Move comfy_extras nodes, fix pylint errors

comfy/cmd/server.py

@@ -64,7 +64,7 @@ def get_comfyui_version():
     comfyui_version = "unknown"
     repo_path = os.path.dirname(os.path.realpath(__file__))
     try:
-        import pygit2
+        import pygit2  # pylint: disable=import-error
         repo = pygit2.Repository(repo_path)
         comfyui_version = repo.describe(describe_strategy=pygit2.GIT_DESCRIBE_TAGS)
     except Exception:

comfy/lora.py

@@ -529,6 +529,7 @@ def calculate_weight(patches, weight, key, intermediate_dtype=torch.float32):
             except Exception as e:
                 logging.error("ERROR {} {} {}".format(patch_type, key, e))
         elif patch_type == "glora":
+            rank = 0
             dora_scale = v[5]
 
             old_glora = False

comfy_extras/nodes/nodes_lora_extract.py

@@ -1,12 +1,15 @@
+import logging
+import os
+
 import torch
+
 import comfy.model_management
 import comfy.utils
-import folder_paths
-import os
-import logging
+from comfy.cmd import folder_paths
 
 CLAMP_QUANTILE = 0.99
 
+
 def extract_lora(diff, rank):
     conv2d = (len(diff.shape) == 4)
     kernel_size = None if not conv2d else diff.size()[2:4]
@@ -20,7 +23,6 @@ def extract_lora(diff, rank):
         else:
             diff = diff.squeeze()
 
-
     U, S, Vh = torch.linalg.svd(diff.float())
     U = U[:, :rank]
     S = S[:rank]
@@ -38,6 +40,7 @@ def extract_lora(diff, rank):
         Vh = Vh.reshape(rank, in_dim, kernel_size[0], kernel_size[1])
     return (U, Vh)
 
+
 class LoraSave:
     def __init__(self):
         self.output_dir = folder_paths.get_output_directory()
@@ -45,10 +48,11 @@ class LoraSave:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": {"filename_prefix": ("STRING", {"default": "loras/ComfyUI_extracted_lora"}),
-                              "rank": ("INT", {"default": 8, "min": 1, "max": 1024, "step": 1}),
-                            },
-                "optional": {"model_diff": ("MODEL",),},
-    }
+                             "rank": ("INT", {"default": 8, "min": 1, "max": 1024, "step": 1}),
+                             },
+                "optional": {"model_diff": ("MODEL",), },
+                }
+
     RETURN_TYPES = ()
     FUNCTION = "save"
     OUTPUT_NODE = True
@@ -86,6 +90,7 @@ class LoraSave:
         comfy.utils.save_torch_file(output_sd, output_checkpoint, metadata=None)
         return {}
 
+
 NODE_CLASS_MAPPINGS = {
     "LoraSave": LoraSave
 }

comfy_extras/nodes/nodes_nf4.py

@@ -1,3 +1,6 @@
+import dataclasses
+from typing import Any
+
 try:
     import bitsandbytes as bnb
     from bitsandbytes.nn.modules import Params4bit, QuantState
@@ -8,8 +11,9 @@ except (ImportError, ModuleNotFoundError):
         pass
 
 
+    @dataclasses.dataclass
     class Params4bit:
-        pass
+        data: Any
 
 
     class QuantState: