrics import MetricCollection as __MetricCollection
+from torchmetrics import Metric as _Metric
+from torchmetrics.collections import MetricCollection as _MetricCollection
 
+from pytorch_lightning.utilities.deprecation import deprecated
 from pytorch_lightning.utilities.distributed import rank_zero_warn
 
 
-class Metric(__Metric):
+class Metric(_Metric):
     r"""
-    This implementation refers to :class:`~torchmetrics.Metric`.
-
-    .. warning:: This metric is deprecated, use ``torchmetrics.Metric``. Will be removed in v1.5.0.
+    .. deprecated::
+        Use :class:`torchmetrics.Metric`. Will be removed in v1.5.0.
     """
 
     def __init__(
@@ -45,16 +45,12 @@ def __init__(
         )
 
 
-class MetricCollection(__MetricCollection):
-    r"""
-    This implementation refers to :class:`~torchmetrics.MetricCollection`.
-
-    .. warning:: This metric is deprecated, use ``torchmetrics.MetricCollection``. Will be removed in v1.5.0.
+class MetricCollection(_MetricCollection):
+    """
+    .. deprecated::
+        Use :class:`torchmetrics.MetricCollection`. Will be removed in v1.5.0.
     """
 
+    @deprecated(target=_MetricCollection, ver_deprecate="1.3.0", ver_remove="1.5.0")
     def __init__(self, metrics: Union[List[Metric], Tuple[Metric], Dict[str, Metric]]):
-        rank_zero_warn(
-            "This `MetricCollection` was deprecated since v1.3.0 in favor of `torchmetrics.MetricCollection`."
-            " It will be removed in v1.5.0", DeprecationWarning
-        )
-        super().__init__(metrics=metrics)
+        pass

pytorch_lightning/metrics/regression/explained_variance.py

@@ -14,12 +14,12 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.explained_variance import (
     _explained_variance_compute,
     _explained_variance_update,
 )
-from pytorch_lightning.metrics.metric import Metric
 from pytorch_lightning.utilities import rank_zero_warn
 
 

pytorch_lightning/metrics/regression/mean_absolute_error.py

@@ -14,12 +14,12 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.mean_absolute_error import (
     _mean_absolute_error_compute,
     _mean_absolute_error_update,
 )
-from pytorch_lightning.metrics.metric import Metric
 
 
 class MeanAbsoluteError(Metric):

pytorch_lightning/metrics/regression/mean_squared_error.py

@@ -14,12 +14,12 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.mean_squared_error import (
     _mean_squared_error_compute,
     _mean_squared_error_update,
 )
-from pytorch_lightning.metrics.metric import Metric
 
 
 class MeanSquaredError(Metric):

pytorch_lightning/metrics/regression/mean_squared_log_error.py

@@ -14,12 +14,12 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.mean_squared_log_error import (
     _mean_squared_log_error_compute,
     _mean_squared_log_error_update,
 )
-from pytorch_lightning.metrics.metric import Metric
 
 
 class MeanSquaredLogError(Metric):

pytorch_lightning/metrics/regression/psnr.py

@@ -14,10 +14,10 @@
 from typing import Any, Optional, Sequence, Tuple, Union
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning import utilities
 from pytorch_lightning.metrics.functional.psnr import _psnr_compute, _psnr_update
-from pytorch_lightning.metrics.metric import Metric
 
 
 class PSNR(Metric):

pytorch_lightning/metrics/regression/r2score.py

@@ -14,9 +14,9 @@
 from typing import Any, Callable, Optional
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.r2score import _r2score_compute, _r2score_update
-from pytorch_lightning.metrics.metric import Metric
 
 
 class R2Score(Metric):

pytorch_lightning/metrics/regression/ssim.py

@@ -14,9 +14,9 @@
 from typing import Any, Optional, Sequence
 
 import torch
+from torchmetrics import Metric
 
 from pytorch_lightning.metrics.functional.ssim import _ssim_compute, _ssim_update
-from pytorch_lightning.metrics.metric import Metric
 from pytorch_lightning.utilities import rank_zero_warn
 
