Merge pull request #5992 from yuvalabou/F541

Fix F541: f-string without any placeholders
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AUTOMATIC1111 2022-12-25 09:16:08 +03:00 committed by GitHub
commit b12de850ae
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10 changed files with 18 additions and 18 deletions

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

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@ -382,7 +382,7 @@ class VQAutoEncoder(nn.Module):
self.load_state_dict(torch.load(model_path, map_location='cpu')['params']) self.load_state_dict(torch.load(model_path, map_location='cpu')['params'])
logger.info(f'vqgan is loaded from: {model_path} [params]') logger.info(f'vqgan is loaded from: {model_path} [params]')
else: else:
raise ValueError(f'Wrong params!') raise ValueError('Wrong params!')
def forward(self, x): def forward(self, x):
@ -431,7 +431,7 @@ class VQGANDiscriminator(nn.Module):
elif 'params' in chkpt: elif 'params' in chkpt:
self.load_state_dict(torch.load(model_path, map_location='cpu')['params']) self.load_state_dict(torch.load(model_path, map_location='cpu')['params'])
else: else:
raise ValueError(f'Wrong params!') raise ValueError('Wrong params!')
def forward(self, x): def forward(self, x):
return self.main(x) return self.main(x)

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@ -277,7 +277,7 @@ def load_hypernetwork(filename):
print(traceback.format_exc(), file=sys.stderr) print(traceback.format_exc(), file=sys.stderr)
else: else:
if shared.loaded_hypernetwork is not None: if shared.loaded_hypernetwork is not None:
print(f"Unloading hypernetwork") print("Unloading hypernetwork")
shared.loaded_hypernetwork = None 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 initial_step = hypernetwork.step or 0
if initial_step >= steps: 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 return hypernetwork, filename
scheduler = LearnRateScheduler(learn_rate, steps, initial_step) scheduler = LearnRateScheduler(learn_rate, steps, initial_step)

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@ -599,7 +599,7 @@ def read_info_from_image(image):
Negative prompt: {json_info["uc"]} 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""" 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: 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) print(traceback.format_exc(), file=sys.stderr)
return geninfo, items return geninfo, items

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

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@ -137,15 +137,15 @@ def load_with_extra(filename, extra_handler=None, *args, **kwargs):
except pickle.UnpicklingError: except pickle.UnpicklingError:
print(f"Error verifying pickled file from {filename}:", file=sys.stderr) print(f"Error verifying pickled file from {filename}:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr) print(traceback.format_exc(), file=sys.stderr)
print(f"-----> !!!! The file is most likely corrupted !!!! <-----", file=sys.stderr) print("-----> !!!! 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("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 return None
except Exception: except Exception:
print(f"Error verifying pickled file from {filename}:", file=sys.stderr) print(f"Error verifying pickled file from {filename}:", file=sys.stderr)
print(traceback.format_exc(), 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("\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("You can skip this check with --disable-safe-unpickle commandline argument.\n\n", file=sys.stderr)
return None return None
return unsafe_torch_load(filename, *args, **kwargs) return unsafe_torch_load(filename, *args, **kwargs)

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@ -117,13 +117,13 @@ def select_checkpoint():
return checkpoint_info return checkpoint_info
if len(checkpoints_list) == 0: 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: if shared.cmd_opts.ckpt is not None:
print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr) print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr)
print(f" - directory {model_path}", file=sys.stderr) print(f" - directory {model_path}", file=sys.stderr)
if shared.cmd_opts.ckpt_dir is not None: 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" - 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) exit(1)
checkpoint_info = next(iter(checkpoints_list.values())) checkpoint_info = next(iter(checkpoints_list.values()))
@ -324,7 +324,7 @@ def load_model(checkpoint_info=None):
script_callbacks.model_loaded_callback(sd_model) script_callbacks.model_loaded_callback(sd_model)
print(f"Model loaded.") print("Model loaded.")
return sd_model 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: if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
sd_model.to(devices.device) sd_model.to(devices.device)
print(f"Weights loaded.") print("Weights loaded.")
return sd_model return sd_model

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@ -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: if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
sd_model.to(devices.device) sd_model.to(devices.device)
print(f"VAE Weights loaded.") print("VAE Weights loaded.")
return sd_model return sd_model

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@ -263,7 +263,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
initial_step = embedding.step or 0 initial_step = embedding.step or 0
if initial_step >= steps: 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 return embedding, filename
scheduler = LearnRateScheduler(learn_rate, steps, initial_step) scheduler = LearnRateScheduler(learn_rate, steps, initial_step)

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@ -140,7 +140,7 @@ class Script(scripts.Script):
try: try:
args = cmdargs(line) args = cmdargs(line)
except Exception: 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) print(traceback.format_exc(), file=sys.stderr)
args = {"prompt": line} args = {"prompt": line}
else: else: