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

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Merged
patrickvonplaten merged 1 commit into from
May 30, 2023
Merged

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

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5 changes: 5 additions & 0 deletions examples/community/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down Expand Up @@ -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
Expand Down
16 changes: 8 additions & 8 deletions examples/community/stable_diffusion_controlnet_reference.py
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Original file line number Diff line number Diff line change
Expand Up @@ -505,8 +505,8 @@ def hack_CrossAttnDownBlock2D_forward(
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)
Expand Down Expand Up @@ -545,8 +545,8 @@ def hacked_DownBlock2D_forward(self, hidden_states, temb=None):
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)
Expand Down Expand Up @@ -605,8 +605,8 @@ def hacked_CrossAttnUpBlock2D_forward(
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)
Expand Down Expand Up @@ -642,8 +642,8 @@ def hacked_UpBlock2D_forward(self, hidden_states, res_hidden_states_tuple, temb=
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)
Expand Down
16 changes: 8 additions & 8 deletions examples/community/stable_diffusion_reference.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -499,8 +499,8 @@ def hack_CrossAttnDownBlock2D_forward(
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)
Expand Down Expand Up @@ -539,8 +539,8 @@ def hacked_DownBlock2D_forward(self, hidden_states, temb=None):
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)
Expand Down Expand Up @@ -599,8 +599,8 @@ def hacked_CrossAttnUpBlock2D_forward(
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)
Expand Down Expand Up @@ -636,8 +636,8 @@ def hacked_UpBlock2D_forward(self, hidden_states, res_hidden_states_tuple, temb=
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)
Expand Down