 

pytorch_lightning/trainer/connectors/logger_connector/metrics_holder.py

@@ -15,8 +15,7 @@
 from typing import Any
 
 import torch
-
-from pytorch_lightning.metrics.metric import Metric
+from torchmetrics import Metric
 
 
 class MetricsHolder:

pytorch_lightning/utilities/deprecation.py

@@ -0,0 +1,73 @@
+# Copyright The PyTorch Lightning team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# 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.
+import inspect
+from functools import wraps
+from typing import Any, Callable, List, Tuple
+
+from pytorch_lightning.utilities import rank_zero_warn
+
+
+def get_func_arguments_and_types(func: Callable) -> List[Tuple[str, Tuple, Any]]:
+    """Parse function arguments, types and default values
+
+    Example:
+        >>> get_func_arguments_and_types(get_func_arguments_and_types)
+        [('func', typing.Callable, <class 'inspect._empty'>)]
+    """
+    func_default_params = inspect.signature(func).parameters
+    name_type_default = []
+    for arg in func_default_params:
+        arg_type = func_default_params[arg].annotation
+        arg_default = func_default_params[arg].default
+        name_type_default.append((arg, arg_type, arg_default))
+    return name_type_default
+
+
+def deprecated(target: Callable, ver_deprecate: str = "", ver_remove: str = "") -> Callable:
+    """
+    Decorate a function or class ``__init__`` with warning message
+     and pass all arguments directly to the target class/method.
+     """
+
+    def inner_function(func):
+
+        @wraps(func)
+        def wrapped_fn(*args, **kwargs):
+            is_class = inspect.isclass(target)
+            target_func = target.__init__ if is_class else target
+            # warn user only once in lifetime
+            if not getattr(inner_function, 'warned', False):
+                target_str = f'{target.__module__}.{target.__name__}'
+                func_name = func.__qualname__.split('.')[-2] if is_class else func.__name__
+                rank_zero_warn(
+                    f"The `{func_name}` was deprecated since v{ver_deprecate} in favor of `{target_str}`."
+                    f" It will be removed in v{ver_remove}.", DeprecationWarning
+                )
+                inner_function.warned = True
+
+            if args:  # in case any args passed move them to kwargs
+                # parse only the argument names
+                cls_arg_names = [arg[0] for arg in get_func_arguments_and_types(func)]
+                # convert args to kwargs
+                kwargs.update({k: v for k, v in zip(cls_arg_names, args)})
+
+            target_args = [arg[0] for arg in get_func_arguments_and_types(target_func)]
+            assert all(arg in target_args for arg in kwargs), \
+                "Failed mapping, arguments missing in target func: %s" % [arg not in target_args for arg in kwargs]
+            # all args were already moved to kwargs
+            return target_func(**kwargs)
+
+        return wrapped_fn
+
+    return inner_function

tests/deprecated_api/test_remove_1-5_metrics.py

@@ -16,6 +16,7 @@
 import pytest
 import torch
 
+from pytorch_lightning.metrics import Accuracy, MetricCollection
 from pytorch_lightning.metrics.utils import get_num_classes, select_topk, to_categorical, to_onehot
 
 
@@ -34,3 +35,14 @@ def test_v1_5_0_metrics_utils():
     x = torch.tensor([[0.2, 0.5], [0.9, 0.1]])
     with pytest.deprecated_call(match="It will be removed in v1.5.0"):
         assert torch.equal(to_categorical(x), torch.Tensor([1, 0]).to(int))
+
+
+def test_v1_5_0_metrics_collection():
+    target = torch.tensor([0, 2, 0, 2, 0, 1, 0, 2])
+    preds = torch.tensor([2, 1, 2, 0, 1, 2, 2, 2])
+    with pytest.deprecated_call(
+        match="The `MetricCollection` was deprecated since v1.3.0 in favor"
+        " of `torchmetrics.collections.MetricCollection`. It will be removed in v1.5.0"
+    ):
+        metrics = MetricCollection([Accuracy()])
+    assert metrics(preds, target) == {'Accuracy': torch.Tensor([0.1250])[0]}

tests/metrics/test_metric_lightning.py

@@ -1,7 +1,7 @@
 import torch
+from torchmetrics import Metric, MetricCollection
 
 from pytorch_lightning import Trainer
-from pytorch_lightning.metrics import Metric, MetricCollection
 from tests.helpers.boring_model import BoringModel