add builtin framepack

Signed-off-by: Vladimir Mandic <mandic00@live.com>

scripts/instantir/sdxl_instantir.py

@@ -362,7 +362,7 @@ class InstantIRPipeline(
             f'{k.replace("unet.", "")}': v for k, v in lora_state_dict.items() if k.startswith("unet.")
         }
         unet_state_dict = convert_unet_state_dict_to_peft(unet_state_dict)
-        lora_state_dict = dict()
+        lora_state_dict = {}
         for k, v in unet_state_dict.items():
             if "ip" in k:
                 k = k.replace("attn2", "attn2.processor")

scripts/postprocessing_pixelart.py

@@ -24,7 +24,7 @@ class ScriptPixelArt(scripts_postprocessing.ScriptPostprocessing):
             "pixelart_sharpen_amount": pixelart_sharpen_amount,
         }
 
-    def process(self, pp: scripts_postprocessing.PostprocessedImage, pixelart_enabled: bool, pixelart_use_edge_detection: bool, pixelart_block_size: int, pixelart_edge_block_size: int, pixelart_image_weight: float, pixelart_sharpen_amount: float):
+    def process(self, pp: scripts_postprocessing.PostprocessedImage, pixelart_enabled: bool, pixelart_use_edge_detection: bool, pixelart_block_size: int, pixelart_edge_block_size: int, pixelart_image_weight: float, pixelart_sharpen_amount: float): # pylint: disable=arguments-differ
         if not pixelart_enabled:
             return
         from modules.postprocess.pixelart import img_to_pixelart, edge_detect_for_pixelart

scripts/pulid/eva_clip/eva_vit_model.py

@@ -9,7 +9,7 @@ import torch.nn as nn
 import torch.nn.functional as F
 try:
     from timm.models.layers import drop_path, to_2tuple, trunc_normal_
-except:
+except Exception:
     from timm.layers import drop_path, to_2tuple, trunc_normal_
 
 from .transformer import PatchDropout
@@ -18,7 +18,7 @@ from .rope import VisionRotaryEmbedding, VisionRotaryEmbeddingFast
 if os.getenv('ENV_TYPE') == 'deepspeed':
     try:
         from deepspeed.runtime.activation_checkpointing.checkpointing import checkpoint
-    except:
+    except Exception:
         from torch.utils.checkpoint import checkpoint
 else:
     from torch.utils.checkpoint import checkpoint
@@ -27,7 +27,7 @@ try:
     import xformers
     import xformers.ops as xops
     XFORMERS_IS_AVAILBLE = True
-except:
+except Exception:
     XFORMERS_IS_AVAILBLE = False
 
 class DropPath(nn.Module):

scripts/pulid/eva_clip/model.py

@@ -14,7 +14,7 @@ from torch import nn
 
 try:
     from .hf_model import HFTextEncoder
-except:
+except Exception:
     HFTextEncoder = None
 from .modified_resnet import ModifiedResNet
 from .timm_model import TimmModel
@@ -23,7 +23,7 @@ from .transformer import LayerNorm, QuickGELU, Attention, VisionTransformer, Tex
 
 try:
     from apex.normalization import FusedLayerNorm
-except:
+except Exception:
     FusedLayerNorm = LayerNorm
 
 @dataclass

scripts/pulid/eva_clip/tokenizer.py

@@ -116,7 +116,7 @@ class SimpleTokenizer(object):
                     j = word.index(first, i)
                     new_word.extend(word[i:j])
                     i = j
-                except:
+                except Exception:
                     new_word.extend(word[i:])
                     break
 

scripts/pulid/eva_clip/transformer.py

@@ -10,7 +10,7 @@ from torch.nn import functional as F
 
 try:
     from timm.models.layers import trunc_normal_
-except:
+except Exception:
     from timm.layers import trunc_normal_
 
 from .rope import VisionRotaryEmbedding, VisionRotaryEmbeddingFast