mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00

Kevin Turner 6fdbc1978d

* initial commit of DiffusionPipeline class

* spike: proof of concept using diffusers for txt2img

* doc: type hints for Generator

* refactor(model_cache): factor out load_ckpt

* model_cache: add ability to load a diffusers model pipeline

and update associated things in Generate & Generator to not instantly fail when that happens

* model_cache: fix model default image dimensions

* txt2img: support switching diffusers schedulers

* diffusers: let the scheduler do its scaling of the initial latents

Remove IPNDM scheduler; it is not behaving.

* web server: update image_progress callback for diffusers data

* diffusers: restore prompt weighting feature

* diffusers: fix set-sampler error following model switch

* diffusers: use InvokeAIDiffuserComponent for conditioning

* cross_attention_control: stub (no-op) implementations for diffusers

* model_cache: let offload_model work with DiffusionPipeline, sorta.

* models.yaml.example: add diffusers-format model, set as default

* test-invoke-conda: use diffusers-format model
test-invoke-conda: put huggingface-token where the library can use it

* environment-mac: upgrade to diffusers 0.7 (from 0.6)

this was already done for linux; mac must have been lost in the merge.

* preload_models: explicitly load diffusers models

In non-interactive mode too, as long as you're logged in.

* fix(model_cache): don't check `model.config` in diffusers format

clean-up from recent merge.

* diffusers integration: support img2img

* dev: upgrade to diffusers 0.8 (from 0.7.1)

We get to remove some code by using methods that were factored out in the base class.

* refactor: remove backported img2img.get_timesteps

now that we can use it directly from diffusers 0.8.1

* ci: use diffusers model

* dev: upgrade to diffusers 0.9 (from 0.8.1)

* lint: correct annotations for Python 3.9.

* lint: correct AttributeError.name reference for Python 3.9.

* CI: prefer diffusers-1.4 because it no longer requires a token

The RunwayML models still do.

* build: there's yet another place to update requirements?

* configure: try to download models even without token

Models in the CompVis and stabilityai repos no longer require them. (But runwayml still does.)

* configure: add troubleshooting info for config-not-found

* fix(configure): prepend root to config path

* fix(configure): remove second `default: true` from models example

* CI: simplify test-on-push logic now that we don't need secrets

The "test on push but only in forks" logic was only necessary when tests didn't work for PRs-from-forks.

* create an embedding_manager for diffusers

* internal: avoid importing diffusers DummyObject

see https://github.com/huggingface/diffusers/issues/1479

* fix "config attributes…not expected" diffusers warnings.

* fix deprecated scheduler construction

* work around an apparent MPS torch bug that causes conditioning to have no effect

* 🚧 post-rebase repair

* preliminary support for outpainting (no masking yet)

* monkey-patch diffusers.attention and use Invoke lowvram code

* add always_use_cpu arg to bypass MPS

* add cross-attention control support to diffusers (fails on MPS)

For unknown reasons MPS produces garbage output with .swap(). Use
--always_use_cpu arg to invoke.py for now to test this code on MPS.

* diffusers support for the inpainting model

* fix debug_image to not crash with non-RGB images.

* inpainting for the normal model [WIP]

This seems to be performing well until the LAST STEP, at which point it dissolves to confetti.

* fix off-by-one bug in cross-attention-control (#1774)

prompt token sequences begin with a "beginning-of-sequence" marker <bos> and end with a repeated "end-of-sequence" marker <eos> - to make a default prompt length of <bos> + 75 prompt tokens + <eos>. the .swap() code was failing to take the column for <bos> at index 0 into account. the changes here do that, and also add extra handling for a single <eos> (which may be redundant but which is included for completeness).

based on my understanding and some assumptions about how this all works, the reason .swap() nevertheless seemed to do the right thing, to some extent, is because over multiple steps the conditioning process in Stable Diffusion operates as a feedback loop. a change to token n-1 has flow-on effects to how the [1x4x64x64] latent tensor is modified by all the tokens after it, - and as the next step is processed, all the tokens before it as well. intuitively, a token's conditioning effects "echo" throughout the whole length of the prompt. so even though the token at n-1 was being edited when what the user actually wanted was to edit the token at n, it nevertheless still had some non-negligible effect, in roughly the right direction, often enough that it seemed like it was working properly.

* refactor common CrossAttention stuff into a mixin so that the old ldm code can still work if necessary

* inpainting for the normal model. I think it works this time.

* diffusers: reset num_vectors_per_token

sync with 44a0055571

* diffusers: txt2img2img (hires_fix)

with so much slicing and dicing of pipeline methods to stitch them together

* refactor(diffusers): reduce some code duplication amongst the different tasks

* fixup! refactor(diffusers): reduce some code duplication amongst the different tasks

* diffusers: enable DPMSolver++ scheduler

* diffusers: upgrade to diffusers 0.10, add Heun scheduler

* diffusers(ModelCache): stopgap to make from_cpu compatible with diffusers

* CI: default to diffusers-1.5 now that runwayml token requirement is gone

* diffusers: update to 0.10 (and transformers to 4.25)

* diffusers: use xformers when available

diffusers no longer auto-enables this as of 0.10.2.

* diffusers: make masked img2img behave better with multi-step schedulers

re-randomizing the noise each step was confusing them.

* diffusers: work more better with more models.

fixed relative path problem with local models.

fixed models on hub not always having a `fp16` branch.

* diffusers: stopgap fix for attention_maps_callback crash after recent merge

* fixup import merge conflicts

correction for 061c5369a2

* test: add tests/inpainting inputs for masked img2img

* diffusers(AddsMaskedGuidance): partial fix for k-schedulers

Prevents them from crashing, but results are still hot garbage.

