Remove deprecated compute_on_step in Regression

CHANGELOG.md

@@ -38,7 +38,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Removed deprecated `compute_on_step` argument ([#962](https://github.com/PyTorchLightning/metrics/pull/962))
 
 
--
+- Removed deprecated `compute_on_step` argument in Regression ([#967](https://github.com/PyTorchLightning/metrics/pull/967))
 
 
 ### Fixed

torchmetrics/regression/cosine_similarity.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, List, Optional
+from typing import Any, Dict, List
 
 import torch
 from torch import Tensor
@@ -40,12 +40,6 @@ class CosineSimilarity(Metric):
 
     Args:
         reduction: how to reduce over the batch dimension using 'sum', 'mean' or 'none' (taking the individual scores)
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Example:
@@ -65,10 +59,9 @@ class CosineSimilarity(Metric):
     def __init__(
         self,
         reduction: Literal["mean", "sum", "none", None] = "sum",
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
         allowed_reduction = ("sum", "mean", "none", None)
         if reduction not in allowed_reduction:
             raise ValueError(f"Expected argument `reduction` to be one of {allowed_reduction} but got {reduction}")

torchmetrics/regression/explained_variance.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, Optional, Sequence, Union
+from typing import Any, Dict, Sequence, Union
 
 import torch
 from torch import Tensor, tensor
@@ -47,12 +47,6 @@ class ExplainedVariance(Metric):
             * ``'uniform_average'`` scores are uniformly averaged
             * ``'variance_weighted'`` scores are weighted by their individual variances
 
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Raises:
@@ -85,10 +79,9 @@ class ExplainedVariance(Metric):
     def __init__(
         self,
         multioutput: str = "uniform_average",
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
         allowed_multioutput = ("raw_values", "uniform_average", "variance_weighted")
         if multioutput not in allowed_multioutput:
             raise ValueError(

torchmetrics/regression/log_mse.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, Optional
+from typing import Any, Dict
 
 import torch
 from torch import Tensor, tensor
@@ -28,12 +28,6 @@ class MeanSquaredLogError(Metric):
     Where :math:`y` is a tensor of target values, and :math:`\hat{y}` is a tensor of predictions.
 
     Args:
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Example:
@@ -55,10 +49,9 @@ class MeanSquaredLogError(Metric):
 
     def __init__(
         self,
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
 
         self.add_state("sum_squared_log_error", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("total", default=tensor(0), dist_reduce_fx="sum")

torchmetrics/regression/mae.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, Optional
+from typing import Any, Dict
 
 import torch
 from torch import Tensor, tensor
@@ -28,12 +28,6 @@ class MeanAbsoluteError(Metric):
     Where :math:`y` is a tensor of target values, and :math:`\hat{y}` is a tensor of predictions.
 
     Args:
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Example:
@@ -51,10 +45,9 @@ class MeanAbsoluteError(Metric):
 
     def __init__(
         self,
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
 
         self.add_state("sum_abs_error", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("total", default=tensor(0), dist_reduce_fx="sum")

torchmetrics/regression/mape.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, Optional
+from typing import Any, Dict
 
 import torch
 from torch import Tensor, tensor
@@ -31,12 +31,6 @@ class MeanAbsolutePercentageError(Metric):
     Where :math:`y` is a tensor of target values, and :math:`\hat{y}` is a tensor of predictions.
 
