From 14e55a330146bda01f883a79e3900314a79eb22c Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Wed, 3 May 2023 14:28:59 +0900
Subject: print PIL.UnidentifiedImageError
---
modules/img2img.py | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
(limited to 'modules/img2img.py')
diff --git a/modules/img2img.py b/modules/img2img.py
index 56c846d6..9fc3a698 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -48,7 +48,8 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
try:
img = Image.open(image)
- except UnidentifiedImageError:
+ except UnidentifiedImageError as e:
+ print(e)
continue
# Use the EXIF orientation of photos taken by smartphones.
img = ImageOps.exif_transpose(img)
--
cgit v1.2.3
From 762265eab58cdb8f2d6398769bab43d8b8db0075 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 07:52:45 +0300
Subject: autofixes from ruff
---
extensions-builtin/LDSR/ldsr_model_arch.py | 1 -
extensions-builtin/LDSR/sd_hijack_autoencoder.py | 2 +-
modules/api/api.py | 14 +++++++-------
modules/extras.py | 4 ++--
modules/images.py | 4 ++--
modules/img2img.py | 2 +-
modules/prompt_parser.py | 2 +-
modules/realesrgan_model.py | 2 +-
modules/sd_disable_initialization.py | 2 +-
modules/sd_hijack.py | 4 ++--
modules/sd_hijack_ip2p.py | 2 +-
modules/sd_hijack_optimizations.py | 1 -
modules/sd_models.py | 6 +++---
modules/textual_inversion/textual_inversion.py | 2 +-
modules/ui.py | 13 ++++++-------
modules/ui_extensions.py | 2 +-
modules/ui_extra_networks.py | 2 +-
pyproject.toml | 4 +++-
scripts/outpainting_mk_2.py | 2 +-
scripts/postprocessing_upscale.py | 6 +++---
scripts/xyz_grid.py | 2 +-
webui.py | 2 +-
22 files changed, 40 insertions(+), 41 deletions(-)
(limited to 'modules/img2img.py')
diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py
index bc11cc6e..2339de7f 100644
--- a/extensions-builtin/LDSR/ldsr_model_arch.py
+++ b/extensions-builtin/LDSR/ldsr_model_arch.py
@@ -110,7 +110,6 @@ class LDSR:
diffusion_steps = int(steps)
eta = 1.0
- down_sample_method = 'Lanczos'
gc.collect()
if torch.cuda.is_available:
diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
index 8e03c7f8..db2231dd 100644
--- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py
+++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
@@ -165,7 +165,7 @@ class VQModel(pl.LightningModule):
def validation_step(self, batch, batch_idx):
log_dict = self._validation_step(batch, batch_idx)
with self.ema_scope():
- log_dict_ema = self._validation_step(batch, batch_idx, suffix="_ema")
+ self._validation_step(batch, batch_idx, suffix="_ema")
return log_dict
def _validation_step(self, batch, batch_idx, suffix=""):
diff --git a/modules/api/api.py b/modules/api/api.py
index 9bb95dfd..d47c39fc 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -60,7 +60,7 @@ def decode_base64_to_image(encoding):
try:
image = Image.open(BytesIO(base64.b64decode(encoding)))
return image
- except Exception as err:
+ except Exception:
raise HTTPException(status_code=500, detail="Invalid encoded image")
def encode_pil_to_base64(image):
@@ -264,11 +264,11 @@ class Api:
if request.alwayson_scripts and (len(request.alwayson_scripts) > 0):
for alwayson_script_name in request.alwayson_scripts.keys():
alwayson_script = self.get_script(alwayson_script_name, script_runner)
- if alwayson_script == None:
+ if alwayson_script is None:
raise HTTPException(status_code=422, detail=f"always on script {alwayson_script_name} not found")
# Selectable script in always on script param check
- if alwayson_script.alwayson == False:
- raise HTTPException(status_code=422, detail=f"Cannot have a selectable script in the always on scripts params")
+ if alwayson_script.alwayson is False:
+ raise HTTPException(status_code=422, detail="Cannot have a selectable script in the always on scripts params")
# always on script with no arg should always run so you don't really need to add them to the requests
if "args" in request.alwayson_scripts[alwayson_script_name]:
# min between arg length in scriptrunner and arg length in the request
@@ -310,7 +310,7 @@ class Api:
p.outpath_samples = opts.outdir_txt2img_samples
shared.state.begin()
- if selectable_scripts != None:
+ if selectable_scripts is not None:
p.script_args = script_args
processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
else:
@@ -367,7 +367,7 @@ class Api:
p.outpath_samples = opts.outdir_img2img_samples
shared.state.begin()
- if selectable_scripts != None:
+ if selectable_scripts is not None:
p.script_args = script_args
processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
else:
@@ -642,7 +642,7 @@ class Api:
sd_hijack.apply_optimizations()
shared.state.end()
return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
- except AssertionError as msg:
+ except AssertionError:
shared.state.end()
return TrainResponse(info=f"train embedding error: {error}")
diff --git a/modules/extras.py b/modules/extras.py
index ff4e9c4e..eb4f0b42 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -136,14 +136,14 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
result_is_instruct_pix2pix_model = False
if theta_func2:
- shared.state.textinfo = f"Loading B"
+ shared.state.textinfo = "Loading B"
print(f"Loading {secondary_model_info.filename}...")
theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
else:
theta_1 = None
if theta_func1:
- shared.state.textinfo = f"Loading C"
+ shared.state.textinfo = "Loading C"
print(f"Loading {tertiary_model_info.filename}...")
theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu')
diff --git a/modules/images.py b/modules/images.py
index a41965ab..3d5d76cc 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -409,13 +409,13 @@ class FilenameGenerator:
time_format = args[0] if len(args) > 0 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 as _:
+ except pytz.exceptions.UnknownTimeZoneError:
time_zone = None
time_zone_time = time_datetime.astimezone(time_zone)
try:
formatted_time = time_zone_time.strftime(time_format)
- except (ValueError, TypeError) as _:
+ except (ValueError, TypeError):
formatted_time = time_zone_time.strftime(self.default_time_format)
return sanitize_filename_part(formatted_time, replace_spaces=False)
diff --git a/modules/img2img.py b/modules/img2img.py
index 9fc3a698..cdae301a 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -59,7 +59,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
# try to find corresponding mask for an image using simple filename matching
mask_image_path = os.path.join(inpaint_mask_dir, os.path.basename(image))
# if not found use first one ("same mask for all images" use-case)
- if not mask_image_path in inpaint_masks:
+ if mask_image_path not in inpaint_masks:
mask_image_path = inpaint_masks[0]
mask_image = Image.open(mask_image_path)
p.image_mask = mask_image
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 69665372..e084e948 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -92,7 +92,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
def get_schedule(prompt):
try:
tree = schedule_parser.parse(prompt)
- except lark.exceptions.LarkError as e:
+ except lark.exceptions.LarkError:
if 0:
import traceback
traceback.print_exc()
diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py
index efd7fca5..9ec1adf2 100644
--- a/modules/realesrgan_model.py
+++ b/modules/realesrgan_model.py
@@ -134,6 +134,6 @@ def get_realesrgan_models(scaler):
),
]
return models
- except Exception as e:
+ except Exception:
print("Error making Real-ESRGAN models list:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py
index c4a09d15..9fc89dc6 100644
--- a/modules/sd_disable_initialization.py
+++ b/modules/sd_disable_initialization.py
@@ -61,7 +61,7 @@ class DisableInitialization:
if res is None:
res = original(url, *args, local_files_only=False, **kwargs)
return res
- except Exception as e:
+ except Exception:
return original(url, *args, local_files_only=False, **kwargs)
def transformers_utils_hub_get_from_cache(url, *args, local_files_only=False, **kwargs):
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index f4bb0266..d8135211 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -118,7 +118,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs):
try:
#Delete temporary weights if appended
del sd_model._custom_loss_weight
- except AttributeError as e:
+ except AttributeError:
pass
#If we have an old loss function, reset the loss function to the original one
@@ -133,7 +133,7 @@ def apply_weighted_forward(sd_model):
def undo_weighted_forward(sd_model):
try:
del sd_model.weighted_forward
- except AttributeError as e:
+ except AttributeError:
pass
diff --git a/modules/sd_hijack_ip2p.py b/modules/sd_hijack_ip2p.py
index 3c727d3b..41ed54a2 100644
--- a/modules/sd_hijack_ip2p.py
+++ b/modules/sd_hijack_ip2p.py
@@ -10,4 +10,4 @@ def should_hijack_ip2p(checkpoint_info):
ckpt_basename = os.path.basename(checkpoint_info.filename).lower()
cfg_basename = os.path.basename(sd_models_config.find_checkpoint_config_near_filename(checkpoint_info)).lower()
- return "pix2pix" in ckpt_basename and not "pix2pix" in cfg_basename
+ return "pix2pix" in ckpt_basename and "pix2pix" not in cfg_basename
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index f10865cd..b623d53d 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -296,7 +296,6 @@ def sub_quad_attention(q, k, v, q_chunk_size=1024, kv_chunk_size=None, kv_chunk_
if chunk_threshold_bytes is not None and qk_matmul_size_bytes <= chunk_threshold_bytes:
# the big matmul fits into our memory limit; do everything in 1 chunk,
# i.e. send it down the unchunked fast-path
- query_chunk_size = q_tokens
kv_chunk_size = k_tokens
with devices.without_autocast(disable=q.dtype == v.dtype):
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 36f643e1..11c1a344 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -239,7 +239,7 @@ def read_metadata_from_safetensors(filename):
if isinstance(v, str) and v[0:1] == '{':
try:
res[k] = json.loads(v)
- except Exception as e:
+ except Exception:
pass
return res
@@ -467,7 +467,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
try:
with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd):
sd_model = instantiate_from_config(sd_config.model)
- except Exception as e:
+ except Exception:
pass
if sd_model is None:
@@ -544,7 +544,7 @@ def reload_model_weights(sd_model=None, info=None):
try:
load_model_weights(sd_model, checkpoint_info, state_dict, timer)
- except Exception as e:
+ except Exception:
print("Failed to load checkpoint, restoring previous")
load_model_weights(sd_model, current_checkpoint_info, None, timer)
raise
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 4368eb63..f753b75f 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -603,7 +603,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
try:
vectorSize = list(data['string_to_param'].values())[0].shape[0]
- except Exception as e:
+ except Exception:
vectorSize = '?'
checkpoint = sd_models.select_checkpoint()
diff --git a/modules/ui.py b/modules/ui.py
index d02f6e82..2171f3aa 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -246,7 +246,7 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
all_seeds = gen_info.get('all_seeds', [-1])
res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
- except json.decoder.JSONDecodeError as e:
+ except json.decoder.JSONDecodeError:
if gen_info_string != '':
print("Error parsing JSON generation info:", file=sys.stderr)
print(gen_info_string, file=sys.stderr)
@@ -736,8 +736,8 @@ def create_ui():
with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch:
hidden = '
Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
gr.HTML(
- f"Process images in a directory on the same machine where the server is running." +
- f"
Use an empty output directory to save pictures normally instead of writing to the output directory." +
+ "
Process images in a directory on the same machine where the server is running." +
+ "
Use an empty output directory to save pictures normally instead of writing to the output directory." +
f"
Add inpaint batch mask directory to enable inpaint batch processing."
f"{hidden}
"
)
@@ -746,7 +746,6 @@ def create_ui():
img2img_batch_inpaint_mask_dir = gr.Textbox(label="Inpaint batch mask directory (required for inpaint batch processing only)", **shared.hide_dirs, elem_id="img2img_batch_inpaint_mask_dir")
img2img_tabs = [tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]
- img2img_image_inputs = [init_img, sketch, init_img_with_mask, inpaint_color_sketch]
for i, tab in enumerate(img2img_tabs):
tab.select(fn=lambda tabnum=i: tabnum, inputs=[], outputs=[img2img_selected_tab])
@@ -1290,8 +1289,8 @@ def create_ui():
with gr.Column(elem_id='ti_gallery_container'):
ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
- ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4)
- ti_progress = gr.HTML(elem_id="ti_progress", value="")
+ gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4)
+ gr.HTML(elem_id="ti_progress", value="")
ti_outcome = gr.HTML(elem_id="ti_error", value="")
create_embedding.click(
@@ -1668,7 +1667,7 @@ def create_ui():
interface.render()
if os.path.exists(os.path.join(script_path, "notification.mp3")):
- audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
+ gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
footer = shared.html("footer.html")
footer = footer.format(versions=versions_html())
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index d9faf85a..ed70abe5 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -490,7 +490,7 @@ def create_ui():
config_states.list_config_states()
with gr.Blocks(analytics_enabled=False) as ui:
- with gr.Tabs(elem_id="tabs_extensions") as tabs:
+ with gr.Tabs(elem_id="tabs_extensions"):
with gr.TabItem("Installed", id="installed"):
with gr.Row(elem_id="extensions_installed_top"):
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index 8c3dea56..49e06289 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -263,7 +263,7 @@ def create_ui(container, button, tabname):
ui.stored_extra_pages = pages_in_preferred_order(extra_pages.copy())
ui.tabname = tabname
- with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
+ with gr.Tabs(elem_id=tabname+"_extra_tabs"):
for page in ui.stored_extra_pages:
page_id = page.title.lower().replace(" ", "_")
diff --git a/pyproject.toml b/pyproject.toml
index 9e9662ad..1e164abc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -2,7 +2,9 @@
ignore = [
"E501",
- "E731"
+ "E731",
+ "E402", # Module level import not at top of file
+ "F401" # Module imported but unused
]
exclude = ["extensions"]
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py
index 670bb8ac..b10fed6c 100644
--- a/scripts/outpainting_mk_2.py
+++ b/scripts/outpainting_mk_2.py
@@ -72,7 +72,7 @@ def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.0
height = _np_src_image.shape[1]
num_channels = _np_src_image.shape[2]
- np_src_image = _np_src_image[:] * (1. - np_mask_rgb)
+ _np_src_image[:] * (1. - np_mask_rgb)
np_mask_grey = (np.sum(np_mask_rgb, axis=2) / 3.)
img_mask = np_mask_grey > 1e-6
ref_mask = np_mask_grey < 1e-3
diff --git a/scripts/postprocessing_upscale.py b/scripts/postprocessing_upscale.py
index ef1186ac..edb70ac0 100644
--- a/scripts/postprocessing_upscale.py
+++ b/scripts/postprocessing_upscale.py
@@ -98,13 +98,13 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
assert upscaler2 or (upscaler_2_name is None), f'could not find upscaler named {upscaler_2_name}'
upscaled_image = self.upscale(pp.image, pp.info, upscaler1, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop)
- pp.info[f"Postprocess upscaler"] = upscaler1.name
+ pp.info["Postprocess upscaler"] = upscaler1.name
if upscaler2 and upscaler_2_visibility > 0:
second_upscale = self.upscale(pp.image, pp.info, upscaler2, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop)
upscaled_image = Image.blend(upscaled_image, second_upscale, upscaler_2_visibility)
- pp.info[f"Postprocess upscaler 2"] = upscaler2.name
+ pp.info["Postprocess upscaler 2"] = upscaler2.name
pp.image = upscaled_image
@@ -134,4 +134,4 @@ class ScriptPostprocessingUpscaleSimple(ScriptPostprocessingUpscale):
assert upscaler1, f'could not find upscaler named {upscaler_name}'
pp.image = self.upscale(pp.image, pp.info, upscaler1, 0, upscale_by, 0, 0, False)
- pp.info[f"Postprocess upscaler"] = upscaler1.name
+ pp.info["Postprocess upscaler"] = upscaler1.name
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index a725d74a..2ff42ef8 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -316,7 +316,7 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
return Processed(p, [])
z_count = len(zs)
- sub_grids = [None] * z_count
+
for i in range(z_count):
start_index = (i * len(xs) * len(ys)) + i
end_index = start_index + len(xs) * len(ys)
diff --git a/webui.py b/webui.py
index 727ebd31..ec3d2aba 100644
--- a/webui.py
+++ b/webui.py
@@ -360,7 +360,7 @@ def webui():
if cmd_opts.subpath:
redirector = FastAPI()
redirector.get("/")
- mounted_app = gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}")
+ gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}")
wait_on_server(shared.demo)
print('Restarting UI...')
