Simplify a bunch of len(x) > 0/len(x) == 0 style expressions

This commit is contained in:
Aarni Koskela 2023-06-02 14:58:10 +03:00
parent 3e995778fc
commit 51864790fd
25 changed files with 47 additions and 48 deletions

View File

@ -91,8 +91,9 @@ class VQModel(pl.LightningModule):
del sd[k]
missing, unexpected = self.load_state_dict(sd, strict=False)
print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys")
if len(missing) > 0:
if missing:
print(f"Missing Keys: {missing}")
if unexpected:
print(f"Unexpected Keys: {unexpected}")
def on_train_batch_end(self, *args, **kwargs):

View File

@ -195,9 +195,9 @@ class DDPMV1(pl.LightningModule):
missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict(
sd, strict=False)
print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys")
if len(missing) > 0:
if missing:
print(f"Missing Keys: {missing}")
if len(unexpected) > 0:
if unexpected:
print(f"Unexpected Keys: {unexpected}")
def q_mean_variance(self, x_start, t):

View File

@ -9,14 +9,14 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork):
def activate(self, p, params_list):
additional = shared.opts.sd_lora
if additional != "None" and additional in lora.available_loras and len([x for x in params_list if x.items[0] == additional]) == 0:
if additional != "None" and additional in lora.available_loras and not any(x for x in params_list if x.items[0] == additional):
p.all_prompts = [x + f"<lora:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts]
params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
names = []
multipliers = []
for params in params_list:
assert len(params.items) > 0
assert params.items
names.append(params.items[0])
multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0)

View File

@ -219,7 +219,7 @@ def load_lora(name, lora_on_disk):
else:
raise AssertionError(f"Bad Lora layer name: {key_diffusers} - must end in lora_up.weight, lora_down.weight or alpha")
if len(keys_failed_to_match) > 0:
if keys_failed_to_match:
print(f"Failed to match keys when loading Lora {lora_on_disk.filename}: {keys_failed_to_match}")
return lora
@ -267,7 +267,7 @@ def load_loras(names, multipliers=None):
lora.multiplier = multipliers[i] if multipliers else 1.0
loaded_loras.append(lora)
if len(failed_to_load_loras) > 0:
if failed_to_load_loras:
sd_hijack.model_hijack.comments.append("Failed to find Loras: " + ", ".join(failed_to_load_loras))

View File

@ -21,7 +21,7 @@ class ExtraOptionsSection(scripts.Script):
self.setting_names = []
with gr.Blocks() as interface:
with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and len(shared.opts.extra_options) > 0 else gr.Group(), gr.Row():
with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and shared.opts.extra_options else gr.Group(), gr.Row():
for setting_name in shared.opts.extra_options:
with FormColumn():
comp = ui_settings.create_setting_component(setting_name)

View File

@ -280,7 +280,7 @@ class Api:
script_args[0] = selectable_idx + 1
# Now check for always on scripts
if request.alwayson_scripts and (len(request.alwayson_scripts) > 0):
if request.alwayson_scripts:
for alwayson_script_name in request.alwayson_scripts.keys():
alwayson_script = self.get_script(alwayson_script_name, script_runner)
if alwayson_script is None:

View File

@ -21,7 +21,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
def f(*args, **kwargs):
# if the first argument is a string that says "task(...)", it is treated as a job id
if len(args) > 0 and type(args[0]) == str and args[0][0:5] == "task(" and args[0][-1] == ")":
if args and type(args[0]) == str and args[0].startswith("task(") and args[0].endswith(")"):
id_task = args[0]
progress.add_task_to_queue(id_task)
else:

View File

@ -9,7 +9,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
def activate(self, p, params_list):
additional = shared.opts.sd_hypernetwork
if additional != "None" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0:
if additional != "None" and additional in shared.hypernetworks and not any(x for x in params_list if x.items[0] == additional):
hypernet_prompt_text = f"<hypernet:{additional}:{shared.opts.extra_networks_default_multiplier}>"
p.all_prompts = [f"{prompt}{hypernet_prompt_text}" for prompt in p.all_prompts]
params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
@ -17,7 +17,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork):
names = []
multipliers = []
for params in params_list:
assert len(params.items) > 0
assert params.items
names.append(params.items[0])
multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0)

View File

@ -55,7 +55,7 @@ def image_from_url_text(filedata):
if filedata is None:
return None
if type(filedata) == list and len(filedata) > 0 and type(filedata[0]) == dict and filedata[0].get("is_file", False):
if type(filedata) == list and filedata and type(filedata[0]) == dict and filedata[0].get("is_file", False):
filedata = filedata[0]
if type(filedata) == dict and filedata.get("is_file", False):
@ -437,7 +437,7 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component,
vals_pairs = [f"{k}: {v}" for k, v in vals.items()]
return gr.Dropdown.update(value=vals_pairs, choices=vals_pairs, visible=len(vals_pairs) > 0)
return gr.Dropdown.update(value=vals_pairs, choices=vals_pairs, visible=bool(vals_pairs))
paste_fields = paste_fields + [(override_settings_component, paste_settings)]
@ -454,5 +454,3 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component,
outputs=[],
show_progress=False,
)

