Merge pull request #158 from JohannesGaessler/progress-printing
More informative progress printing
This commit is contained in:
commit
701f76b29a
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@ -55,6 +55,7 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
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"Denoising strength change factor": denoising_strength_change_factor
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"Denoising strength change factor": denoising_strength_change_factor
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}
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}
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)
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)
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print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
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if is_loopback:
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if is_loopback:
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output_images, info = None, None
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output_images, info = None, None
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@ -171,5 +172,6 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
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if processed is None:
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if processed is None:
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processed = process_images(p)
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processed = process_images(p)
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shared.total_tqdm.clear()
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return processed.images, processed.js(), plaintext_to_html(processed.info)
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return processed.images, processed.js(), plaintext_to_html(processed.info)
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@ -6,6 +6,7 @@ import modules.ui as ui
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import gradio as gr
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import gradio as gr
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from modules.processing import StableDiffusionProcessing
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from modules.processing import StableDiffusionProcessing
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from modules import shared
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class Script:
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class Script:
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filename = None
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filename = None
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@ -137,6 +138,8 @@ class ScriptRunner:
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script_args = args[script.args_from:script.args_to]
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script_args = args[script.args_from:script.args_to]
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processed = script.run(p, *script_args)
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processed = script.run(p, *script_args)
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shared.total_tqdm.clear()
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return processed
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return processed
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@ -70,13 +70,14 @@ def extended_tdqm(sequence, *args, desc=None, **kwargs):
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state.sampling_steps = len(sequence)
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state.sampling_steps = len(sequence)
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state.sampling_step = 0
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state.sampling_step = 0
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for x in tqdm.tqdm(sequence, *args, desc=state.job, **kwargs):
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for x in tqdm.tqdm(sequence, *args, desc=state.job, file=shared.progress_print_out, **kwargs):
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if state.interrupted:
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if state.interrupted:
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break
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break
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yield x
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yield x
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state.sampling_step += 1
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state.sampling_step += 1
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shared.total_tqdm.update()
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ldm.models.diffusion.ddim.tqdm = lambda *args, desc=None, **kwargs: extended_tdqm(*args, desc=desc, **kwargs)
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ldm.models.diffusion.ddim.tqdm = lambda *args, desc=None, **kwargs: extended_tdqm(*args, desc=desc, **kwargs)
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@ -146,13 +147,14 @@ def extended_trange(count, *args, **kwargs):
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state.sampling_steps = count
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state.sampling_steps = count
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state.sampling_step = 0
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state.sampling_step = 0
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for x in tqdm.trange(count, *args, desc=state.job, **kwargs):
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for x in tqdm.trange(count, *args, desc=state.job, file=shared.progress_print_out, **kwargs):
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if state.interrupted:
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if state.interrupted:
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break
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break
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yield x
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yield x
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state.sampling_step += 1
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state.sampling_step += 1
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shared.total_tqdm.update()
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class KDiffusionSampler:
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class KDiffusionSampler:
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@ -1,9 +1,11 @@
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import sys
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import argparse
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import argparse
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import json
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import json
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import os
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import os
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import gradio as gr
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import gradio as gr
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import torch
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import torch
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import tqdm
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import modules.artists
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import modules.artists
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from modules.paths import script_path, sd_path
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from modules.paths import script_path, sd_path
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@ -124,6 +126,7 @@ class Options:
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"upscale_at_full_resolution_padding": OptionInfo(16, "Inpainting at full resolution: padding, in pixels, for the masked region.", gr.Slider, {"minimum": 0, "maximum": 128, "step": 4}),
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"upscale_at_full_resolution_padding": OptionInfo(16, "Inpainting at full resolution: padding, in pixels, for the masked region.", gr.Slider, {"minimum": 0, "maximum": 128, "step": 4}),
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"show_progressbar": OptionInfo(True, "Show progressbar"),
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"show_progressbar": OptionInfo(True, "Show progressbar"),
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"show_progress_every_n_steps": OptionInfo(0, "Show show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
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"show_progress_every_n_steps": OptionInfo(0, "Show show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
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"multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job. Broken in PyCharm console."),
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"face_restoration_model": OptionInfo(None, "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
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"face_restoration_model": OptionInfo(None, "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
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"code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
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"code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
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}
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}
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@ -165,4 +168,32 @@ sd_upscalers = []
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sd_model = None
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sd_model = None
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progress_print_out = sys.stdout
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class TotalTQDM:
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def __init__(self):
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self._tqdm = None
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def reset(self):
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self._tqdm = tqdm.tqdm(
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desc="Total progress",
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total=state.job_count * state.sampling_steps,
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position=1,
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file=progress_print_out
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)
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def update(self):
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if not opts.multiple_tqdm:
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return
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if self._tqdm is None:
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self.reset()
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self._tqdm.update()
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def clear(self):
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if self._tqdm is not None:
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self._tqdm.close()
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self._tqdm = None
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total_tqdm = TotalTQDM()
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@ -25,6 +25,7 @@ def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, r
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tiling=tiling,
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tiling=tiling,
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)
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)
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print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
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processed = modules.scripts.scripts_txt2img.run(p, *args)
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processed = modules.scripts.scripts_txt2img.run(p, *args)
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if processed is not None:
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if processed is not None:
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@ -32,5 +33,7 @@ def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, r
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else:
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else:
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processed = process_images(p)
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processed = process_images(p)
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shared.total_tqdm.clear()
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return processed.images, processed.js(), plaintext_to_html(processed.info)
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return processed.images, processed.js(), plaintext_to_html(processed.info)
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