Merge pull request #5992 from yuvalabou/F541

Fix F541: f-string without any placeholders

extensions-builtin/LDSR/ldsr_model_arch.py

@@ -26,7 +26,7 @@ def load_model_from_config(self, half_attention):
         global cached_ldsr_model
 
         if shared.opts.ldsr_cached and cached_ldsr_model is not None:
-            print(f"Loading model from cache")
+            print("Loading model from cache")
             model: torch.nn.Module = cached_ldsr_model
         else:
             print(f"Loading model from {self.modelPath}")

modules/codeformer/vqgan_arch.py

@@ -382,7 +382,7 @@ def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, att
                 self.load_state_dict(torch.load(model_path, map_location='cpu')['params'])
                 logger.info(f'vqgan is loaded from: {model_path} [params]')
             else:
-                raise ValueError(f'Wrong params!')
+                raise ValueError('Wrong params!')
 
 
     def forward(self, x):
@@ -431,7 +431,7 @@ def __init__(self, nc=3, ndf=64, n_layers=4, model_path=None):
             elif 'params' in chkpt:
                 self.load_state_dict(torch.load(model_path, map_location='cpu')['params'])
             else:
-                raise ValueError(f'Wrong params!')
+                raise ValueError('Wrong params!')
 
     def forward(self, x):
         return self.main(x)

modules/hypernetworks/hypernetwork.py

@@ -277,7 +277,7 @@ def load_hypernetwork(filename):
             print(traceback.format_exc(), file=sys.stderr)
     else:
         if shared.loaded_hypernetwork is not None:
-            print(f"Unloading hypernetwork")
+            print("Unloading hypernetwork")
 
         shared.loaded_hypernetwork = None
 
@@ -443,7 +443,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
 
     initial_step = hypernetwork.step or 0
     if initial_step >= steps:
-        shared.state.textinfo = f"Model has already been trained beyond specified max steps"
+        shared.state.textinfo = "Model has already been trained beyond specified max steps"
         return hypernetwork, filename
 
     scheduler = LearnRateScheduler(learn_rate, steps, initial_step)

modules/images.py

@@ -599,7 +599,7 @@ def read_info_from_image(image):
 Negative prompt: {json_info["uc"]}
 Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Clip skip: 2, ENSD: 31337"""
         except Exception:
-            print(f"Error parsing NovelAI image generation parameters:", file=sys.stderr)
+            print("Error parsing NovelAI image generation parameters:", file=sys.stderr)
             print(traceback.format_exc(), file=sys.stderr)
 
     return geninfo, items

modules/interrogate.py

@@ -172,7 +172,7 @@ def interrogate(self, pil_image):
                             res += ", " + match
 
         except Exception:
-            print(f"Error interrogating", file=sys.stderr)
+            print("Error interrogating", file=sys.stderr)
             print(traceback.format_exc(), file=sys.stderr)
             res += "<error>"
 

modules/safe.py

@@ -137,15 +137,15 @@ def extra(module, name):
     except pickle.UnpicklingError:
         print(f"Error verifying pickled file from {filename}:", file=sys.stderr)
         print(traceback.format_exc(), file=sys.stderr)
-        print(f"-----> !!!! The file is most likely corrupted !!!! <-----", file=sys.stderr)
-        print(f"You can skip this check with --disable-safe-unpickle commandline argument, but that is not going to help you.\n\n", file=sys.stderr)
+        print("-----> !!!! The file is most likely corrupted !!!! <-----", file=sys.stderr)
+        print("You can skip this check with --disable-safe-unpickle commandline argument, but that is not going to help you.\n\n", file=sys.stderr)
         return None
 
     except Exception:
         print(f"Error verifying pickled file from {filename}:", file=sys.stderr)
         print(traceback.format_exc(), file=sys.stderr)
-        print(f"\nThe file may be malicious, so the program is not going to read it.", file=sys.stderr)
-        print(f"You can skip this check with --disable-safe-unpickle commandline argument.\n\n", file=sys.stderr)
+        print("\nThe file may be malicious, so the program is not going to read it.", file=sys.stderr)
+        print("You can skip this check with --disable-safe-unpickle commandline argument.\n\n", file=sys.stderr)
         return None
 
     return unsafe_torch_load(filename, *args, **kwargs)

modules/sd_models.py

@@ -117,13 +117,13 @@ def select_checkpoint():
         return checkpoint_info
 
     if len(checkpoints_list) == 0:
-        print(f"No checkpoints found. When searching for checkpoints, looked at:", file=sys.stderr)
+        print("No checkpoints found. When searching for checkpoints, looked at:", file=sys.stderr)
         if shared.cmd_opts.ckpt is not None:
             print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr)
         print(f" - directory {model_path}", file=sys.stderr)
         if shared.cmd_opts.ckpt_dir is not None:
             print(f" - directory {os.path.abspath(shared.cmd_opts.ckpt_dir)}", file=sys.stderr)
-        print(f"Can't run without a checkpoint. Find and place a .ckpt file into any of those locations. The program will exit.", file=sys.stderr)
+        print("Can't run without a checkpoint. Find and place a .ckpt file into any of those locations. The program will exit.", file=sys.stderr)
         exit(1)
 
     checkpoint_info = next(iter(checkpoints_list.values()))
@@ -324,7 +324,7 @@ def load_model(checkpoint_info=None):
 
     script_callbacks.model_loaded_callback(sd_model)
 
-    print(f"Model loaded.")
+    print("Model loaded.")
     return sd_model
 
 
@@ -359,5 +359,5 @@ def reload_model_weights(sd_model=None, info=None):
     if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
         sd_model.to(devices.device)
 
-    print(f"Weights loaded.")
+    print("Weights loaded.")
     return sd_model

modules/sd_vae.py

@@ -208,5 +208,5 @@ def reload_vae_weights(sd_model=None, vae_file="auto"):
     if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
         sd_model.to(devices.device)
 
-    print(f"VAE Weights loaded.")
+    print("VAE Weights loaded.")
     return sd_model

modules/textual_inversion/textual_inversion.py

@@ -263,7 +263,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
 
     initial_step = embedding.step or 0
     if initial_step >= steps:
-        shared.state.textinfo = f"Model has already been trained beyond specified max steps"
+        shared.state.textinfo = "Model has already been trained beyond specified max steps"
         return embedding, filename
     scheduler = LearnRateScheduler(learn_rate, steps, initial_step)
 

scripts/prompts_from_file.py

@@ -140,7 +140,7 @@ def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_txt: str):
                 try:
                     args = cmdargs(line)
                 except Exception:
-                    print(f"Error parsing line [line] as commandline:", file=sys.stderr)
+                    print(f"Error parsing line {line} as commandline:", file=sys.stderr)
                     print(traceback.format_exc(), file=sys.stderr)
                     args = {"prompt": line}
             else: