Merge branch 'comfyanonymous:master' into fix/secure-combo

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Dr.Lt.Data 2023-07-01 11:11:41 +09:00 committed by GitHub
commit c7e7ebad75
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5 changed files with 43 additions and 13 deletions

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@ -29,7 +29,8 @@ This ui will let you design and execute advanced stable diffusion pipelines usin
- [Upscale Models (ESRGAN, ESRGAN variants, SwinIR, Swin2SR, etc...)](https://comfyanonymous.github.io/ComfyUI_examples/upscale_models/)
- [unCLIP Models](https://comfyanonymous.github.io/ComfyUI_examples/unclip/)
- [GLIGEN](https://comfyanonymous.github.io/ComfyUI_examples/gligen/)
- Latent previews with [TAESD](https://github.com/madebyollin/taesd)
- [Model Merging](https://comfyanonymous.github.io/ComfyUI_examples/model_merging/)
- Latent previews with [TAESD](#how-to-show-high-quality-previews)
- Starts up very fast.
- Works fully offline: will never download anything.
- [Config file](extra_model_paths.yaml.example) to set the search paths for models.

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@ -89,8 +89,7 @@ LORA_UNET_MAP_RESNET = {
"skip_connection": "resnets_{}_conv_shortcut"
}
def load_lora(path, to_load):
lora = utils.load_torch_file(path, safe_load=True)
def load_lora(lora, to_load):
patch_dict = {}
loaded_keys = set()
for x in to_load:
@ -501,10 +500,10 @@ class ModelPatcher:
self.backup = {}
def load_lora_for_models(model, clip, lora_path, strength_model, strength_clip):
def load_lora_for_models(model, clip, lora, strength_model, strength_clip):
key_map = model_lora_keys(model.model)
key_map = model_lora_keys(clip.cond_stage_model, key_map)
loaded = load_lora(lora_path, key_map)
loaded = load_lora(lora, key_map)
new_modelpatcher = model.clone()
k = new_modelpatcher.add_patches(loaded, strength_model)
new_clip = clip.clone()

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@ -14,7 +14,7 @@ class ModelMergeSimple:
RETURN_TYPES = ("MODEL",)
FUNCTION = "merge"
CATEGORY = "_for_testing/model_merging"
CATEGORY = "advanced/model_merging"
def merge(self, model1, model2, ratio):
m = model1.clone()
@ -35,7 +35,7 @@ class ModelMergeBlocks:
RETURN_TYPES = ("MODEL",)
FUNCTION = "merge"
CATEGORY = "_for_testing/model_merging"
CATEGORY = "advanced/model_merging"
def merge(self, model1, model2, **kwargs):
m = model1.clone()
@ -68,7 +68,7 @@ class CheckpointSave:
FUNCTION = "save"
OUTPUT_NODE = True
CATEGORY = "_for_testing/model_merging"
CATEGORY = "advanced/model_merging"
def save(self, model, clip, vae, filename_prefix, prompt=None, extra_pnginfo=None):
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)

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@ -110,7 +110,7 @@ def format_value(x):
else:
return str(x)
def recursive_execute(server, prompt, outputs, current_item, extra_data, executed, prompt_id, outputs_ui):
def recursive_execute(server, prompt, outputs, current_item, extra_data, executed, prompt_id, outputs_ui, object_storage):
unique_id = current_item
inputs = prompt[unique_id]['inputs']
class_type = prompt[unique_id]['class_type']
@ -125,7 +125,7 @@ def recursive_execute(server, prompt, outputs, current_item, extra_data, execute
input_unique_id = input_data[0]
output_index = input_data[1]
if input_unique_id not in outputs:
result = recursive_execute(server, prompt, outputs, input_unique_id, extra_data, executed, prompt_id, outputs_ui)
result = recursive_execute(server, prompt, outputs, input_unique_id, extra_data, executed, prompt_id, outputs_ui, object_storage)
if result[0] is not True:
# Another node failed further upstream
return result
@ -136,7 +136,11 @@ def recursive_execute(server, prompt, outputs, current_item, extra_data, execute
if server.client_id is not None:
server.last_node_id = unique_id
server.send_sync("executing", { "node": unique_id, "prompt_id": prompt_id }, server.client_id)
obj = class_def()
obj = object_storage.get((unique_id, class_type), None)
if obj is None:
obj = class_def()
object_storage[(unique_id, class_type)] = obj
output_data, output_ui = get_output_data(obj, input_data_all)
outputs[unique_id] = output_data
@ -256,6 +260,7 @@ def recursive_output_delete_if_changed(prompt, old_prompt, outputs, current_item
class PromptExecutor:
def __init__(self, server):
self.outputs = {}
self.object_storage = {}
self.outputs_ui = {}
self.old_prompt = {}
self.server = server
@ -322,6 +327,17 @@ class PromptExecutor:
for o in to_delete:
d = self.outputs.pop(o)
del d
to_delete = []
for o in self.object_storage:
if o[0] not in prompt:
to_delete += [o]
else:
p = prompt[o[0]]
if o[1] != p['class_type']:
to_delete += [o]
for o in to_delete:
d = self.object_storage.pop(o)
del d
for x in prompt:
recursive_output_delete_if_changed(prompt, self.old_prompt, self.outputs, x)
@ -349,7 +365,7 @@ class PromptExecutor:
# This call shouldn't raise anything if there's an error deep in
# the actual SD code, instead it will report the node where the
# error was raised
success, error, ex = recursive_execute(self.server, prompt, self.outputs, output_node_id, extra_data, executed, prompt_id, self.outputs_ui)
success, error, ex = recursive_execute(self.server, prompt, self.outputs, output_node_id, extra_data, executed, prompt_id, self.outputs_ui, self.object_storage)
if success is not True:
self.handle_execution_error(prompt_id, prompt, current_outputs, executed, error, ex)
break

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@ -434,6 +434,9 @@ class CLIPSetLastLayer:
return (clip,)
class LoraLoader:
def __init__(self):
self.loaded_lora = None
@classmethod
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
@ -452,7 +455,18 @@ class LoraLoader:
return (model, clip)
lora_path = folder_paths.get_full_path("loras", lora_name)
model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora_path, strength_model, strength_clip)
lora = None
if self.loaded_lora is not None:
if self.loaded_lora[0] == lora_path:
lora = self.loaded_lora[1]
else:
del self.loaded_lora
if lora is None:
lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
self.loaded_lora = (lora_path, lora)
model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora, strength_model, strength_clip)
return (model_lora, clip_lora)
class VAELoader: