add progress bar to modelmerger
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@ -172,6 +172,17 @@ function submit_img2img(){
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return res
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}
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function modelmerger(){
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var id = randomId()
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requestProgress(id, gradioApp().getElementById('modelmerger_results_panel'), null, function(){})
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gradioApp().getElementById('modelmerger_result').innerHTML = ''
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var res = create_submit_args(arguments)
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res[0] = id
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return res
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}
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function ask_for_style_name(_, prompt_text, negative_prompt_text) {
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name_ = prompt('Style name:')
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@ -274,14 +274,15 @@ def create_config(ckpt_result, config_source, a, b, c):
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shutil.copyfile(cfg, checkpoint_filename)
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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, config_source):
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def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source):
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shared.state.begin()
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shared.state.job = 'model-merge'
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shared.state.job_count = 1
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def fail(message):
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shared.state.textinfo = message
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shared.state.end()
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return [message, *[gr.update() for _ in range(4)]]
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return [*[gr.update() for _ in range(4)], message]
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def weighted_sum(theta0, theta1, alpha):
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return ((1 - alpha) * theta0) + (alpha * theta1)
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@ -320,9 +321,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
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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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shared.state.job_count += 1
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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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shared.state.sampling_steps = len(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 key in theta_2:
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@ -330,8 +334,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
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theta_1[key] = theta_func1(theta_1[key], t2)
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else:
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theta_1[key] = torch.zeros_like(theta_1[key])
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shared.state.sampling_step += 1
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del theta_2
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shared.state.nextjob()
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shared.state.textinfo = f"Loading {primary_model_info.filename}..."
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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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@ -340,6 +348,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
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chckpoint_dict_skip_on_merge = ["cond_stage_model.transformer.text_model.embeddings.position_ids"]
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shared.state.sampling_steps = len(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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@ -367,6 +376,8 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
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if save_as_half:
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theta_0[key] = theta_0[key].half()
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shared.state.sampling_step += 1
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# I believe this part should be discarded, but I'll leave it for now until I am sure
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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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@ -393,6 +404,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
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output_modelname = os.path.join(ckpt_dir, filename)
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shared.state.nextjob()
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shared.state.textinfo = f"Saving to {output_modelname}..."
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print(f"Saving to {output_modelname}...")
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@ -410,4 +422,4 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
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shared.state.textinfo = "Checkpoint saved to " + output_modelname
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shared.state.end()
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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 [*[gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)], "Checkpoint saved to " + output_modelname]
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@ -72,7 +72,7 @@ def progressapi(req: ProgressRequest):
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if job_count > 0:
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progress += job_no / job_count
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if sampling_steps > 0:
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if sampling_steps > 0 and job_count > 0:
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progress += 1 / job_count * sampling_step / sampling_steps
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progress = min(progress, 1)
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@ -1208,8 +1208,9 @@ def create_ui():
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with gr.Row():
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modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
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with gr.Column(variant='panel'):
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submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
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with gr.Column(variant='compact', elem_id="modelmerger_results_container"):
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with gr.Group(elem_id="modelmerger_results_panel"):
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modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)
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with gr.Blocks(analytics_enabled=False) as train_interface:
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with gr.Row().style(equal_height=False):
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@ -1753,12 +1754,14 @@ def create_ui():
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print("Error loading/saving model file:", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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modules.sd_models.list_models() # to remove the potentially missing models from the list
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return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
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return [*[gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"]
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return results
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modelmerger_merge.click(
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fn=modelmerger,
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fn=wrap_gradio_gpu_call(modelmerger, extra_outputs=lambda: [gr.update() for _ in range(4)]),
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_js='modelmerger',
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inputs=[
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dummy_component,
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primary_model_name,
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secondary_model_name,
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tertiary_model_name,
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@ -1770,11 +1773,11 @@ def create_ui():
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config_source,
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],
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outputs=[
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submit_result,
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primary_model_name,
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secondary_model_name,
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tertiary_model_name,
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component_dict['sd_model_checkpoint'],
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modelmerger_result,
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]
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)
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@ -737,6 +737,11 @@ footer {
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line-height: 2.4em;
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}
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#modelmerger_results_container{
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margin-top: 1em;
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overflow: visible;
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}
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/* The following handles localization for right-to-left (RTL) languages like Arabic.
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The rtl media type will only be activated by the logic in javascript/localization.js.
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If you change anything above, you need to make sure it is RTL compliant by just running
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