134883aec4
* 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>
75 lines
1.7 KiB
C++
75 lines
1.7 KiB
C++
#ifndef __STABLE_DIFFUSION_H__
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#define __STABLE_DIFFUSION_H__
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#include <memory>
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#include <string>
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#include <vector>
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enum RNGType {
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STD_DEFAULT_RNG,
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CUDA_RNG
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};
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enum SampleMethod {
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EULER_A,
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EULER,
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HEUN,
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DPM2,
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DPMPP2S_A,
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DPMPP2M,
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DPMPP2Mv2,
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LCM,
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N_SAMPLE_METHODS
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};
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enum Schedule {
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DEFAULT,
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DISCRETE,
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KARRAS,
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N_SCHEDULES
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};
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class StableDiffusionGGML;
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class StableDiffusion {
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private:
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std::shared_ptr<StableDiffusionGGML> sd;
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public:
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StableDiffusion(int n_threads = -1,
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bool vae_decode_only = false,
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std::string taesd_path = "",
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bool free_params_immediately = false,
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std::string lora_model_dir = "",
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RNGType rng_type = STD_DEFAULT_RNG);
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bool load_from_file(const std::string& model_path,
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const std::string& vae_path,
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ggml_type wtype,
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Schedule d = DEFAULT);
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std::vector<uint8_t*> txt2img(
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std::string prompt,
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std::string negative_prompt,
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float cfg_scale,
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int width,
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int height,
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SampleMethod sample_method,
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int sample_steps,
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int64_t seed,
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int batch_count);
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std::vector<uint8_t*> img2img(
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const uint8_t* init_img_data,
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std::string prompt,
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std::string negative_prompt,
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float cfg_scale,
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int width,
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int height,
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SampleMethod sample_method,
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int sample_steps,
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float strength,
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int64_t seed);
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};
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std::string sd_get_system_info();
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#endif // __STABLE_DIFFUSION_H__
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