diff --git a/torchvision/transforms/v2/functional/_geometry.py b/torchvision/transforms/v2/functional/_geometry.py
index c9551c9eea4..b9124f280bd 100644
--- a/torchvision/transforms/v2/functional/_geometry.py
+++ b/torchvision/transforms/v2/functional/_geometry.py
@@ -190,17 +190,14 @@ def resize_image_tensor(
         if interpolation == InterpolationMode.NEAREST or interpolation == InterpolationMode.NEAREST_EXACT:
             # uint8 dtype can be included for cpu and cuda input if nearest mode
             acceptable_dtypes.append(torch.uint8)
-        elif interpolation == InterpolationMode.BILINEAR and image.device.type == "cpu":
+        elif (
+            interpolation == InterpolationMode.BILINEAR
+            and image.device.type == "cpu"
+            and "AVX2" in torch.backends.cpu.get_cpu_capability()
+        ):
             # uint8 dtype support for bilinear mode is limited to cpu and
             # according to our benchmarks non-AVX CPUs should prefer u8->f32->interpolate->u8 path
-            if "AVX2" in torch.backends.cpu.get_cpu_capability():
-                acceptable_dtypes.append(torch.uint8)
-
-                # TODO: Remove when https://github.com/pytorch/pytorch/pull/101136 is landed
-                if dtype == torch.uint8 and not (
-                    image.is_contiguous() or image.is_contiguous(memory_format=torch.channels_last)
-                ):
-                    image = image.contiguous(memory_format=torch.channels_last)
+            acceptable_dtypes.append(torch.uint8)
 
         strides = image.stride()
         if image.is_contiguous(memory_format=torch.channels_last) and image.shape[0] == 1 and numel != strides[0]: