Merge pull request #158 from JohannesGaessler/progress-printing

More informative progress printing
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AUTOMATIC1111 2022-09-08 18:34:45 +03:00 committed by GitHub
commit 701f76b29a
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5 changed files with 43 additions and 2 deletions

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@ -55,6 +55,7 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
"Denoising strength change factor": denoising_strength_change_factor "Denoising strength change factor": denoising_strength_change_factor
} }
) )
print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
if is_loopback: if is_loopback:
output_images, info = None, None output_images, info = None, None
@ -171,5 +172,6 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
if processed is None: if processed is None:
processed = process_images(p) processed = process_images(p)
shared.total_tqdm.clear()
return processed.images, processed.js(), plaintext_to_html(processed.info) return processed.images, processed.js(), plaintext_to_html(processed.info)

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@ -6,6 +6,7 @@ import modules.ui as ui
import gradio as gr import gradio as gr
from modules.processing import StableDiffusionProcessing from modules.processing import StableDiffusionProcessing
from modules import shared
class Script: class Script:
filename = None filename = None
@ -137,6 +138,8 @@ class ScriptRunner:
script_args = args[script.args_from:script.args_to] script_args = args[script.args_from:script.args_to]
processed = script.run(p, *script_args) processed = script.run(p, *script_args)
shared.total_tqdm.clear()
return processed return processed

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@ -70,13 +70,14 @@ def extended_tdqm(sequence, *args, desc=None, **kwargs):
state.sampling_steps = len(sequence) state.sampling_steps = len(sequence)
state.sampling_step = 0 state.sampling_step = 0
for x in tqdm.tqdm(sequence, *args, desc=state.job, **kwargs): for x in tqdm.tqdm(sequence, *args, desc=state.job, file=shared.progress_print_out, **kwargs):
if state.interrupted: if state.interrupted:
break break
yield x yield x
state.sampling_step += 1 state.sampling_step += 1
shared.total_tqdm.update()
ldm.models.diffusion.ddim.tqdm = lambda *args, desc=None, **kwargs: extended_tdqm(*args, desc=desc, **kwargs) ldm.models.diffusion.ddim.tqdm = lambda *args, desc=None, **kwargs: extended_tdqm(*args, desc=desc, **kwargs)
@ -146,13 +147,14 @@ def extended_trange(count, *args, **kwargs):
state.sampling_steps = count state.sampling_steps = count
state.sampling_step = 0 state.sampling_step = 0
for x in tqdm.trange(count, *args, desc=state.job, **kwargs): for x in tqdm.trange(count, *args, desc=state.job, file=shared.progress_print_out, **kwargs):
if state.interrupted: if state.interrupted:
break break
yield x yield x
state.sampling_step += 1 state.sampling_step += 1
shared.total_tqdm.update()
class KDiffusionSampler: class KDiffusionSampler:

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@ -1,9 +1,11 @@
import sys
import argparse import argparse
import json import json
import os import os
import gradio as gr import gradio as gr
import torch import torch
import tqdm
import modules.artists import modules.artists
from modules.paths import script_path, sd_path from modules.paths import script_path, sd_path
@ -124,6 +126,7 @@ class Options:
"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}), "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}),
"show_progressbar": OptionInfo(True, "Show progressbar"), "show_progressbar": OptionInfo(True, "Show progressbar"),
"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}), "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}),
"multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job. Broken in PyCharm console."),
"face_restoration_model": OptionInfo(None, "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}), "face_restoration_model": OptionInfo(None, "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
"code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), "code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
} }
@ -165,4 +168,32 @@ sd_upscalers = []
sd_model = None sd_model = None
progress_print_out = sys.stdout
class TotalTQDM:
def __init__(self):
self._tqdm = None
def reset(self):
self._tqdm = tqdm.tqdm(
desc="Total progress",
total=state.job_count * state.sampling_steps,
position=1,
file=progress_print_out
)
def update(self):
if not opts.multiple_tqdm:
return
if self._tqdm is None:
self.reset()
self._tqdm.update()
def clear(self):
if self._tqdm is not None:
self._tqdm.close()
self._tqdm = None
total_tqdm = TotalTQDM()

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@ -25,6 +25,7 @@ def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, r
tiling=tiling, tiling=tiling,
) )
print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
processed = modules.scripts.scripts_txt2img.run(p, *args) processed = modules.scripts.scripts_txt2img.run(p, *args)
if processed is not None: if processed is not None:
@ -32,5 +33,7 @@ def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, r
else: else:
processed = process_images(p) processed = process_images(p)
shared.total_tqdm.clear()
return processed.images, processed.js(), plaintext_to_html(processed.info) return processed.images, processed.js(), plaintext_to_html(processed.info)