DarthAffe/stable-diffusion.cpp
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feat: support new chroma radiance "x0_x32_proto" (#1209)

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stduhpf 2026-01-19 16:51:26 +01:00 committed by GitHub
parent e50e1f253d
commit b87fe13afd
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1 changed files with 20 additions and 8 deletions
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flux.hpp
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@ -748,7 +748,7 @@ namespace Flux {
int nerf_depth = 4; int nerf_depth = 4;
int nerf_max_freqs = 8; int nerf_max_freqs = 8;
bool use_x0 = false; bool use_x0 = false;
bool use_patch_size_32 = false; bool fake_patch_size_x2 = false;
}; };
struct FluxParams { struct FluxParams {
@ -786,8 +786,11 @@ namespace Flux {
Flux(FluxParams params) Flux(FluxParams params)
: params(params) { : params(params) {
if (params.version == VERSION_CHROMA_RADIANCE) { if (params.version == VERSION_CHROMA_RADIANCE) {
std::pair<int, int> kernel_size = {16, 16}; std::pair<int, int> kernel_size = {params.patch_size, params.patch_size};
std::pair<int, int> stride = kernel_size; if (params.chroma_radiance_params.fake_patch_size_x2) {
kernel_size = {params.patch_size / 2, params.patch_size / 2};
}
std::pair<int, int> stride = kernel_size;
blocks["img_in_patch"] = std::make_shared<Conv2d>(params.in_channels, blocks["img_in_patch"] = std::make_shared<Conv2d>(params.in_channels,
params.hidden_size, params.hidden_size,
@ -1082,7 +1085,7 @@ namespace Flux {
auto img = pad_to_patch_size(ctx, x); auto img = pad_to_patch_size(ctx, x);
auto orig_img = img; auto orig_img = img;
if (params.chroma_radiance_params.use_patch_size_32) { if (params.chroma_radiance_params.fake_patch_size_x2) {
// It's supposed to be using GGML_SCALE_MODE_NEAREST, but this seems more stable // It's supposed to be using GGML_SCALE_MODE_NEAREST, but this seems more stable
// Maybe the implementation of nearest-neighbor interpolation in ggml behaves differently than the one in PyTorch? // Maybe the implementation of nearest-neighbor interpolation in ggml behaves differently than the one in PyTorch?
// img = F.interpolate(img, size=(H//2, W//2), mode="nearest") // img = F.interpolate(img, size=(H//2, W//2), mode="nearest")
@ -1303,7 +1306,8 @@ namespace Flux {
flux_params.ref_index_scale = 10.f; flux_params.ref_index_scale = 10.f;
flux_params.use_mlp_silu_act = true; flux_params.use_mlp_silu_act = true;
} }
int64_t head_dim = 0; int64_t head_dim = 0;
int64_t actual_radiance_patch_size = -1;
for (auto pair : tensor_storage_map) { for (auto pair : tensor_storage_map) {
std::string tensor_name = pair.first; std::string tensor_name = pair.first;
if (!starts_with(tensor_name, prefix)) if (!starts_with(tensor_name, prefix))
@ -1316,9 +1320,12 @@ namespace Flux {
flux_params.chroma_radiance_params.use_x0 = true; flux_params.chroma_radiance_params.use_x0 = true;
} }
if (tensor_name.find("__32x32__") != std::string::npos) { if (tensor_name.find("__32x32__") != std::string::npos) {
LOG_DEBUG("using patch size 32 prediction"); LOG_DEBUG("using patch size 32");
flux_params.chroma_radiance_params.use_patch_size_32 = true; flux_params.patch_size = 32;
flux_params.patch_size = 32; }
if (tensor_name.find("img_in_patch.weight") != std::string::npos) {
actual_radiance_patch_size = pair.second.ne[0];
LOG_DEBUG("actual radiance patch size: %d", actual_radiance_patch_size);
} }
if (tensor_name.find("distilled_guidance_layer.in_proj.weight") != std::string::npos) { if (tensor_name.find("distilled_guidance_layer.in_proj.weight") != std::string::npos) {
// Chroma // Chroma
@ -1351,6 +1358,11 @@ namespace Flux {
head_dim = pair.second.ne[0]; head_dim = pair.second.ne[0];
} }
} }
if (actual_radiance_patch_size > 0 && actual_radiance_patch_size != flux_params.patch_size) {
GGML_ASSERT(flux_params.patch_size == 2 * actual_radiance_patch_size);
LOG_DEBUG("using fake x2 patch size");
flux_params.chroma_radiance_params.fake_patch_size_x2 = true;
}
flux_params.num_heads = static_cast<int>(flux_params.hidden_size / head_dim); flux_params.num_heads = static_cast<int>(flux_params.hidden_size / head_dim);