Commit graph

71 commits

Author SHA1 Message Date
Pierre Chapuis c421cfd56c add a test for IP-Adapter + ControlNet 2023-09-13 14:24:53 +02:00
Pierre Chapuis cf9efb57c8 remove useless torch.no_grad() contexts 2023-09-13 11:14:09 +02:00
Cédric Deltheil eea340c6c4 add support for SDXL IP-Adapter
This only supports the latest SDXL IP-Adapter release (2023.9.8) which
builds upon the ViT-H/14 CLIP image encoder.
2023-09-12 18:00:39 +02:00
Cédric Deltheil f4e9707297 sdxl test: refreshed reference image
The former one was generated using SDXL 0.9 vs 1.0. The new one has been
generated with diffusers:

    import torch
    from diffusers import StableDiffusionXLPipeline, DDIMScheduler

    noise_scheduler = DDIMScheduler(
        num_train_timesteps=1000,
        beta_start=0.00085,
        beta_end=0.012,
        beta_schedule="scaled_linear",
        clip_sample=False,
        set_alpha_to_one=False,
        steps_offset=1,
    )

    base_model_path = "/path/to/stabilityai/stable-diffusion-xl-base-1.0"

    device = "cuda"
    prompt = "a cute cat, detailed high-quality professional image"
    negative_prompt = "lowres, bad anatomy, bad hands, cropped, worst quality"
    seed = 2

    pipe = StableDiffusionXLPipeline.from_pretrained(base_model_path, scheduler=noise_scheduler, torch_dtype=torch.float16, add_watermarker=False)
    pipe = pipe.to(device)
    generator = torch.Generator(device).manual_seed(seed)
    images = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=30, generator=generator).images
2023-09-12 10:59:26 +02:00
Cédric Deltheil 0e38928c8d sdxl test: add missing torch no_grad 2023-09-12 10:59:26 +02:00
Pierre Chapuis be54cfc016 fix weight loading for float16 LoRAs 2023-09-11 16:14:19 +02:00
Cédric Deltheil e5425e2968 make IP-Adapter generic for SD1 and SDXL 2023-09-08 16:38:01 +02:00
limiteinductive 2786117469 implement SDXL + e2e test on random init 2023-09-07 18:34:42 +02:00
Cédric Deltheil c55917e293 add IP-Adapter support for SD 1.5
Official repo: https://github.com/tencent-ailab/IP-Adapter
2023-09-06 15:12:48 +02:00
Cédric Deltheil d4dd45fd4d use Module's load_from_safetensors
Instead of manual calls to load_state_dict
2023-09-06 15:06:51 +02:00
Pierre Chapuis 4388968ad3 Update tests/e2e/test_diffusion.py
Co-authored-by: Cédric Deltheil <355031+deltheil@users.noreply.github.com>
2023-09-06 11:49:55 +02:00
Pierre Chapuis 864937a776 support injecting several LoRAs simultaneously 2023-09-06 11:49:55 +02:00
Cédric Deltheil b933fabf31 unet: get rid of clip_embedding attribute for SD1
It is implicitly defined by the underlying cross-attention layer. This
also makes it consistent with SDXL.
2023-09-01 19:23:33 +02:00
Pierre Chapuis 73813310d0 rename SelfAttentionInjection to ReferenceOnlyControl and vice-versa 2023-09-01 17:29:48 +02:00
Pierre Chapuis 0f476ea18b make high-level adapters Adapters
This generalizes the Adapter abstraction to higher-level
constructs such as high-level LoRA (targeting e.g. the
SD UNet), ControlNet and Reference-Only Control.

Some adapters now work by adapting child models with
"sub-adapters" that they inject / eject when needed.
2023-08-31 10:57:18 +02:00
Pierre Chapuis 18c84c7b72 shorter import paths 2023-08-29 16:57:40 +02:00
Doryan Kaced 3680f9d196 Add support for learned concepts e.g. via textual inversion 2023-08-28 10:37:39 +02:00
limiteinductive 92a21bc21e refactor latent_diffusion module 2023-08-25 12:30:20 +02:00
Pierre Chapuis 1065dfe10b add empty __init__.py files to make pytest happy
(otherwise it wants unique file basenames)
2023-08-23 17:49:59 +02:00
Pierre Chapuis 97b162d9a0 add InformativeDrawings
https://github.com/carolineec/informative-drawings

This is the preprocessor for the Lineart ControlNet.
2023-08-16 12:29:09 +02:00
Cédric Deltheil 48f674c433 initial commit 2023-08-04 15:28:41 +02:00