mrq/stable-diffusion-webui
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Merge branch 'AUTOMATIC1111:master' into master

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不会画画的中医不是好程序员 2022-10-14 14:43:44 +08:00 committed by GitHub
commit f7712e28e5
3 changed files with 33 additions and 14 deletions
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7
javascript/hints.js
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@ -83,9 +83,12 @@ titles = {
"Do not add watermark to images": "If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be behaving in an unethical manner.",
"Filename word regex": "This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.",
"Filename join string": "This string will be used to hoin split words into a single line if the option above is enabled.",
"Filename join string": "This string will be used to join split words into a single line if the option above is enabled.",
"Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply."
"Quicksettings list": "List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.",
"Weighted Sum": "Result = A * (1 - M) + B * M",
"Add difference": "Result = A + (B - C) * (1 - M)",
}

29
modules/extras.py
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@ -159,48 +159,61 @@ def run_pnginfo(image):
return '', geninfo, info
def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount, save_as_half, custom_name):
def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, interp_amount, save_as_half, custom_name):
# Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation)
def weighted_sum(theta0, theta1, alpha):
def weighted_sum(theta0, theta1, theta2, alpha):
return ((1 - alpha) * theta0) + (alpha * theta1)
# Smoothstep (https://en.wikipedia.org/wiki/Smoothstep)
def sigmoid(theta0, theta1, alpha):
def sigmoid(theta0, theta1, theta2, alpha):
alpha = alpha * alpha * (3 - (2 * alpha))
return theta0 + ((theta1 - theta0) * alpha)
# Inverse Smoothstep (https://en.wikipedia.org/wiki/Smoothstep)
def inv_sigmoid(theta0, theta1, alpha):
def inv_sigmoid(theta0, theta1, theta2, alpha):
import math
alpha = 0.5 - math.sin(math.asin(1.0 - 2.0 * alpha) / 3.0)
return theta0 + ((theta1 - theta0) * alpha)
def add_difference(theta0, theta1, theta2, alpha):
return theta0 + (theta1 - theta2) * (1.0 - alpha)
primary_model_info = sd_models.checkpoints_list[primary_model_name]
secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None)
print(f"Loading {primary_model_info.filename}...")
primary_model = torch.load(primary_model_info.filename, map_location='cpu')
theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model)
print(f"Loading {secondary_model_info.filename}...")
secondary_model = torch.load(secondary_model_info.filename, map_location='cpu')
theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model)
theta_1 = sd_models.get_state_dict_from_checkpoint(secondary_model)
if teritary_model_info is not None:
print(f"Loading {teritary_model_info.filename}...")
teritary_model = torch.load(teritary_model_info.filename, map_location='cpu')
theta_2 = sd_models.get_state_dict_from_checkpoint(teritary_model)
else:
theta_2 = None
theta_funcs = {
"Weighted Sum": weighted_sum,
"Sigmoid": sigmoid,
"Inverse Sigmoid": inv_sigmoid,
"Add difference": add_difference,
}
theta_func = theta_funcs[interp_method]
print(f"Merging...")
for key in tqdm.tqdm(theta_0.keys()):
if 'model' in key and key in theta_1:
theta_0[key] = theta_func(theta_0[key], theta_1[key], (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
theta_0[key] = theta_func(theta_0[key], theta_1[key], theta_2[key] if theta_2 else None, (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
if save_as_half:
theta_0[key] = theta_0[key].half()
# I believe this part should be discarded, but I'll leave it for now until I am sure
for key in theta_1.keys():
if 'model' in key and key not in theta_0:
theta_0[key] = theta_1[key]
@ -219,4 +232,4 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
sd_models.list_models()
print(f"Checkpoint saved.")
return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(3)]
return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]

11
modules/ui.py
View File

@ -1032,11 +1032,12 @@ def create_ui(wrap_gradio_gpu_call):
gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
with gr.Row():
primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary Model Name")
secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary Model Name")
primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
custom_name = gr.Textbox(label="Custom Name (Optional)")
interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation Amount', value=0.3)
interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method")
interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation amount (1 - M)', value=0.3)
interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid", "Add difference"], value="Weighted Sum", label="Interpolation Method")
save_as_half = gr.Checkbox(value=False, label="Save as float16")
modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
@ -1482,6 +1483,7 @@ Requested path was: {f}
inputs=[
primary_model_name,
secondary_model_name,
tertiary_model_name,
interp_method,
interp_amount,
save_as_half,
@ -1491,6 +1493,7 @@ Requested path was: {f}
submit_result,
primary_model_name,
secondary_model_name,
tertiary_model_name,
component_dict['sd_model_checkpoint'],
]
)