--
cgit v1.2.3
From 96d6ca4199e7c5eee8d451618de5161cea317c40 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 08:25:25 +0300
Subject: manual fixes for ruff
---
extensions-builtin/LDSR/ldsr_model_arch.py | 2 +-
extensions-builtin/LDSR/scripts/ldsr_model.py | 3 +-
extensions-builtin/LDSR/sd_hijack_autoencoder.py | 10 +-
extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 26 ++---
extensions-builtin/ScuNET/scunet_model_arch.py | 9 +-
extensions-builtin/SwinIR/scripts/swinir_model.py | 2 +-
modules/api/api.py | 129 +++++++++++-----------
modules/api/models.py | 5 +-
modules/codeformer/codeformer_arch.py | 2 +-
modules/esrgan_model_arch.py | 2 +
modules/extra_networks_hypernet.py | 2 +-
modules/images.py | 4 +-
modules/img2img.py | 1 -
modules/interrogate.py | 1 -
modules/modelloader.py | 6 +-
modules/models/diffusion/ddpm_edit.py | 26 ++---
modules/models/diffusion/uni_pc/sampler.py | 3 +-
modules/processing.py | 2 +-
modules/prompt_parser.py | 11 +-
modules/textual_inversion/autocrop.py | 2 +-
modules/ui.py | 8 +-
modules/upscaler.py | 2 +-
22 files changed, 129 insertions(+), 129 deletions(-)
(limited to 'modules/img2img.py')
diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py
index 2339de7f..a5fb8907 100644
--- a/extensions-builtin/LDSR/ldsr_model_arch.py
+++ b/extensions-builtin/LDSR/ldsr_model_arch.py
@@ -243,7 +243,7 @@ def make_convolutional_sample(batch, model, custom_steps=None, eta=1.0, quantize
x_sample_noquant = model.decode_first_stage(sample, force_not_quantize=True)
log["sample_noquant"] = x_sample_noquant
log["sample_diff"] = torch.abs(x_sample_noquant - x_sample)
- except:
+ except Exception:
pass
log["sample"] = x_sample
diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py
index da19cff1..e8dc083c 100644
--- a/extensions-builtin/LDSR/scripts/ldsr_model.py
+++ b/extensions-builtin/LDSR/scripts/ldsr_model.py
@@ -7,7 +7,8 @@ from basicsr.utils.download_util import load_file_from_url
from modules.upscaler import Upscaler, UpscalerData
from ldsr_model_arch import LDSR
from modules import shared, script_callbacks
-import sd_hijack_autoencoder, sd_hijack_ddpm_v1
+import sd_hijack_autoencoder
+import sd_hijack_ddpm_v1
class UpscalerLDSR(Upscaler):
diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
index db2231dd..6303fed5 100644
--- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py
+++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
@@ -1,16 +1,21 @@
# The content of this file comes from the ldm/models/autoencoder.py file of the compvis/stable-diffusion repo
# The VQModel & VQModelInterface were subsequently removed from ldm/models/autoencoder.py when we moved to the stability-ai/stablediffusion repo
# As the LDSR upscaler relies on VQModel & VQModelInterface, the hijack aims to put them back into the ldm.models.autoencoder
-
+import numpy as np
import torch
import pytorch_lightning as pl
import torch.nn.functional as F
from contextlib import contextmanager
+
+from torch.optim.lr_scheduler import LambdaLR
+
+from ldm.modules.ema import LitEma
from taming.modules.vqvae.quantize import VectorQuantizer2 as VectorQuantizer
from ldm.modules.diffusionmodules.model import Encoder, Decoder
from ldm.util import instantiate_from_config
import ldm.models.autoencoder
+from packaging import version
class VQModel(pl.LightningModule):
def __init__(self,
@@ -249,7 +254,8 @@ class VQModel(pl.LightningModule):
if plot_ema:
with self.ema_scope():
xrec_ema, _ = self(x)
- if x.shape[1] > 3: xrec_ema = self.to_rgb(xrec_ema)
+ if x.shape[1] > 3:
+ xrec_ema = self.to_rgb(xrec_ema)
log["reconstructions_ema"] = xrec_ema
return log
diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
index 5c0488e5..4d3f6c56 100644
--- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
+++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
@@ -450,7 +450,7 @@ class LatentDiffusionV1(DDPMV1):
self.cond_stage_key = cond_stage_key
try:
self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1
- except:
+ except Exception:
self.num_downs = 0
if not scale_by_std:
self.scale_factor = scale_factor
@@ -877,16 +877,6 @@ class LatentDiffusionV1(DDPMV1):
c = self.q_sample(x_start=c, t=tc, noise=torch.randn_like(c.float()))
return self.p_losses(x, c, t, *args, **kwargs)
- def _rescale_annotations(self, bboxes, crop_coordinates): # TODO: move to dataset
- def rescale_bbox(bbox):
- x0 = clamp((bbox[0] - crop_coordinates[0]) / crop_coordinates[2])
- y0 = clamp((bbox[1] - crop_coordinates[1]) / crop_coordinates[3])
- w = min(bbox[2] / crop_coordinates[2], 1 - x0)
- h = min(bbox[3] / crop_coordinates[3], 1 - y0)
- return x0, y0, w, h
-
- return [rescale_bbox(b) for b in bboxes]
-
def apply_model(self, x_noisy, t, cond, return_ids=False):
if isinstance(cond, dict):
@@ -1157,8 +1147,10 @@ class LatentDiffusionV1(DDPMV1):
if i % log_every_t == 0 or i == timesteps - 1:
intermediates.append(x0_partial)
- if callback: callback(i)
- if img_callback: img_callback(img, i)
+ if callback:
+ callback(i)
+ if img_callback:
+ img_callback(img, i)
return img, intermediates
@torch.no_grad()
@@ -1205,8 +1197,10 @@ class LatentDiffusionV1(DDPMV1):
if i % log_every_t == 0 or i == timesteps - 1:
intermediates.append(img)
- if callback: callback(i)
- if img_callback: img_callback(img, i)
+ if callback:
+ callback(i)
+ if img_callback:
+ img_callback(img, i)
if return_intermediates:
return img, intermediates
@@ -1322,7 +1316,7 @@ class LatentDiffusionV1(DDPMV1):
if inpaint:
# make a simple center square
- b, h, w = z.shape[0], z.shape[2], z.shape[3]
+ h, w = z.shape[2], z.shape[3]
mask = torch.ones(N, h, w).to(self.device)
# zeros will be filled in
mask[:, h // 4:3 * h // 4, w // 4:3 * w // 4] = 0.