* fix --safety_checker arg parsing

and add note to diffusers loader about where safety checker gets called

* generate: fix import error

* CI: don't try to read the old init location

* diffusers: support loading an alternate VAE

* CI: remove sh-syntax if-statement so it doesn't crash powershell

* CI: fold strings in yaml because backslash is not line-continuation in powershell

* attention maps callback stuff for diffusers

* build: fix syntax error in environment-mac

* diffusers: add INITIAL_MODELS with diffusers-compatible repos

* re-enable the embedding manager; closes #1778

* Squashed commit of the following:

commit e4a956abc37fcb5cf188388b76b617bc5c8fda7d
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 15:43:07 2022 +0100

    import new load handling from EmbeddingManager and cleanup

commit c4abe91a5ba0d415b45bf734068385668b7a66e6
Merge: 032e856e 1efc6397
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 15:09:53 2022 +0100

    Merge branch 'feature_textual_inversion_mgr' into dev/diffusers_with_textual_inversion_manager

commit 032e856eefb3bbc39534f5daafd25764bcfcef8b
Merge: 8b4f0fe9 bc515e24
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 15:08:01 2022 +0100

    Merge remote-tracking branch 'upstream/dev/diffusers' into dev/diffusers_with_textual_inversion_manager

commit 1efc6397fc6e61c1aff4b0258b93089d61de5955
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 15:04:28 2022 +0100

    cleanup and add performance notes

commit e400f804ac471a0ca2ba432fd658778b20c7bdab
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 14:45:07 2022 +0100

    fix bug and update unit tests

commit deb9ae0ae1016750e93ce8275734061f7285a231
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 14:28:29 2022 +0100

    textual inversion manager seems to work

commit 162e02505dec777e91a983c4d0fb52e950d25ff0
Merge: cbad4583 12769b3d
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 11:58:03 2022 +0100

    Merge branch 'main' into feature_textual_inversion_mgr

commit cbad45836c6aace6871a90f2621a953f49433131
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 11:54:10 2022 +0100

    use position embeddings

commit 070344c69b0e0db340a183857d0a787b348681d3
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 11:53:47 2022 +0100

    Don't crash CLI on exceptions

commit b035ac8c6772dfd9ba41b8eeb9103181cda028f8
Author: Damian Stewart <d@damianstewart.com>
Date:   Sun Dec 18 11:11:55 2022 +0100

    add missing position_embeddings

commit 12769b3d3562ef71e0f54946b532ad077e10043c
Author: Damian Stewart <d@damianstewart.com>
Date:   Fri Dec 16 13:33:25 2022 +0100

    debugging why it don't work

commit bafb7215eabe1515ca5e8388fd3bb2f3ac5362cf
Author: Damian Stewart <d@damianstewart.com>
Date:   Fri Dec 16 13:21:33 2022 +0100

    debugging why it don't work

commit 664a6e9e14
Author: Damian Stewart <d@damianstewart.com>
Date:   Fri Dec 16 12:48:38 2022 +0100

    use TextualInversionManager in place of embeddings (wip, doesn't work)

commit 8b4f0fe9d6e4e2643b36dfa27864294785d7ba4e
Author: Damian Stewart <d@damianstewart.com>
Date:   Fri Dec 16 12:48:38 2022 +0100

    use TextualInversionManager in place of embeddings (wip, doesn't work)

commit ffbe1ab11163ba712e353d89404e301d0e0c6cdf
Merge: 6e4dad60 023df37e
Author: Damian Stewart <d@damianstewart.com>
Date:   Fri Dec 16 02:37:31 2022 +0100

    Merge branch 'feature_textual_inversion_mgr' into dev/diffusers

commit 023df37eff
Author: Damian Stewart <d@damianstewart.com>
Date:   Fri Dec 16 02:36:54 2022 +0100

    cleanup

commit 05fac594ea
Author: Damian Stewart <d@damianstewart.com>
Date:   Fri Dec 16 02:07:49 2022 +0100

    tweak error checking

commit 009f32ed39
Author: damian <null@damianstewart.com>
Date:   Thu Dec 15 21:29:47 2022 +0100

    unit tests passing for embeddings with vector length >1

commit beb1b08d9a
Author: Damian Stewart <d@damianstewart.com>
Date:   Thu Dec 15 13:39:09 2022 +0100

    more explicit equality tests when overwriting

commit 44d8a5a7c8
Author: Damian Stewart <d@damianstewart.com>
Date:   Thu Dec 15 13:30:13 2022 +0100

    wip textual inversion manager (unit tests passing for 1v embedding overwriting)

commit 417c2b57d9
Author: Damian Stewart <d@damianstewart.com>
Date:   Thu Dec 15 12:30:55 2022 +0100

    wip textual inversion manager (unit tests passing for base stuff + padding)

commit 2e80872e3b
Author: Damian Stewart <d@damianstewart.com>
Date:   Thu Dec 15 10:57:57 2022 +0100

    wip new TextualInversionManager

* stop using WeightedFrozenCLIPEmbedder

* store diffusion models locally

- configure_invokeai.py reconfigured to store diffusion models rather than
  CompVis models
- hugging face caching model is used, but cache is set to ~/invokeai/models/repo_id
- models.yaml does **NOT** use path, just repo_id
- "repo_name" changed to "repo_id" to following hugging face conventions
- Models are loaded with full precision pending further work.

* allow non-local files during development

* path takes priority over repo_id

* MVP for model_cache and configure_invokeai

- Feature complete (almost)

- configure_invokeai.py downloads both .ckpt and diffuser models,
  along with their VAEs. Both types of download are controlled by
  a unified INITIAL_MODELS.yaml file.

- model_cache can load both type of model and switches back and forth
  in CPU. No memory leaks detected

TO DO:

  1. I have not yet turned on the LocalOnly flag for diffuser models, so
     the code will check the Hugging Face repo for updates before using the
     locally cached models. This will break firewalled systems. I am thinking
     of putting in a global check for internet connectivity at startup time
     and setting the LocalOnly flag based on this. It would be good to check
     updates if there is connectivity.

  2. I have not gone completely through INITIAL_MODELS.yaml to check which
     models are available as diffusers and which are not. So models like
     PaperCut and VoxelArt may not load properly. The runway and stability
     models are checked, as well as the Trinart models.

