mirror of
https://github.com/leejet/stable-diffusion.cpp.git
synced 2026-11-11 19:36:33 +00:00
48 lines
2.8 KiB
C++
48 lines
2.8 KiB
C++
#include "conditioning/conditioner.hpp"
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#include "model/diffusion/hunyuan.hpp"
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#include "model_definition.h"
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#include "pipeline/model_builders.h"
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static bool build_hunyuan_video(const sd::model_builders::Context& ctx, const TokenizerConfig& tokenizers, sd::model_builders::CoreRunners& result) {
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const auto* sd_ctx_params = &ctx.params;
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const auto& tensor_storage_map = ctx.tensor_storage_map;
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const auto version = ctx.version;
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const auto& weight_manager = ctx.weight_manager;
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result.conditioner = std::make_shared<LLMEmbedder>(ctx.backends.runtime_backend(SDBackendModule::TE),
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tensor_storage_map,
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version,
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"",
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false,
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weight_manager,
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tokenizers);
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result.diffusion = std::make_shared<Hunyuan::HunyuanVideoRunner>(ctx.backends.runtime_backend(SDBackendModule::DIFFUSION),
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tensor_storage_map,
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"model.diffusion_model",
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version,
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weight_manager);
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return true;
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}
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const std::vector<ModelDefinition>& hunyuan_video_definitions() {
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static const std::vector<ModelDefinition> definitions = [] {
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std::vector<ModelDefinition> result;
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{
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ModelDefinition definition;
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definition.version = VERSION_HUNYUAN_VIDEO;
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definition.geometry = {1, 32, 3};
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definition.name = "Hunyuan Video";
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definition.traits.is_dit = true;
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definition.traits.supports_video_generation = true;
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definition.traits.vae_kind = ModelVAEKind::HUNYUAN;
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definition.traits.video_tae = true;
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definition.sampling = {FLOW_PRED, 7.f};
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definition.sampling.default_sample_method = EULER_SAMPLE_METHOD;
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definition.sampling.default_scheduler = DISCRETE_SCHEDULER;
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definition.build = build_hunyuan_video;
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result.push_back(std::move(definition));
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}
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return result;
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}();
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return definitions;
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}
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