diff --git a/extensions-builtin/ScuNET/scunet_model_arch.py b/extensions-builtin/ScuNET/scunet_model_arch.py
index 43ca8d36..8028918a 100644
--- a/extensions-builtin/ScuNET/scunet_model_arch.py
+++ b/extensions-builtin/ScuNET/scunet_model_arch.py
@@ -61,7 +61,9 @@ class WMSA(nn.Module):
Returns:
output: tensor shape [b h w c]
"""
- if self.type != 'W': x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2))
+ if self.type != 'W':
+ x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2))
+
x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size)
h_windows = x.size(1)
w_windows = x.size(2)
@@ -85,8 +87,9 @@ class WMSA(nn.Module):
output = self.linear(output)
output = rearrange(output, 'b (w1 w2) (p1 p2) c -> b (w1 p1) (w2 p2) c', w1=h_windows, p1=self.window_size)
- if self.type != 'W': output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2),
- dims=(1, 2))
+ if self.type != 'W':
+ output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2), dims=(1, 2))
+
return output
def relative_embedding(self):
diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py
index e8783bca..d77c3a92 100644
--- a/extensions-builtin/SwinIR/scripts/swinir_model.py
+++ b/extensions-builtin/SwinIR/scripts/swinir_model.py
@@ -45,7 +45,7 @@ class UpscalerSwinIR(Upscaler):
img = upscale(img, model)
try:
torch.cuda.empty_cache()
- except:
+ except Exception:
pass
return img
diff --git a/modules/api/api.py b/modules/api/api.py
index d47c39fc..f52d371b 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -15,7 +15,8 @@ from secrets import compare_digest
import modules.shared as shared
from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing
-from modules.api.models import *
+from modules.api import models
+from modules.shared import opts
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
from modules.textual_inversion.textual_inversion import create_embedding, train_embedding
from modules.textual_inversion.preprocess import preprocess
@@ -25,20 +26,21 @@ from modules.sd_models import checkpoints_list, unload_model_weights, reload_mod
from modules.sd_models_config import find_checkpoint_config_near_filename
from modules.realesrgan_model import get_realesrgan_models
from modules import devices
-from typing import List
+from typing import Dict, List, Any
import piexif
import piexif.helper
+
def upscaler_to_index(name: str):
try:
return [x.name.lower() for x in shared.sd_upscalers].index(name.lower())
- except:
- raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in sd_upscalers])}")
+ except Exception:
+ raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}")
def script_name_to_index(name, scripts):
try:
return [script.title().lower() for script in scripts].index(name.lower())
- except:
+ except Exception:
raise HTTPException(status_code=422, detail=f"Script '{name}' not found")
def validate_sampler_name(name):
@@ -99,7 +101,7 @@ def api_middleware(app: FastAPI):
import starlette # importing just so it can be placed on silent list
from rich.console import Console
console = Console()
- except:
+ except Exception:
import traceback
rich_available = False
@@ -166,36 +168,36 @@ class Api:
self.app = app
self.queue_lock = queue_lock
api_middleware(self.app)
- self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse)
- self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse)
- self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse)
- self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
- self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse)
- self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse)
+ self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=models.TextToImageResponse)
+ self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=models.ImageToImageResponse)
+ self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=models.ExtrasSingleImageResponse)
+ self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=models.ExtrasBatchImagesResponse)
+ self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=models.PNGInfoResponse)
+ self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=models.ProgressResponse)
self.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"])
self.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"])
self.add_api_route("/sdapi/v1/skip", self.skip, methods=["POST"])
- self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel)
+ self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=models.OptionsModel)
self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"])
- self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=FlagsModel)
- self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem])
- self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem])
- self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem])
- self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem])
- self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem])
- self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem])
- self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[PromptStyleItem])
- self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=EmbeddingsResponse)
+ self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=models.FlagsModel)
+ self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[models.SamplerItem])
+ self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[models.UpscalerItem])
+ self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[models.SDModelItem])
+ self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[models.HypernetworkItem])
+ self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[models.FaceRestorerItem])
+ self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[models.RealesrganItem])
+ self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[models.PromptStyleItem])
+ self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=models.EmbeddingsResponse)
self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"])
- self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=CreateResponse)
- self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=CreateResponse)
- self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=PreprocessResponse)
- self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse)
- self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse)
- self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse)
+ self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=models.CreateResponse)
+ self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=models.CreateResponse)
+ self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=models.PreprocessResponse)
+ self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=models.TrainResponse)
+ self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=models.TrainResponse)
+ self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=models.MemoryResponse)
self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"])
self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])
- self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList)
+ self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList)
self.default_script_arg_txt2img = []
self.default_script_arg_img2img = []
@@ -224,7 +226,7 @@ class Api:
t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles]
i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles]
- return ScriptsList(txt2img = t2ilist, img2img = i2ilist)
+ return models.ScriptsList(txt2img=t2ilist, img2img=i2ilist)
def get_script(self, script_name, script_runner):
if script_name is None or script_name == "":
@@ -276,7 +278,7 @@ class Api:
script_args[alwayson_script.args_from + idx] = request.alwayson_scripts[alwayson_script_name]["args"][idx]
return script_args
- def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
+ def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
script_runner = scripts.scripts_txt2img
if not script_runner.scripts:
script_runner.initialize_scripts(False)
@@ -320,9 +322,9 @@ class Api:
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
- return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
+ return models.TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
- def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI):
+ def img2imgapi(self, img2imgreq: models.StableDiffusionImg2ImgProcessingAPI):
init_images = img2imgreq.init_images
if init_images is None:
raise HTTPException(status_code=404, detail="Init image not found")
@@ -381,9 +383,9 @@ class Api:
img2imgreq.init_images = None
img2imgreq.mask = None
- return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
+ return models.ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
- def extras_single_image_api(self, req: ExtrasSingleImageRequest):
+ def extras_single_image_api(self, req: models.ExtrasSingleImageRequest):
reqDict = setUpscalers(req)
reqDict['image'] = decode_base64_to_image(reqDict['image'])
@@ -391,9 +393,9 @@ class Api:
with self.queue_lock:
result = postprocessing.run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", save_output=False, **reqDict)
- return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
+ return models.ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
- def extras_batch_images_api(self, req: ExtrasBatchImagesRequest):
+ def extras_batch_images_api(self, req: models.ExtrasBatchImagesRequest):
reqDict = setUpscalers(req)
image_list = reqDict.pop('imageList', [])
@@ -402,15 +404,15 @@ class Api:
with self.queue_lock:
result = postprocessing.run_extras(extras_mode=1, image_folder=image_folder, image="", input_dir="", output_dir="", save_output=False, **reqDict)
- return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
+ return models.ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
- def pnginfoapi(self, req: PNGInfoRequest):
+ def pnginfoapi(self, req: models.PNGInfoRequest):
if(not req.image.strip()):
- return PNGInfoResponse(info="")
+ return models.PNGInfoResponse(info="")
image = decode_base64_to_image(req.image.strip())
if image is None:
- return PNGInfoResponse(info="")
+ return models.PNGInfoResponse(info="")
geninfo, items = images.read_info_from_image(image)
if geninfo is None:
@@ -418,13 +420,13 @@ class Api:
items = {**{'parameters': geninfo}, **items}
- return PNGInfoResponse(info=geninfo, items=items)
+ return models.PNGInfoResponse(info=geninfo, items=items)
- def progressapi(self, req: ProgressRequest = Depends()):
+ def progressapi(self, req: models.ProgressRequest = Depends()):
# copy from check_progress_call of ui.py
if shared.state.job_count == 0:
- return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo)
+ return models.ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo)
# avoid dividing zero
progress = 0.01
@@ -446,9 +448,9 @@ class Api:
if shared.state.current_image and not req.skip_current_image:
current_image = encode_pil_to_base64(shared.state.current_image)
- return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo)
+ return models.ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo)
- def interrogateapi(self, interrogatereq: InterrogateRequest):
+ def interrogateapi(self, interrogatereq: models.InterrogateRequest):
image_b64 = interrogatereq.image
if image_b64 is None:
raise HTTPException(status_code=404, detail="Image not found")
@@ -465,7 +467,7 @@ class Api:
else:
raise HTTPException(status_code=404, detail="Model not found")
- return InterrogateResponse(caption=processed)
+ return models.InterrogateResponse(caption=processed)
def interruptapi(self):
shared.state.interrupt()
@@ -570,36 +572,36 @@ class Api:
filename = create_embedding(**args) # create empty embedding
sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() # reload embeddings so new one can be immediately used
shared.state.end()
- return CreateResponse(info=f"create embedding filename: {filename}")
+ return models.CreateResponse(info=f"create embedding filename: {filename}")
except AssertionError as e:
shared.state.end()
- return TrainResponse(info=f"create embedding error: {e}")
+ return models.TrainResponse(info=f"create embedding error: {e}")
def create_hypernetwork(self, args: dict):
try:
shared.state.begin()
filename = create_hypernetwork(**args) # create empty embedding
shared.state.end()
- return CreateResponse(info=f"create hypernetwork filename: {filename}")
+ return models.CreateResponse(info=f"create hypernetwork filename: {filename}")
except AssertionError as e:
shared.state.end()
- return TrainResponse(info=f"create hypernetwork error: {e}")
+ return models.TrainResponse(info=f"create hypernetwork error: {e}")
def preprocess(self, args: dict):
try:
shared.state.begin()
preprocess(**args) # quick operation unless blip/booru interrogation is enabled
shared.state.end()
- return PreprocessResponse(info = 'preprocess complete')
+ return models.PreprocessResponse(info = 'preprocess complete')
except KeyError as e:
shared.state.end()
- return PreprocessResponse(info=f"preprocess error: invalid token: {e}")
+ return models.PreprocessResponse(info=f"preprocess error: invalid token: {e}")
except AssertionError as e:
shared.state.end()
- return PreprocessResponse(info=f"preprocess error: {e}")
+ return models.PreprocessResponse(info=f"preprocess error: {e}")
except FileNotFoundError as e:
shared.state.end()
- return PreprocessResponse(info=f'preprocess error: {e}')
+ return models.PreprocessResponse(info=f'preprocess error: {e}')
def train_embedding(self, args: dict):
try:
@@ -617,10 +619,10 @@ class Api:
if not apply_optimizations:
sd_hijack.apply_optimizations()
shared.state.end()
- return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
+ return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
except AssertionError as msg:
shared.state.end()
- return TrainResponse(info=f"train embedding error: {msg}")
+ return models.TrainResponse(info=f"train embedding error: {msg}")
def train_hypernetwork(self, args: dict):
try:
@@ -641,14 +643,15 @@ class Api:
if not apply_optimizations:
sd_hijack.apply_optimizations()
shared.state.end()
- return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
+ return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
except AssertionError:
shared.state.end()
- return TrainResponse(info=f"train embedding error: {error}")
+ return models.TrainResponse(info=f"train embedding error: {error}")
def get_memory(self):
try:
- import os, psutil
+ import os
+ import psutil
process = psutil.Process(os.getpid())
res = process.memory_info() # only rss is cross-platform guaranteed so we dont rely on other values
ram_total = 100 * res.rss / process.memory_percent() # and total memory is calculated as actual value is not cross-platform safe
@@ -675,10 +678,10 @@ class Api:
'events': warnings,
}
else:
- cuda = { 'error': 'unavailable' }
+ cuda = {'error': 'unavailable'}
except Exception as err:
- cuda = { 'error': f'{err}' }
- return MemoryResponse(ram = ram, cuda = cuda)
+ cuda = {'error': f'{err}'}
+ return models.MemoryResponse(ram=ram, cuda=cuda)
def launch(self, server_name, port):
self.app.include_router(self.router)
diff --git a/modules/api/models.py b/modules/api/models.py
index 4a70f440..4d291076 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -223,8 +223,9 @@ for key in _options:
if(_options[key].dest != 'help'):
flag = _options[key]
_type = str
- if _options[key].default is not None: _type = type(_options[key].default)
- flags.update({flag.dest: (_type,Field(default=flag.default, description=flag.help))})
+ if _options[key].default is not None:
+ _type = type(_options[key].default)
+ flags.update({flag.dest: (_type, Field(default=flag.default, description=flag.help))})
FlagsModel = create_model("Flags", **flags)
diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py
index 11dcc3ee..f1a7cf09 100644
--- a/modules/codeformer/codeformer_arch.py
+++ b/modules/codeformer/codeformer_arch.py
@@ -7,7 +7,7 @@ from torch import nn, Tensor
import torch.nn.functional as F
from typing import Optional, List
-from modules.codeformer.vqgan_arch import *
+from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock
from basicsr.utils import get_root_logger
from basicsr.utils.registry import ARCH_REGISTRY
diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py
index 6071fea7..7f8bc7c0 100644
--- a/modules/esrgan_model_arch.py
+++ b/modules/esrgan_model_arch.py
@@ -438,9 +438,11 @@ def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=1, bias=
padding = padding if pad_type == 'zero' else 0
if convtype=='PartialConv2D':
+ from torchvision.ops import PartialConv2d # this is definitely not going to work, but PartialConv2d doesn't work anyway and this shuts up static analyzer
c = PartialConv2d(in_nc, out_nc, kernel_size=kernel_size, stride=stride, padding=padding,
dilation=dilation, bias=bias, groups=groups)
elif convtype=='DeformConv2D':
+ from torchvision.ops import DeformConv2d # not tested
c = DeformConv2d(in_nc, out_nc, kernel_size=kernel_size, stride=stride, padding=padding,
dilation=dilation, bias=bias, groups=groups)
elif convtype=='Conv3D':
diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py
index 04f27c9f..aa2a14ef 100644
--- a/modules/extra_networks_hypernet.py
+++ b/modules/extra_networks_hypernet.py
@@ -1,4 +1,4 @@
-from modules import extra_networks, shared, extra_networks
+from modules import extra_networks, shared
from modules.hypernetworks import hypernetwork
diff --git a/modules/images.py b/modules/images.py
index 3d5d76cc..5eb6d855 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -472,9 +472,9 @@ def get_next_sequence_number(path, basename):
prefix_length = len(basename)
for p in os.listdir(path):
if p.startswith(basename):
- l = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element)
+ parts = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element)
try:
- result = max(int(l[0]), result)
+ result = max(int(parts[0]), result)
except ValueError:
pass
diff --git a/modules/img2img.py b/modules/img2img.py
index cdae301a..32b1ecd6 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -13,7 +13,6 @@ from modules.shared import opts, state
import modules.shared as shared
import modules.processing as processing
from modules.ui import plaintext_to_html
-import modules.images as images
import modules.scripts
diff --git a/modules/interrogate.py b/modules/interrogate.py
index 9f7d657f..22df9216 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -11,7 +11,6 @@ import torch.hub
from torchvision import transforms
from torchvision.transforms.functional import InterpolationMode
-import modules.shared as shared
from modules import devices, paths, shared, lowvram, modelloader, errors
blip_image_eval_size = 384
diff --git a/modules/modelloader.py b/modules/modelloader.py
index cb85ac4f..cf685000 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -108,12 +108,12 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None):
print(f"Moving {file} from {src_path} to {dest_path}.")
try:
shutil.move(fullpath, dest_path)
- except:
+ except Exception:
pass
if len(os.listdir(src_path)) == 0:
print(f"Removing empty folder: {src_path}")
shutil.rmtree(src_path, True)
- except:
+ except Exception:
pass
@@ -141,7 +141,7 @@ def load_upscalers():
full_model = f"modules.{model_name}_model"
try:
importlib.import_module(full_model)
- except:
+ except Exception:
pass
datas = []
diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py
index f880bc3c..611c2b69 100644
--- a/modules/models/diffusion/ddpm_edit.py
+++ b/modules/models/diffusion/ddpm_edit.py
@@ -479,7 +479,7 @@ class LatentDiffusion(DDPM):
self.cond_stage_key = cond_stage_key
try:
self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1
- except:
+ except Exception:
self.num_downs = 0
if not scale_by_std:
self.scale_factor = scale_factor
@@ -891,16 +891,6 @@ class LatentDiffusion(DDPM):
c = self.q_sample(x_start=c, t=tc, noise=torch.randn_like(c.float()))
return self.p_losses(x, c, t, *args, **kwargs)
- def _rescale_annotations(self, bboxes, crop_coordinates): # TODO: move to dataset
- def rescale_bbox(bbox):
- x0 = clamp((bbox[0] - crop_coordinates[0]) / crop_coordinates[2])
- y0 = clamp((bbox[1] - crop_coordinates[1]) / crop_coordinates[3])
- w = min(bbox[2] / crop_coordinates[2], 1 - x0)
- h = min(bbox[3] / crop_coordinates[3], 1 - y0)
- return x0, y0, w, h
-
- return [rescale_bbox(b) for b in bboxes]
-
def apply_model(self, x_noisy, t, cond, return_ids=False):
if isinstance(cond, dict):
@@ -1171,8 +1161,10 @@ class LatentDiffusion(DDPM):
if i % log_every_t == 0 or i == timesteps - 1:
intermediates.append(x0_partial)
- if callback: callback(i)
- if img_callback: img_callback(img, i)
+ if callback:
+ callback(i)
+ if img_callback:
+ img_callback(img, i)
return img, intermediates
@torch.no_grad()
@@ -1219,8 +1211,10 @@ class LatentDiffusion(DDPM):
if i % log_every_t == 0 or i == timesteps - 1:
intermediates.append(img)
- if callback: callback(i)
- if img_callback: img_callback(img, i)
+ if callback:
+ callback(i)
+ if img_callback:
+ img_callback(img, i)
if return_intermediates:
return img, intermediates
@@ -1337,7 +1331,7 @@ class LatentDiffusion(DDPM):
if inpaint:
# make a simple center square
- b, h, w = z.shape[0], z.shape[2], z.shape[3]
+ h, w = z.shape[2], z.shape[3]
mask = torch.ones(N, h, w).to(self.device)
# zeros will be filled in
mask[:, h // 4:3 * h // 4, w // 4:3 * w // 4] = 0.
diff --git a/modules/models/diffusion/uni_pc/sampler.py b/modules/models/diffusion/uni_pc/sampler.py
index a241c8a7..0a9defa1 100644
--- a/modules/models/diffusion/uni_pc/sampler.py
+++ b/modules/models/diffusion/uni_pc/sampler.py
@@ -54,7 +54,8 @@ class UniPCSampler(object):
if conditioning is not None:
if isinstance(conditioning, dict):
ctmp = conditioning[list(conditioning.keys())[0]]
- while isinstance(ctmp, list): ctmp = ctmp[0]
+ while isinstance(ctmp, list):
+ ctmp = ctmp[0]
cbs = ctmp.shape[0]
if cbs != batch_size:
print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
diff --git a/modules/processing.py b/modules/processing.py
index 1a76e552..6f5233c1 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -664,7 +664,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if not shared.opts.dont_fix_second_order_samplers_schedule:
try:
step_multiplier = 2 if sd_samplers.all_samplers_map.get(p.sampler_name).aliases[0] in ['k_dpmpp_2s_a', 'k_dpmpp_2s_a_ka', 'k_dpmpp_sde', 'k_dpmpp_sde_ka', 'k_dpm_2', 'k_dpm_2_a', 'k_heun'] else 1
- except:
+ except Exception:
pass
uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps * step_multiplier, cached_uc)
c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps * step_multiplier, cached_c)
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index e084e948..3a720721 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -54,18 +54,21 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
"""
def collect_steps(steps, tree):
- l = [steps]
+ res = [steps]
+
class CollectSteps(lark.Visitor):
def scheduled(self, tree):
tree.children[-1] = float(tree.children[-1])
if tree.children[-1] < 1:
tree.children[-1] *= steps
tree.children[-1] = min(steps, int(tree.children[-1]))
- l.append(tree.children[-1])
+ res.append(tree.children[-1])
+
def alternate(self, tree):
- l.extend(range(1, steps+1))
+ res.extend(range(1, steps+1))
+
CollectSteps().visit(tree)
- return sorted(set(l))
+ return sorted(set(res))
def at_step(step, tree):
class AtStep(lark.Transformer):
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py
index ba1bdcd4..d7d8d2e3 100644
--- a/modules/textual_inversion/autocrop.py
+++ b/modules/textual_inversion/autocrop.py
@@ -185,7 +185,7 @@ def image_face_points(im, settings):
try:
faces = classifier.detectMultiScale(gray, scaleFactor=1.1,
minNeighbors=7, minSize=(minsize, minsize), flags=cv2.CASCADE_SCALE_IMAGE)
- except:
+ except Exception:
continue
if len(faces) > 0:
diff --git a/modules/ui.py b/modules/ui.py
index 2171f3aa..6beda76f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1,15 +1,9 @@
-import html
import json
-import math
import mimetypes
import os
-import platform
-import random
import sys
-import tempfile
-import time
import traceback
-from functools import partial, reduce
+from functools import reduce
import warnings
import gradio as gr
diff --git a/modules/upscaler.py b/modules/upscaler.py
index e2eaa730..0ad4fe99 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -45,7 +45,7 @@ class Upscaler:
try:
import cv2
self.can_tile = True
- except:
+ except Exception:
pass
@abstractmethod
--
cgit v1.2.3
From f741a98baccae100fcfb40c017b5c35c5cba1b0c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 08:43:42 +0300
Subject: imports cleanup for ruff
---
extensions-builtin/Lora/lora.py | 1 -
extensions-builtin/ScuNET/scripts/scunet_model.py | 1 -
extensions-builtin/SwinIR/scripts/swinir_model.py | 3 +--
modules/codeformer/codeformer_arch.py | 4 +---
modules/codeformer/vqgan_arch.py | 2 --
modules/codeformer_model.py | 4 +---
modules/config_states.py | 2 +-
modules/esrgan_model.py | 2 +-
modules/esrgan_model_arch.py | 1 -
modules/extensions.py | 1 -
modules/generation_parameters_copypaste.py | 4 ----
modules/hypernetworks/hypernetwork.py | 3 +--
modules/hypernetworks/ui.py | 2 --
modules/images.py | 2 +-
modules/img2img.py | 5 +----
modules/mac_specific.py | 1 -
modules/modelloader.py | 1 -
modules/models/diffusion/uni_pc/uni_pc.py | 1 -
modules/processing.py | 5 ++---
modules/sd_hijack.py | 2 +-
modules/sd_hijack_inpainting.py | 6 ------
modules/sd_hijack_ip2p.py | 5 +----
modules/sd_hijack_xlmr.py | 2 --
modules/sd_models.py | 2 +-
modules/sd_models_config.py | 1 -
modules/sd_samplers_kdiffusion.py | 1 -
modules/sd_vae.py | 3 ---
modules/shared.py | 3 ---
modules/styles.py | 9 ---------
modules/textual_inversion/autocrop.py | 4 +---
modules/textual_inversion/image_embedding.py | 2 +-
modules/textual_inversion/preprocess.py | 4 ----
modules/textual_inversion/textual_inversion.py | 1 -
modules/txt2img.py | 9 +++------
modules/ui.py | 5 ++---
modules/ui_extra_networks.py | 1 -
modules/ui_postprocessing.py | 2 +-
modules/upscaler.py | 2 --
modules/xlmr.py | 2 +-
pyproject.toml | 11 +++++++----
scripts/custom_code.py | 2 +-
scripts/outpainting_mk_2.py | 4 ++--
scripts/poor_mans_outpainting.py | 4 ++--
scripts/prompt_matrix.py | 7 ++-----
scripts/prompts_from_file.py | 5 +----
scripts/sd_upscale.py | 4 ++--
scripts/xyz_grid.py | 6 ++----
webui.py | 2 +-
48 files changed, 42 insertions(+), 114 deletions(-)
(limited to 'modules/img2img.py')
diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py
index ba1293df..0ab43229 100644
--- a/extensions-builtin/Lora/lora.py
+++ b/extensions-builtin/Lora/lora.py
@@ -1,4 +1,3 @@
-import glob
import os
import re
import torch
diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py
index c7fd5739..aa2fdb3a 100644
--- a/extensions-builtin/ScuNET/scripts/scunet_model.py
+++ b/extensions-builtin/ScuNET/scripts/scunet_model.py
@@ -13,7 +13,6 @@ import modules.upscaler
from modules import devices, modelloader
from scunet_model_arch import SCUNet as net
from modules.shared import opts
-from modules import images
class UpscalerScuNET(modules.upscaler.Upscaler):
diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py
index d77c3a92..55dd94ab 100644
--- a/extensions-builtin/SwinIR/scripts/swinir_model.py
+++ b/extensions-builtin/SwinIR/scripts/swinir_model.py
@@ -1,4 +1,3 @@
-import contextlib
import os
import numpy as np
@@ -8,7 +7,7 @@ from basicsr.utils.download_util import load_file_from_url
from tqdm import tqdm
from modules import modelloader, devices, script_callbacks, shared
-from modules.shared import cmd_opts, opts, state
+from modules.shared import opts, state
from swinir_model_arch import SwinIR as net
from swinir_model_arch_v2 import Swin2SR as net2
from modules.upscaler import Upscaler, UpscalerData
diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py
index f1a7cf09..00c407de 100644
--- a/modules/codeformer/codeformer_arch.py
+++ b/modules/codeformer/codeformer_arch.py
@@ -1,14 +1,12 @@
# this file is copied from CodeFormer repository. Please see comment in modules/codeformer_model.py
import math
-import numpy as np
import torch
from torch import nn, Tensor
import torch.nn.functional as F
-from typing import Optional, List
+from typing import Optional
from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock
-from basicsr.utils import get_root_logger
from basicsr.utils.registry import ARCH_REGISTRY
def calc_mean_std(feat, eps=1e-5):
diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py
index e7293683..820e6b12 100644
--- a/modules/codeformer/vqgan_arch.py
+++ b/modules/codeformer/vqgan_arch.py
@@ -5,11 +5,9 @@ VQGAN code, adapted from the original created by the Unleashing Transformers aut
https://github.com/samb-t/unleashing-transformers/blob/master/models/vqgan.py
'''
-import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
-import copy
from basicsr.utils import get_root_logger
from basicsr.utils.registry import ARCH_REGISTRY
diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py
index 8d84bbc9..8e56cb89 100644
--- a/modules/codeformer_model.py
+++ b/modules/codeformer_model.py
@@ -33,11 +33,9 @@ def setup_model(dirname):
try:
from torchvision.transforms.functional import normalize
from modules.codeformer.codeformer_arch import CodeFormer
- from basicsr.utils.download_util import load_file_from_url
- from basicsr.utils import imwrite, img2tensor, tensor2img
+ from basicsr.utils import img2tensor, tensor2img
from facelib.utils.face_restoration_helper import FaceRestoreHelper
from facelib.detection.retinaface import retinaface
- from modules.shared import cmd_opts
net_class = CodeFormer
diff --git a/modules/config_states.py b/modules/config_states.py
index 2ea00929..8f1ff428 100644
--- a/modules/config_states.py
+++ b/modules/config_states.py
@@ -14,7 +14,7 @@ from collections import OrderedDict
import git
from modules import shared, extensions
-from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path, config_states_dir
+from modules.paths_internal import script_path, config_states_dir
all_config_states = OrderedDict()
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index f4369257..85aa6934 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -6,7 +6,7 @@ from PIL import Image
from basicsr.utils.download_util import load_file_from_url
import modules.esrgan_model_arch as arch
-from modules import shared, modelloader, images, devices