  3. Add stanzas for SD 2.0 and 2.1 in INITIAL_MODELS.yaml

REMAINING PROBLEMS NOT DIRECTLY RELATED TO MODEL_CACHE:

  1. When loading a .ckpt file there are lots of messages like this:

     Warning! ldm.modules.attention.CrossAttention is no longer being
     maintained. Please use InvokeAICrossAttention instead.

     I'm not sure how to address this.

  2. The ckpt models ***don't actually run*** due to the lack of special-case
     support for them in the generator objects. For example, here's the hard
     crash you get when you run txt2img against the legacy waifu-diffusion-1.3
     model:
```
     >> An error occurred:
     Traceback (most recent call last):
       File "/data/lstein/InvokeAI/ldm/invoke/CLI.py", line 140, in main
           main_loop(gen, opt)
      File "/data/lstein/InvokeAI/ldm/invoke/CLI.py", line 371, in main_loop
         gen.prompt2image(
      File "/data/lstein/InvokeAI/ldm/generate.py", line 496, in prompt2image
	 results = generator.generate(
      File "/data/lstein/InvokeAI/ldm/invoke/generator/base.py", line 108, in generate
         image = make_image(x_T)
      File "/data/lstein/InvokeAI/ldm/invoke/generator/txt2img.py", line 33, in make_image
         pipeline_output = pipeline.image_from_embeddings(
      File "/home/lstein/invokeai/.venv/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1265, in __getattr__
         raise AttributeError("'{}' object has no attribute '{}'".format(
     AttributeError: 'LatentDiffusion' object has no attribute 'image_from_embeddings'
```

  3. The inpainting diffusion model isn't working. Here's the output of "banana
     sushi" when inpainting-1.5 is loaded:

```
    Traceback (most recent call last):
      File "/data/lstein/InvokeAI/ldm/generate.py", line 496, in prompt2image
        results = generator.generate(
      File "/data/lstein/InvokeAI/ldm/invoke/generator/base.py", line 108, in generate
        image = make_image(x_T)
      File "/data/lstein/InvokeAI/ldm/invoke/generator/txt2img.py", line 33, in make_image
        pipeline_output = pipeline.image_from_embeddings(
      File "/data/lstein/InvokeAI/ldm/invoke/generator/diffusers_pipeline.py", line 301, in image_from_embeddings
        result_latents, result_attention_map_saver = self.latents_from_embeddings(
      File "/data/lstein/InvokeAI/ldm/invoke/generator/diffusers_pipeline.py", line 330, in latents_from_embeddings
        result: PipelineIntermediateState = infer_latents_from_embeddings(
      File "/data/lstein/InvokeAI/ldm/invoke/generator/diffusers_pipeline.py", line 185, in __call__
        for result in self.generator_method(*args, **kwargs):
      File "/data/lstein/InvokeAI/ldm/invoke/generator/diffusers_pipeline.py", line 367, in generate_latents_from_embeddings
        step_output = self.step(batched_t, latents, guidance_scale,
      File "/home/lstein/invokeai/.venv/lib/python3.9/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
        return func(*args, **kwargs)
      File "/data/lstein/InvokeAI/ldm/invoke/generator/diffusers_pipeline.py", line 409, in step
        step_output = self.scheduler.step(noise_pred, timestep, latents, **extra_step_kwargs)
      File "/home/lstein/invokeai/.venv/lib/python3.9/site-packages/diffusers/schedulers/scheduling_lms_discrete.py", line 223, in step
        pred_original_sample = sample - sigma * model_output
    RuntimeError: The size of tensor a (9) must match the size of tensor b (4) at non-singleton dimension 1
```

* proper support for float32/float16

- configure script now correctly detects user's preference for
  fp16/32 and downloads the correct diffuser version. If fp16
  version not available, falls back to fp32 version.

- misc code cleanup and simplification in model_cache

* add on-the-fly conversion of .ckpt to diffusers models

1. On-the-fly conversion code can be found in the file ldm/invoke/ckpt_to_diffusers.py.

2. A new !optimize command has been added to the CLI. Should be ported to Web GUI.

User experience on the CLI is this:

```
invoke> !optimize /home/lstein/invokeai/models/ldm/stable-diffusion-v1/sd-v1-4.ckpt
INFO: Converting legacy weights file /home/lstein/invokeai/models/ldm/stable-diffusion-v1/sd-v1-4.ckpt to optimized diffuser model.
      This operation will take 30-60s to complete.
Success. Optimized model is now located at /home/lstein/tmp/invokeai/models/optimized-ckpts/sd-v1-4
Writing new config file entry for sd-v1-4...

>> New configuration:
sd-v1-4:
  description: Optimized version of sd-v1-4
  format: diffusers
  path: /home/lstein/tmp/invokeai/models/optimized-ckpts/sd-v1-4

OK to import [n]? y
>> Verifying that new model loads...
>> Current VRAM usage:  2.60G
>> Offloading stable-diffusion-2.1 to CPU
>> Loading diffusers model from /home/lstein/tmp/invokeai/models/optimized-ckpts/sd-v1-4
  | Using faster float16 precision
You have disabled the safety checker for <class 'ldm.invoke.generator.diffusers_pipeline.StableDiffusionGeneratorPipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion \
license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances,\
 disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .
  | training width x height = (512 x 512)
>> Model loaded in 3.48s
>> Max VRAM used to load the model: 2.17G
>> Current VRAM usage:2.17G
>> Textual inversions available:
>> Setting Sampler to k_lms (LMSDiscreteScheduler)
Keep model loaded? [y]
```

* add parallel set of generator files for ckpt legacy generation

* generation using legacy ckpt models now working

* diffusers: fix missing attention_maps_callback

fix for 23eb80b404

* associate legacy CrossAttention with .ckpt models

* enable autoconvert

New --autoconvert CLI option will scan a designated directory for
new .ckpt files, convert them into diffuser models, and import
them into models.yaml.

Works like this:

   invoke.py --autoconvert /path/to/weights/directory

In ModelCache added two new methods:

  autoconvert_weights(config_path, weights_directory_path, models_directory_path)
  convert_and_import(ckpt_path, diffuser_path)

* diffusers: update to diffusers 0.11 (from 0.10.2)

* fix vae loading & width/height calculation

* refactor: encapsulate these conditioning data into one container

* diffusers: fix some noise-scaling issues by pushing the noise-mixing down to the common function

* add support for safetensors and accelerate

* set local_files_only when internet unreachable

* diffusers: fix error-handling path when model repo has no fp16 branch

* fix generatorinpaint error

Fixes :
  "ModuleNotFoundError: No module named 'ldm.invoke.generatorinpaint'
   https://github.com/invoke-ai/InvokeAI/pull/1583#issuecomment-1363634318

* quench diffuser safety-checker warning

* diffusers: support stochastic DDIM eta parameter

* fix conda env creation on macos

* fix cross-attention with diffusers 0.11

* diffusers: the VAE needs to be tiling as well as the U-Net

* diffusers: comment on subfolders

* diffusers: embiggen!

* diffusers: make model_cache.list_models serializable

* diffusers(inpaint): restore scaling functionality

* fix requirements clash between numba and numpy 1.24

* diffusers: allow inpainting model to do non-inpainting tasks

* start expanding model_cache functionality

* add import_ckpt_model() and import_diffuser_model() methods to model_manager

- in addition, model_cache.py is now renamed to model_manager.py

* allow "recommended" flag to be optional in INITIAL_MODELS.yaml

* configure_invokeai now downloads VAE diffusers in advance

* rename ModelCache to ModelManager

* remove support for `repo_name` in models.yaml

* check for and refuse to load embeddings trained on incompatible models

* models.yaml.example: s/repo_name/repo_id

and remove extra INITIAL_MODELS now that the main one has diffusers models in it.

* add MVP textual inversion script

* refactor(InvokeAIDiffuserComponent): factor out _combine()

* InvokeAIDiffuserComponent: implement threshold

* InvokeAIDiffuserComponent: diagnostic logs for threshold

...this does not look right

* add a curses-based frontend to textual inversion

- not quite working yet
- requires npyscreen installed
- on windows will also have the windows-curses requirement, but not added
  to requirements yet

* add curses-based interface for textual inversion

* fix crash in convert_and_import()

- This corrects a "local variable referenced before assignment" error
  in model_manager.convert_and_import()

* potential workaround for no 'state_dict' key error

- As reported in https://github.com/huggingface/diffusers/issues/1876

* create TI output dir if needed

* Update environment-lin-cuda.yml (#2159)

Fixing line 42 to be the proper order to define the transformers requirement: ~= instead of =~

* diffusers: update sampler-to-scheduler mapping

based on https://github.com/huggingface/diffusers/issues/277#issuecomment-1371428672

* improve user exp for ckt to diffusers conversion

- !optimize_models command now operates on an existing ckpt file entry in models.yaml
- replaces existing entry, rather than adding a new one
- offers to delete the ckpt file after conversion

* web: adapt progress callback to deal with old generator or new diffusers pipeline

* clean-up model_manager code

- add_model() verified to work for .ckpt local paths,
  .ckpt remote URLs, diffusers local paths, and
  diffusers repo_ids

- convert_and_import() verified to work for local and
  remove .ckpt files

* handle edge cases for import_model() and convert_model()

* add support for safetensor .ckpt files

* fix name error

* code cleanup with pyflake

* improve model setting behavior

- If the user enters an invalid model name at startup time, will not
  try to load it, warn, and use default model
- CLI UI enhancement: include currently active model in the command
  line prompt.

* update test-invoke-pip.yml
- fix model cache path to point to runwayml/stable-diffusion-v1-5
- remove `skip-sd-weights` from configure_invokeai.py args

* exclude dev/diffusers from "fail for draft PRs"

* disable "fail on PR jobs"

* re-add `--skip-sd-weights` since no space

* update workflow environments
- include `INVOKE_MODEL_RECONFIGURE: '--yes'`

* clean up model load failure handling

- Allow CLI to run even when no model is defined or loadable.
- Inhibit stack trace when model load fails - only show last error
- Give user *option* to run configure_invokeai.py when no models
  successfully load.
- Restart invokeai after reconfiguration.

* further edge-case handling

1) only one model in models.yaml file, and that model is broken
2) no models in models.yaml
3) models.yaml doesn't exist at all

* fix incorrect model status listing

- "cached" was not being returned from list_models()
- normalize handling of exceptions during model loading:
   - Passing an invalid model name to generate.set_model() will return
     a KeyError
   - All other exceptions are returned as the appropriate Exception

* CI: do download weights (if not already cached)

* diffusers: fix scheduler loading in offline mode

* CI: fix model name (no longer has `diffusers-` prefix)

* Update txt2img2img.py (#2256)

* fixes to share models with HuggingFace cache system

- If HF_HOME environment variable is defined, then all huggingface models
  are stored in that directory following the standard conventions.
- For seamless interoperability, set HF_HOME to ~/.cache/huggingface
- If HF_HOME not defined, then models are stored in ~/invokeai/models.
  This is equivalent to setting HF_HOME to ~/invokeai/models

A future commit will add a migration mechanism so that this change doesn't
break previous installs.

* feat - make model storage compatible with hugging face caching system

This commit alters the InvokeAI model directory to be compatible with
hugging face, making it easier to share diffusers (and other models)
across different programs.

- If the HF_HOME environment variable is not set, then models are
  cached in ~/invokeai/models in a format that is identical to the
  HuggingFace cache.

- If HF_HOME is set, then models are cached wherever HF_HOME points.

- To enable sharing with other HuggingFace library clients, set
  HF_HOME to ~/.cache/huggingface to set the default cache location
  or to ~/invokeai/models to have huggingface cache inside InvokeAI.

* fixes to share models with HuggingFace cache system

    - If HF_HOME environment variable is defined, then all huggingface models
      are stored in that directory following the standard conventions.
    - For seamless interoperability, set HF_HOME to ~/.cache/huggingface
    - If HF_HOME not defined, then models are stored in ~/invokeai/models.
      This is equivalent to setting HF_HOME to ~/invokeai/models

    A future commit will add a migration mechanism so that this change doesn't
    break previous installs.

