Add sd3 support by leejet · Pull Request #298 · leejet/stable-diffusion.cpp

leejet · 2024-07-07T10:09:09Z

How to Use

Pull the latest code and build.
Download sd3_medium_incl_clips_t5xxlfp16.safetensors from https://huggingface.co/stabilityai/stable-diffusion-3-medium.
Try prompts you like, for example:

./bin/sd -m ../models/sd3_medium_incl_clips_t5xxlfp16.safetensors -H 1024 -W 1024 -p 'a lovely cat holding a sign says \"Stable diffusion 3\"' --cfg-scale 4.5 --sampling-method euler -v

Green-Sky · 2024-07-07T11:12:26Z

Heck yea. gonna test later when I remember.

btw, for some reason it shows 2mil new lines of code, but the diff certainly does not

how did you manage to glitch this?

edit: nvm, call me blind, its the vocab.hpp. do we really need it as code in the repo? also the name "vocab" is probably too generic.

leejet · 2024-07-07T12:35:45Z

Heck yea. gonna test later when I remember.

btw, for some reason it shows 2mil new lines of code, but the diff certainly does not how did you manage to glitch this?

edit: nvm, call me blind, its the vocab.hpp. do we really need it as code in the repo? also the name "vocab" is probably too generic.

vocab.hpp contains the vocabulary of clip and t5's tokenizer. Almost all sd models don't have this part, so I put it directly in the binary file so that we don't have to use an extra argument to specify the vocabulary file to use.

Green-Sky · 2024-07-08T07:58:20Z

did a malformed 512x512, so defaults, run:
teddy bear with SD3 on a sign

Green-Sky · 2024-07-08T08:02:46Z

question, what does the second text conditioning do?

[DEBUG] stable-diffusion.cpp:477  - finished loaded file
[DEBUG] stable-diffusion.cpp:1261 - txt2img 1024x1024
[DEBUG] stable-diffusion.cpp:1014 - prompt after extract and remove lora: "teddy bear with SD3 on a sign"
[INFO ] stable-diffusion.cpp:560  - Attempting to apply 0 LoRAs
[INFO ] stable-diffusion.cpp:1019 - apply_loras completed, taking 0.00s
[DEBUG] conditioner.hpp:687  - parse 'teddy bear with SD3 on a sign' to [['teddy bear with SD3 on a sign', 1], ]
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] t5.hpp:397  - token length: 77
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 1.40 MB(RAM)
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 2.33 MB(RAM)
[DEBUG] ggml_extend.hpp:932  - t5 compute buffer size: 11.94 MB(RAM)
[DEBUG] conditioner.hpp:930  - computing condition graph completed, taking 3815 ms
[DEBUG] conditioner.hpp:687  - parse '' to [['', 1], ]
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] t5.hpp:397  - token length: 77
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 1.40 MB(RAM)
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 2.33 MB(RAM)
[DEBUG] ggml_extend.hpp:932  - t5 compute buffer size: 11.94 MB(RAM)
[DEBUG] conditioner.hpp:930  - computing condition graph completed, taking 3797 ms
[INFO ] stable-diffusion.cpp:1143 - get_learned_condition completed, taking 7614 ms

Green-Sky · 2024-07-08T09:32:19Z

ok did a 1024x1024 with euler sampler

$ result/bin/sd -m ../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors -p "teddy bear with SD3 on a sign" -t 12 -W 1024 -H 1024 --cfg-scale 4.5 -v --sampling-method euler

