Commit Graph

48 Commits

Author SHA1 Message Date
233869b56a Mac MPS FP16 fixes
This PR is to allow FP16 precision to work on Macs with MPS. In addition, it centralizes the torch fixes/workarounds
required for MPS into a new backend utility file `mps_fixes.py`. This is conditionally imported in `api_app.py`/`cli_app.py`.

Many MANY thanks to StAlKeR7779 for patiently working to debug and fix these issues.
2023-07-04 18:10:53 -04:00
2465c7987b Revert "restore 3.9 compatibility by replacing | with Union[]"
This reverts commit 76bafeb99e.
2023-07-03 10:56:41 -04:00
76bafeb99e restore 3.9 compatibility by replacing | with Union[] 2023-07-03 10:55:04 -04:00
a01998d095 Remove more old logic 2023-06-19 15:57:28 +10:00
7b35162b9e Remove old logic except for inpaint, add support for lora and ti to inpaint node 2023-06-19 15:57:28 +10:00
c9ae26a176 Merge branch 'main' into lstein/new-model-manager 2023-06-13 23:37:52 +03:00
68405910ba Upgrade to Diffusers 0.17.0 2023-06-08 04:42:52 +12:00
98773b20ac merge with main 2023-06-01 18:09:49 -04:00
a91dee87d0 Added support for ControlNet and MultiControlNet to legacy non-nodal Txt2Img in backend/generator. Although backend/generator will likely disappear by v3.x, right now they are very useful for testing core ControlNet and MultiControlNet functionality while node codebase is rapidly evolving. 2023-05-26 21:44:00 -04:00
5f8f51436a merge with main; fix conflicts 2023-05-25 22:40:45 -04:00
fb0b63c580 fix(nodes): fix seam painting
The problem was the same seed was getting used for the seam painting pass, causing the fried look.

Same issue as if you do img2img on a txt2img with the same seed/prompt.

Thanks to @hipsterusername for teaming up to debug this. We got pretty deep into the weeds.
2023-05-25 00:58:03 +10:00
baf5451fa0 Merge branch 'main' into lstein/new-model-manager 2023-05-13 22:01:34 -04:00
8a836247c8 Add DPMPP Single, Euler Karras and DPMPP2 Multi Karras Schedulers 2023-05-12 02:23:33 +12:00
9a383e456d Codesplit SCHEDULER_MAP for reusage 2023-05-12 00:40:03 +12:00
3ffff023b2 Add missing key to scheduler_map
It was breaking coz the sampler was not being reset. So needs a key on each. Will simplify this later.
2023-05-12 00:08:50 +12:00
d1029138d2 Default to DDIM if scheduler is missing 2023-05-11 22:54:35 +12:00
06b5800d28 Add UniPC Scheduler 2023-05-11 22:43:18 +12:00
8ad8c5c67a resolve conflicts with main 2023-05-11 00:19:20 -04:00
49db6f4fac fix(nodes): fix trivial typing issues 2023-05-11 11:55:51 +10:00
206e6b1730 feat(nodes): wip inpaint node 2023-05-11 11:55:51 +10:00
e0214a32bc mostly ported to new manager API; needs testing 2023-05-06 00:44:12 -04:00
8db20e0d95 rename log to logger throughout 2023-04-29 09:43:40 -04:00
0b0e6fe448 convert remainder of print() to log.info() 2023-04-14 15:15:14 -04:00
5fe38f7c88 fix(backend): simple typing fixes 2023-03-26 17:07:03 +11:00
f329fddab9 make step_callback work again in generate() call
This PR fixes #2951 and restores the step_callback argument in the
refactored generate() method. Note that this issue states that
"something is still wrong because steps and step are zero." However,
I think this is confusion over the call signature of the callback, which
since the diffusers merge has been `callback(state:PipelineIntermediateState)`