* fix error "no attribute CkptInpaint"

* model_manager.list_models() returns entire model config stanza+status

* Initial Draft - Model Manager Diffusers

* added hash function to diffusers

* implement sha256 hashes on diffusers models

* Add Model Manager Support for Diffusers

* fix various problems with model manager

- in cli import functions, fix not enough values to unpack from
  _get_name_and_desc()
- fix crash when using old-style vae: value with new-style diffuser

* rebuild frontend

* fix dictconfig-not-serializable issue

* fix NoneType' object is not subscriptable crash in model_manager

* fix "str has no attribute get" error in model_manager list_models()

* Add path and repo_id support for Diffusers Model Manager

Also fixes bugs

* Fix tooltip IT localization not working

* Add Version Number To WebUI

* Optimize Model Search

* Fix incorrect font on the Model Manager UI

* Fix image degradation on merge fixes - [Experimental]

This change should effectively fix a couple of things.

- Fix image degradation on subsequent merges of the canvas layers.
- Fix the slight transparent border that is left behind when filling the bounding box with a color.
- Fix the left over line of color when filling a bounding box with color.

So far there are no side effects for this. If any, please report.

* Add local model filtering for Diffusers / Checkpoints

* Go to home on modal close for the Add Modal UI

* Styling Fixes

* Model Manager Diffusers Localization Update

* Add Safe Tensor scanning to Model Manager

* Fix model edit form dispatching string values instead of numbers.

* Resolve VAE handling / edge cases for supplied repos

* defer injecting tokens for textual inversions until they're used for the first time

* squash a console warning

* implement model migration check

* add_model() overwrites previous config rather than merges

* fix model config file attribute merging

* fix precision handling in textual inversion script

* allow ckpt conversion script to work with safetensors .ckpts

Applied patch here:
beb932c5d1

* fix name "args" is not defined crash in textual_inversion_training

* fix a second NameError: name 'args' is not defined crash

* fix loading of the safety checker from the global cache dir

* add installation step to textual inversion frontend

- After a successful training run, the script will copy learned_embeds.bin
  to a subfolder of the embeddings directory.
- User given the option to delete the logs and intermediate checkpoints
  (which together use 7-8G of space)
- If textual inversion training fails, reports the error gracefully.

* don't crash out on incompatible embeddings

- put try: blocks around places where the system tries to load an embedding
  which is incompatible with the currently loaded model

* add support for checkpoint resuming

* textual inversion preferences are saved and restored between sessions

- Preferences are stored in a file named text-inversion-training/preferences.conf
- Currently the resume-from-checkpoint option is not working correctly. Possible
  bug in textual_inversion_training.py?

* copy learned_embeddings.bin into right location

* add front end for diffusers model merging

- Front end doesn't do anything yet!!!!
- Made change to model name parsing in CLI to support ability to have merged models
  with the "+" character in their names.

* improve inpainting experience

- recommend ckpt version of inpainting-1.5 to user
- fix get_noise() bug in ckpt version of omnibus.py

* update environment*yml

* tweak instructions to install HuggingFace token

* bump version number

* enhance update scripts

- update scripts will now fetch new INITIAL_MODELS.yaml so that
  configure_invokeai.py will know about the diffusers versions.

* enhance invoke.sh/invoke.bat launchers

- added configure_invokeai.py to menu
- menu defaults to browser-based invoke

* remove conda workflow (#2321)

* fix `token_ids has shape torch.Size([79]) - expected [77]`

* update CHANGELOG.md with 2.3.* info

- Add information on how formats have changed and the upgrade process.
- Add short bug list.

Co-authored-by: Damian Stewart <d@damianstewart.com>
Co-authored-by: Damian Stewart <null@damianstewart.com>
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
Co-authored-by: Wybartel-luxmc <37852506+Wybartel-luxmc@users.noreply.github.com>
Co-authored-by: mauwii <Mauwii@outlook.de>
Co-authored-by: mickr777 <115216705+mickr777@users.noreply.github.com>
Co-authored-by: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Co-authored-by: Eugene Brodsky <ebr@users.noreply.github.com>
Co-authored-by: Matthias Wild <40327258+mauwii@users.noreply.github.com>

2023-01-15 09:22:46 -05:00

26 KiB

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title
Changelog

:octicons-log-16: Changelog

v2.3.0 (15 January 2023)

**Transition to diffusers

Version 2.3 provides support for both the traditional .ckpt weight checkpoint files as well as the HuggingFace diffusers format. This introduces several changes you should know about.

The models.yaml format has been updated. There are now two different type of configuration stanza. The traditional ckpt one will look like this, with a format of ckpt and a weights field that points to the absolute or ROOTDIR-relative location of the ckpt file.

inpainting-1.5:
   description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
   repo_id: runwayml/stable-diffusion-inpainting
   format: ckpt
   width: 512
   height: 512
   weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
   config: configs/stable-diffusion/v1-inpainting-inference.yaml
   vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt

A configuration stanza for a diffusers model hosted at HuggingFace will look like this, with a format of diffusers and a repo_id that points to the repository ID of the model on HuggingFace:

stable-diffusion-2.1:
description: Stable Diffusion version 2.1 diffusers model (5.21 GB)
repo_id: stabilityai/stable-diffusion-2-1
format: diffusers

A configuration stanza for a diffuers model stored locally should look like this, with a format of diffusers, but a path field that points at the directory that contains model_index.json:

waifu-diffusion:
description: Latest waifu diffusion 1.4
format: diffusers
path: models/diffusers/hakurei-haifu-diffusion-1.4

The format of the models directory has changed to mimic the HuggingFace cache directory. By default, diffusers models are now automatically downloaded and retrieved from the directory ROOTDIR/models/diffusers, while other models are stored in the directory ROOTDIR/models/hub. This organization is the same as that used by HuggingFace for its cache management.

