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feat: add Qwen Image 2.1 prefix KV cache (#2035)

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leejet
2026-09-23 23:08:21 +08:00
committed by GitHub
parent e6281b6318
commit 2dc7f5408a
9 changed files with 237 additions and 81 deletions
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src/pipeline/diffusion_engine.cpp
+22
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@@ -7,6 +7,7 @@
#include <list>
#include <mutex>
#include <set>
#include <tuple>
#include <type_traits>
#include <unordered_set>
#include <utility>
@@ -2255,6 +2256,15 @@ sd::Tensor<float> StableDiffusionGGML::sample(const std::shared_ptr<DiffusionMod
};
RunnerEndOnExit sample_diffusion_runner_end{work_diffusion_model.get()};
// These inputs are immutable for this sampling run. Extensions may replace or
// modify them per step, so those paths need an explicit stability contract first.
const bool cache_qwen_prefix = version == VERSION_QWEN_IMAGE_2_1 &&
std::none_of(generation_extensions.begin(), generation_extensions.end(),
[](const auto& extension) { return extension->is_enabled(); });
using QwenPrefixInputs = std::tuple<const sd::Tensor<float>*, const sd::Tensor<int32_t>*,
const std::vector<sd::Tensor<float>>*>;
std::vector<QwenPrefixInputs> qwen_prefix_inputs;
RunnerEndOnExit sample_control_runner_end{!control_image.empty() && control_net != nullptr ? control_net.get() : nullptr};
const bool apply_denoise_mask = !denoise_mask.empty() &&
@@ -2524,6 +2534,18 @@ sd::Tensor<float> StableDiffusionGGML::sample(const std::shared_ptr<DiffusionMod
extension->before_diffusion(diffusion_params, step);
}
if (cache_qwen_prefix) {
auto* extra = std::get_if<QwenImage21DiffusionExtra>(&diffusion_params.extra);
if (extra != nullptr) {
auto key = std::make_tuple(diffusion_params.context, extra->image_slots,
diffusion_params.ref_image_params.pass_to_dit ? diffusion_params.ref_latents : nullptr);
auto entry = std::find(qwen_prefix_inputs.begin(), qwen_prefix_inputs.end(), key);
extra->prefix_id = static_cast<uint64_t>(entry - qwen_prefix_inputs.begin()) + 1;
if (entry == qwen_prefix_inputs.end()) {
qwen_prefix_inputs.push_back(key);
}
}
}
auto output_opt = work_diffusion_model->compute(n_threads, diffusion_params);
if (output_opt.empty()) {
LOG_ERROR("diffusion model compute failed");