[Community, Enhancement] Add reference tricks in README (#3589)

add reference tricks

examples/community/README.md

@@ -1326,6 +1326,8 @@ image.save('tensorrt_img2img_new_zealand_hills.png')
 
 This pipeline uses the Reference Control. Refer to the [sd-webui-controlnet discussion: Reference-only Control](https://github.com/Mikubill/sd-webui-controlnet/discussions/1236)[sd-webui-controlnet discussion: Reference-adain Control](https://github.com/Mikubill/sd-webui-controlnet/discussions/1280).
 
+Based on [this issue](https://github.com/huggingface/diffusers/issues/3566),
+- `EulerAncestralDiscreteScheduler` got poor results.
 
 ```py
 import torch
@@ -1369,6 +1371,9 @@ Output Image of `reference_attn=True` and `reference_adain=True`
 
 This pipeline uses the Reference Control with ControlNet. Refer to the [sd-webui-controlnet discussion: Reference-only Control](https://github.com/Mikubill/sd-webui-controlnet/discussions/1236)[sd-webui-controlnet discussion: Reference-adain Control](https://github.com/Mikubill/sd-webui-controlnet/discussions/1280).
 
+Based on [this issue](https://github.com/huggingface/diffusers/issues/3566),
+- `EulerAncestralDiscreteScheduler` got poor results.
+- `guess_mode=True` works well for ControlNet v1.1
 
 ```py
 import cv2

examples/community/stable_diffusion_controlnet_reference.py

@@ -505,8 +505,8 @@ class StableDiffusionControlNetReferencePipeline(StableDiffusionControlNetPipeli
                 if MODE == "write":
                     if gn_auto_machine_weight >= self.gn_weight:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
-                        self.mean_bank.append(mean)
-                        self.var_bank.append(var)
+                        self.mean_bank.append([mean])
+                        self.var_bank.append([var])
                 if MODE == "read":
                     if len(self.mean_bank) > 0 and len(self.var_bank) > 0:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
@@ -545,8 +545,8 @@ class StableDiffusionControlNetReferencePipeline(StableDiffusionControlNetPipeli
                 if MODE == "write":
                     if gn_auto_machine_weight >= self.gn_weight:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
-                        self.mean_bank.append(mean)
-                        self.var_bank.append(var)
+                        self.mean_bank.append([mean])
+                        self.var_bank.append([var])
                 if MODE == "read":
                     if len(self.mean_bank) > 0 and len(self.var_bank) > 0:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
@@ -605,8 +605,8 @@ class StableDiffusionControlNetReferencePipeline(StableDiffusionControlNetPipeli
                 if MODE == "write":
                     if gn_auto_machine_weight >= self.gn_weight:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
-                        self.mean_bank.append(mean)
-                        self.var_bank.append(var)
+                        self.mean_bank.append([mean])
+                        self.var_bank.append([var])
                 if MODE == "read":
                     if len(self.mean_bank) > 0 and len(self.var_bank) > 0:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
@@ -642,8 +642,8 @@ class StableDiffusionControlNetReferencePipeline(StableDiffusionControlNetPipeli
                 if MODE == "write":
                     if gn_auto_machine_weight >= self.gn_weight:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
-                        self.mean_bank.append(mean)
-                        self.var_bank.append(var)
+                        self.mean_bank.append([mean])
+                        self.var_bank.append([var])
                 if MODE == "read":
                     if len(self.mean_bank) > 0 and len(self.var_bank) > 0:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)

examples/community/stable_diffusion_reference.py

@@ -499,8 +499,8 @@ class StableDiffusionReferencePipeline(StableDiffusionPipeline):
                 if MODE == "write":
                     if gn_auto_machine_weight >= self.gn_weight:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
-                        self.mean_bank.append(mean)
-                        self.var_bank.append(var)
+                        self.mean_bank.append([mean])
+                        self.var_bank.append([var])
                 if MODE == "read":
                     if len(self.mean_bank) > 0 and len(self.var_bank) > 0:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
@@ -539,8 +539,8 @@ class StableDiffusionReferencePipeline(StableDiffusionPipeline):
                 if MODE == "write":
                     if gn_auto_machine_weight >= self.gn_weight:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
-                        self.mean_bank.append(mean)
-                        self.var_bank.append(var)
+                        self.mean_bank.append([mean])
+                        self.var_bank.append([var])
                 if MODE == "read":
                     if len(self.mean_bank) > 0 and len(self.var_bank) > 0:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
@@ -599,8 +599,8 @@ class StableDiffusionReferencePipeline(StableDiffusionPipeline):
                 if MODE == "write":
                     if gn_auto_machine_weight >= self.gn_weight:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
-                        self.mean_bank.append(mean)
-                        self.var_bank.append(var)
+                        self.mean_bank.append([mean])
+                        self.var_bank.append([var])
                 if MODE == "read":
                     if len(self.mean_bank) > 0 and len(self.var_bank) > 0:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
@@ -636,8 +636,8 @@ class StableDiffusionReferencePipeline(StableDiffusionPipeline):
                 if MODE == "write":
                     if gn_auto_machine_weight >= self.gn_weight:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)
-                        self.mean_bank.append(mean)
-                        self.var_bank.append(var)
+                        self.mean_bank.append([mean])
+                        self.var_bank.append([var])
                 if MODE == "read":
                     if len(self.mean_bank) > 0 and len(self.var_bank) > 0:
                         var, mean = torch.var_mean(hidden_states, dim=(2, 3), keepdim=True, correction=0)