+from modules import modelloader, images, devices
from modules.upscaler import Upscaler, UpscalerData
from modules.shared import opts
diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py
index 7f8bc7c0..4de9dd8d 100644
--- a/modules/esrgan_model_arch.py
+++ b/modules/esrgan_model_arch.py
@@ -2,7 +2,6 @@
from collections import OrderedDict
import math
-import functools
import torch
import torch.nn as nn
import torch.nn.functional as F
diff --git a/modules/extensions.py b/modules/extensions.py
index 34d9d654..829f8cd9 100644
--- a/modules/extensions.py
+++ b/modules/extensions.py
@@ -3,7 +3,6 @@ import sys
import traceback
import time
-from datetime import datetime
import git
from modules import shared
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index fe8b18b2..f1c59c46 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -1,15 +1,11 @@
import base64
-import html
import io
-import math
import os
import re
-from pathlib import Path
import gradio as gr
from modules.paths import data_path
from modules import shared, ui_tempdir, script_callbacks
-import tempfile
from PIL import Image
re_param_code = r'\s*([\w ]+):\s*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)'
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 1fc49537..9fe749b7 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -1,4 +1,3 @@
-import csv
import datetime
import glob
import html
@@ -18,7 +17,7 @@ from modules.textual_inversion.learn_schedule import LearnRateScheduler
from torch import einsum
from torch.nn.init import normal_, xavier_normal_, xavier_uniform_, kaiming_normal_, kaiming_uniform_, zeros_
-from collections import defaultdict, deque
+from collections import deque
from statistics import stdev, mean
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index 76599f5a..be168736 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -1,6 +1,4 @@
import html
-import os
-import re
import gradio as gr
import modules.hypernetworks.hypernetwork
diff --git a/modules/images.py b/modules/images.py
index 5eb6d855..7392cb8b 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -19,7 +19,7 @@ import json
import hashlib
from modules import sd_samplers, shared, script_callbacks, errors
-from modules.shared import opts, cmd_opts
+from modules.shared import opts
LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
diff --git a/modules/img2img.py b/modules/img2img.py
index 32b1ecd6..d704bf90 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -1,12 +1,9 @@
-import math
import os
-import sys
-import traceback
import numpy as np
from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops, UnidentifiedImageError
-from modules import devices, sd_samplers
+from modules import sd_samplers
from modules.generation_parameters_copypaste import create_override_settings_dict
from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images
from modules.shared import opts, state
diff --git a/modules/mac_specific.py b/modules/mac_specific.py
index 40ce2101..5c2f92a1 100644
--- a/modules/mac_specific.py
+++ b/modules/mac_specific.py
@@ -1,6 +1,5 @@
import torch
import platform
-from modules import paths
from modules.sd_hijack_utils import CondFunc
from packaging import version
diff --git a/modules/modelloader.py b/modules/modelloader.py
index cf685000..92ada694 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -1,4 +1,3 @@
-import glob
import os
import shutil
import importlib
diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py
index 11b330bc..a4c4ef4e 100644
--- a/modules/models/diffusion/uni_pc/uni_pc.py
+++ b/modules/models/diffusion/uni_pc/uni_pc.py
@@ -1,5 +1,4 @@
import torch
-import torch.nn.functional as F
import math
from tqdm.auto import trange
diff --git a/modules/processing.py b/modules/processing.py
index 6f5233c1..c3932d6b 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -2,7 +2,6 @@ import json
import math
import os
import sys
-import warnings
import hashlib
import torch
@@ -11,10 +10,10 @@ from PIL import Image, ImageFilter, ImageOps
import random
import cv2
from skimage import exposure
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List
import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks, extra_networks, sd_vae_approx, scripts
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts
from modules.sd_hijack import model_hijack
from modules.shared import opts, cmd_opts, state
import modules.shared as shared
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index d8135211..81573b78 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -3,7 +3,7 @@ from torch.nn.functional import silu
from types import MethodType
import modules.textual_inversion.textual_inversion
-from modules import devices, sd_hijack_optimizations, shared, sd_hijack_checkpoint
+from modules import devices, sd_hijack_optimizations, shared
from modules.hypernetworks import hypernetwork
from modules.shared import cmd_opts
from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hijack_xlmr, xlmr
diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py
index 55a2ce4d..344d75c8 100644
--- a/modules/sd_hijack_inpainting.py
+++ b/modules/sd_hijack_inpainting.py
@@ -1,15 +1,9 @@
-import os
import torch
-from einops import repeat
-from omegaconf import ListConfig
-
import ldm.models.diffusion.ddpm
import ldm.models.diffusion.ddim
import ldm.models.diffusion.plms
-from ldm.models.diffusion.ddpm import LatentDiffusion
-from ldm.models.diffusion.plms import PLMSSampler
from ldm.models.diffusion.ddim import DDIMSampler, noise_like
from ldm.models.diffusion.sampling_util import norm_thresholding
diff --git a/modules/sd_hijack_ip2p.py b/modules/sd_hijack_ip2p.py
index 41ed54a2..6fe6b6ff 100644
--- a/modules/sd_hijack_ip2p.py
+++ b/modules/sd_hijack_ip2p.py
@@ -1,8 +1,5 @@
-import collections
import os.path
-import sys
-import gc
-import time
+
def should_hijack_ip2p(checkpoint_info):
from modules import sd_models_config
diff --git a/modules/sd_hijack_xlmr.py b/modules/sd_hijack_xlmr.py
index 4ac51c38..28528329 100644
--- a/modules/sd_hijack_xlmr.py
+++ b/modules/sd_hijack_xlmr.py
@@ -1,8 +1,6 @@
-import open_clip.tokenizer
import torch
from modules import sd_hijack_clip, devices
-from modules.shared import opts
class FrozenXLMREmbedderWithCustomWords(sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords):
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 11c1a344..1c09c709 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -565,7 +565,7 @@ def reload_model_weights(sd_model=None, info=None):
def unload_model_weights(sd_model=None, info=None):
- from modules import lowvram, devices, sd_hijack
+ from modules import devices, sd_hijack
timer = Timer()
if model_data.sd_model:
diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py
index 7a79925a..9bfe1237 100644
--- a/modules/sd_models_config.py
+++ b/modules/sd_models_config.py
@@ -1,4 +1,3 @@
-import re
import os
import torch
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 0fc9f456..3b8e9622 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -1,7 +1,6 @@
from collections import deque
import torch
import inspect
-import einops
import k_diffusion.sampling
from modules import prompt_parser, devices, sd_samplers_common
diff --git a/modules/sd_vae.py b/modules/sd_vae.py
index 521e485a..b7176125 100644
--- a/modules/sd_vae.py
+++ b/modules/sd_vae.py
@@ -1,8 +1,5 @@
-import torch
-import safetensors.torch
import os
import collections
-from collections import namedtuple
from modules import paths, shared, devices, script_callbacks, sd_models
import glob
from copy import deepcopy
diff --git a/modules/shared.py b/modules/shared.py
index 4631965b..44cd2c0c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -1,12 +1,9 @@
-import argparse
import datetime
import json
import os
import sys
import time
-import requests
-from PIL import Image
import gradio as gr
import tqdm
diff --git a/modules/styles.py b/modules/styles.py
index 11642075..c22769cf 100644
--- a/modules/styles.py
+++ b/modules/styles.py
@@ -1,18 +1,9 @@
-# We need this so Python doesn't complain about the unknown StableDiffusionProcessing-typehint at runtime
-from __future__ import annotations
-
import csv
import os
import os.path
import typing
-import collections.abc as abc
-import tempfile
import shutil
-if typing.TYPE_CHECKING:
- # Only import this when code is being type-checked, it doesn't have any effect at runtime
- from .processing import StableDiffusionProcessing
-
class PromptStyle(typing.NamedTuple):
name: str
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py
index d7d8d2e3..7770d22f 100644
--- a/modules/textual_inversion/autocrop.py
+++ b/modules/textual_inversion/autocrop.py
@@ -1,10 +1,8 @@
import cv2
import requests
import os
-from collections import defaultdict
-from math import log, sqrt
import numpy as np
-from PIL import Image, ImageDraw
+from PIL import ImageDraw
GREEN = "#0F0"
BLUE = "#00F"
diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py
index 5593f88c..ee0e850a 100644
--- a/modules/textual_inversion/image_embedding.py
+++ b/modules/textual_inversion/image_embedding.py
