Compose len

monai/transforms/compose.py

@@ -231,6 +231,26 @@ def randomize(self, data: Optional[Any] = None) -> None:
                     f'Transform "{tfm_name}" in Compose not randomized\n{tfm_name}.{type_error}.', RuntimeWarning
                 )
 
+    def flatten(self):
+        """Return a Composition with a simple list of transforms, as opposed to any nested Compositions.
+
+        e.g., `t1 = Compose([x, x, x, x, Compose([Compose([x, x]), x, x])]).flatten()`
+        will result in the equivalent of `t1 = Compose([x, x, x, x, x, x, x, x])`.
+
+        """
+        new_transforms = []
+        for t in self.transforms:
+            if isinstance(t, Compose):
+                new_transforms += t.flatten().transforms
+            else:
+                new_transforms.append(t)
+
+        return Compose(new_transforms)
+
+    def __len__(self):
+        """Return number of transformations."""
+        return len(self.flatten().transforms)
+
     def __call__(self, input_):
         for _transform in self.transforms:
             input_ = apply_transform(_transform, input_)

tests/test_compose.py

@@ -156,6 +156,17 @@ def test_data_loader_2(self):
             self.assertAlmostEqual(out_1.cpu().item(), 0.131966779)
         set_determinism(None)
 
+    def test_flatten_and_len(self):
+        x = AddChannel()
+        t1 = Compose([x, x, x, x, Compose([Compose([x, x]), x, x])])
+
+        t2 = t1.flatten()
+        for t in t2.transforms:
+            self.assertNotIsInstance(t, Compose)
+
+        # test len
+        self.assertEqual(len(t1), 8)
+
 
 if __name__ == "__main__":
     unittest.main()