diff --git a/ldm/invoke/generator/omnibus.py b/ldm/invoke/generator/omnibus.py
index 43192cd152..b6ddbfdb03 100644
--- a/ldm/invoke/generator/omnibus.py
+++ b/ldm/invoke/generator/omnibus.py
@@ -2,6 +2,7 @@
 
 import torch
 import numpy as  np
+from einops import repeat
 from PIL import Image
 from ldm.invoke.generator.base import downsampling
 from ldm.invoke.generator.img2img import Img2Img
@@ -33,6 +34,7 @@ class Omnibus(Img2Img,Txt2Img):
         Return value depends on the seed at the time you call it.
         """
         self.perlin = perlin
+        num_samples = 1
 
         sampler.make_schedule(
             ddim_num_steps=steps, ddim_eta=ddim_eta, verbose=False
@@ -77,7 +79,7 @@ class Omnibus(Img2Img,Txt2Img):
                         masked_image,
                         prompt=prompt,
                         device=model.device,
-                        num_samples=1
+                        num_samples=num_samples,
                     )
                     
                     c = model.cond_stage_model.encode(batch["txt"])
@@ -86,7 +88,7 @@ class Omnibus(Img2Img,Txt2Img):
                     for ck in model.concat_keys:
                         cc = batch[ck].float()
                         if ck != model.masked_image_key:
-                            bchw = [num_samples, 4, h//8, w//8]
+                            bchw = [num_samples, 4, height//8, width//8]
                             cc = torch.nn.functional.interpolate(cc, size=bchw[-2:])
                         else:
                             cc = model.get_first_stage_encoding(model.encode_first_stage(cc))
@@ -99,7 +101,7 @@ class Omnibus(Img2Img,Txt2Img):
                     # uncond cond
                     uc_cross = model.get_unconditional_conditioning(num_samples, "")
                     uc_full = {"c_concat": [c_cat], "c_crossattn": [uc_cross]}
-                    shape = [model.channels, h//8, w//8]
+                    shape = [model.channels, height//8, width//8]
                     
                     samples, = sampler.sample(
                         batch_size = 1,
@@ -121,6 +123,7 @@ class Omnibus(Img2Img,Txt2Img):
         return make_image
 
     def make_batch_sd(
+            self,
             image,
             mask,
             masked_image,