@@ -2,7 +2,7 @@ import base64
import json
import numpy as np
import zlib
-from PIL import Image, PngImagePlugin, ImageDraw, ImageFont
+from PIL import Image, ImageDraw, ImageFont
from fonts.ttf import Roboto
import torch
from modules.shared import opts
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index da0bcb26..d0cad09e 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -1,13 +1,9 @@
import os
from PIL import Image, ImageOps
import math
-import platform
-import sys
import tqdm
-import time
from modules import paths, shared, images, deepbooru
-from modules.shared import opts, cmd_opts
from modules.textual_inversion import autocrop
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index f753b75f..9ed9ba45 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -1,7 +1,6 @@
import os
import sys
import traceback
-import inspect
from collections import namedtuple
import torch
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 16841d0f..f022381c 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -1,18 +1,15 @@
import modules.scripts
-from modules import sd_samplers
+from modules import sd_samplers, processing
from modules.generation_parameters_copypaste import create_override_settings_dict
-from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, \
- StableDiffusionProcessingImg2Img, process_images
from modules.shared import opts, cmd_opts
import modules.shared as shared
-import modules.processing as processing
from modules.ui import plaintext_to_html
def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, override_settings_texts, *args):
override_settings = create_override_settings_dict(override_settings_texts)
- p = StableDiffusionProcessingTxt2Img(
+ p = processing.StableDiffusionProcessingTxt2Img(
sd_model=shared.sd_model,
outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,
@@ -53,7 +50,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
processed = modules.scripts.scripts_txt2img.run(p, *args)
if processed is None:
- processed = process_images(p)
+ processed = processing.process_images(p)
p.close()
diff --git a/modules/ui.py b/modules/ui.py
index 6beda76f..f7e57593 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -14,10 +14,10 @@ from PIL import Image, PngImagePlugin
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing, progress
-from modules.ui_components import FormRow, FormColumn, FormGroup, ToolButton, FormHTML
+from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
from modules.paths import script_path, data_path
-from modules.shared import opts, cmd_opts, restricted_opts
+from modules.shared import opts, cmd_opts
import modules.codeformer_model
import modules.generation_parameters_copypaste as parameters_copypaste
@@ -28,7 +28,6 @@ import modules.shared as shared
import modules.styles
import modules.textual_inversion.ui
from modules import prompt_parser
-from modules.images import save_image
from modules.sd_hijack import model_hijack
from modules.sd_samplers import samplers, samplers_for_img2img
from modules.textual_inversion import textual_inversion
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index 49e06289..800e467a 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -1,4 +1,3 @@
-import glob
import os.path
import urllib.parse
from pathlib import Path
diff --git a/modules/ui_postprocessing.py b/modules/ui_postprocessing.py
index f25639e5..c7dc1154 100644
--- a/modules/ui_postprocessing.py
+++ b/modules/ui_postprocessing.py
@@ -1,5 +1,5 @@
import gradio as gr
-from modules import scripts_postprocessing, scripts, shared, gfpgan_model, codeformer_model, ui_common, postprocessing, call_queue
+from modules import scripts, shared, ui_common, postprocessing, call_queue
import modules.generation_parameters_copypaste as parameters_copypaste
diff --git a/modules/upscaler.py b/modules/upscaler.py
index 0ad4fe99..777593b0 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -2,8 +2,6 @@ import os
from abc import abstractmethod
import PIL
-import numpy as np
-import torch
from PIL import Image
import modules.shared
diff --git a/modules/xlmr.py b/modules/xlmr.py
index beab3fdf..e056c3f6 100644
--- a/modules/xlmr.py
+++ b/modules/xlmr.py
@@ -1,4 +1,4 @@
-from transformers import BertPreTrainedModel,BertModel,BertConfig
+from transformers import BertPreTrainedModel, BertConfig
import torch.nn as nn
import torch
from transformers.models.xlm_roberta.configuration_xlm_roberta import XLMRobertaConfig
diff --git a/pyproject.toml b/pyproject.toml
index 1e164abc..9caa9ba2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,10 +1,13 @@
[tool.ruff]
+exclude = ["extensions"]
+
ignore = [
"E501",
- "E731",
- "E402", # Module level import not at top of file
- "F401" # Module imported but unused
+
+ "F401", # Module imported but unused
]
-exclude = ["extensions"]
+
+[tool.ruff.per-file-ignores]
+"webui.py" = ["E402"] # Module level import not at top of file
\ No newline at end of file
diff --git a/scripts/custom_code.py b/scripts/custom_code.py
index f36a3675..cc6f0d49 100644
--- a/scripts/custom_code.py
+++ b/scripts/custom_code.py
@@ -4,7 +4,7 @@ import ast
import copy
from modules.processing import Processed
-from modules.shared import opts, cmd_opts, state
+from modules.shared import cmd_opts
def convertExpr2Expression(expr):
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py
index b10fed6c..665dbe89 100644
--- a/scripts/outpainting_mk_2.py
+++ b/scripts/outpainting_mk_2.py
@@ -7,9 +7,9 @@ import modules.scripts as scripts
import gradio as gr
from PIL import Image, ImageDraw
-from modules import images, processing, devices
+from modules import images
from modules.processing import Processed, process_images
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
# this function is taken from https://github.com/parlance-zz/g-diffuser-bot
diff --git a/scripts/poor_mans_outpainting.py b/scripts/poor_mans_outpainting.py
index ddcbd2d3..c0bbecc1 100644
--- a/scripts/poor_mans_outpainting.py
+++ b/scripts/poor_mans_outpainting.py
@@ -4,9 +4,9 @@ import modules.scripts as scripts
import gradio as gr
from PIL import Image, ImageDraw
-from modules import images, processing, devices
+from modules import images, devices
from modules.processing import Processed, process_images
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
class Script(scripts.Script):
diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py
index e9b11517..fb06beab 100644
--- a/scripts/prompt_matrix.py
+++ b/scripts/prompt_matrix.py
@@ -1,14 +1,11 @@
import math
-from collections import namedtuple
-from copy import copy
-import random
import modules.scripts as scripts
import gradio as gr
from modules import images
-from modules.processing import process_images, Processed
-from modules.shared import opts, cmd_opts, state
+from modules.processing import process_images
+from modules.shared import opts, state
import modules.sd_samplers
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index 76dc5778..149bc85f 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -1,6 +1,4 @@
import copy
-import math
-import os
import random
import sys
import traceback
@@ -11,8 +9,7 @@ import gradio as gr
from modules import sd_samplers
from modules.processing import Processed, process_images
-from PIL import Image
-from modules.shared import opts, cmd_opts, state
+from modules.shared import state
def process_string_tag(tag):
diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py
index 332d76d9..d873a09c 100644
--- a/scripts/sd_upscale.py
+++ b/scripts/sd_upscale.py
@@ -4,9 +4,9 @@ import modules.scripts as scripts
import gradio as gr
from PIL import Image
-from modules import processing, shared, sd_samplers, images, devices
+from modules import processing, shared, images, devices
from modules.processing import Processed
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
class Script(scripts.Script):
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 2ff42ef8..332e0ecd 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -10,15 +10,13 @@ import numpy as np
import modules.scripts as scripts
import gradio as gr
-from modules import images, paths, sd_samplers, processing, sd_models, sd_vae
+from modules import images, sd_samplers, processing, sd_models, sd_vae
from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
import modules.shared as shared
import modules.sd_samplers
import modules.sd_models
import modules.sd_vae
-import glob
-import os
import re
from modules.ui_components import ToolButton
diff --git a/webui.py b/webui.py
index ec3d2aba..48277075 100644
--- a/webui.py
+++ b/webui.py
@@ -43,7 +43,7 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__:
torch.__long_version__ = torch.__version__
torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
-from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states
+from modules import shared, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states
import modules.codeformer_model as codeformer
import modules.face_restoration
import modules.gfpgan_model as gfpgan
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