From ac54e0076052a196b7df961eb1f792c9ff4d7f22 Mon Sep 17 00:00:00 2001 From: leejet Date: Thu, 24 Oct 2024 21:58:03 +0800 Subject: [PATCH] feat: add sd3.5 support (#445) --- README.md | 22 +++--- assets/sd3.5_large.png | Bin 0 -> 1893605 bytes conditioner.hpp | 4 +- denoiser.hpp | 79 +++++++++++----------- docs/sd3.md | 20 ++++++ examples/cli/main.cpp | 29 +++++--- ggml_extend.hpp | 9 ++- mmdit.hpp | 148 +++++++++++++++++++++++++++++------------ model.cpp | 20 +++++- model.h | 1 + stable-diffusion.cpp | 42 +++++++----- stable-diffusion.h | 1 + vae.hpp | 2 +- 13 files changed, 250 insertions(+), 127 deletions(-) create mode 100644 assets/sd3.5_large.png create mode 100644 docs/sd3.md diff --git a/README.md b/README.md index 0fe607e2..c1ba396f 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ Inference of Stable Diffusion and Flux in pure C/C++ - Plain C/C++ implementation based on [ggml](https://github.com/ggerganov/ggml), working in the same way as [llama.cpp](https://github.com/ggerganov/llama.cpp) - Super lightweight and without external dependencies -- SD1.x, SD2.x, SDXL and SD3 support +- SD1.x, SD2.x, SDXL and [SD3/SD3.5](./docs/sd3.md) support - !!!The VAE in SDXL encounters NaN issues under FP16, but unfortunately, the ggml_conv_2d only operates under FP16. Hence, a parameter is needed to specify the VAE that has fixed the FP16 NaN issue. You can find it here: [SDXL VAE FP16 Fix](https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/blob/main/sdxl_vae.safetensors). - [Flux-dev/Flux-schnell Support](./docs/flux.md) @@ -197,23 +197,24 @@ usage: ./bin/sd [arguments] arguments: -h, --help show this help message and exit -M, --mode [MODEL] run mode (txt2img or img2img or convert, default: txt2img) - -t, --threads N number of threads to use during computation (default: -1). + -t, --threads N number of threads to use during computation (default: -1) If threads <= 0, then threads will be set to the number of CPU physical cores -m, --model [MODEL] path to full model --diffusion-model path to the standalone diffusion model --clip_l path to the clip-l text encoder - --t5xxl path to the the t5xxl text encoder. + --clip_g path to the clip-l text encoder + --t5xxl path to the the t5xxl text encoder --vae [VAE] path to vae --taesd [TAESD_PATH] path to taesd. Using Tiny AutoEncoder for fast decoding (low quality) --control-net [CONTROL_PATH] path to control net model - --embd-dir [EMBEDDING_PATH] path to embeddings. - --stacked-id-embd-dir [DIR] path to PHOTOMAKER stacked id embeddings. - --input-id-images-dir [DIR] path to PHOTOMAKER input id images dir. + --embd-dir [EMBEDDING_PATH] path to embeddings + --stacked-id-embd-dir [DIR] path to PHOTOMAKER stacked id embeddings + --input-id-images-dir [DIR] path to PHOTOMAKER input id images dir --normalize-input normalize PHOTOMAKER input id images - --upscale-model [ESRGAN_PATH] path to esrgan model. Upscale images after generate, just RealESRGAN_x4plus_anime_6B supported by now. + --upscale-model [ESRGAN_PATH] path to esrgan model. Upscale images after generate, just RealESRGAN_x4plus_anime_6B supported by now --upscale-repeats Run the ESRGAN upscaler this many times (default 1) --type [TYPE] weight type (f32, f16, q4_0, q4_1, q5_0, q5_1, q8_0, q2_k, q3_k, q4_k) - If not specified, the default is the type of the weight file. + If not specified, the default is the type of the weight file --lora-model-dir [DIR] lora model directory -i, --init-img [IMAGE] path to the input image, required by img2img --control-image [IMAGE] path to image condition, control net @@ -232,13 +233,13 @@ arguments: --steps STEPS number of sample steps (default: 20) --rng {std_default, cuda} RNG (default: cuda) -s SEED, --seed SEED RNG seed (default: 42, use random seed for < 0) - -b, --batch-count COUNT number of images to generate. + -b, --batch-count COUNT number of images to generate --schedule {discrete, karras, exponential, ays, gits} Denoiser sigma schedule (default: discrete) --clip-skip N ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer (default: -1) <= 0 represents unspecified, will be 1 for SD1.x, 2 for SD2.x --vae-tiling process vae in tiles to reduce memory usage --vae-on-cpu keep vae in cpu (for low vram) - --clip-on-cpu keep clip in cpu (for low vram). + --clip-on-cpu keep clip in cpu (for low vram) --control-net-cpu keep controlnet in cpu (for low vram) --canny apply canny preprocessor (edge detection) --color Colors the logging tags according to level @@ -253,6 +254,7 @@ arguments: # ./bin/sd -m ../models/sd_xl_base_1.0.safetensors --vae ../models/sdxl_vae-fp16-fix.safetensors -H 1024 -W 1024 -p "a lovely cat" -v # ./bin/sd -m ../models/sd3_medium_incl_clips_t5xxlfp16.safetensors -H 1024 -W 1024 -p 'a lovely cat holding a sign says \"Stable Diffusion CPP\"' --cfg-scale 4.5 --sampling-method euler -v # ./bin/sd --diffusion-model ../models/flux1-dev-q3_k.gguf --vae ../models/ae.sft --clip_l ../models/clip_l.safetensors --t5xxl ../models/t5xxl_fp16.safetensors -p "a lovely cat holding a sign says 'flux.cpp'" --cfg-scale 1.0 --sampling-method euler -v +# ./bin/sd -m ..\models\sd3.5_large.safetensors --clip_l ..\models\clip_l.safetensors --clip_g ..\models\clip_g.safetensors --t5xxl ..\models\t5xxl_fp16.safetensors -H 1024 -W 1024 -p 'a lovely cat holding a sign says \"Stable diffusion 3.5 Large\"' --cfg-scale 4.5 --sampling-method euler -v ``` Using formats of different precisions will yield results of varying quality. diff --git a/assets/sd3.5_large.png b/assets/sd3.5_large.png new file mode 100644 index 0000000000000000000000000000000000000000..b76b13225d06a4986ca36e748c5901183f041e4c GIT binary patch literal 1893605 zcmX`Sd0Z0t{|7$9a33O`-~|Ypni_(YnZ=YZuGz%kE2=-+X_M-{Z$0439Y;%*^}!e!ZX9yGl80DvcaO z1^|FIO_7!X09f=V79e8K&5-U)-~Vk^PRUxSRhO!l7OX5NT>+>$B|ok%C|S$NQ?KM` zek{o^URK0Wb5;}=E#s_EuU)|jpR-b(TT;NuFD@)xwW9dPWgJobSWddSw5TAQJZEKr zc11ErD2U~x%BONx`FZ%!X%_%6zN6!()a^@7T zLysf~go$PU_Z7>T`D1=TNit_eK6>^KCI9yq@hjAY=#4I0@nh+VSWd>QsmYwYRrzZ4 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