DarthAffe/stable-diffusion.cpp
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refactor: centralize circular RoPE and extend image model support (#2039)

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leejet authored and GitHub committed 2026-09-24 01:45:14 +08:00
1 parent 500ef5fa7c
commit 88411ef1e0
17 files changed
+611 -564
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src/model/diffusion/ideogram4.hpp
+28 -43
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@@ -149,18 +149,21 @@ namespace Ideogram4 {
return std::make_shared<Linear>(in_features, out_features, bias);
}
__STATIC_INLINE__ std::vector<float> gen_ideogram4_pe(int grid_h,
int grid_w,
int bs,
int context_len,
int head_dim,
int rope_theta,
const std::vector<int>& mrope_section,
bool circular_x = false,
bool circular_y = false) {
__STATIC_INLINE__ Rope::Embedding gen_ideogram4_pe(int grid_h,
int grid_w,
int bs,
int context_len,
int head_dim,
int rope_theta,
const std::vector<int>& mrope_section) {
GGML_ASSERT(bs == 1);
std::vector<std::vector<float>> ids(static_cast<size_t>(bs) * (context_len + grid_h * grid_w),
std::vector<float>(3, 0.f));
Rope::Embedding result;
result.batch_size = bs;
result.positions.append_tokens(context_len);
result.positions.append_image(grid_h, grid_w);
result.ids.assign(static_cast<size_t>(bs) * (context_len + grid_h * grid_w),
std::vector<float>(3, 0.f));
auto& ids = result.ids;
for (int i = 0; i < context_len; ++i) {
ids[i] = {static_cast<float>(i), static_cast<float>(i), static_cast<float>(i)};
@@ -175,29 +178,13 @@ namespace Ideogram4 {
}
}
std::vector<std::vector<int>> axis_wrap_dims(3);
if (circular_y || circular_x) {
size_t total_len = static_cast<size_t>(bs) * (context_len + grid_h * grid_w);
axis_wrap_dims[1].assign(total_len, 0);
axis_wrap_dims[2].assign(total_len, 0);
if (circular_y) {
for (size_t idx = static_cast<size_t>(context_len); idx < total_len; ++idx) {
axis_wrap_dims[1][idx] = grid_h;
}
}
if (circular_x) {
for (size_t idx = static_cast<size_t>(context_len); idx < total_len; ++idx) {
axis_wrap_dims[2][idx] = grid_w;
}
}
}
return Rope::embed_interleaved_mrope(ids,
bs,
static_cast<float>(rope_theta),
head_dim,
mrope_section,
axis_wrap_dims);
result.values = Rope::embed_interleaved_mrope(ids,
bs,
static_cast<float>(rope_theta),
head_dim,
mrope_section,
&result.frequencies);
return result;
}
class Ideogram4Attention : public GGMLBlock {
@@ -509,15 +496,13 @@ namespace Ideogram4 {
int64_t head_dim = config.emb_dim / config.num_heads;
auto runner_ctx = get_context();
pe_vec = gen_ideogram4_pe(static_cast<int>(grid_h),
static_cast<int>(grid_w),
static_cast<int>(x->ne[3]),
static_cast<int>(context_len),
static_cast<int>(head_dim),
static_cast<int>(config.rope_theta),
config.mrope_section,
runner_ctx.circular_x_enabled,
runner_ctx.circular_y_enabled);
pe_vec = finish_rope_pe(gen_ideogram4_pe(static_cast<int>(grid_h),
static_cast<int>(grid_w),
static_cast<int>(x->ne[3]),
static_cast<int>(context_len),
static_cast<int>(head_dim),
static_cast<int>(config.rope_theta),
config.mrope_section));
auto pe = ggml_new_tensor_4d(compute_ctx, GGML_TYPE_F32, 2, 2, head_dim / 2, pos_len);
set_backend_tensor_data(pe, pe_vec.data());