This allows you to share diffusers and ckpt model files easily with other machine learning applications that use the HuggingFace libraries. To do this, set the environment variable HF_HOME before starting up InvokeAI to tell it what directory to cache models in. To tell InvokeAI to use the standard HuggingFace cache directory, you would set HF_HOME like this (Linux/Mac):

export HF_HOME=~/.cache/hugging_face
If you upgrade to InvokeAI 2.3.* from an earlier version, there will be a one-time migration from the old models directory format to the new one. You will see a message about this the first time you start invoke.py.
Both the front end back ends of the model manager have been rewritten to accommodate diffusers. You can import models using their local file path, using their URLs, or their HuggingFace repo_ids. On the command line, all these syntaxes work:
```
!import_model stabilityai/stable-diffusion-2-1-base
!import_model /opt/sd-models/sd-1.4.ckpt
!import_model https://huggingface.co/Fictiverse/Stable_Diffusion_PaperCut_Model/blob/main/PaperCut_v1.ckpt
```

**KNOWN BUGS (15 January 2023)

On CUDA systems, the 768 pixel stable-diffusion-2.0 and stable-diffusion-2.1 models can only be run as diffusers models when the xformer library is installed and configured. Without xformers, InvokeAI returns black images.
Inpainting and outpainting have regressed in quality.

Both these issues are being actively worked on.

v2.2.4 (11 December 2022)

the invokeai directory

Previously there were two directories to worry about, the directory that contained the InvokeAI source code and the launcher scripts, and the invokeai directory that contained the models files, embeddings, configuration and outputs. With the 2.2.4 release, this dual system is done away with, and everything, including the invoke.bat and invoke.sh launcher scripts, now live in a directory named invokeai. By default this directory is located in your home directory (e.g. \Users\yourname on Windows), but you can select where it goes at install time.

After installation, you can delete the install directory (the one that the zip file creates when it unpacks). Do not delete or move the invokeai directory!

Initialization file invokeai/invokeai.init

You can place frequently-used startup options in this file, such as the default number of steps or your preferred sampler. To keep everything in one place, this file has now been moved into the invokeai directory and is named invokeai.init.

To update from Version 2.2.3

The easiest route is to download and unpack one of the 2.2.4 installer files. When it asks you for the location of the invokeai runtime directory, respond with the path to the directory that contains your 2.2.3 invokeai. That is, if invokeai lives at C:\Users\fred\invokeai, then answer with C:\Users\fred and answer "Y" when asked if you want to reuse the directory.

The update.sh (update.bat) script that came with the 2.2.3 source installer does not know about the new directory layout and won't be fully functional.

To update to 2.2.5 (and beyond) there's now an update path

As they become available, you can update to more recent versions of InvokeAI using an update.sh (update.bat) script located in the invokeai directory. Running it without any arguments will install the most recent version of InvokeAI. Alternatively, you can get set releases by running the update.sh script with an argument in the command shell. This syntax accepts the path to the desired release's zip file, which you can find by clicking on the green "Code" button on this repository's home page.

Other 2.2.4 Improvements

Fix InvokeAI GUI initialization by @addianto in #1687
fix link in documentation by @lstein in #1728
Fix broken link by @ShawnZhong in #1736
Remove reference to binary installer by @lstein in #1731
documentation fixes for 2.2.3 by @lstein in #1740
Modify installer links to point closer to the source installer by @ebr in #1745
add documentation warning about 1650/60 cards by @lstein in #1753
Fix Linux source URL in installation docs by @andybearman in #1756
Make install instructions discoverable in readme by @damian0815 in #1752
typo fix by @ofirkris in #1755
Non-interactive model download (support HUGGINGFACE_TOKEN) by @ebr in #1578
fix(srcinstall): shell installer - cp scripts instead of linking by @tildebyte in #1765
stability and usage improvements to binary & source installers by @lstein in #1760
fix off-by-one bug in cross-attention-control by @damian0815 in #1774
Eventually update APP_VERSION to 2.2.3 by @spezialspezial in #1768
invoke script cds to its location before running by @lstein in #1805
Make PaperCut and VoxelArt models load again by @lstein in #1730
Fix --embedding_directory / --embedding_path not working by @blessedcoolant in #1817
Clean up readme by @hipsterusername in #1820
Optimized Docker build with support for external working directory by @ebr in #1544
disable pushing the cloud container by @mauwii in #1831
Fix docker push github action and expand with additional metadata by @ebr in #1837
Fix Broken Link To Notebook by @VedantMadane in #1821
Account for flat models by @spezialspezial in #1766
Update invoke.bat.in isolate environment variables by @lynnewu in #1833
Arch Linux Specific PatchMatch Instructions & fixing conda install on linux by @SammCheese in #1848
Make force free GPU memory work in img2img by @addianto in #1844
New installer by @lstein

v2.2.3 (2 December 2022)

!!! Note

This point release removes references to the binary installer from the
installation guide. The binary installer is not stable at the current
time. First time users are encouraged to use the "source" installer as
described in [Installing InvokeAI with the Source Installer](installation/deprecated_documentation/INSTALL_SOURCE.md)

With InvokeAI 2.2, this project now provides enthusiasts and professionals a robust workflow solution for creating AI-generated and human facilitated compositions. Additional enhancements have been made as well, improving safety, ease of use, and installation.

Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2).

