From 66d4ddce1c1386cf782c53949852ea4b6f622d24 Mon Sep 17 00:00:00 2001
From: AbdullahRasheed45 <abdullahRasheed45@gmail.com>
Date: Fri, 31 Jul 2026 03:21:14 +0100
Subject: [PATCH] fix(validation): correct argument validation in auroc,
 logauc, and pesq metrics

Four more instances of the same 'and' vs 'or' logical operator bug found in
the broader codebase, affecting different metric families.

- PerceptualEvaluationSpeechQuality (audio/pesq.py):
  n_processes=0 or a negative integer was accepted without raising an error.

- BinaryAUROC functional API (functional/classification/auroc.py):
  max_fpr as an out-of-range float (e.g. 2.0) was accepted without error
  because the condition was 'not isinstance(float) AND in range (0,1]'
  instead of 'not isinstance(float) OR not in range (0,1]'.

- RetrievalAUROC class API (retrieval/auroc.py):
  Same max_fpr bug as above in the class __init__.

- BinaryLogAUC / MulticlassLogAUC / MultilabelLogAUC
  (functional/classification/logauc.py):
  fpr_range validation used 'and' instead of 'or', so a list of length 2
  would bypass the tuple type check.

Fix: replace 'and' with 'or' (and restructure the max_fpr check using De
Morgan's law) so that an invalid argument raises ValueError when either the
type check or the value check fails.
---
 src/torchmetrics/audio/pesq.py                       | 2 +-
 src/torchmetrics/functional/classification/auroc.py  | 2 +-
 src/torchmetrics/functional/classification/logauc.py | 2 +-
 src/torchmetrics/retrieval/auroc.py                  | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/torchmetrics/audio/pesq.py b/src/torchmetrics/audio/pesq.py
index 38146f6c943..deef13398c4 100644
--- a/src/torchmetrics/audio/pesq.py
+++ b/src/torchmetrics/audio/pesq.py
@@ -114,7 +114,7 @@ def __init__(
         if mode not in ("wb", "nb"):
             raise ValueError(f"Expected argument `mode` to either be 'wb' or 'nb' but got {mode}")
         self.mode = mode
-        if not isinstance(n_processes, int) and n_processes <= 0:
+        if not isinstance(n_processes, int) or n_processes <= 0:
             raise ValueError(f"Expected argument `n_processes` to be an int larger than 0 but got {n_processes}")
         self.n_processes = n_processes
 
diff --git a/src/torchmetrics/functional/classification/auroc.py b/src/torchmetrics/functional/classification/auroc.py
index 1dfd752ee22..3be1c294824 100644
--- a/src/torchmetrics/functional/classification/auroc.py
+++ b/src/torchmetrics/functional/classification/auroc.py
@@ -76,7 +76,7 @@ def _binary_auroc_arg_validation(
     ignore_index: Optional[int] = None,
 ) -> None:
     _binary_precision_recall_curve_arg_validation(thresholds, ignore_index)
-    if max_fpr is not None and not isinstance(max_fpr, float) and 0 < max_fpr <= 1:
+    if max_fpr is not None and (not isinstance(max_fpr, float) or not (0 < max_fpr <= 1)):
         raise ValueError(f"Arguments `max_fpr` should be a float in range (0, 1], but got: {max_fpr}")
 
 
diff --git a/src/torchmetrics/functional/classification/logauc.py b/src/torchmetrics/functional/classification/logauc.py
index 17ff4bbbceb..2033f12c5c1 100644
--- a/src/torchmetrics/functional/classification/logauc.py
+++ b/src/torchmetrics/functional/classification/logauc.py
@@ -26,7 +26,7 @@
 
 def _validate_fpr_range(fpr_range: Tuple[float, float]) -> None:
     """Validate the `fpr_range` argument for the logauc metric."""
-    if not isinstance(fpr_range, tuple) and not len(fpr_range) == 2:
+    if not isinstance(fpr_range, tuple) or len(fpr_range) != 2:
         raise ValueError(f"The `fpr_range` should be a tuple of two floats, but got {type(fpr_range)}.")
     if not (0 <= fpr_range[0] < fpr_range[1] <= 1):
         raise ValueError(f"The `fpr_range` should be a tuple of two floats in the range [0, 1], but got {fpr_range}.")
diff --git a/src/torchmetrics/retrieval/auroc.py b/src/torchmetrics/retrieval/auroc.py
index 6d4382894a4..52e2651c343 100644
--- a/src/torchmetrics/retrieval/auroc.py
+++ b/src/torchmetrics/retrieval/auroc.py
@@ -114,7 +114,7 @@ def __init__(
         if top_k is not None and not (isinstance(top_k, int) and top_k > 0):
             raise ValueError("`top_k` has to be a positive integer or None")
         self.top_k = top_k
-        if max_fpr is not None and not isinstance(max_fpr, float) and 0 < max_fpr <= 1:
+        if max_fpr is not None and (not isinstance(max_fpr, float) or not (0 < max_fpr <= 1)):
             raise ValueError(f"Arguments `max_fpr` should be a float in range (0, 1], but got: {max_fpr}")
         self.max_fpr = max_fpr