More informative progress printing

modules/img2img.py

@@ -52,6 +52,7 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
         inpainting_mask_invert=inpainting_mask_invert,
         extra_generation_params={"Denoising Strength": denoising_strength}
     )
+    print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
 
     if is_loopback:
         output_images, info = None, None
@@ -168,5 +169,6 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
         if processed is None:
             processed = process_images(p)
 
+    shared.total_tqdm.clear()
 
     return processed.images, processed.js(), plaintext_to_html(processed.info)

modules/scripts.py

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

modules/sd_samplers.py

@@ -70,13 +70,14 @@ def extended_tdqm(sequence, *args, desc=None, **kwargs):
     state.sampling_steps = len(sequence)
     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:
             break
 
         yield x
 
         state.sampling_step += 1
+        shared.total_tqdm.update()
 
 
 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_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:
             break
 
         yield x
 
         state.sampling_step += 1
+        shared.total_tqdm.update()
 
 
 class KDiffusionSampler:

modules/shared.py

@@ -1,9 +1,11 @@
+import sys
 import argparse
 import json
 import os
 
 import gradio as gr
 import torch
+import tqdm
 
 import modules.artists
 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}),
         "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}),
+        "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]}),
         "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
 
+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()

modules/txt2img.py

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