From 65a76a086b116ae018db3b96ce48f3464b6c9ae8 Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Tue, 5 Sep 2023 11:54:28 +1200
Subject: [PATCH] cleanup: Some basic cleanup

---
 invokeai/backend/ip_adapter/__init__.py   |  2 +-
 invokeai/backend/ip_adapter/ip_adapter.py |  6 ++----
 invokeai/backend/ip_adapter/resampler.py  |  3 ++-
 invokeai/backend/ip_adapter/utils.py      | 11 +++++------
 4 files changed, 10 insertions(+), 12 deletions(-)

diff --git a/invokeai/backend/ip_adapter/__init__.py b/invokeai/backend/ip_adapter/__init__.py
index 852ee25813..68cb7069a5 100644
--- a/invokeai/backend/ip_adapter/__init__.py
+++ b/invokeai/backend/ip_adapter/__init__.py
@@ -1 +1 @@
-from .ip_adapter import IPAdapter, IPAdapterXL, IPAdapterPlus
+from .ip_adapter import IPAdapter, IPAdapterPlus, IPAdapterXL
diff --git a/invokeai/backend/ip_adapter/ip_adapter.py b/invokeai/backend/ip_adapter/ip_adapter.py
index 81bc6db847..b8f55fb59c 100644
--- a/invokeai/backend/ip_adapter/ip_adapter.py
+++ b/invokeai/backend/ip_adapter/ip_adapter.py
@@ -1,13 +1,11 @@
 # copied from https://github.com/tencent-ailab/IP-Adapter (Apache License 2.0)
 #   and modified as needed
 
-import os
 from typing import List
 
 import torch
-from diffusers import StableDiffusionPipeline
-from transformers import CLIPVisionModelWithProjection, CLIPImageProcessor
 from PIL import Image
+from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
 
 # FIXME: Getting errors when trying to use PyTorch 2.0 versions of IPAttnProcessor and AttnProcessor
 #   so for now falling back to the default versions
@@ -16,7 +14,7 @@ from PIL import Image
 #     from .attention_processor import IPAttnProcessor2_0 as IPAttnProcessor, AttnProcessor2_0 as AttnProcessor
 # else:
 #     from .attention_processor import IPAttnProcessor, AttnProcessor
-from .attention_processor import IPAttnProcessor, AttnProcessor
+from .attention_processor import AttnProcessor, IPAttnProcessor
 from .resampler import Resampler
 
 
diff --git a/invokeai/backend/ip_adapter/resampler.py b/invokeai/backend/ip_adapter/resampler.py
index 38c4b06dcf..3d326568a0 100644
--- a/invokeai/backend/ip_adapter/resampler.py
+++ b/invokeai/backend/ip_adapter/resampler.py
@@ -1,6 +1,7 @@
 # copied from https://github.com/tencent-ailab/IP-Adapter (Apache License 2.0)
 
-# tencent ailab comment: modified from https://github.com/mlfoundations/open_flamingo/blob/main/open_flamingo/src/helpers.py
+# tencent ailab comment: modified from
+# https://github.com/mlfoundations/open_flamingo/blob/main/open_flamingo/src/helpers.py
 import math
 
 import torch
diff --git a/invokeai/backend/ip_adapter/utils.py b/invokeai/backend/ip_adapter/utils.py
index 049d8163c2..d43cf12154 100644
--- a/invokeai/backend/ip_adapter/utils.py
+++ b/invokeai/backend/ip_adapter/utils.py
@@ -1,18 +1,16 @@
 # copied from https://github.com/tencent-ailab/IP-Adapter (Apache License 2.0)
 #   and modified as needed
 
-import inspect
-import warnings
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import Any, Callable, Dict, List, Optional, Union
 
 import numpy as np
 import PIL.Image
 import torch
 import torch.nn.functional as F
-from diffusers.utils import is_compiled_module
-from diffusers.pipelines.controlnet.multicontrolnet import MultiControlNetModel
 from diffusers.models import ControlNetModel
+from diffusers.pipelines.controlnet.multicontrolnet import MultiControlNetModel
 from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
+from diffusers.utils import is_compiled_module
 
 
 def is_torch2_available():
@@ -59,7 +57,8 @@ def generate(
         prompt (`str` or `List[str]`, *optional*):
             The prompt or prompts to guide the image generation. If not defined, one has to pass `prompt_embeds`.
             instead.
-        image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, `List[np.ndarray]`,:
+        image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`,
+        `List[np.ndarray]`,:
                 `List[List[torch.FloatTensor]]`, `List[List[np.ndarray]]` or `List[List[PIL.Image.Image]]`):
             The ControlNet input condition. ControlNet uses this input condition to generate guidance to Unet. If
             the type is specified as `Torch.FloatTensor`, it is passed to ControlNet as is. `PIL.Image.Image` can