Fix: make y optional in ignore_background (#8647)

Fixes # .

### Description

This PR addresses a TODO in `monai/metrics/active_learning_metrics.py`
by making the `y` argument optional in the `ignore_background` utility
function. This allows for cleaner code when only `y_pred` needs to be
processed, as seen in `active_learning_metrics.py`.

### Types of changes
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [x] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [x] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: Tristan Kirscher <85068746+Kirscher@users.noreply.github.com>
Signed-off-by: Eric Kerfoot <17726042+ericspod@users.noreply.github.com>
Co-authored-by: Eric Kerfoot <17726042+ericspod@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

Author: 3 people

monai/metrics/active_learning_metrics.py

@@ -129,9 +129,7 @@ def compute_variance(
     y_pred = y_pred.float()
 
     if not include_background:
-        y = y_pred
-        # TODO If this utils is made to be optional for 'y' it would be nice
-        y_pred, y = ignore_background(y_pred=y_pred, y=y)
+        y_pred, _ = ignore_background(y_pred=y_pred)
 
     # Set any values below 0 to threshold
     y_pred[y_pred <= 0] = threshold

monai/metrics/utils.py

@@ -15,7 +15,7 @@
 from collections.abc import Iterable, Sequence
 from functools import cache, partial
 from types import ModuleType
-from typing import Any
+from typing import Any, overload
 
 import numpy as np
 import torch
@@ -55,19 +55,30 @@
 ]
 
 
-def ignore_background(y_pred: NdarrayTensor, y: NdarrayTensor) -> tuple[NdarrayTensor, NdarrayTensor]:
+@overload
+def ignore_background(y_pred: NdarrayTensor, y: NdarrayTensor) -> tuple[NdarrayTensor, NdarrayTensor]: ...
+
+
+@overload
+def ignore_background(y_pred: NdarrayTensor, y: None = ...) -> tuple[NdarrayTensor, None]: ...
+
+
+def ignore_background(
+    y_pred: NdarrayTensor, y: NdarrayTensor | None = None
+) -> tuple[NdarrayTensor, NdarrayTensor | None]:
     """
     This function is used to remove background (the first channel) for `y_pred` and `y`.
 
     Args:
         y_pred: predictions. As for classification tasks,
             `y_pred` should has the shape [BN] where N is larger than 1. As for segmentation tasks,
             the shape should be [BNHW] or [BNHWD].
-        y: ground truth, the first dim is batch.
+        y: optional ground truth, the first dim is batch.
 
     """
 
-    y = y[:, 1:] if y.shape[1] > 1 else y  # type: ignore[assignment]
+    if y is not None:
+        y = y[:, 1:] if y.shape[1] > 1 else y  # type: ignore[assignment]
     y_pred = y_pred[:, 1:] if y_pred.shape[1] > 1 else y_pred  # type: ignore[assignment]
     return y_pred, y