diff --git a/conditioning/embeddings.py b/conditioning/embeddings.py
index ca3f4fd..da33b4f 100644
--- a/conditioning/embeddings.py
+++ b/conditioning/embeddings.py
@@ -163,6 +163,8 @@ def get_attn_mask(img_size=64):
 
 def prepare_embeddings(conds, latent_shape, idxs, use_masked_att=False):
     batch_size, _, latent_height, latent_width = latent_shape
+    if idxs is None:
+        idxs = list(range(batch_size))
     embeddings = create_zero_input_tensors(
         batch_size, latent_width, latent_height)
     if use_masked_att:
diff --git a/conditioning/fusers_patch.py b/conditioning/fusers_patch.py
index a58f023..69479d2 100644
--- a/conditioning/fusers_patch.py
+++ b/conditioning/fusers_patch.py
@@ -40,14 +40,7 @@ class FusersPatch(torch.nn.Module):
         self.idxs = idxs
         self.device = device
 
-    def _get_position_objs(self, extra_options):
-        idxs = None
-        if extra_options is not None:
-            if 'ad_params' in extra_options:
-                idxs = extra_options['ad_params']['sub_idxs']
-            elif 'sub_idxs' in extra_options:
-                idxs = extra_options['sub_idxs']
-
+    def _get_position_objs(self, idxs):
         embeddings = prepare_embeddings(
             self.conds, self.latent_shape, idxs, True)
         for key in embeddings:
@@ -55,10 +48,34 @@ class FusersPatch(torch.nn.Module):
         objs, drop_box_mask = self.positionnet(embeddings)
         return {'objs': objs, 'drop_box_mask': drop_box_mask}
 
+    def _get_idxs(self, extra_options):
+        idxs = None
+        if extra_options is not None:
+            if 'ad_params' in extra_options:
+                idxs = extra_options['ad_params']['sub_idxs']
+            elif 'sub_idxs' in extra_options:
+                idxs = extra_options['sub_idxs']
+        
+        return idxs
+
     @torch.no_grad()
     def forward(self, x, extra_options):
+        print('--------', x.shape)
         block, idx = extra_options['block']
         fuser_idx = block_map[block][idx]
         fuser = self.fusers_list[fuser_idx]
-        attn = fuser(x, self._get_position_objs(extra_options))
-        return attn.to(torch.float16)
+        attn_total = []
+        idxs = self._get_idxs(extra_options)
+        print('idxs', idxs)
+        for i in range(0, len(x), self.fusers_batch_size):
+            batch_idxs = idxs[i:i+self.fusers_batch_size]
+            x_idxs = list(range(i, i+self.fusers_batch_size))
+            # print('batch_idxs', batch_idxs, x_idxs)
+            # print('x[x_idxs].shape', x[x_idxs].shape)
+            # print('doing attn')
+            attn = fuser(x[x_idxs], self._get_position_objs(batch_idxs))
+            # print('attn.shape', attn.shape)
+            attn_total.append(attn)
+        attn_total = torch.cat(attn_total)
+        print(attn_total.shape)
+        return attn_total.to(torch.float16)
diff --git a/nodes/instance_diffusion_tracking_prompt_node.py b/nodes/instance_diffusion_tracking_prompt_node.py
index f30a9d9..197fe37 100644
--- a/nodes/instance_diffusion_tracking_prompt_node.py
+++ b/nodes/instance_diffusion_tracking_prompt_node.py
@@ -11,7 +11,7 @@ class InstanceDiffusionTrackingPromptNode:
                              "tracking": ("TRACKING", ),
                              "positionnet": ("POSITIONNET", ),
                              "fusers": ("FUSERS", ),
-                             "fusers_batch_size": ("INT", {"default": 5, "min": 0, "max": 10000, "step": 8}),
+                             "fusers_batch_size": ("INT", {"default": 8, "min": 1, "max": 10000, "step": 1}),
                              "positive_text": ("STRING", {"multiline": True}),
                              "negative_text": ("STRING", {"multiline": True}),
                              }}