From 05933840f0676dd1a90a7e2ad3f2a0672624b2cd Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 31 May 2023 19:56:37 +0300
Subject: rename print_error to report, use it with together with package name

---
 modules/textual_inversion/textual_inversion.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

(limited to 'modules/textual_inversion/textual_inversion.py')

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index b3dcb140..8da050ca 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -12,9 +12,8 @@ import numpy as np
 from PIL import Image, PngImagePlugin
 from torch.utils.tensorboard import SummaryWriter
 
-from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint
+from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors
 import modules.textual_inversion.dataset
-from modules.errors import print_error
 from modules.textual_inversion.learn_schedule import LearnRateScheduler
 
 from modules.textual_inversion.image_embedding import embedding_to_b64, embedding_from_b64, insert_image_data_embed, extract_image_data_embed, caption_image_overlay
@@ -219,7 +218,7 @@ class EmbeddingDatabase:
 
                     self.load_from_file(fullfn, fn)
                 except Exception:
-                    print_error(f"Error loading embedding {fn}", exc_info=True)
+                    errors.report(f"Error loading embedding {fn}", exc_info=True)
                     continue
 
     def load_textual_inversion_embeddings(self, force_reload=False):
@@ -643,7 +642,7 @@ Last saved image: {html.escape(last_saved_image)}<br/>
         filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
         save_embedding(embedding, optimizer, checkpoint, embedding_name, filename, remove_cached_checksum=True)
     except Exception:
-        print_error("Error training embedding", exc_info=True)
+        errors.report("Error training embedding", exc_info=True)
     finally:
         pbar.leave = False
         pbar.close()
-- 
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