@@ -358,7 +358,14 @@ def flatten(self):
             else:
                 new_transforms.append(t)
 
-        return Compose(new_transforms)
+        return Compose(
+            new_transforms,
+            map_items=self.map_items,
+            unpack_items=self.unpack_items,
+            log_stats=self.log_stats,
+            lazy=self._lazy,
+            overrides=self.overrides,
+        )
 
     def __len__(self):
         """Return number of transformations."""
 
@@ -824,6 +824,123 @@ def noop(x):
         self.assertEqual(len(flat.transforms), 3)
         self.assertIsInstance(flat.transforms[1], mt.Compose)
 
+    def test_multiple_children_with_mixed_map_items(self):
+        """Multiple internal Composes with different map_items should be handled correctly."""
+
+        def add_one(items):
+            if isinstance(items, list):
+                return [x + 1 for x in items]
+            return items + 1
+
+        def multiply_two(items):
+            if isinstance(items, list):
+                return [x * 2 for x in items]
+            return items * 2
+
+        # Parent with map_items=False processes the entire input as one unit
+        # Child 1 (map_items=True) will map over each item in what it receives
+        # Child 2 (map_items=False) will process the entire thing
+        pipeline = mt.Compose(
+            [
+                mt.Compose([add_one], map_items=True),
+                mt.Compose([multiply_two], map_items=False),
+            ],
+            map_items=False,
+        )
+
+        # Input [1, 2, 3]
+        # First child with map_items=True maps add_one over [1,2,3]: [2, 3, 4]
+        # Second child with map_items=False receives [2,3,4] and applies multiply_two: [4, 6, 8]
+        result = pipeline([1, 2, 3])
+        self.assertEqual(result, [4, 6, 8])
+
+    def test_flatten_with_multiple_children_preserves_both(self):
+        """flatten() should preserve child with different map_items but flatten child with same."""
+
+        def noop(x):
+            return x
+
+        parent = mt.Compose(
+            [
+                noop,
+                mt.Compose([noop, noop], map_items=True),  # Same as parent, will be flattened
+                mt.Compose([noop, noop], map_items=False),  # Different, will be preserved
+                noop,
+            ]
+        )
+        flat = parent.flatten()
+        # First nested Compose(map_items=True) will be flattened into parent
+        # Second nested Compose(map_items=False) will be preserved
+        # Result: noop + noop + noop + Compose([noop, noop]) + noop = 5 transforms
+        self.assertEqual(len(flat.transforms), 5)
+        # Check that the preserved one is at the correct position
+        self.assertIsInstance(flat.transforms[3], mt.Compose)
+        self.assertEqual(flat.transforms[3].map_items, False)
+
+    def test_three_level_nesting_respects_different_map_items(self):
+        """Three-level nesting with different map_items at each level."""
+
+        def add_one(x):
+            return x + 1
+
+        # Level 1 (outermost): map_items=True (default)
+        # Level 2: map_items=False
+        # Level 3: map_items=True (same as level 2, so will be flattened into level 2)
+        innermost = mt.Compose([add_one], map_items=True)
+        middle = mt.Compose([add_one, innermost], map_items=False)
+        outer = mt.Compose([middle])
+
+        # Test with a simple value
+        # outer has map_items=True (default), middle has map_items=False
+        # So middle should be preserved and receive the input as-is
+        result = outer(5)
+        # outer(5) -> maps to middle -> middle(5) with map_items=False
+        # middle(5) -> add_one(5) = 6, then innermost(6) with map_items=True
+        # innermost(6) -> add_one(6) = 7
+        self.assertEqual(result, 7)
+
+    def test_inverse_with_multiple_children_different_map_items(self):
+        """Inverse should work correctly with multiple children having different map_items."""
+        pipeline = mt.Compose(
+            [
+                mt.Flip(0),
+                mt.Compose([mt.Flip(1)], map_items=False),
+                mt.Compose([mt.Flip(0)], map_items=True),
+            ]
+        )
+        data = torch.randn(2, 4, 4)
+        result = pipeline(data)
+        restored = pipeline.inverse(result)
+        torch.testing.assert_close(data, restored)
+
+    def test_flatten_with_mixed_same_and_different_map_items(self):
+        """flatten() should merge children with same map_items but preserve those with different."""
+
+        def noop(x):
+            return x
+
+        # Parent has map_items=True (default)
+        # Child 1 has map_items=True (same as parent) -> should be flattened
+        # Child 2 has map_items=False (different from parent) -> should NOT be flattened
+        parent = mt.Compose(
+            [
+                noop,
+                mt.Compose([noop, noop], map_items=True),  # Same as parent, will be flattened
+                mt.Compose([noop, noop], map_items=False),  # Different from parent, will be preserved
+                noop,
+            ]
+        )
+        flat = parent.flatten()
+        # After flatten:
+        # - noop (preserved)
+        # - 2 noops from first Compose (flattened because map_items=True matches parent)
+        # - Compose([noop, noop], map_items=False) (preserved because different)
+        # - noop (preserved)
+        # Total: 5 transforms
+        self.assertEqual(len(flat.transforms), 5)
+        self.assertIsInstance(flat.transforms[3], mt.Compose)
+        self.assertEqual(flat.transforms[3].map_items, False)
+
 
 class TestComposeCallableInput(unittest.TestCase):