Merge pull request #5404 from szhublox/merger-ram-usage
Merger ram usage
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commit
e5e557fa5d
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@ -62,7 +62,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
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# Also keep track of original file names
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# Also keep track of original file names
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imageNameArr = []
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imageNameArr = []
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outputs = []
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outputs = []
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if extras_mode == 1:
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if extras_mode == 1:
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#convert file to pillow image
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#convert file to pillow image
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for img in image_folder:
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for img in image_folder:
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@ -234,7 +234,7 @@ def run_pnginfo(image):
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return '', geninfo, info
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return '', geninfo, info
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def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
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def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
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def weighted_sum(theta0, theta1, alpha):
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def weighted_sum(theta0, theta1, alpha):
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return ((1 - alpha) * theta0) + (alpha * theta1)
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return ((1 - alpha) * theta0) + (alpha * theta1)
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@ -246,30 +246,25 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
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primary_model_info = sd_models.checkpoints_list[primary_model_name]
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primary_model_info = sd_models.checkpoints_list[primary_model_name]
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secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
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secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
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teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None)
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tertiary_model_info = sd_models.checkpoints_list.get(tertiary_model_name, None)
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result_is_inpainting_model = False
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result_is_inpainting_model = False
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print(f"Loading {primary_model_info.filename}...")
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theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
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print(f"Loading {secondary_model_info.filename}...")
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theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
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if teritary_model_info is not None:
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print(f"Loading {teritary_model_info.filename}...")
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theta_2 = sd_models.read_state_dict(teritary_model_info.filename, map_location='cpu')
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else:
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theta_2 = None
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theta_funcs = {
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theta_funcs = {
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"Weighted sum": (None, weighted_sum),
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"Weighted sum": (None, weighted_sum),
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"Add difference": (get_difference, add_difference),
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"Add difference": (get_difference, add_difference),
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}
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}
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theta_func1, theta_func2 = theta_funcs[interp_method]
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theta_func1, theta_func2 = theta_funcs[interp_method]
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print(f"Merging...")
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if theta_func1 and not tertiary_model_info:
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return ["Failed: Interpolation method requires a tertiary model."] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
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print(f"Loading {secondary_model_info.filename}...")
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theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
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if theta_func1:
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if theta_func1:
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print(f"Loading {tertiary_model_info.filename}...")
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theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu')
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for key in tqdm.tqdm(theta_1.keys()):
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for key in tqdm.tqdm(theta_1.keys()):
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if 'model' in key:
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if 'model' in key:
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if key in theta_2:
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if key in theta_2:
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@ -277,7 +272,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
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theta_1[key] = theta_func1(theta_1[key], t2)
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theta_1[key] = theta_func1(theta_1[key], t2)
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else:
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else:
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theta_1[key] = torch.zeros_like(theta_1[key])
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theta_1[key] = torch.zeros_like(theta_1[key])
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del theta_2
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del theta_2
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print(f"Loading {primary_model_info.filename}...")
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theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
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print("Merging...")
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for key in tqdm.tqdm(theta_0.keys()):
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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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if 'model' in key and key in theta_1:
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@ -307,6 +307,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
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theta_0[key] = theta_1[key]
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theta_0[key] = theta_1[key]
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if save_as_half:
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if save_as_half:
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theta_0[key] = theta_0[key].half()
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theta_0[key] = theta_0[key].half()
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del theta_1
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ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
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ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
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@ -332,5 +333,5 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
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sd_models.list_models()
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sd_models.list_models()
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print(f"Checkpoint saved.")
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print("Checkpoint saved.")
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return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
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return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
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