diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index 4f8d0027bd6..9cba49440d1 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -7,6 +7,7 @@
 import pickle
 import random
 import re
+import sys
 from copy import deepcopy
 from pathlib import Path
 from unittest import mock
@@ -186,7 +187,20 @@ def _check_functional_scripted_smoke(functional, input, *args, **kwargs):
         functional_scripted(input.as_subclass(torch.Tensor), *args, **kwargs)
 
 
-def check_functional(functional, input, *args, check_scripted_smoke=True, **kwargs):
+def _check_functional_torch_compile_smoke(functional, input, *args, **kwargs):
+    """Checks if the functional can be torch compiled and the compiled version can be called without error."""
+    if not isinstance(input, torch.Tensor):
+        return
+
+    functional_compiled = torch.compile(functional)
+    functional_compiled(input, *args, **kwargs)
+
+    explanation = torch._dynamo.explain(functional_compiled)(input, *args, **kwargs)
+    # TODO: Set expected value to 0 once fixed the graph break related to function registration
+    assert explanation.graph_break_count in (0, 1)
+
+
+def check_functional(functional, input, *args, check_scripted_smoke=True, check_torch_compile_smoke=True, **kwargs):
     unknown_input = object()
     with pytest.raises(TypeError, match=re.escape(str(type(unknown_input)))):
         functional(unknown_input, *args, **kwargs)
@@ -204,6 +218,16 @@ def check_functional(functional, input, *args, check_scripted_smoke=True, **kwar
     if check_scripted_smoke:
         _check_functional_scripted_smoke(functional, input, *args, **kwargs)
 
+    # Skip check on Windows as torch.compile does not work on Win32
+    if check_torch_compile_smoke and sys.platform != "win32":
+        # Temporary fix to catch deprectation warning
+        # This can be removed once https://github.com/pytorch/pytorch/pull/113023 is merged:
+        import warnings
+
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", category=DeprecationWarning)
+            _check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
+
 
 def check_functional_kernel_signature_match(functional, *, kernel, input_type):
     """Checks if the signature of the functional matches the kernel signature."""
@@ -656,6 +680,7 @@ def test_functional(self, size, make_input):
             size=size,
             antialias=True,
             check_scripted_smoke=not isinstance(size, int),
+            check_torch_compile_smoke=False,
         )
 
     @pytest.mark.parametrize(
@@ -3469,7 +3494,12 @@ def test_kernel(self, kernel, make_input):
     )
     def test_functional(self, make_input):
         check_functional(
-            F.resized_crop, make_input(self.INPUT_SIZE), **self.CROP_KWARGS, size=self.OUTPUT_SIZE, antialias=True
+            F.resized_crop,
+            make_input(self.INPUT_SIZE),
+            **self.CROP_KWARGS,
+            size=self.OUTPUT_SIZE,
+            antialias=True,
+            check_torch_compile_smoke=False,
         )
 
     @pytest.mark.parametrize(
@@ -3949,7 +3979,7 @@ def test_kernel_video(self):
         [make_image_tensor, make_image_pil, make_image, make_bounding_boxes, make_segmentation_mask, make_video],
     )
     def test_functional(self, make_input):
-        check_functional(F.perspective, make_input(), **self.MINIMAL_KWARGS)
+        check_functional(F.perspective, make_input(), **self.MINIMAL_KWARGS, check_torch_compile_smoke=False)
 
     @pytest.mark.parametrize(
         ("kernel", "input_type"),
@@ -4106,7 +4136,7 @@ def test_kernel_video(self):
 
     @pytest.mark.parametrize("make_input", [make_image_tensor, make_image_pil, make_image, make_video])
     def test_functional(self, make_input):
-        check_functional(F.equalize, make_input())
+        check_functional(F.equalize, make_input(), check_torch_compile_smoke=False)
 
     @pytest.mark.parametrize(
         ("kernel", "input_type"),
diff --git a/torchvision/tv_tensors/__init__.py b/torchvision/tv_tensors/__init__.py
index d55e10e8620..2e58d9d4c6a 100644
--- a/torchvision/tv_tensors/__init__.py
+++ b/torchvision/tv_tensors/__init__.py
@@ -8,6 +8,10 @@
 from ._video import Video
 
 
+# TODO: Fix this. We skip this method as it leads to
+# RecursionError: maximum recursion depth exceeded while calling a Python object
+# Keeping it here, leads to graph breaks between multiple functional ops instead of having a single graph
+@torch.compiler.disable
 def wrap(wrappee, *, like, **kwargs):
     """[BETA] Convert a :class:`torch.Tensor` (``wrappee``) into the same :class:`~torchvision.tv_tensors.TVTensor` subclass as ``like``.