Merge pull request #10259 from AUTOMATIC1111/ruff

Ruff

1 files changed, 7 insertions, 9 deletions

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 4368eb63..9e1b2b9a 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -1,7 +1,6 @@
 import os

 import sys

 import traceback

-import inspect

 from collections import namedtuple

 

 import torch

@@ -30,7 +29,7 @@ textual_inversion_templates = {}
 def list_textual_inversion_templates():

     textual_inversion_templates.clear()

 

-    for root, dirs, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir):

+    for root, _, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir):

         for fn in fns:

             path = os.path.join(root, fn)

 

@@ -167,8 +166,7 @@ class EmbeddingDatabase:
         # textual inversion embeddings

         if 'string_to_param' in data:

             param_dict = data['string_to_param']

-            if hasattr(param_dict, '_parameters'):

-                param_dict = getattr(param_dict, '_parameters')  # fix for torch 1.12.1 loading saved file from torch 1.11

+            param_dict = getattr(param_dict, '_parameters', param_dict)  # fix for torch 1.12.1 loading saved file from torch 1.11

             assert len(param_dict) == 1, 'embedding file has multiple terms in it'

             emb = next(iter(param_dict.items()))[1]

         # diffuser concepts

@@ -199,7 +197,7 @@ class EmbeddingDatabase:
         if not os.path.isdir(embdir.path):

             return

 

-        for root, dirs, fns in os.walk(embdir.path, followlinks=True):

+        for root, _, fns in os.walk(embdir.path, followlinks=True):

             for fn in fns:

                 try:

                     fullfn = os.path.join(root, fn)

@@ -216,7 +214,7 @@ class EmbeddingDatabase:
     def load_textual_inversion_embeddings(self, force_reload=False):

         if not force_reload:

             need_reload = False

-            for path, embdir in self.embedding_dirs.items():

+            for embdir in self.embedding_dirs.values():

                 if embdir.has_changed():

                     need_reload = True

                     break

@@ -229,7 +227,7 @@ class EmbeddingDatabase:
         self.skipped_embeddings.clear()

         self.expected_shape = self.get_expected_shape()

 

-        for path, embdir in self.embedding_dirs.items():

+        for embdir in self.embedding_dirs.values():

             self.load_from_dir(embdir)

             embdir.update()

 

@@ -470,7 +468,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
     try:

         sd_hijack_checkpoint.add()

 

-        for i in range((steps-initial_step) * gradient_step):

+        for _ in range((steps-initial_step) * gradient_step):

             if scheduler.finished:

                 break

             if shared.state.interrupted:

@@ -603,7 +601,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
 

                         try:

                             vectorSize = list(data['string_to_param'].values())[0].shape[0]

-                        except Exception as e:

+                        except Exception:

                             vectorSize = '?'

 

                         checkpoint = sd_models.select_checkpoint()