     Args:
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Note:
@@ -63,10 +57,9 @@ class MeanAbsolutePercentageError(Metric):
 
     def __init__(
         self,
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
 
         self.add_state("sum_abs_per_error", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("total", default=tensor(0.0), dist_reduce_fx="sum")

torchmetrics/regression/mse.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, Optional
+from typing import Any, Dict
 
 import torch
 from torch import Tensor, tensor
@@ -29,12 +29,6 @@ class MeanSquaredError(Metric):
 
     Args:
         squared: If True returns MSE value, if False returns RMSE value.
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Example:
@@ -54,10 +48,9 @@ class MeanSquaredError(Metric):
     def __init__(
         self,
         squared: bool = True,
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
 
         self.add_state("sum_squared_error", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("total", default=tensor(0), dist_reduce_fx="sum")

torchmetrics/regression/pearson.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, List, Optional, Tuple
+from typing import Any, Dict, List, Tuple
 
 import torch
 from torch import Tensor
@@ -66,12 +66,6 @@ class PearsonCorrCoef(Metric):
     - ``target``(float tensor): ``(N,)``
 
     Args:
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Example:
@@ -96,10 +90,9 @@ class PearsonCorrCoef(Metric):
 
     def __init__(
         self,
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
 
         self.add_state("mean_x", default=torch.tensor(0.0), dist_reduce_fx=None)
         self.add_state("mean_y", default=torch.tensor(0.0), dist_reduce_fx=None)

torchmetrics/regression/r2.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, Optional
+from typing import Any, Dict
 
 import torch
 from torch import Tensor, tensor
@@ -49,13 +49,6 @@ class R2Score(Metric):
             * ``'raw_values'`` returns full set of scores
             * ``'uniform_average'`` scores are uniformly averaged
             * ``'variance_weighted'`` scores are weighted by their individual variances
-
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Raises:
@@ -91,10 +84,9 @@ def __init__(
         num_outputs: int = 1,
         adjusted: int = 0,
         multioutput: str = "uniform_average",
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
 
         self.num_outputs = num_outputs
 

torchmetrics/regression/spearman.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, List, Optional
+from typing import Any, Dict, List
 
 import torch
 from torch import Tensor
@@ -33,12 +33,6 @@ class SpearmanCorrCoef(Metric):
     on the rank variables.
 
     Args:
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Example:
@@ -57,10 +51,9 @@ class SpearmanCorrCoef(Metric):
 
     def __init__(
         self,
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
         rank_zero_warn(
             "Metric `SpearmanCorrcoef` will save all targets and predictions in the buffer."
             " For large datasets, this may lead to large memory footprint."

torchmetrics/regression/symmetric_mape.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, Optional
+from typing import Any, Dict
 
 from torch import Tensor, tensor
 
@@ -30,12 +30,6 @@ class SymmetricMeanAbsolutePercentageError(Metric):
     Where :math:`y` is a tensor of target values, and :math:`\hat{y}` is a tensor of predictions.
 
     Args:
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Note:
@@ -60,10 +54,9 @@ class SymmetricMeanAbsolutePercentageError(Metric):
 
     def __init__(
         self,
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
 
         self.add_state("sum_abs_per_error", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("total", default=tensor(0.0), dist_reduce_fx="sum")

torchmetrics/regression/tweedie_deviance.py

@@ -11,7 +11,7 @@
 # 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 typing import Any, Dict, Optional
+from typing import Any, Dict
 
 import torch
 from torch import Tensor
@@ -54,12 +54,6 @@ class TweedieDevianceScore(Metric):
             - power = 3 : Inverse Gaussian distribution. (Requires: targets > 0 and preds > 0.)
             - otherwise : Positive stable distribution. (Requires: targets > 0 and preds > 0.)
 
-        compute_on_step:
-            Forward only calls ``update()`` and returns None if this is set to False.
-
-            .. deprecated:: v0.8
-                Argument has no use anymore and will be removed v0.9.
-
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Example:
@@ -79,10 +73,9 @@ class TweedieDevianceScore(Metric):
     def __init__(
         self,
         power: float = 0.0,
-        compute_on_step: Optional[bool] = None,
         **kwargs: Dict[str, Any],
     ) -> None:
-        super().__init__(compute_on_step=compute_on_step, **kwargs)
+        super().__init__(**kwargs)
         if 0 < power < 1:
             raise ValueError(f"Deviance Score is not defined for power={power}.")