DarthAffe/stable-diffusion.cpp
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turn pmid lora apply back on

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bssrdf committed 2024-02-16 11:50:46 -05:00
1 parent 26f591db6d
commit 62b0a9b9f8
3 files changed
+35 -21
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pmid.hpp
+18 -10
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@@ -211,10 +211,10 @@ struct FuseModule{
// print_ggml_tensor(stacked_id_embeds, true, "stacked_id_embeds_before_concat");
stacked_id_embeds = ggml_cont(ctx, ggml_permute(ctx, stacked_id_embeds, 0, 2, 1, 3));
// print_ggml_tensor(stacked_id_embeds, true, "stacked_id_embeds_after_permute");
print_ggml_tensor(stacked_id_embeds, true, "stacked_id_embeds_after_permute");
if(left && right){
// print_ggml_tensor(left, true, "left");
// print_ggml_tensor(right, true, "right");
print_ggml_tensor(left, true, "left");
print_ggml_tensor(right, true, "right");
stacked_id_embeds = ggml_concat(ctx, left, stacked_id_embeds);
stacked_id_embeds = ggml_concat(ctx, stacked_id_embeds, right);
}else if(left){
@@ -474,10 +474,10 @@ struct PhotoMakerIDEncoder : public GGMLModule {
ggml_backend_tensor_set(cls, cls_h.data(), 0, ggml_nbytes(cls));
ggml_backend_tensor_set(positions, pos.data(), 0, ggml_nbytes(positions));
ggml_backend_tensor_set(class_tokens_mask_pos, ctmpos.data(), 0, ggml_nbytes(class_tokens_mask_pos));
std::vector<float> zeros;
for (int i = 0; i < hidden_size; i++) {
zeros.push_back(0.f);
}
// std::vector<float> zeros;
// for (int i = 0; i < hidden_size; i++) {
// zeros.push_back(0.f);
// }
if(left){
if(type == GGML_TYPE_F16){
std::vector<ggml_fp16_t> zeros(ggml_nelements(left), ggml_fp32_to_fp16(0.f));
@@ -752,15 +752,23 @@ struct PhotoMakerLoraModel : public GGMLModule {
continue;
}
ggml_tensor* lora_up_orig = lora_up;
// print_ggml_tensor(lora_down, true, lora_down_name.c_str());
// print_ggml_tensor(lora_up, true, lora_up_name.c_str());
// ggml_tensor* lora_up_orig = lora_up;
applied_lora_tensors.insert(lora_up_name);
applied_lora_tensors.insert(lora_down_name);
// ggml_mul_mat requires tensor b transposed
// lora_down = ggml_cont(ctx0, ggml_transpose(ctx0, lora_down));
// struct ggml_tensor* updown = ggml_mul_mat(ctx0, lora_down, lora_up);
// updown = ggml_cont(ctx0, updown);
// same as in lora.hpp
lora_down = ggml_cont(ctx0, ggml_transpose(ctx0, lora_down));
struct ggml_tensor* updown = ggml_mul_mat(ctx0, lora_down, lora_up);
updown = ggml_cont(ctx0, updown);
struct ggml_tensor* updown = ggml_mul_mat(ctx0, lora_up, lora_down);
updown = ggml_cont(ctx0, ggml_transpose(ctx0, updown));
updown = ggml_reshape(ctx0, updown, weight);
GGML_ASSERT(ggml_nelements(updown) == ggml_nelements(weight));
updown = ggml_scale_inplace(ctx0, updown, multiplier);
ggml_tensor* final_weight;