Merge pull request #1185 from bmaltais/checkpoint-merger-ui-improvement
(feat): Rework Checkpoint Merger UI for better clarity and usability
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AUTOMATIC1111
GitHub
commit
15f333a266
3 changed files with 32 additions and 28 deletions
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@ -140,7 +140,7 @@ def run_pnginfo(image):
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return '', geninfo, info
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def run_modelmerger(modelname_0, modelname_1, interp_method, interp_amount):
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def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount):
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# Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation)
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def weighted_sum(theta0, theta1, alpha):
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return ((1 - alpha) * theta0) + (alpha * theta1)
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@ -150,26 +150,26 @@ def run_modelmerger(modelname_0, modelname_1, interp_method, interp_amount):
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alpha = alpha * alpha * (3 - (2 * alpha))
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return theta0 + ((theta1 - theta0) * alpha)
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if os.path.exists(modelname_0):
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model0_filename = modelname_0
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modelname_0 = os.path.splitext(os.path.basename(modelname_0))[0]
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if os.path.exists(primary_model_name):
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primary_model_filename = primary_model_name
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primary_model_name = os.path.splitext(os.path.basename(primary_model_name))[0]
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else:
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model0_filename = 'models/' + modelname_0 + '.ckpt'
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primary_model_filename = 'models/' + primary_model_name + '.ckpt'
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if os.path.exists(modelname_1):
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model1_filename = modelname_1
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modelname_1 = os.path.splitext(os.path.basename(modelname_1))[0]
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if os.path.exists(secondary_model_name):
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secondary_model_filename = secondary_model_name
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secondary_model_name = os.path.splitext(os.path.basename(secondary_model_name))[0]
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else:
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model1_filename = 'models/' + modelname_1 + '.ckpt'
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secondary_model_filename = 'models/' + secondary_model_name + '.ckpt'
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print(f"Loading {model0_filename}...")
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model_0 = torch.load(model0_filename, map_location='cpu')
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print(f"Loading {primary_model_filename}...")
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primary_model = torch.load(primary_model_filename, map_location='cpu')
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print(f"Loading {model1_filename}...")
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model_1 = torch.load(model1_filename, map_location='cpu')
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theta_0 = model_0['state_dict']
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theta_1 = model_1['state_dict']
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print(f"Loading {secondary_model_filename}...")
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secondary_model = torch.load(secondary_model_filename, map_location='cpu')
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theta_0 = primary_model['state_dict']
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theta_1 = secondary_model['state_dict']
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theta_funcs = {
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"Weighted Sum": weighted_sum,
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@ -180,15 +180,15 @@ def run_modelmerger(modelname_0, modelname_1, interp_method, interp_amount):
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print(f"Merging...")
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for key in tqdm.tqdm(theta_0.keys()):
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if 'model' in key and key in theta_1:
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theta_0[key] = theta_func(theta_0[key], theta_1[key], interp_amount)
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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
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for key in theta_1.keys():
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if 'model' in key and key not in theta_0:
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theta_0[key] = theta_1[key]
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output_modelname = 'models/' + modelname_0 + '-' + modelname_1 + '-' + interp_method.replace(" ", "_") + '-' + str(interp_amount) + '-merged.ckpt'
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output_modelname = 'models/' + primary_model_name + '_' + str(round(interp_amount,2)) + '-' + secondary_model_name + '_' + str(round((float(1.0) - interp_amount),2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
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print(f"Saving to {output_modelname}...")
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torch.save(model_0, output_modelname)
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torch.save(primary_model, output_modelname)
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print(f"Checkpoint saved.")
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return "Checkpoint saved to " + output_modelname
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return "Checkpoint saved to " + output_modelname
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@ -10,7 +10,7 @@ from ldm.util import instantiate_from_config
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from modules import shared
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CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash'])
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CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name'])
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checkpoints_list = {}
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try:
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@ -45,7 +45,8 @@ def list_models():
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if os.path.exists(cmd_ckpt):
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h = model_hash(cmd_ckpt)
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title = modeltitle(cmd_ckpt, h)
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checkpoints_list[title] = CheckpointInfo(cmd_ckpt, title, h)
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model_name = title.rsplit(".",1)[0] # remove extension if present
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checkpoints_list[title] = CheckpointInfo(cmd_ckpt, title, h, model_name)
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elif cmd_ckpt is not None and cmd_ckpt != shared.default_sd_model_file:
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print(f"Checkpoint in --ckpt argument not found: {cmd_ckpt}", file=sys.stderr)
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@ -53,7 +54,8 @@ def list_models():
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for filename in glob.glob(model_dir + '/**/*.ckpt', recursive=True):
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h = model_hash(filename)
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title = modeltitle(filename, h)
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checkpoints_list[title] = CheckpointInfo(filename, title, h)
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model_name = title.rsplit(".",1)[0] # remove extension if present
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checkpoints_list[title] = CheckpointInfo(filename, title, h, model_name)
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def model_hash(filename):
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@ -859,10 +859,12 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
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with gr.Column(variant='panel'):
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gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>/models</b> directory.</p>")
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modelname_0 = gr.Textbox(elem_id="modelmerger_modelname_0", label="Model Name (to)")
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modelname_1 = gr.Textbox(elem_id="modelmerger_modelname_1", label="Model Name (from)")
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interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid"], value="Weighted Sum", label="Interpolation Method")
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with gr.Row():
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ckpt_name_list = sorted([x.model_name for x in modules.sd_models.checkpoints_list.values()])
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primary_model_name = gr.Dropdown(ckpt_name_list, elem_id="modelmerger_primary_model_name", label="Primary Model Name")
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secondary_model_name = gr.Dropdown(ckpt_name_list, elem_id="modelmerger_secondary_model_name", label="Secondary Model Name")
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interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation Amount', value=0.3)
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interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid"], value="Weighted Sum", label="Interpolation Method")
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submit = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
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with gr.Column(variant='panel'):
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@ -871,8 +873,8 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
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submit.click(
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fn=run_modelmerger,
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inputs=[
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modelname_0,
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modelname_1,
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primary_model_name,
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secondary_model_name,
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interp_method,
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interp_amount
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],
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