Mirrors
/
stable-diffusion-webui
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

fix F541 f-string without any placeholders

This commit is contained in:
Yuval Aboulafia 2022-12-24 21:35:29 +02:00
parent 5927d3fa95
commit 3bf5591efe
10 changed files with 18 additions and 18 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
extensions-builtin/LDSR/ldsr_model_arch.py
View File

@ -26,7 +26,7 @@ class LDSR:
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}")

4
modules/codeformer/vqgan_arch.py
View File

@ -382,7 +382,7 @@ class VQAutoEncoder(nn.Module):
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 @@ class VQGANDiscriminator(nn.Module):
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)

4
modules/hypernetworks/hypernetwork.py
View File

@ -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
@ -417,7 +417,7 @@ 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)

2
modules/images.py
View File

@ -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

2
modules/interrogate.py
View File

@ -172,7 +172,7 @@ class InterrogateModels:
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>"

8
modules/safe.py
View File

@ -137,15 +137,15 @@ def load_with_extra(filename, extra_handler=None, *args, **kwargs):
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)

8
modules/sd_models.py
View File

@ -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

2
modules/sd_vae.py
View File

@ -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

2
modules/textual_inversion/textual_inversion.py
View File

@ -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)

2
scripts/prompts_from_file.py
View File

@ -140,7 +140,7 @@ class Script(scripts.Script):
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: