test jit tolist failure (#14040)

also moved tests to test_jit_footguns

test/test_jit.py

@@ -513,24 +513,6 @@ class TestJit(unittest.TestCase):
     with self.assertRaises(AssertionError):
       f(Tensor([2.0])).item()
 
-  def test_jit_item_not_supported(self):
-    # .item() is not jittable because the output shape depends on runtime values
-    @TinyJit
-    def f(x:Tensor) -> Tensor: return Tensor.zeros(x.sum().item())
-    for _ in range(3): f(Tensor([1, 1, 1]))  # sum=3
-    result = f(Tensor([2, 2, 2]))  # sum=6, but jit baked in n=3
-    self.assertEqual(result.shape, (3,))  # wrong, should be (6,)
-
-  def test_jit_masked_select_not_supported(self):
-    # masked_select uses .item() internally, so output size gets baked in
-    @TinyJit
-    def f(x:Tensor, mask:Tensor) -> Tensor: return x.masked_select(mask)
-    mask_2 = Tensor([True, False, True, False])
-    for _ in range(3): f(Tensor([1, 2, 3, 4]), mask_2)
-    mask_3 = Tensor([True, True, True, False])
-    result = f(Tensor([1, 2, 3, 4]), mask_3)
-    self.assertEqual(result.shape, (2,))  # wrong, should be (3,)
-
 @unittest.skip("Pending multioutput implementation #3607")
 class TestMultioutputJit(unittest.TestCase):
   def _test(self, f):

test/test_jit_footguns.py

@@ -217,6 +217,35 @@ class TestJitFootguns(unittest.TestCase):
       for _ in range(3):
         f(Tensor([1]), Tensor([2]))
 
+  def test_item_creates_unrealized_return(self):
+    """.item() in shape computation creates unrealized return with baked-in shape."""
+    @TinyJit
+    def f(x): return Tensor.zeros(x.sum().item())
+
+    for _ in range(3): f(Tensor([1, 1, 1]))  # captures with sum=3
+    result = f(Tensor([2, 2, 2]))  # sum=6, but shape is baked in
+    assert result.shape == (3,)  # should be (6,)!
+
+  def test_item_bakes_in_values(self):
+    """.item() value is baked in, causing wrong output shapes (silent failure)."""
+    @TinyJit
+    def f(x, mask): return x.masked_select(mask)
+
+    mask_2 = Tensor([True, False, True, False])
+    for _ in range(3): f(Tensor([1, 2, 3, 4]), mask_2)
+    mask_3 = Tensor([True, True, True, False])
+    result = f(Tensor([1, 2, 3, 4]), mask_3)
+    assert result.shape == (2,)  # should be (3,)!
+
+  def test_tolist_bakes_in_values(self):
+    """.tolist() returns Python values that get baked in (silent failure)."""
+    @TinyJit
+    def f(x): return Tensor(x.tolist())
+
+    for _ in range(3): f(Tensor([1, 2, 3]))
+    result = f(Tensor([4, 5, 6]))
+    np.testing.assert_equal(result.numpy(), [1, 2, 3])  # should be [4,5,6]!
+
 
 class TestJitCorrectBehavior(unittest.TestCase):
   """Behaviors that work correctly - documented for clarity."""