diff --git a/sgm/util.py b/sgm/util.py
index 06f48a882..96181ed74 100644
--- a/sgm/util.py
+++ b/sgm/util.py
@@ -64,37 +64,36 @@ def do_autocast(*args, **kwargs):
 def load_partial_from_config(config):
     return partial(get_obj_from_str(config["target"]), **config.get("params", dict()))
 
-
 def log_txt_as_img(wh, xc, size=10):
     # wh a tuple of (width, height)
     # xc a list of captions to plot
     b = len(xc)
-    txts = list()
+    txt = Image.new("RGB", wh, color="white")
+    draw = ImageDraw.Draw(txt)
+    font = ImageFont.truetype("data/DejaVuSans.ttf", size=size)
+    nc = int(40 * (wh[0] / 256))
+    txts = []
+    
     for bi in range(b):
-        txt = Image.new("RGB", wh, color="white")
-        draw = ImageDraw.Draw(txt)
-        font = ImageFont.truetype("data/DejaVuSans.ttf", size=size)
-        nc = int(40 * (wh[0] / 256))
         if isinstance(xc[bi], list):
             text_seq = xc[bi][0]
         else:
             text_seq = xc[bi]
         lines = "\n".join(
-            text_seq[start : start + nc] for start in range(0, len(text_seq), nc)
+            text_seq[start: start + nc] for start in range(0, len(text_seq), nc)
         )
 
         try:
             draw.text((0, 0), lines, fill="black", font=font)
         except UnicodeEncodeError:
-            print("Cant encode string for logging. Skipping.")
+            print("Can't encode string for logging. Skipping.")
+
+        txt_arr = np.array(txt) / 127.5 - 1.0
+        txts.append(txt_arr)
 
-        txt = np.array(txt).transpose(2, 0, 1) / 127.5 - 1.0
-        txts.append(txt)
     txts = np.stack(txts)
-    txts = torch.tensor(txts)
     return txts
 
-
 def partialclass(cls, *args, **kwargs):
     class NewCls(cls):
         __init__ = functools.partialmethod(cls.__init__, *args, **kwargs)