drop deprecated fbeta metrics (#5322)

* drop deprecated fbeta metrics

* flake8

* imports

* chlog

CHANGELOG.md

@@ -32,6 +32,11 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Removed
 
+- Removed deprecated checkpoint argument `filepath` ([#5321](https://github.com/PyTorchLightning/pytorch-lightning/pull/5321))
+
+
+- Removed deprecated `Fbeta`, `f1_score` and `fbeta_score` metrics ([#5322](https://github.com/PyTorchLightning/pytorch-lightning/pull/5322))
+
 
 ### Fixed
 

pytorch_lightning/metrics/classification/__init__.py

@@ -14,7 +14,7 @@
 from pytorch_lightning.metrics.classification.accuracy import Accuracy  # noqa: F401
 from pytorch_lightning.metrics.classification.average_precision import AveragePrecision  # noqa: F401
 from pytorch_lightning.metrics.classification.confusion_matrix import ConfusionMatrix  # noqa: F401
-from pytorch_lightning.metrics.classification.f_beta import FBeta, Fbeta, F1  # noqa: F401
+from pytorch_lightning.metrics.classification.f_beta import FBeta, F1  # noqa: F401
 from pytorch_lightning.metrics.classification.hamming_distance import HammingDistance  # noqa: F401
 from pytorch_lightning.metrics.classification.precision_recall import Precision, Recall  # noqa: F401
 from pytorch_lightning.metrics.classification.precision_recall_curve import PrecisionRecallCurve  # noqa: F401

pytorch_lightning/metrics/classification/f_beta.py

@@ -132,34 +132,6 @@ class FBeta(Metric):
                               self.actual_positives, self.beta, self.average)
 
 
-# todo: remove in v1.2
-class Fbeta(FBeta):
-    r"""
-    Computes `F-score <https://en.wikipedia.org/wiki/F-score>`_
-
-    .. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.classification.f_beta.FBeta`
-    """
-    def __init__(
-        self,
-        num_classes: int,
-        beta: float = 1.0,
-        threshold: float = 0.5,
-        average: str = "micro",
-        multilabel: bool = False,
-        compute_on_step: bool = True,
-        dist_sync_on_step: bool = False,
-        process_group: Optional[Any] = None,
-    ):
-        rank_zero_warn(
-            "This `Fbeta` was deprecated in v1.0.x in favor of"
-            " `from pytorch_lightning.metrics.classification.f_beta import FBeta`."
-            " It will be removed in v1.2.0", DeprecationWarning
-        )
-        super().__init__(
-            num_classes, beta, threshold, average, multilabel, compute_on_step, dist_sync_on_step, process_group
-        )
-
-
 class F1(FBeta):
     """
     Computes F1 metric. F1 metrics correspond to a harmonic mean of the

pytorch_lightning/metrics/functional/__init__.py

@@ -16,8 +16,6 @@ from pytorch_lightning.metrics.functional.classification import (  # noqa: F401
     auc,
     auroc,
     dice_score,
-    f1_score,
-    fbeta_score,
     get_num_classes,
     iou,
     multiclass_auroc,

pytorch_lightning/metrics/functional/classification.py

@@ -18,7 +18,6 @@ import torch
 from distutils.version import LooseVersion
 
 from pytorch_lightning.metrics.functional.average_precision import average_precision as __ap
-from pytorch_lightning.metrics.functional.f_beta import fbeta as __fb, f1 as __f1
 from pytorch_lightning.metrics.functional.precision_recall_curve import (
     _binary_clf_curve,
     precision_recall_curve as __prc
@@ -837,48 +836,3 @@ def average_precision(
         " It will be removed in v1.3.0", DeprecationWarning
     )
     return __ap(preds=pred, target=target, sample_weights=sample_weight, pos_label=pos_label)
-
-
-# todo: remove in 1.2
-def fbeta_score(
-        pred: torch.Tensor,
-        target: torch.Tensor,
-        beta: float,
-        num_classes: Optional[int] = None,
-        class_reduction: str = 'micro',
-) -> torch.Tensor:
-    """
-    Computes the F-beta score which is a weighted harmonic mean of precision and recall.
-
-    .. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.functional.f_beta.fbeta`
-    """
-    rank_zero_warn(
-        "This `average_precision` was deprecated in v1.0.x in favor of"
-        " `from pytorch_lightning.metrics.functional.f_beta import fbeta`."
-        " It will be removed in v1.2.0", DeprecationWarning
-    )
-    if num_classes is None:
-        num_classes = get_num_classes(pred, target)
-    return __fb(preds=pred, target=target, beta=beta, num_classes=num_classes, average=class_reduction)
-
-
-# todo: remove in 1.2
-def f1_score(
-        pred: torch.Tensor,
-        target: torch.Tensor,
-        num_classes: Optional[int] = None,
-        class_reduction: str = 'micro',
-) -> torch.Tensor:
-    """
-    Computes the F1-score (a.k.a F-measure), which is the harmonic mean of the precision and recall.
-
-    .. warning :: Deprecated in favor of :func:`~pytorch_lightning.metrics.functional.f_beta.f1`
-    """
-    rank_zero_warn(
-        "This `average_precision` was deprecated in v1.0.x in favor of"
-        " `from pytorch_lightning.metrics.functional.f_beta import f1`."
-        " It will be removed in v1.2.0", DeprecationWarning
-    )
-    if num_classes is None:
-        num_classes = get_num_classes(pred, target)
-    return __f1(preds=pred, target=target, num_classes=num_classes, average=class_reduction)

tests/deprecated_api/test_remove_1-2.py

@@ -12,20 +12,3 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Test deprecated functionality which will be removed in vX.Y.Z"""
-
-import pytest
-import torch
-
-
-def test_v1_2_0_deprecated_metrics():
-    from pytorch_lightning.metrics.classification import Fbeta
-    from pytorch_lightning.metrics.functional.classification import f1_score, fbeta_score
-
-    with pytest.deprecated_call(match='will be removed in v1.2'):
-        Fbeta(2)
-
-    with pytest.deprecated_call(match='will be removed in v1.2'):
-        fbeta_score(torch.tensor([0, 1, 2, 3]), torch.tensor([0, 1, 2, 1]), 0.2)
-
-    with pytest.deprecated_call(match='will be removed in v1.2'):
-        f1_score(torch.tensor([0, 1, 0, 1]), torch.tensor([0, 1, 0, 0]))