Possible to Disable/Control Progress Bars (TQDM)?

[kevinjdolan]

I was trying to search through the code to figure out where the progress bars are being generated, but I could not locate them. I assume they are being powered by TQDM.

I am getting frustrating output when the logs are output to a file in the context of a Docker container running on Kubernetes. I would like to either remove the TQDM rendering altogether, or modify so that it is not producing the input characters intended for a live console.

Is there a documented way to control the TQDM rendering? If not, can you point me in the right direction for how to control these?

[kevinjdolan]

I was able to disable the progress produced by the guided-diffusion library through a monkey-patched hack:

def _disable_progress():
    from guided_diffusion.gaussian_diffusion import GaussianDiffusion
    orig_ddim = GaussianDiffusion.ddim_sample_loop_progressive
    orig_plms = GaussianDiffusion.plms_sample_loop_progressive
    def new_ddim(*args, **kwargs):
        kwargs['progress'] = False
        return orig_ddim(*args, **kwargs)
    def new_plms(*args, **kwargs):
        kwargs['progress'] = False
        return orig_plms(*args, **kwargs)
    GaussianDiffusion.ddim_sample_loop_progressive = new_ddim
    GaussianDiffusion.plms_sample_loop_progressive = new_plms

This succeeds at removing the progress bars.

A cleaner way would be to accept an environment variable, perhaps here:

runner.py#373

        show_progress = not os.environ.get('DISCOART_DISABLE_PROGRESS')
        if args.diffusion_sampling_mode == 'ddim':
            samples = sample_fn(
                model,
                (args.batch_size, 3, side_y, side_x),
                clip_denoised=args.clip_denoised,
                model_kwargs={},
                cond_fn=cond_fn,
                progress=show_progress,
                skip_timesteps=skip_steps,
                init_image=init,
                randomize_class=args.randomize_class,
                eta=args.eta,
                transformation_fn=lambda x: symmetry_transformation_fn(
                    x, args.use_horizontal_symmetry, args.use_vertical_symmetry
                ),
                transformation_percent=args.transformation_percent,
            )
        else:
            samples = sample_fn(
                model,
                (args.batch_size, 3, side_y, side_x),
                clip_denoised=args.clip_denoised,
                model_kwargs={},
                cond_fn=cond_fn,
                progress=show_progress,
                skip_timesteps=skip_steps,
                init_image=init,
                randomize_class=args.randomize_class,
                order=2,
            )

Apparently this does not solve my problem, however! I am seeing a lot of newlines being generated but I am not sure where they are coming from, and this is not an issue when I am running it interactively. Odd behavior!

[kevinjdolan]

For reference, this is the output in the logging file that I am seeing:

                   discoart-8bdf8c8e141c11edb869751f290d0983
╭────────────────────────────┬─────────────────────────────────────────────────╮
│                   Argument │ Value                                           │
├────────────────────────────┼─────────────────────────────────────────────────┤
│                 batch_name │ None                                            │
│                batch_size* │ 4                                               │
│                 clamp_grad │ True                                            │
│                  clamp_max │ 0.05                                            │
│              clip_denoised │ False                                           │
│       clip_guidance_scale* │ 524.288                                         │
│                clip_models │ ['ViT-B-32::openai', 'ViT-B-16::openai',        │
│                            │ 'RN50::openai']                                 │
│      clip_models_schedules │ None                                            │
│                cut_ic_pow* │ [1.0]*800+[4.0]*200                             │
│               cut_icgray_p │ [0.2]*400+[0]*600                               │
│              cut_innercut* │ [16]*400+[48]*600                               │
│              cut_overview* │ [48]*400+[16]*600                               │
│        cut_schedules_group │ None                                            │
│              cutn_batches* │ 1                                               │
│            diffusion_model │ 512x512_diffusion_uncond_finetune_008100        │
│     diffusion_model_config │ None                                            │
│    diffusion_sampling_mode │ ddim                                            │
│               display_rate │ None                                            │
│                        eta │ 0.8                                             │
│                    gif_fps │ 20                                              │
│             gif_size_ratio │ 0.5                                             │
│                 init_image │ None                                            │
│                 init_scale │ 1000                                            │
│                 n_batches* │ 1                                               │
│             name_docarray* │ discoart-8bdf8c8e141c11edb869751f290d0983       │
│        on_misspelled_token │ ignore                                          │
│                perlin_init │ False                                           │
│                perlin_mode │ mixed                                           │
│                   rand_mag │ 0.05                                            │
│            randomize_class │ True                                            │
│               range_scale* │ 250                                             │
│                  sat_scale │ 0                                               │
│                 save_rate* │ 10                                              │
│                      seed* │ 3605636296                                      │
│                  skip_augs │ False                                           │
│                 skip_event │ None                                            │
│                 skip_steps │ 0                                               │
│                     steps* │ 100                                             │
│                 stop_event │ None                                            │
│           text_clip_on_cpu │ False                                           │
│              text_prompts* │ ['Overheard at the Orchard', 'Sven Nordqvist    │
│                            │ Illustration']                                  │
│     transformation_percent │ [0.09]                                          │
│ truncate_overlength_prompt │ False                                           │
│                   tv_scale │ 0                                               │
│    use_horizontal_symmetry │ False                                           │
│        use_secondary_model │ True                                            │
│      use_vertical_symmetry │ False                                           │
│              width_height* │ [512, 512]                                      │
╰────────────────────────────┴─────────────────────────────────────────────────╯
                 showing all args (bold * args are non-default)
Loading diffusion model 512x512_diffusion_uncond_finetune_008100...
Found model disco-diffusion/512x512_diffusion_uncond_finetune_008100 in local cache!
...done in 0.00s: (Loading diffusion model 512x512_diffusion_uncond_finetune_008100)
Augmenting disco cache path to: /cache/models/disco-diffusion/512x512_diffusion_uncond_finetune_008100
Loading diffusion model secondary...
Found model disco-diffusion/secondary in local cache!
...done in 0.00s: (Loading diffusion model secondary)
Augmenting disco cache path to: /cache/models/disco-diffusion/secondary
2022-08-04 17:40:49,826 - discoart - INFO - preparing models...
Setting up [LPIPS] perceptual loss: trunk [vgg], v[0.1], spatial [off]
Loading model from: /usr/local/lib/python3.10/site-packages/lpips/weights/v0.1/vgg.pth
2022-08-04 17:40:51,561 - discoart - INFO - creating artworks `discoart-8bdf8c8e141c11edb869751f290d0983` (0/1)...










































































































2022-08-04 17:43:58,149 - discoart - INFO - done! discoart-8bdf8c8e141c11edb869751f290d0983

[entmike]

Yes it would be great to kill the TQDM/progress bar stuff for integration use cases.

[hanxiao]

from 0.11.2 set env DISCOART_DISABLE_TQDM=1

btw, we are K8s and cloud-native expert, more expert than diffusion 😉 , if you encounter any problem when deploying DiscoArt in production env such as K8s, please let us know @kevinjdolan

FYI @jina-ai/engineering