View File

@ -406,7 +406,7 @@ class FilenameGenerator:
prompt_no_style = self.prompt
for style in shared.prompt_styles.get_style_prompts(self.p.styles):
if len(style) > 0:
if style:
for part in style.split("{prompt}"):
prompt_no_style = prompt_no_style.replace(part, "").replace(", ,", ",").strip().strip(',')
@ -415,7 +415,7 @@ class FilenameGenerator:
return sanitize_filename_part(prompt_no_style, replace_spaces=False)
def prompt_words(self):
words = [x for x in re_nonletters.split(self.prompt or "") if len(x) > 0]
words = [x for x in re_nonletters.split(self.prompt or "") if x]
if len(words) == 0:
words = ["empty"]
return sanitize_filename_part(" ".join(words[0:opts.directories_max_prompt_words]), replace_spaces=False)
@ -423,7 +423,7 @@ class FilenameGenerator:
def datetime(self, *args):
time_datetime = datetime.datetime.now()
time_format = args[0] if len(args) > 0 and args[0] != "" else self.default_time_format
time_format = args[0] if (args and args[0] != "") else self.default_time_format
try:
time_zone = pytz.timezone(args[1]) if len(args) > 1 else None
except pytz.exceptions.UnknownTimeZoneError:

View File

@ -21,8 +21,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
is_inpaint_batch = False
if inpaint_mask_dir:
inpaint_masks = shared.listfiles(inpaint_mask_dir)
is_inpaint_batch = len(inpaint_masks) > 0
if is_inpaint_batch:
is_inpaint_batch = bool(inpaint_masks)
print(f"\nInpaint batch is enabled. {len(inpaint_masks)} masks found.")
print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.")

View File

@ -230,9 +230,9 @@ class DDPM(pl.LightningModule):
missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict(
sd, strict=False)
print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys")
if len(missing) > 0:
if missing:
print(f"Missing Keys: {missing}")
if len(unexpected) > 0:
if unexpected:
print(f"Unexpected Keys: {unexpected}")
def q_mean_variance(self, x_start, t):

View File

@ -975,7 +975,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest")
if self.enable_hr and latent_scale_mode is None:
assert len([x for x in shared.sd_upscalers if x.name == self.hr_upscaler]) > 0, f"could not find upscaler named {self.hr_upscaler}"
if not any(x.name == self.hr_upscaler for x in shared.sd_upscalers):
raise Exception(f"could not find upscaler named {self.hr_upscaler}")
x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))

View File

@ -336,11 +336,11 @@ def parse_prompt_attention(text):
round_brackets.append(len(res))
elif text == '[':
square_brackets.append(len(res))
elif weight is not None and len(round_brackets) > 0:
elif weight is not None and round_brackets:
multiply_range(round_brackets.pop(), float(weight))
elif text == ')' and len(round_brackets) > 0:
elif text == ')' and round_brackets:
multiply_range(round_brackets.pop(), round_bracket_multiplier)
elif text == ']' and len(square_brackets) > 0:
elif text == ']' and square_brackets:
multiply_range(square_brackets.pop(), square_bracket_multiplier)
else:
parts = re.split(re_break, text)

View File

@ -287,14 +287,14 @@ def list_unets_callback():
def add_callback(callbacks, fun):
stack = [x for x in inspect.stack() if x.filename != __file__]
filename = stack[0].filename if len(stack) > 0 else 'unknown file'
filename = stack[0].filename if stack else 'unknown file'
callbacks.append(ScriptCallback(filename, fun))
def remove_current_script_callbacks():
stack = [x for x in inspect.stack() if x.filename != __file__]
filename = stack[0].filename if len(stack) > 0 else 'unknown file'
filename = stack[0].filename if stack else 'unknown file'
if filename == 'unknown file':
return
for callback_list in callback_map.values():

View File

@ -167,7 +167,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
chunk.multipliers += [weight] * emb_len
position += embedding_length_in_tokens
if len(chunk.tokens) > 0 or len(chunks) == 0:
if chunk.tokens or not chunks:
next_chunk(is_last=True)
return chunks, token_count

View File

@ -74,7 +74,7 @@ def forward_old(self: sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase, text
self.hijack.comments += hijack_comments
if len(used_custom_terms) > 0:
if used_custom_terms:
embedding_names = ", ".join(f"{word} [{checksum}]" for word, checksum in used_custom_terms)
self.hijack.comments.append(f"Used embeddings: {embedding_names}")

