* add wan vace t2v support
* add --vace-strength option
* add vace i2v support
* fix the processing of vace_context
* add vace v2v support
* update docs
* kontext: support ref images indices
* lora: support x_embedder
* update help message
* Support for negative indices
* support for OmniControl (offsets at index 0)
* c++11 compat
* add --increase-ref-index option
* simplify the logic and fix some issues
* update README.md
* remove unused variable
---------
Co-authored-by: leejet <leejet714@gmail.com>
* Wan MoE: Automatic expert routing based on timestep boundary
* unify code style and fix some issues
---------
Co-authored-by: leejet <leejet714@gmail.com>
* add wan vae suppport
* add wan model support
* add umt5 support
* add wan2.1 t2i support
* make flash attn work with wan
* make wan a little faster
* add wan2.1 t2v support
* add wan gguf support
* add offload params to cpu support
* add wan2.1 i2v support
* crop image before resize
* set default fps to 16
* add diff lora support
* fix wan2.1 i2v
* introduce sd_sample_params_t
* add wan2.2 t2v support
* add wan2.2 14B i2v support
* add wan2.2 ti2v support
* add high noise lora support
* sync: update ggml submodule url
* avoid build failure on linux
* avoid build failure
* update ggml
* update ggml
* fix sd_version_is_wan
* update ggml, fix cpu im2col_3d
* fix ggml_nn_attention_ext mask
* add cache support to ggml runner
* fix the issue of illegal memory access
* unify image loading processing
* add wan2.1/2.2 FLF2V support
* fix end_image mask
* update to latest ggml
* add GGUFReader
* update docs
* Conv2DDirect for VAE stage
* Enable only for Vulkan, reduced duplicated code
* Cmake option to use conv2d direct
* conv2d direct always on for opencl
* conv direct as a flag
* fix merge typo
* Align conv2d behavior to flash attention's
* fix readme
* add conv2d direct for controlnet
* add conv2d direct for esrgan
* clean code, use enable_conv2d_direct/get_all_blocks
* format code
---------
Co-authored-by: leejet <leejet714@gmail.com>
* feat: add new scheduler types, clip skip and vae to image embedded params
- If a non default scheduler is set, include it in the 'Sampler' tag in the data
embedded into the final image.
- If a custom VAE path is set, include the vae name (without path and extension)
in embedded image params under a `VAE:` tag.
- If a custom Clip skip is set, include that Clip skip value in embedded image
params under a `Clip skip:` tag.
* feat: add separate diffusion and text models to metadata
---------
Co-authored-by: one-lithe-rune <skapusniak@lithe-runes.com>
* Instruct-p2p support
* support 2 conditionings cfg
* Do not re-encode the exact same image twice
* fixes for 2-cfg
* Fix pix2pix latent inputs + improve inpainting a bit + fix naming
* prepare for other pix2pix-like models
* Support sdxl ip2p
* fix reference image embeddings
* Support 2-cond cfg properly in cli
* fix typo in help
* Support masks for ip2p models
* unify code style
* delete unused code
* use edit mode
* add img_cond
* format code
---------
Co-authored-by: leejet <leejet714@gmail.com>
* repair flash attention in _ext
this does not fix the currently broken fa behind the define, which is only used by VAE
Co-authored-by: FSSRepo <FSSRepo@users.noreply.github.com>
* make flash attention in the diffusion model a runtime flag
no support for sd3 or video
* remove old flash attention option and switch vae over to attn_ext
* update docs
* format code
---------
Co-authored-by: FSSRepo <FSSRepo@users.noreply.github.com>
Co-authored-by: leejet <leejet714@gmail.com>
* mmdit-x
* add support for sd3.5 medium
* add skip layer guidance support (mmdit only)
* ignore slg if slg_scale is zero (optimization)
* init out_skip once
* slg support for flux (expermiental)
* warn if version doesn't support slg
* refactor slg cli args
* set default slg_scale to 0 (oops)
* format code
---------
Co-authored-by: leejet <leejet714@gmail.com>
* add flux support
* avoid build failures in non-CUDA environments
* fix schnell support
* add k quants support
* add support for applying lora to quantized tensors
* add inplace conversion support for f8_e4m3 (#359)
in the same way it is done for bf16
like how bf16 converts losslessly to fp32,
f8_e4m3 converts losslessly to fp16
* add xlabs flux comfy converted lora support
* update docs
---------
Co-authored-by: Erik Scholz <Green-Sky@users.noreply.github.com>
Added NVIDEA's new "Align Your Steps" style scheduler in accordance with their
quick start guide. Currently has handling for SD1.5, SDXL, and SVD, using the
noise levels from their paper to generate the sigma values. Can be selected
using the --schedule ays command line switch. Updates the main.cpp help
message and README to reflect this option, also they now inform the user
of the --color switch as well.
---------
Co-authored-by: leejet <leejet714@gmail.com>
* apply pmid lora only once for multiple txt2img calls
* add better support for SDXL LoRA
* fix for some sdxl lora, like lcm-lora-xl
---------
Co-authored-by: bssrdf <bssrdf@gmail.com>
Co-authored-by: leejet <leejet714@gmail.com>
* Support png image and resize image with 64 pixels in img2img mode
* update the error information
---------
Co-authored-by: leejet <leejet714@gmail.com>
* Fixed a double free issue when running multiple backends on the CPU, eg: CLIP
and the primary backend, as this would result in the *_backend pointers both
pointing to the same thing resulting in a segfault when calling the
StableDiffusionGGML destructor.
* Improve logging to allow for a color switch on the command line interface.
Changed the base log_printf function to not bake the log level directly into
the log buffer as that information is already passed the logging function via
the level parameter and it's easier to add in there than strip it out.
* Added a fix for certain SDXL LoRAs that don't seem to follow the expected
naming convention, converts over the tensor name during the LoRA model
loading. Added some logging of useful LoRA loading information. Had to
increase the base size of the GGML graph as the existing size results in an
insufficient graph memory error when using SDXL LoRAs.
* small fixes
---------
Co-authored-by: leejet <leejet714@gmail.com>
* first efforts at implementing photomaker; lots more to do
* added PhotoMakerIDEncoder model in SD
* fixed soem bugs; now photomaker model weights can be loaded into their tensor buffers
* added input id image loading
* added preprocessing inpit id images
* finished get_num_tensors
* fixed a bug in remove_duplicates
* add a get_learned_condition_with_trigger function to do photomaker stuff
* add a convert_token_to_id function for photomaker to extract trigger word's token id
* making progress; need to implement tokenizer decoder
* making more progress; finishing vision model forward
* debugging vision_model outputs
* corrected clip vision model output
* continue making progress in id fusion process
* finished stacked id embedding; to be tested
* remove garbage file
* debuging graph compute
* more progress; now alloc buffer failed
* fixed wtype issue; input images can only be 1 because issue with transformer when batch size > 1 (to be investigated)
* added delayed subject conditioning; now photomaker runs and generates images
* fixed stat_merge_step
* added photomaker lora model (to be tested)
* reworked pmid lora
* finished applying pmid lora; to be tested
* finalized pmid lora
* add a few print tensor; tweak in sample again
* small tweak; still not getting ID faces
* fixed a bug in FuseBlock forward; also remove diag_mask op in for vision transformer; getting better results
* disable pmid lora apply for now; 1 input image seems working; > 1 not working
* turn pmid lora apply back on
* fixed a decode bug
* fixed a bug in ggml's conv_2d, and now > 1 input images working
* add style_ratio as a cli param; reworked encode with trigger for attention weights
* merge commit fixing lora free param buffer error
* change default style ratio to 10%
* added an option to offload vae decoder to CPU for mem-limited gpus
* removing image normalization step seems making ID fidelity much higher
* revert default style ratio back ro 20%
* added an option for normalizing input ID images; cleaned up debugging code
* more clean up
* fixed bugs; now failed with cuda error; likely out-of-mem on GPU
* free pmid model params when required
* photomaker working properly now after merging and adapting to GGMLBlock API
* remove tensor renaming; fixing names in the photomaker model file
* updated README.md to include instructions and notes for running PhotoMaker
* a bit clean up
* remove -DGGML_CUDA_FORCE_MMQ; more clean up and README update
* add input image requirement in README
* bring back freeing pmid lora params buffer; simply pooled output of CLIPvision
* remove MultiheadAttention2; customized MultiheadAttention
* added a WIN32 get_files_from_dir; turn off Photomakder if receiving no input images
* update docs
* fix ci error
* make stable-diffusion.h a pure c header file
This reverts commit 27887b630d.
* fix ci error
* format code
* reuse get_learned_condition
* reuse pad_tokens
* reuse CLIPVisionModel
* reuse LoraModel
* add --clip-on-cpu
* fix lora name conversion for SDXL
---------
Co-authored-by: bssrdf <bssrdf@gmail.com>
Co-authored-by: leejet <leejet714@gmail.com>
* add controlnet to pipeline
* add cli params
* control strength cli param
* cli param keep controlnet in cpu
* add Textual Inversion
* add canny preprocessor
* refactor: change ggml_type_sizef to ggml_row_size
* process hint once time
* ignore the embedding name case
---------
Co-authored-by: leejet <leejet714@gmail.com>
* add taesd implementation
* taesd gpu offloading
* show seed when generating image with -s -1
* less restrictive with larger images
* cuda: im2col speedup x2
* cuda: group norm speedup x90
* quantized models now works in cuda :)
* fix cal mem size
---------
Co-authored-by: leejet <leejet714@gmail.com>
* set ggml url to FSSRepo/ggml
* ggml-alloc integration
* offload all functions to gpu
* gguf format + native converter
* merge custom vae to a model
* full offload to gpu
* improve pretty progress
---------
Co-authored-by: leejet <leejet714@gmail.com>
* Write generation parameter exif data into output pngs.
This adds prompt, negative prompt (if nonempty) and other generation
parameters to the output file as a tEXt PNG block, in the same format as
AUTOMATIC1111 webui does.
In order to keep everything free of external library dependencies, I
have somewhat dirtily hacked this into the stb_image_write
implementation.
* Mention png text data in README.md, include "karras" in sampler text
* add Steps/Model/RNG to parameter string
---------
Co-authored-by: leejet <leejet714@gmail.com>
Concretely, this allows switching to the "Karras" schedule from the
Karras et al 2022 paper, equivalent to the samplers marked as "Karras"
in the AUTOMATIC1111 WebUI. This choice is in principle orthogonal to
the sampler choice and can be given independently.
* Add Euler sampler
* Add Heun sampler
* Add DPM++ (2M) sampler
* Add modified DPM++ (2M) "v2" sampler.
This was proposed in a issue discussion of the stable diffusion webui,
at https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8457
and apparently works around overstepping of the DPM++ (2M) method with
small step counts.
The parameter is called dpmpp2mv2 here.
* match code style
---------
Co-authored-by: Urs Ganse <urs@nerd2nerd.org>
Co-authored-by: leejet <leejet714@gmail.com>
* move main and stb-libs to subfolder
* cmake : general additions
* ci : add simple building
---------
Co-authored-by: leejet <31925346+leejet@users.noreply.github.com>
