typing: regression

CHANGELOG.md

@@ -15,7 +15,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Changed
 
 - Extend typing ([#330](https://github.com/PyTorchLightning/metrics/pull/330),
-    [#332](https://github.com/PyTorchLightning/metrics/pull/332))
+    [#332](https://github.com/PyTorchLightning/metrics/pull/332),
+    [#333](https://github.com/PyTorchLightning/metrics/pull/333))
 
 
 ### Deprecated

setup.cfg

@@ -73,16 +73,6 @@ files = torchmetrics
 disallow_untyped_defs = True
 ignore_missing_imports = True
 
-# todo: add proper typing to this module...
-[mypy-torchmetrics.image.ssim]
-ignore_errors = True
-[mypy-torchmetrics.image.psnr]
-ignore_errors = True
-
 # todo: add proper typing to this module...
 [mypy-torchmetrics.classification.*]
 ignore_errors = True
-
-# todo: add proper typing to this module...
-[mypy-torchmetrics.regression.*]
-ignore_errors = True

torchmetrics/image/psnr.py

@@ -68,6 +68,8 @@ class PSNR(Metric):
         Half precision is only support on GPU for this metric
 
     """
+    min_target: Tensor
+    max_target: Tensor
 
     def __init__(
         self,
@@ -110,7 +112,7 @@ def __init__(
         self.reduction = reduction
         self.dim = tuple(dim) if isinstance(dim, Sequence) else dim
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 
@@ -131,7 +133,7 @@ def update(self, preds: Tensor, target: Tensor) -> None:
             self.sum_squared_error.append(sum_squared_error)
             self.total.append(n_obs)
 
-    def compute(self):
+    def compute(self) -> Tensor:
         """
         Compute peak signal-to-noise ratio over state.
         """

torchmetrics/image/ssim.py

@@ -84,7 +84,7 @@ def __init__(
         self.k2 = k2
         self.reduction = reduction
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 
@@ -96,7 +96,7 @@ def update(self, preds: Tensor, target: Tensor) -> None:
         self.y_pred.append(preds)
         self.y.append(target)
 
-    def compute(self):
+    def compute(self) -> Tensor:
         """
         Computes explained variance over state.
         """

torchmetrics/regression/cosine_similarity.py

@@ -80,7 +80,7 @@ def __init__(
         self.add_state("target", [], dist_reduce_fx="cat")
         self.reduction = reduction
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update metric states with predictions and targets.
 

torchmetrics/regression/explained_variance.py

@@ -77,6 +77,11 @@ class ExplainedVariance(Metric):
         >>> explained_variance(preds, target)
         tensor([0.9677, 1.0000])
     """
+    n_obs: Tensor
+    sum_error: Tensor
+    sum_squared_error: Tensor
+    sum_target: Tensor
+    sum_squared_target: Tensor
 
     def __init__(
         self,
@@ -97,14 +102,14 @@ def __init__(
             raise ValueError(
                 f"Invalid input to argument `multioutput`. Choose one of the following: {allowed_multioutput}"
             )
-        self.multioutput = multioutput
+        self.multioutput: str = multioutput
         self.add_state("sum_error", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("sum_squared_error", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("sum_target", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("sum_squared_target", default=tensor(0.0), dist_reduce_fx="sum")
         self.add_state("n_obs", default=tensor(0.0), dist_reduce_fx="sum")
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 

torchmetrics/regression/mean_absolute_error.py

@@ -66,7 +66,7 @@ def __init__(
         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")
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 

torchmetrics/regression/mean_absolute_percentage_error.py

@@ -77,7 +77,7 @@ def __init__(
         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")
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 

torchmetrics/regression/mean_squared_error.py

@@ -71,7 +71,7 @@ def __init__(
         self.add_state("total", default=tensor(0), dist_reduce_fx="sum")
         self.squared = squared
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 

torchmetrics/regression/mean_squared_log_error.py

@@ -72,7 +72,7 @@ def __init__(
         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")
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 

torchmetrics/regression/pearson.py

@@ -77,7 +77,7 @@ def __init__(
         self.add_state("preds", default=[], dist_reduce_fx="cat")
         self.add_state("target", default=[], dist_reduce_fx="cat")
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 

torchmetrics/regression/r2score.py

@@ -123,7 +123,7 @@ def __init__(
         self.add_state("residual", default=torch.zeros(self.num_outputs), dist_reduce_fx="sum")
         self.add_state("total", default=tensor(0), dist_reduce_fx="sum")
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.
 

torchmetrics/regression/spearman.py

@@ -75,7 +75,7 @@ def __init__(
         self.add_state("preds", default=[], dist_reduce_fx="cat")
         self.add_state("target", default=[], dist_reduce_fx="cat")
 
-    def update(self, preds: Tensor, target: Tensor) -> None:
+    def update(self, preds: Tensor, target: Tensor) -> None:  # type: ignore
         """
         Update state with predictions and targets.