View File

@ -77,27 +77,27 @@ def focal_point(im, settings):
pois = []
weight_pref_total = 0
if len(corner_points) > 0:
if corner_points:
weight_pref_total += settings.corner_points_weight
if len(entropy_points) > 0:
if entropy_points:
weight_pref_total += settings.entropy_points_weight
if len(face_points) > 0:
if face_points:
weight_pref_total += settings.face_points_weight
corner_centroid = None
if len(corner_points) > 0:
if corner_points:
corner_centroid = centroid(corner_points)
corner_centroid.weight = settings.corner_points_weight / weight_pref_total
pois.append(corner_centroid)
entropy_centroid = None
if len(entropy_points) > 0:
if entropy_points:
entropy_centroid = centroid(entropy_points)
entropy_centroid.weight = settings.entropy_points_weight / weight_pref_total
pois.append(entropy_centroid)
face_centroid = None
if len(face_points) > 0:
if face_points:
face_centroid = centroid(face_points)
face_centroid.weight = settings.face_points_weight / weight_pref_total
pois.append(face_centroid)
@ -187,7 +187,7 @@ def image_face_points(im, settings):
except Exception:
continue
if len(faces) > 0:
if faces:
rects = [[f[0], f[1], f[0] + f[2], f[1] + f[3]] for f in faces]
return [PointOfInterest((r[0] +r[2]) // 2, (r[1] + r[3]) // 2, size=abs(r[0]-r[2]), weight=1/len(rects)) for r in rects]
return []

View File

@ -32,7 +32,7 @@ class DatasetEntry:
class PersonalizedBase(Dataset):
def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, cond_model=None, device=None, template_file=None, include_cond=False, batch_size=1, gradient_step=1, shuffle_tags=False, tag_drop_out=0, latent_sampling_method='once', varsize=False, use_weight=False):
re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex) > 0 else None
re_word = re.compile(shared.opts.dataset_filename_word_regex) if shared.opts.dataset_filename_word_regex else None
self.placeholder_token = placeholder_token

View File

@ -47,7 +47,7 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti
caption += shared.interrogator.generate_caption(image)
if params.process_caption_deepbooru:
if len(caption) > 0:
if caption:
caption += ", "
caption += deepbooru.model.tag_multi(image)
@ -67,7 +67,7 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti
caption = caption.strip()
if len(caption) > 0:
if caption:
with open(os.path.join(params.dstdir, f"{basename}.txt"), "w", encoding="utf8") as file:
file.write(caption)

View File

@ -251,7 +251,7 @@ class EmbeddingDatabase:
if self.previously_displayed_embeddings != displayed_embeddings:
self.previously_displayed_embeddings = displayed_embeddings
print(f"Textual inversion embeddings loaded({len(self.word_embeddings)}): {', '.join(self.word_embeddings.keys())}")
if len(self.skipped_embeddings) > 0:
if self.skipped_embeddings:
print(f"Textual inversion embeddings skipped({len(self.skipped_embeddings)}): {', '.join(self.skipped_embeddings.keys())}")
def find_embedding_at_position(self, tokens, offset):

View File

@ -398,7 +398,7 @@ def create_override_settings_dropdown(tabname, row):
dropdown = gr.Dropdown([], label="Override settings", visible=False, elem_id=f"{tabname}_override_settings", multiselect=True)
dropdown.change(
fn=lambda x: gr.Dropdown.update(visible=len(x) > 0),
fn=lambda x: gr.Dropdown.update(visible=bool(x)),
inputs=[dropdown],
outputs=[dropdown],
)

View File

@ -333,7 +333,8 @@ def install_extension_from_url(dirname, url, branch_name=None):
assert not os.path.exists(target_dir), f'Extension directory already exists: {target_dir}'
normalized_url = normalize_git_url(url)
assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed'
if any(x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url):
raise Exception(f'Extension with this URL is already installed: {url}')
tmpdir = os.path.join(paths.data_path, "tmp", dirname)
@ -449,7 +450,7 @@ def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text="
existing = installed_extension_urls.get(normalize_git_url(url), None)
extension_tags = extension_tags + ["installed"] if existing else extension_tags
if len([x for x in extension_tags if x in tags_to_hide]) > 0:
if any(x for x in extension_tags if x in tags_to_hide):
hidden += 1
continue

View File

@ -81,7 +81,7 @@ class UiSettings:
opts.save(shared.config_filename)
except RuntimeError:
return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.'
return opts.dumpjson(), f'{len(changed)} settings changed{": " if changed else ""}{", ".join(changed)}.'
def run_settings_single(self, value, key):
if not opts.same_type(value, opts.data_labels[key].default):

View File

@ -121,8 +121,7 @@ class Script(scripts.Script):
return [checkbox_iterate, checkbox_iterate_batch, prompt_txt]
def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_txt: str):
lines = [x.strip() for x in prompt_txt.splitlines()]
lines = [x for x in lines if len(x) > 0]
lines = [x for x in (x.strip() for x in prompt_txt.splitlines()) if x]
p.do_not_save_grid = True