DarthAffe/stable-diffusion.cpp
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Fix diffusers_style detection

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Stéphane du Hamel 2025-12-06 03:47:52 +01:00
parent 1241323c4a
commit 203d0539fe
1 changed files with 13 additions and 13 deletions
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26
flux.hpp
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@ -88,19 +88,19 @@ namespace Flux {
public:
SelfAttention(int64_t dim,
int64_t num_heads = 8,
bool qkv_bias = false,
bool proj_bias = true,
bool diffusers_style = false)
int64_t num_heads = 8,
bool qkv_bias = false,
bool proj_bias = true,
bool diffusers_style = false)
: num_heads(num_heads) {
int64_t head_dim = dim / num_heads;
if(diffusers_style) {
blocks["qkv"] = std::shared_ptr<GGMLBlock>(new SplitLinear(dim, {dim, dim, dim}, qkv_bias));
if (diffusers_style) {
blocks["qkv"] = std::shared_ptr<GGMLBlock>(new SplitLinear(dim, {dim, dim, dim}, qkv_bias));
} else {
blocks["qkv"] = std::shared_ptr<GGMLBlock>(new Linear(dim, dim * 3, qkv_bias));
blocks["qkv"] = std::shared_ptr<GGMLBlock>(new Linear(dim, dim * 3, qkv_bias));
}
blocks["norm"] = std::shared_ptr<GGMLBlock>(new QKNorm(head_dim));
blocks["proj"] = std::shared_ptr<GGMLBlock>(new Linear(dim, dim, proj_bias));
blocks["norm"] = std::shared_ptr<GGMLBlock>(new QKNorm(head_dim));
blocks["proj"] = std::shared_ptr<GGMLBlock>(new Linear(dim, dim, proj_bias));
}
std::vector<struct ggml_tensor*> pre_attention(GGMLRunnerContext* ctx, struct ggml_tensor* x) {
@ -782,8 +782,8 @@ namespace Flux {
bool use_yak_mlp = false;
bool use_mlp_silu_act = false;
float ref_index_scale = 1.f;
bool diffusers_style = false;
ChromaRadianceParams chroma_radiance_params;
bool diffusers_style = false;
};
struct Flux : public GGMLBlock {
@ -1308,7 +1308,7 @@ namespace Flux {
// not schnell
flux_params.guidance_embed = true;
}
if (tensor_name.find("model.diffusion_model.single_blocks.0.linear1.weight.1") == std::string::npos) {
if (tensor_name.find("model.diffusion_model.single_blocks.0.linear1.weight.1") != std::string::npos) {
flux_params.diffusers_style = true;
}
if (tensor_name.find("distilled_guidance_layer.in_proj.weight") != std::string::npos) {
@ -1466,9 +1466,9 @@ namespace Flux {
flux_params.ref_index_scale,
flux_params.theta,
flux_params.axes_dim,
sd_version_is_longcat(version));
sd_version_is_longcat(version));
int pos_len = pe_vec.size() / flux_params.axes_dim_sum / 2;
auto pe = ggml_new_tensor_4d(compute_ctx, GGML_TYPE_F32, 2, 2, flux_params.axes_dim_sum / 2, pos_len);
auto pe = ggml_new_tensor_4d(compute_ctx, GGML_TYPE_F32, 2, 2, flux_params.axes_dim_sum / 2, pos_len);
// pe->data = pe_vec.data();
// print_ggml_tensor(pe);
// pe->data = nullptr;