Details

Option:
    n_threads:         12
    mode:              txt2img
    model_path:        ../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors
    wtype:             unspecified
    vae_path:
    taesd_path:
    esrgan_path:
    controlnet_path:
    embeddings_path:
    stacked_id_embeddings_path:
    input_id_images_path:
    style ratio:       20.00
    normzalize input image :  false
    output_path:       output.png
    init_img:
    control_image:
    clip on cpu:       false
    controlnet cpu:    false
    vae decoder on cpu:false
    strength(control): 0.90
    prompt:            teddy bear with SD3 on a sign
    negative_prompt:
    min_cfg:           1.00
    cfg_scale:         4.50
    clip_skip:         -1
    width:             1024
    height:            1024
    sample_method:     euler
    schedule:          default
    sample_steps:      20
    strength(img2img): 0.75
    rng:               cuda
    seed:              42
    batch_count:       1
    vae_tiling:        false
    upscale_repeats:   1
System Info:
    BLAS = 0
    SSE3 = 1
    AVX = 1
    AVX2 = 1
    AVX512 = 0
    AVX512_VBMI = 0
    AVX512_VNNI = 0
    FMA = 1
    NEON = 0
    ARM_FMA = 0
    F16C = 1
    FP16_VA = 0
    WASM_SIMD = 0
    VSX = 0
[DEBUG] stable-diffusion.cpp:157  - Using CPU backend
[INFO ] stable-diffusion.cpp:167  - loading model from '../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors'
[INFO ] model.cpp:737  - load ../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors using safetensors format
[DEBUG] model.cpp:803  - init from '../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors'
[INFO ] stable-diffusion.cpp:190  - Stable Diffusion 3 2B
[INFO ] stable-diffusion.cpp:196  - Stable Diffusion weight type: f16
[DEBUG] stable-diffusion.cpp:197  - ggml tensor size = 432 bytes
[DEBUG] clip.hpp:171  - vocab size: 49408
[DEBUG] clip.hpp:182  -  trigger word img already in vocab
[DEBUG] clip.hpp:171  - vocab size: 49408
[DEBUG] clip.hpp:182  -  trigger word img already in vocab
[DEBUG] ggml_extend.hpp:980  - clip params backend buffer size =  235.06 MB(RAM) (196 tensors)
[DEBUG] ggml_extend.hpp:980  - clip params backend buffer size =  1329.29 MB(RAM) (517 tensors)
[DEBUG] ggml_extend.hpp:980  - t5 params backend buffer size =  9083.77 MB(RAM) (219 tensors)
[DEBUG] ggml_extend.hpp:980  - mmdit params backend buffer size =  4086.83 MB(RAM) (491 tensors)
[DEBUG] ggml_extend.hpp:980  - vae params backend buffer size =  94.57 MB(RAM) (138 tensors)
[DEBUG] stable-diffusion.cpp:319  - loading weights
[DEBUG] model.cpp:1389 - loading tensors from ../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors
[INFO ] model.cpp:1535 - unknown tensor 'text_encoders.t5xxl.transformer.encoder.embed_tokens.weight | f16 | 2 [4096, 32128, 1, 1, 1]' in model file
[INFO ] stable-diffusion.cpp:403  - total params memory size = 14829.53MB (VRAM 0.00MB, RAM 14829.53MB): clip 10648.13MB(RAM), unet 4086.83MB(RAM), vae 94.57MB(RAM), controlnet 0.00MB(VRAM), pmid 0.00MB(RAM)
[INFO ] stable-diffusion.cpp:422  - loading model from '../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors' completed, taking 17.16s
[INFO ] stable-diffusion.cpp:436  - running in FLOW mode
[DEBUG] stable-diffusion.cpp:477  - finished loaded file
[DEBUG] stable-diffusion.cpp:1261 - txt2img 1024x1024
[DEBUG] stable-diffusion.cpp:1014 - prompt after extract and remove lora: "teddy bear with SD3 on a sign"
[INFO ] stable-diffusion.cpp:560  - Attempting to apply 0 LoRAs
[INFO ] stable-diffusion.cpp:1019 - apply_loras completed, taking 0.00s
[DEBUG] conditioner.hpp:687  - parse 'teddy bear with SD3 on a sign' to [['teddy bear with SD3 on a sign', 1], ]
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] t5.hpp:397  - token length: 77
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 1.40 MB(RAM)
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 2.33 MB(RAM)
[DEBUG] ggml_extend.hpp:932  - t5 compute buffer size: 11.94 MB(RAM)
[DEBUG] conditioner.hpp:930  - computing condition graph completed, taking 3294 ms
[DEBUG] conditioner.hpp:687  - parse '' to [['', 1], ]
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] t5.hpp:397  - token length: 77
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 1.40 MB(RAM)
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 2.33 MB(RAM)
[DEBUG] ggml_extend.hpp:932  - t5 compute buffer size: 11.94 MB(RAM)
[DEBUG] conditioner.hpp:930  - computing condition graph completed, taking 3302 ms
[INFO ] stable-diffusion.cpp:1143 - get_learned_condition completed, taking 6599 ms
[INFO ] stable-diffusion.cpp:1164 - sampling using Euler method
[INFO ] stable-diffusion.cpp:1168 - generating image: 1/1 - seed 42
[DEBUG] ggml_extend.hpp:932  - mmdit compute buffer size: 1784.58 MB(RAM)
  |==================================================| 20/20 - 89.26s/it
[INFO ] stable-diffusion.cpp:1199 - sampling completed, taking 1793.16s
[INFO ] stable-diffusion.cpp:1207 - generating 1 latent images completed, taking 1794.48s
[INFO ] stable-diffusion.cpp:1210 - decoding 1 latents
[DEBUG] ggml_extend.hpp:932  - vae compute buffer size: 6656.00 MB(RAM)
[DEBUG] stable-diffusion.cpp:884  - computing vae [mode: DECODE] graph completed, taking 62.70s
[INFO ] stable-diffusion.cpp:1220 - latent 1 decoded, taking 62.70s
[INFO ] stable-diffusion.cpp:1224 - decode_first_stage completed, taking 62.70s
[INFO ] stable-diffusion.cpp:1324 - txt2img completed in 1863.80s
save result image to 'output.png'

The 89sec/iteration on cpu is pretty heavy, but it works. Also considering their size, the text encoders are fast too.

Green-Sky · 2024-07-08T09:46:26Z

Running with cuda is very fast, however the vae is once again not fitting into vram and crashes.

[DEBUG] stable-diffusion.cpp:147  - Using CUDA backend
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:   no
ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes
ggml_cuda_init: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 2070, compute capability 7.5, VMM: yes

[INFO ] stable-diffusion.cpp:229  - set clip_on_cpu to true
[INFO ] stable-diffusion.cpp:232  - CLIP: Using CPU backend

[DEBUG] ggml_extend.hpp:980  - clip params backend buffer size =  235.06 MB(RAM) (196 tensors)
[DEBUG] ggml_extend.hpp:980  - clip params backend buffer size =  1329.29 MB(RAM) (517 tensors)
[DEBUG] ggml_extend.hpp:980  - t5 params backend buffer size =  9083.77 MB(RAM) (219 tensors)
[DEBUG] ggml_extend.hpp:980  - mmdit params backend buffer size =  4086.83 MB(VRAM) (491 tensors)
[DEBUG] ggml_extend.hpp:980  - vae params backend buffer size =  94.57 MB(VRAM) (138 tensors)

Details

$ result/bin/sd -m ../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors -p "teddy bear with SD3 on a sign" -t 12 -W 1024 -H 1024 --cfg-scale 4.5 -v --sampling-method euler
Option:
    n_threads:         12
    mode:              txt2img
    model_path:        ../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors
    wtype:             unspecified
    vae_path:
    taesd_path:
    esrgan_path:
    controlnet_path:
    embeddings_path:
    stacked_id_embeddings_path:
    input_id_images_path:
    style ratio:       20.00
    normzalize input image :  false
    output_path:       output.png
    init_img:
    control_image:
    clip on cpu:       false
    controlnet cpu:    false
    vae decoder on cpu:false
    strength(control): 0.90
    prompt:            teddy bear with SD3 on a sign
    negative_prompt:
    min_cfg:           1.00
    cfg_scale:         4.50
    clip_skip:         -1
    width:             1024
    height:            1024
    sample_method:     euler
    schedule:          default
    sample_steps:      20
    strength(img2img): 0.75
    rng:               cuda
    seed:              42
    batch_count:       1
    vae_tiling:        false
    upscale_repeats:   1
System Info:
    BLAS = 1
    SSE3 = 1
    AVX = 1
    AVX2 = 1
    AVX512 = 0
    AVX512_VBMI = 0
    AVX512_VNNI = 0
    FMA = 1
    NEON = 0
    ARM_FMA = 0
    F16C = 1
    FP16_VA = 0
    WASM_SIMD = 0
    VSX = 0
[DEBUG] stable-diffusion.cpp:147  - Using CUDA backend
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:   no
ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes
ggml_cuda_init: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 2070, compute capability 7.5, VMM: yes
[INFO ] stable-diffusion.cpp:167  - loading model from '../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors'
[INFO ] model.cpp:737  - load ../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors using safetensors format
[DEBUG] model.cpp:803  - init from '../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors'
[INFO ] stable-diffusion.cpp:190  - Stable Diffusion 3 2B
[INFO ] stable-diffusion.cpp:196  - Stable Diffusion weight type: f16
[DEBUG] stable-diffusion.cpp:197  - ggml tensor size = 432 bytes
[INFO ] stable-diffusion.cpp:229  - set clip_on_cpu to true
[INFO ] stable-diffusion.cpp:232  - CLIP: Using CPU backend
[DEBUG] clip.hpp:171  - vocab size: 49408
[DEBUG] clip.hpp:182  -  trigger word img already in vocab
[DEBUG] clip.hpp:171  - vocab size: 49408
[DEBUG] clip.hpp:182  -  trigger word img already in vocab
[DEBUG] ggml_extend.hpp:980  - clip params backend buffer size =  235.06 MB(RAM) (196 tensors)
[DEBUG] ggml_extend.hpp:980  - clip params backend buffer size =  1329.29 MB(RAM) (517 tensors)
[DEBUG] ggml_extend.hpp:980  - t5 params backend buffer size =  9083.77 MB(RAM) (219 tensors)