You can see the release video here, which introduces the main WebUI enhancement for version 2.2 - The Unified Canvas. This new workflow is the biggest enhancement added to the WebUI to date, and unlocks a stunning amount of potential for users to create and iterate on their creations. The following sections describe what's new for InvokeAI.

v2.2.2 (30 November 2022)

!!! note

The binary installer is not ready for prime time. First time users are recommended to install via the "source" installer accessible through the links at the bottom of this page.****

Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2).

v2.2.0 (2 December 2022)

Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2).

v2.1.3 (13 November 2022)

A choice of installer scripts that automate installation and configuration. See Installation.
A streamlined manual installation process that works for both Conda and PIP-only installs. See Manual Installation.
The ability to save frequently-used startup options (model to load, steps, sampler, etc) in a .invokeai file. See Client
Support for AMD GPU cards (non-CUDA) on Linux machines.
Multiple bugs and edge cases squashed.

v2.1.0 (2 November 2022)

update mac instructions to use invokeai for env name by @willwillems in #1030
Update .gitignore by @blessedcoolant in #1040
reintroduce fix for m1 from #579 missing after merge by @skurovec in #1056
Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in #1060
Print out the device type which is used by @manzke in #1073
Hires Addition by @hipsterusername in #1063
fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by @skurovec in #1081
Forward dream.py to invoke.py using the same interpreter, add deprecation warning by @db3000 in #1077
fix noisy images at high step counts by @lstein in #1086
Generalize facetool strength argument by @db3000 in #1078
Enable fast switching among models at the invoke> command line by @lstein in #1066
Fix Typo, committed changing ldm environment to invokeai by @jdries3 in #1095
Update generate.py by @unreleased in #1109
Update 'ldm' env to 'invokeai' in troubleshooting steps by @19wolf in #1125
Fixed documentation typos and resolved merge conflicts by @rupeshs in #1123
Fix broken doc links, fix malaprop in the project subtitle by @majick in #1131
Only output facetool parameters if enhancing faces by @db3000 in #1119
Update gitignore to ignore codeformer weights at new location by @spezialspezial in #1136
fix links to point to invoke-ai.github.io #1117 by @mauwii in #1143
Rework-mkdocs by @mauwii in #1144
add option to CLI and pngwriter that allows user to set PNG compression level by @lstein in #1127
Fix img2img DDIM index out of bound by @wfng92 in #1137
Fix gh actions by @mauwii in #1128
update mac instructions to use invokeai for env name by @willwillems in #1030
Update .gitignore by @blessedcoolant in #1040
reintroduce fix for m1 from #579 missing after merge by @skurovec in #1056
Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in #1060
Print out the device type which is used by @manzke in #1073
Hires Addition by @hipsterusername in #1063
fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by @skurovec in #1081
Forward dream.py to invoke.py using the same interpreter, add deprecation warning by @db3000 in #1077
fix noisy images at high step counts by @lstein in #1086
Generalize facetool strength argument by @db3000 in #1078
Enable fast switching among models at the invoke> command line by @lstein in #1066
Fix Typo, committed changing ldm environment to invokeai by @jdries3 in #1095
Fixed documentation typos and resolved merge conflicts by @rupeshs in #1123
Only output facetool parameters if enhancing faces by @db3000 in #1119
add option to CLI and pngwriter that allows user to set PNG compression level by @lstein in #1127
Fix img2img DDIM index out of bound by @wfng92 in #1137
Add text prompt to inpaint mask support by @lstein in #1133
Respect http[s] protocol when making socket.io middleware by @damian0815 in #976
WebUI: Adds Codeformer support by @psychedelicious in #1151
Skips normalizing prompts for web UI metadata by @psychedelicious in #1165
Add Asymmetric Tiling by @carson-katri in #1132
Web UI: Increases max CFG Scale to 200 by @psychedelicious in #1172
Corrects color channels in face restoration; Fixes #1167 by @psychedelicious in #1175
Flips channels using array slicing instead of using OpenCV by @psychedelicious in #1178
Fix typo in docs: s/Formally/Formerly by @noodlebox in #1176
fix clipseg loading problems by @lstein in #1177
Correct color channels in upscale using array slicing by @wfng92 in #1181
Web UI: Filters existing images when adding new images; Fixes #1085 by @psychedelicious in #1171
fix a number of bugs in textual inversion by @lstein in #1190
Improve !fetch, add !replay command by @ArDiouscuros in #882
Fix generation of image with s>1000 by @holstvoogd in #951
Web UI: Gallery improvements by @psychedelicious in #1198
Update CLI.md by @krummrey in #1211
outcropping improvements by @lstein in #1207
add support for loading VAE autoencoders by @lstein in #1216
remove duplicate fix_func for MPS by @wfng92 in #1210
Metadata storage and retrieval fixes by @lstein in #1204
nix: add shell.nix file by @Cloudef in #1170
Web UI: Changes vite dist asset paths to relative by @psychedelicious in #1185
Web UI: Removes isDisabled from PromptInput by @psychedelicious in #1187
Allow user to generate images with initial noise as on M1 / mps system by @ArDiouscuros in #981
feat: adding filename format template by @plucked in #968
Web UI: Fixes broken bundle by @psychedelicious in #1242
Support runwayML custom inpainting model by @lstein in #1243
Update IMG2IMG.md by @talitore in #1262
New dockerfile - including a build- and a run- script as well as a GH-Action by @mauwii in #1233
cut over from karras to model noise schedule for higher steps by @lstein in #1222
Prompt tweaks by @lstein in #1268
Outpainting implementation by @Kyle0654 in #1251
fixing aspect ratio on hires by @tjennings in #1249
Fix-build-container-action by @mauwii in #1274
handle all unicode characters by @damian0815 in #1276
adds models.user.yml to .gitignore by @JakeHL in #1281
remove debug branch, set fail-fast to false by @mauwii in #1284
Protect-secrets-on-pr by @mauwii in #1285
Web UI: Adds initial inpainting implementation by @psychedelicious in #1225
fix environment-mac.yml - tested on x64 and arm64 by @mauwii in #1289
Use proper authentication to download model by @mauwii in #1287
Prevent indexing error for mode RGB by @spezialspezial in #1294
Integrate sd-v1-5 model into test matrix (easily expandable), remove unecesarry caches by @mauwii in #1293
add --no-interactive to configure_invokeai step by @mauwii in #1302
1-click installer and updater. Uses micromamba to install git and conda into a contained environment (if necessary) before running the normal installation script by @cmdr2 in #1253
configure_invokeai.py script downloads the weight files by @lstein in #1290

v2.0.1 (13 October 2022)

fix noisy images at high step count when using k* samplers
dream.py script now calls invoke.py module directly rather than via a new python process (which could break the environment)

