diff --git a/mart/attack/composer/modular.py b/mart/attack/composer/modular.py
index d070436b..c614a3c5 100644
--- a/mart/attack/composer/modular.py
+++ b/mart/attack/composer/modular.py
@@ -9,6 +9,7 @@
 from typing import TYPE_CHECKING, Any, Iterable
 
 import torch
+from torchvision.transforms.functional import to_pil_image
 
 from mart.nn import SequentialDict
 
@@ -19,7 +20,7 @@
 
 
 class Composer(torch.nn.Module):
-    def __init__(self, perturber: Perturber, modules, sequence) -> None:
+    def __init__(self, perturber: Perturber, modules, sequence, visualize: bool = False) -> None:
         """_summary_
 
         Args:
@@ -34,6 +35,7 @@ def __init__(self, perturber: Perturber, modules, sequence) -> None:
         if isinstance(sequence, dict):
             sequence = [sequence[key] for key in sorted(sequence)]
         self.functions = SequentialDict(modules, {"composer": sequence})
+        self.visualize = visualize
 
     def configure_perturbation(self, input: torch.Tensor | Iterable[torch.Tensor]):
         return self.perturber.configure_perturbation(input)
@@ -76,6 +78,12 @@ def _compose(
             input=input, target=target, perturbation=perturbation, step="composer"
         )
 
+        # Visualize intermediate images.
+        if self.visualize:
+            for key, value in output.items():
+                if isinstance(value, torch.Tensor):
+                    to_pil_image(value / 255).save(f"{key}.png")
+
         # SequentialDict returns a dictionary DotDict,
         #  but we only need the return value of the most recently executed module.
         last_added_key = next(reversed(output))