aboutsummaryrefslogtreecommitdiffstats
diff options
context:
space:
mode:
-rw-r--r--.gitignore1
-rw-r--r--javascript/hints.js2
-rw-r--r--modules/api/api.py7
-rw-r--r--modules/generation_parameters_copypaste.py4
-rw-r--r--modules/modelloader.py1
-rw-r--r--modules/processing.py4
-rw-r--r--modules/safe.py18
-rw-r--r--modules/sd_hijack.py1
-rw-r--r--modules/shared.py2
-rw-r--r--modules/textual_inversion/autocrop.py6
-rw-r--r--modules/ui_extensions.py2
11 files changed, 32 insertions, 16 deletions
diff --git a/.gitignore b/.gitignore
index ee53044c..21fa26a7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,5 +1,6 @@
__pycache__
*.ckpt
+*.safetensors
*.pth
/ESRGAN/*
/SwinIR/*
diff --git a/javascript/hints.js b/javascript/hints.js
index ac417ff6..57db35be 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -94,6 +94,8 @@ titles = {
"Add difference": "Result = A + (B - C) * M",
"Learning rate": "how fast should the training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG: 0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.",
+
+ "Clip skip": "Early stopping parameter for CLIP model; 1 is stop at last layer as usual, 2 is stop at penultimate layer, etc."
}
diff --git a/modules/api/api.py b/modules/api/api.py
index 1de3f98f..54ee7cb0 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -152,7 +152,10 @@ class Api:
)
if populate.sampler_name:
populate.sampler_index = None # prevent a warning later on
- p = StableDiffusionProcessingImg2Img(**vars(populate))
+
+ args = vars(populate)
+ args.pop('include_init_images', None) # this is meant to be done by "exclude": True in model, but it's for a reason that I cannot determine.
+ p = StableDiffusionProcessingImg2Img(**args)
imgs = []
for img in init_images:
@@ -170,7 +173,7 @@ class Api:
b64images = list(map(encode_pil_to_base64, processed.images))
- if (not img2imgreq.include_init_images):
+ if not img2imgreq.include_init_images:
img2imgreq.init_images = None
img2imgreq.mask = None
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 01980dca..44fe1a6c 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -184,6 +184,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
else:
res[k] = v
+ # Missing CLIP skip means it was set to 1 (the default)
+ if "Clip skip" not in res:
+ res["Clip skip"] = "1"
+
return res
diff --git a/modules/modelloader.py b/modules/modelloader.py
index e4a6f8ac..7d2f0ade 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -82,6 +82,7 @@ def cleanup_models():
src_path = models_path
dest_path = os.path.join(models_path, "Stable-diffusion")
move_files(src_path, dest_path, ".ckpt")
+ move_files(src_path, dest_path, ".safetensors")
src_path = os.path.join(root_path, "ESRGAN")
dest_path = os.path.join(models_path, "ESRGAN")
move_files(src_path, dest_path)
diff --git a/modules/processing.py b/modules/processing.py
index edceb532..fd995b8a 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -530,8 +530,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
with devices.autocast():
samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
- samples_ddim = samples_ddim.to(devices.dtype_vae)
- x_samples_ddim = decode_first_stage(p.sd_model, samples_ddim)
+ x_samples_ddim = [decode_first_stage(p.sd_model, samples_ddim[i:i+1].to(dtype=devices.dtype_vae))[0].cpu() for i in range(samples_ddim.size(0))]
+ x_samples_ddim = torch.stack(x_samples_ddim).float()
x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
del samples_ddim
diff --git a/modules/safe.py b/modules/safe.py
index a9209e38..10460ad0 100644
--- a/modules/safe.py
+++ b/modules/safe.py
@@ -62,14 +62,12 @@ class RestrictedUnpickler(pickle.Unpickler):
raise Exception(f"global '{module}/{name}' is forbidden")
-allowed_zip_names = ["archive/data.pkl", "archive/version"]
-allowed_zip_names_re = re.compile(r"^archive/data/\d+$")
-
+# Regular expression that accepts 'dirname/version', 'dirname/data.pkl', and 'dirname/data/<number>'
+allowed_zip_names_re = re.compile(r"^([^/]+)/((data/\d+)|version|(data\.pkl))$")
+data_pkl_re = re.compile(r"^([^/]+)/data\.pkl$")
def check_zip_filenames(filename, names):
for name in names:
- if name in allowed_zip_names:
- continue
if allowed_zip_names_re.match(name):
continue
@@ -82,8 +80,14 @@ def check_pt(filename, extra_handler):
# new pytorch format is a zip file
with zipfile.ZipFile(filename) as z:
check_zip_filenames(filename, z.namelist())
-
- with z.open('archive/data.pkl') as file:
+
+ # find filename of data.pkl in zip file: '<directory name>/data.pkl'
+ data_pkl_filenames = [f for f in z.namelist() if data_pkl_re.match(f)]
+ if len(data_pkl_filenames) == 0:
+ raise Exception(f"data.pkl not found in {filename}")
+ if len(data_pkl_filenames) > 1:
+ raise Exception(f"Multiple data.pkl found in {filename}")
+ with z.open(data_pkl_filenames[0]) as file:
unpickler = RestrictedUnpickler(file)
unpickler.extra_handler = extra_handler
unpickler.load()
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index ce583950..95a17093 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -17,6 +17,7 @@ from modules.sd_hijack_optimizations import invokeAI_mps_available
import ldm.modules.attention
import ldm.modules.diffusionmodules.model
+import ldm.modules.diffusionmodules.openaimodel
import ldm.models.diffusion.ddim
import ldm.models.diffusion.plms
import ldm.modules.encoders.modules
diff --git a/modules/shared.py b/modules/shared.py
index c36ee211..42ec4120 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -371,7 +371,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
"comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
"filter_nsfw": OptionInfo(False, "Filter NSFW content"),
- 'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
+ 'CLIP_stop_at_last_layers': OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
}))
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py
index 9859974a..68e1103c 100644
--- a/modules/textual_inversion/autocrop.py
+++ b/modules/textual_inversion/autocrop.py
@@ -276,8 +276,8 @@ def poi_average(pois, settings):
weight += poi.weight
x += poi.x * poi.weight
y += poi.y * poi.weight
- avg_x = round(x / weight)
- avg_y = round(y / weight)
+ avg_x = round(weight and x / weight)
+ avg_y = round(weight and y / weight)
return PointOfInterest(avg_x, avg_y)
@@ -338,4 +338,4 @@ class Settings:
self.face_points_weight = face_points_weight
self.annotate_image = annotate_image
self.destop_view_image = False
- self.dnn_model_path = dnn_model_path \ No newline at end of file
+ self.dnn_model_path = dnn_model_path
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index 030f011e..42667941 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -17,7 +17,7 @@ available_extensions = {"extensions": []}
def check_access():
- assert not shared.cmd_opts.disable_extension_access, "extension access disabed because of commandline flags"
+ assert not shared.cmd_opts.disable_extension_access, "extension access disabled because of command line flags"
def apply_and_restart(disable_list, update_list):