[DEBUG] ggml_extend.hpp:980  - mmdit params backend buffer size =  4086.83 MB(VRAM) (491 tensors)
[DEBUG] ggml_extend.hpp:980  - vae params backend buffer size =  94.57 MB(VRAM) (138 tensors)
[DEBUG] stable-diffusion.cpp:319  - loading weights
[DEBUG] model.cpp:1389 - loading tensors from ../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors
[INFO ] model.cpp:1535 - unknown tensor 'text_encoders.t5xxl.transformer.encoder.embed_tokens.weight | f16 | 2 [4096, 32128, 1, 1, 1]' in model file
[INFO ] stable-diffusion.cpp:403  - total params memory size = 14829.53MB (VRAM 4181.40MB, RAM 10648.13MB): clip 10648.13MB(RAM), unet 4086.83MB(VRAM), vae 94.57MB(VRAM), controlnet 0.00MB(VRAM), pmid 0.00MB(RAM)
[INFO ] stable-diffusion.cpp:422  - loading model from '../stable-diffusion-webui/models/Stable-diffusion/sd3_medium_incl_clips_t5xxlfp16.safetensors' completed, taking 10.88s
[INFO ] stable-diffusion.cpp:436  - running in FLOW mode
[DEBUG] stable-diffusion.cpp:477  - finished loaded file
[DEBUG] stable-diffusion.cpp:1261 - txt2img 1024x1024
[DEBUG] stable-diffusion.cpp:1014 - prompt after extract and remove lora: "teddy bear with SD3 on a sign"
[INFO ] stable-diffusion.cpp:560  - Attempting to apply 0 LoRAs
[INFO ] stable-diffusion.cpp:1019 - apply_loras completed, taking 0.00s
[DEBUG] conditioner.hpp:687  - parse 'teddy bear with SD3 on a sign' to [['teddy bear with SD3 on a sign', 1], ]
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] t5.hpp:397  - token length: 77
ggml_gallocr_reserve_n: reallocating CPU buffer from size 0.00 MiB to 1.40 MiB
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 1.40 MB(RAM)
ggml_gallocr_reserve_n: reallocating CPU buffer from size 0.00 MiB to 2.33 MiB
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 2.33 MB(RAM)
ggml_gallocr_reserve_n: reallocating CPU buffer from size 0.00 MiB to 11.94 MiB
[DEBUG] ggml_extend.hpp:932  - t5 compute buffer size: 11.94 MB(RAM)
[DEBUG] conditioner.hpp:930  - computing condition graph completed, taking 5070 ms
[DEBUG] conditioner.hpp:687  - parse '' to [['', 1], ]
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] clip.hpp:311  - token length: 77
[DEBUG] t5.hpp:397  - token length: 77
ggml_gallocr_reserve_n: reallocating CPU buffer from size 0.00 MiB to 1.40 MiB
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 1.40 MB(RAM)
ggml_gallocr_reserve_n: reallocating CPU buffer from size 0.00 MiB to 2.33 MiB
[DEBUG] ggml_extend.hpp:932  - clip compute buffer size: 2.33 MB(RAM)
ggml_gallocr_reserve_n: reallocating CPU buffer from size 0.00 MiB to 11.94 MiB
[DEBUG] ggml_extend.hpp:932  - t5 compute buffer size: 11.94 MB(RAM)
[DEBUG] conditioner.hpp:930  - computing condition graph completed, taking 5045 ms
[INFO ] stable-diffusion.cpp:1143 - get_learned_condition completed, taking 10119 ms
[INFO ] stable-diffusion.cpp:1164 - sampling using Euler method
[INFO ] stable-diffusion.cpp:1168 - generating image: 1/1 - seed 42
ggml_gallocr_reserve_n: reallocating CUDA0 buffer from size 0.00 MiB to 1786.11 MiB
[DEBUG] ggml_extend.hpp:932  - mmdit compute buffer size: 1786.11 MB(VRAM)
  |==================================================| 20/20 - 4.09s/it
[INFO ] stable-diffusion.cpp:1199 - sampling completed, taking 82.10s
[INFO ] stable-diffusion.cpp:1207 - generating 1 latent images completed, taking 83.02s
[INFO ] stable-diffusion.cpp:1210 - decoding 1 latents
ggml_gallocr_reserve_n: reallocating CUDA0 buffer from size 0.00 MiB to 6656.00 MiB
[DEBUG] ggml_extend.hpp:932  - vae compute buffer size: 6656.00 MB(VRAM)
CUDA error: out of memory
  current device: 0, in function alloc at /build/k1y3zc6zgzlm78m3lslh1m453fn3gsmg-source/ggml/src/ggml-cuda.cu:357
  cuMemCreate(&handle, reserve_size, &prop, 0)
GGML_ASSERT: /build/k1y3zc6zgzlm78m3lslh1m453fn3gsmg-source/ggml/src/ggml-cuda.cu:100: !"CUDA error"
ptrace: Operation not permitted.
No stack.
The program is not being run.
Aborted (core dumped)