This is the test script that I used to determine that `step` is being passed
correctly:

```

from pathlib import Path
from invokeai.backend import ModelManager, PipelineIntermediateState
from invokeai.backend.globals import global_config_dir
from invokeai.backend.generator import Txt2Img

def my_callback(state:PipelineIntermediateState, total_steps:int):
    print(f'callback(step={state.step}/{total_steps})')

def main():
    manager = ModelManager(Path(global_config_dir()) / "models.yaml")
    model = manager.get_model('stable-diffusion-1.5')
    print ('=== TXT2IMG TEST ===')
    steps=30
    output = next(Txt2Img(model).generate(prompt='banana sushi',
                                          iterations=None,
                                          steps=steps,
                                          step_callback=lambda x: my_callback(x,steps)
                                          )
                  )
    print(f'image={output.image}, seed={output.seed}, steps={output.params.steps}')

if __name__=='__main__':
    main()
```
2023-03-24 09:32:47 +11:00
b194180f76 feat(backend): make fast latents method static 2023-03-16 20:03:08 +11:00
0a761d7c43 fix(inpaint): Seam painting being broken 2023-03-15 00:00:08 +13:00
596ba754b1 Removed seed from get_make_image. 2023-03-13 08:15:46 -05:00
b980e563b9 Fix bug #2931 2023-03-13 08:11:09 -05:00
d612f11c11 initialize InvokeAIGenerator object with model, not manager 2023-03-11 09:06:46 -05:00
250b0ab182 add seamless tiling support 2023-03-11 08:33:23 -05:00
675dd12b6c add attention map images to output object 2023-03-11 08:07:01 -05:00
7e76eea059 add embiggen, remove complicated constructor 2023-03-11 07:50:39 -05:00
95954188b2 remove factory pattern
Factory pattern is now removed. Typical usage of the InvokeAIGenerator is now:

```
from invokeai.backend.generator import (
    InvokeAIGeneratorBasicParams,
    Txt2Img,
    Img2Img,
    Inpaint,
)
    params = InvokeAIGeneratorBasicParams(
        model_name = 'stable-diffusion-1.5',
        steps = 30,
        scheduler = 'k_lms',
        cfg_scale = 8.0,
        height = 640,
        width = 640
        )
    print ('=== TXT2IMG TEST ===')
    txt2img = Txt2Img(manager, params)
    outputs = txt2img.generate(prompt='banana sushi', iterations=2)

    for i in outputs:
        print(f'image={output.image}, seed={output.seed}, model={output.params.model_name}, hash={output.model_hash}, steps={output.params.steps}')
```

The `params` argument is optional, so if you wish to accept default
parameters and selectively override them, just do this:

```
    outputs = Txt2Img(manager).generate(prompt='banana sushi',
                                        steps=50,
					scheduler='k_heun',
					model_name='stable-diffusion-2.1'
					)
```
2023-03-10 19:33:04 -05:00
c11e823ff3 remove unused _wrap_results 2023-03-09 16:30:06 -05:00
cde0b6ae8d Merge branch 'main' into refactor/nodes-on-generator 2023-03-09 01:52:45 -05:00
b679a6ba37 model manager defaults to consistent values of device and precision 2023-03-09 01:09:54 -05:00
5d37fa6e36 node-based txt2img working without generate 2023-03-09 00:18:29 -05:00
2db180d909 Make img2img strength 1 behave the same as txt2img (#2895)
* Fix img2img and inpainting code so a strength of 1 behaves the same as txt2img.

* Make generated images identical to their txt2img counterparts when strength is 1.
2023-03-08 22:50:16 +01:00
87789c1de8 add InvokeAIGenerator and InvokeAIGeneratorFactory classes 2023-03-07 23:52:53 -05:00
c703b60986 remove legacy ldm code 2023-03-04 18:16:59 -08:00
53c2c0f91d Update txt2img2img.py 2023-03-04 12:58:33 +11:00
1bfdd54810 Update txt2img2img.py 2023-03-04 11:23:21 +11:00
60a98cacef all vestiges of ldm.invoke removed 2023-03-03 01:02:00 -05:00
6a990565ff all files migrated; tweaks needed 2023-03-03 00:02:15 -05:00
3f0b0f3250 almost all of backend migrated; restoration next 2023-03-02 13:28:17 -05:00
850d1ee984 move models and modules under invokeai/backend/ldm 2023-03-01 18:24:18 -05:00
5b6c61fc75 move models and generator into backend 2023-02-28 08:32:11 -05:00