* 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
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Co-authored-by: FSSRepo <FSSRepo@users.noreply.github.com>
Co-authored-by: leejet <leejet714@gmail.com>
* first attempt at updating to photomaker v2
* continue adding photomaker v2 modules
* finishing the last few pieces for photomaker v2; id_embeds need to be done by a manual step and pass as an input file
* added a name converter for Photomaker V2; build ok
* more debugging underway
* failing at cuda mat_mul
* updated chunk_half to be more efficient; redo feedforward
* fixed a bug: carefully using ggml_view_4d to get chunks of a tensor; strides need to be recalculated or set properly; still failing at soft_max cuda op
* redo weight calculation and weight*v
* fixed a bug now Photomaker V2 kinds of working
* add python script for face detection (Photomaker V2 needs)
* updated readme for photomaker
* fixed a bug causing PMV1 crashing; both V1 and V2 work
* fixed clean_input_ids for PMV2
* fixed a double counting bug in tokenize_with_trigger_token
* updated photomaker readme
* removed some commented code
* improved reconstructing class word free prompt
* changed reading id_embed to raw binary using existing load tensor function; this is more efficient than using model load and also makes it easier to work with sd server
* minor clean up
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Co-authored-by: bssrdf <bssrdf@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
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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
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Co-authored-by: Erik Scholz <Green-Sky@users.noreply.github.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 27887b630db6a92f269f0aef8de9bc9832ab50a9.
* 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
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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
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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
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Co-authored-by: leejet <leejet714@gmail.com>