However, hardcoding vae_on_cpu to true makes it work with 4.10 s/it.

[INFO ] stable-diffusion.cpp:255  - VAE Autoencoder: Using CPU backend

[DEBUG] ggml_extend.hpp:932  - vae compute buffer size: 6656.00 MB(RAM)
[DEBUG] stable-diffusion.cpp:884  - computing vae [mode: DECODE] graph completed, taking 85.62s
[INFO ] stable-diffusion.cpp:1220 - latent 1 decoded, taking 85.62s
[INFO ] stable-diffusion.cpp:1224 - decode_first_stage completed, taking 85.62s
[INFO ] stable-diffusion.cpp:1324 - txt2img completed in 179.18s

Green-Sky · 2024-07-08T10:55:46Z

taesd3 does not work:

[INFO ] tae.hpp:204  - loading taesd from '../stable-diffusion-webui/models/VAE-approx/taesd3_diffusion_pytorch_model.safetensors', decode_only = true
[DEBUG] ggml_extend.hpp:980  - taesd params backend buffer size =   4.67 MB(VRAM) (134 tensors)
[INFO ] model.cpp:737  - load ../stable-diffusion-webui/models/VAE-approx/taesd3_diffusion_pytorch_model.safetensors using safetensors format
[DEBUG] model.cpp:803  - init from '../stable-diffusion-webui/models/VAE-approx/taesd3_diffusion_pytorch_model.safetensors'
[DEBUG] model.cpp:1389 - loading tensors from ../stable-diffusion-webui/models/VAE-approx/taesd3_diffusion_pytorch_model.safetensors
[ERROR] model.cpp:1544 - tensor 'decoder.layers.0.weight' has wrong shape in model file: got [3, 3, 16, 64], expected [3, 3, 4, 64]
[WARN ] model.cpp:1451 - process tensor failed: 'decoder.layers.0.weight'
[ERROR] model.cpp:1560 - load tensors from file failed
[ERROR] tae.hpp:222  - load tae tensors from model loader failed
new_sd_ctx_t failed

edit: also loras dont work yet. (tried flash-diffusion)

FSSRepo · 2024-07-08T13:32:18Z

@leejet hello!, in diffusion_model.hpp there is a typo DiffuisionModel class name

leejet · 2024-07-28T07:41:22Z

@leejet hello!, in diffusion_model.hpp there is a typo DiffuisionModel class name

Fixed!

leejet · 2024-07-28T07:42:57Z

The support for taesd3 and lora will be added later in a separate PR. This PR seems to have all its functionalities completed, so I'll merge it now.

leejet added 3 commits July 7, 2024 17:54

feat: add sd3 support

7fd9746

remove some debug codes

adcfa6e

avoid build failures in macos

3f3c328

leejet added 2 commits July 7, 2024 20:54

update README.md

4cc7840

update example image

984a772

leejet mentioned this pull request Jul 7, 2024

Support for SD3 #287

Closed

airMeng mentioned this pull request Jul 25, 2024

SYCL support #308

Closed

fix typo

cce01e9

leejet merged commit 73c2176 into master Jul 28, 2024

leejet deleted the sd3 branch September 16, 2025 15:35

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Add sd3 support - #298

Add sd3 support#298
leejet merged 6 commits into
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leejet commented Jul 7, 2024

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leejet commented Jul 7, 2024

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