From 80083d7a743a393ee3dc03b4842f8cce38a408c0 Mon Sep 17 00:00:00 2001
From: AayushMainali-Github <aayushmainali.codes@gmail.com>
Date: Tue, 25 Aug 2026 13:15:44 +0000
Subject: [PATCH] Fix ElasticTransform to reject negative sigma values

---
 test/test_transforms.py                | 8 ++++++++
 test/test_transforms_v2.py             | 5 +++++
 torchvision/transforms/transforms.py   | 3 +++
 torchvision/transforms/v2/_geometry.py | 4 +++-
 4 files changed, 19 insertions(+), 1 deletion(-)

diff --git a/test/test_transforms.py b/test/test_transforms.py
index b9fa620e187..fb68427cf14 100644
--- a/test/test_transforms.py
+++ b/test/test_transforms.py
@@ -2208,6 +2208,14 @@ def test_elastic_transformation():
         transforms.ElasticTransform(alpha=2.0, sigma=[1.0, True])
     with pytest.raises(ValueError, match=r"sigma is a sequence its length should be 2"):
         transforms.ElasticTransform(alpha=2.0, sigma=[1.0, 0.0, 1.0])
+    with pytest.raises(ValueError, match=r"sigma should have non-negative values"):
+        transforms.ElasticTransform(alpha=2.0, sigma=-100.0)
+    with pytest.raises(ValueError, match=r"sigma should have non-negative values"):
+        transforms.ElasticTransform(alpha=2.0, sigma=[-100.0, -100.0])
+    with pytest.raises(ValueError, match=r"sigma should have non-negative values"):
+        transforms.ElasticTransform(alpha=2.0, sigma=[-100.0, 100.0])
+    with pytest.raises(ValueError, match=r"sigma should have non-negative values"):
+        transforms.ElasticTransform(alpha=2.0, sigma=[100.0, -100.0])
 
     t = transforms.transforms.ElasticTransform(alpha=2.0, sigma=2.0, interpolation=Image.BILINEAR)
     assert t.interpolation == transforms.InterpolationMode.BILINEAR
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index 6d9f9732552..c5f7d3382b0 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -3427,6 +3427,11 @@ def test_transform(self, make_input, size, device):
             check_v1_compatibility=check_v1_compatibility,
         )
 
+    @pytest.mark.parametrize("sigma", [-100, -100.0, [-100, -100], [-100.0, 100.0], [100.0, -100.0]])
+    def test_transform_negative_sigma(self, sigma):
+        with pytest.raises(ValueError, match="sigma should have non-negative values"):
+            transforms.ElasticTransform(sigma=sigma)
+
 
 class TestToPureTensor:
     def test_correctness(self):
diff --git a/torchvision/transforms/transforms.py b/torchvision/transforms/transforms.py
index e33b3e28194..60e2d6adde9 100644
--- a/torchvision/transforms/transforms.py
+++ b/torchvision/transforms/transforms.py
@@ -2063,6 +2063,7 @@ class ElasticTransform(torch.nn.Module):
     Args:
         alpha (float or sequence of floats): Magnitude of displacements. Default is 50.0.
         sigma (float or sequence of floats): Smoothness of displacements. Default is 5.0.
+            Values must be non-negative.
         interpolation (InterpolationMode): Desired interpolation enum defined by
             :class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.BILINEAR``.
             If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported.
@@ -2104,6 +2105,8 @@ def __init__(self, alpha=50.0, sigma=5.0, interpolation=InterpolationMode.BILINE
             sigma = [float(sigma), float(sigma)]
         if isinstance(sigma, (list, tuple)) and len(sigma) == 1:
             sigma = [sigma[0], sigma[0]]
+        if any(s < 0 for s in sigma):
+            raise ValueError(f"sigma should have non-negative values. Got {list(sigma)}")
 
         self.sigma = sigma
 
diff --git a/torchvision/transforms/v2/_geometry.py b/torchvision/transforms/v2/_geometry.py
index 278b58eae2f..dbb3fdf380c 100644
--- a/torchvision/transforms/v2/_geometry.py
+++ b/torchvision/transforms/v2/_geometry.py
@@ -1053,7 +1053,7 @@ class ElasticTransform(Transform):
         alpha (float or sequence of floats, optional): Magnitude of displacements.
             Default is 50.0. A single value is ``[alpha, alpha]``.
         sigma (float or sequence of floats, optional): Smoothness of displacements.
-            Default is 5.0. A single value is ``[sigma, sigma]``.
+            Default is 5.0. A single value is ``[sigma, sigma]``. Values must be non-negative.
         interpolation (str or InterpolationMode, optional): Desired interpolation enum defined by
             :class:`torchvision.transforms.v2.InterpolationMode`.
             Accepted string values are ``"nearest"``, ``"nearest-exact"``, ``"bilinear"``, ``"bicubic"``,
@@ -1081,6 +1081,8 @@ def __init__(
         super().__init__()
         self.alpha = _setup_number_or_seq(alpha, "alpha")
         self.sigma = _setup_number_or_seq(sigma, "sigma")
+        if any(s < 0 for s in self.sigma):
+            raise ValueError(f"sigma should have non-negative values. Got {list(self.sigma)}")
 
         self.interpolation = interpolation
         self.fill = fill