v2.0.0 (9 October 2022)

dream.py script renamed invoke.py. A dream.py script wrapper remains for backward compatibility.
Completely new WebGUI - launch with python3 scripts/invoke.py --web
Support for inpainting and outpainting
img2img runs on all k* samplers
Support for negative prompts
Support for CodeFormer face reconstruction
Support for Textual Inversion on Macintoshes
Support in both WebGUI and CLI for post-processing of previously-generated images using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas), and "embiggen" upscaling. See the !fix command.
New --hires option on invoke> line allows larger images to be created without duplicating elements, at the cost of some performance.
New --perlin and --threshold options allow you to add and control variation during image generation (see Thresholding and Perlin Noise Initialization)
Extensive metadata now written into PNG files, allowing reliable regeneration of images and tweaking of previous settings.
Command-line completion in invoke.py now works on Windows, Linux and Mac platforms.
Improved command-line completion behavior New commands added:
- List command-line history with !history
- Search command-line history with !search
- Clear history with !clear
Deprecated --full_precision / -F. Simply omit it and invoke.py will auto configure. To switch away from auto use the new flag like --precision=float32.

v1.14 (11 September 2022)

Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
Full support for Apple hardware with M1 or M2 chips.
Add "seamless mode" for circular tiling of image. Generates beautiful effects. (prixt).
Inpainting support.
Improved web server GUI.
Lots of code and documentation cleanups.

v1.13 (3 September 2022)

Support image variations (see VARIATIONS (Kevin Gibbons and many contributors and reviewers)
Supports a Google Colab notebook for a standalone server running on Google hardware Arturo Mendivil
WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling Kevin Gibbons
WebUI supports incremental display of in-progress images during generation Kevin Gibbons
A new configuration file scheme that allows new models (including upcoming stable-diffusion-v1.5) to be added without altering the code. (David Wager)
Can specify --grid on invoke.py command line as the default.
Miscellaneous internal bug and stability fixes.
Works on M1 Apple hardware.
Multiple bug fixes.

v1.12 (28 August 2022)

Improved file handling, including ability to read prompts from standard input. (kudos to Yunsaki
The web server is now integrated with the invoke.py script. Invoke by adding --web to the invoke.py command arguments.
Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically enabled if the GFPGAN directory is located as a sibling to Stable Diffusion. VRAM requirements are modestly reduced. Thanks to both Blessedcoolant and Oceanswave for their work on this.
You can now swap samplers on the invoke> command line. Blessedcoolant

v1.11 (26 August 2022)

NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to Oceanswave
You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc. Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch.
Variant generation support temporarily disabled pending more general solution.
Created a feature branch named yunsaki-morphing-invoke which adds experimental support for iteratively modifying the prompt and its parameters. Please seePull Request #86 for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified significantly.

v1.10 (25 August 2022)

A barebones but fully functional interactive web server for online generation of txt2img and img2img.

v1.09 (24 August 2022)

A new -v option allows you to generate multiple variants of an initial image in img2img mode. (kudos to Oceanswave. See this discussion in the PR for examples and details on use)
Added ability to personalize text to image generation (kudos to Oceanswave and nicolai256)
Enabled all of the samplers from k_diffusion

v1.08 (24 August 2022)

Escape single quotes on the invoke> command before trying to parse. This avoids parse errors.
Removed instruction to get Python3.8 as first step in Windows install. Anaconda3 does it for you.
Added bounds checks for numeric arguments that could cause crashes.
Cleaned up the copyright and license agreement files.

v1.07 (23 August 2022)

Image filenames will now never fill gaps in the sequence, but will be assigned the next higher name in the chosen directory. This ensures that the alphabetic and chronological sort orders are the same.

v1.06 (23 August 2022)

Added weighted prompt support contributed by xraxra
Example of using weighted prompts to tweak a demonic figure contributed by bmaltais

v1.05 (22 August 2022 - after the drop)

Filenames now use the following formats: 000010.95183149.png -- Two files produced by the same command (e.g. -n2), 000010.26742632.png -- distinguished by a different seed.

000011.455191342.01.png -- Two files produced by the same command using 000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.

000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid can be regenerated with the indicated key
It should no longer be possible for one image to overwrite another
You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve the path of the output directory.

v1.04 (22 August 2022 - after the drop)

Updated README to reflect installation of the released weights.
Suppressed very noisy and inconsequential warning when loading the frozen CLIP tokenizer.

v1.03 (22 August 2022)

The original txt2img and img2img scripts from the CompViz repository have been moved into a subfolder named "orig_scripts", to reduce confusion.

v1.02 (21 August 2022)

A copy of the prompt and all of its switches and options is now stored in the corresponding image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py, or an image editor that allows you to explore the full metadata. Please run "conda env update" to load the k_lms dependencies!!

v1.01 (21 August 2022)

added k_lms sampling. Please run "conda env update" to load the k_lms dependencies!!
use half precision arithmetic by default, resulting in faster execution and lower memory requirements Pass argument --full_precision to invoke.py to get slower but more accurate image generation

26 KiB Raw Blame History

:octicons-log-16: Changelog

v2.3.0 (15 January 2023)

v2.2.4 (11 December 2022)

v2.2.3 (2 December 2022)

v2.2.2 (30 November 2022)

v2.2.0 (2 December 2022)

v2.1.3 (13 November 2022)

v2.1.0 (2 November 2022)

v2.0.1 (13 October 2022)

v2.0.0 (9 October 2022)

v1.14 (11 September 2022)

v1.13 (3 September 2022)

v1.12 (28 August 2022)

v1.11 (26 August 2022)

v1.10 (25 August 2022)

v1.09 (24 August 2022)

v1.08 (24 August 2022)

v1.07 (23 August 2022)

v1.06 (23 August 2022)

v1.05 (22 August 2022 - after the drop)

v1.04 (22 August 2022 - after the drop)

v1.03 (22 August 2022)

v1.02 (21 August 2022)

v1.01 (21 August 2022)

Links

26 KiB

Raw Blame History