upstream-archive/stable-diffusion.cpp
1
0
Fork 0
mirror of https://github.com/leejet/stable-diffusion.cpp.git synced 2026-07-30 06:40:41 -05:00
Code Issues Packages Projects Releases Wiki Activity

turn pmid lora apply back on

Browse Source
This commit is contained in:
bssrdf
2024-02-16 11:50:46 -05:00
parent 26f591db6d
commit 62b0a9b9f8
3 changed files with 35 additions and 21 deletions
Download Patch File Download Diff File Expand all files Collapse all files

24
clip.hpp
View File

@@ -973,15 +973,15 @@ struct CLIPVisionModel {
struct ggml_tensor * inp = ggml_conv_2d(ctx0, patch_embeddings_f16, x, patch_size, patch_size, 0, 0, 1, 1);
ggml_set_name(inp, "inp_conv_2d");
// print_ggml_tensor(inp, true, "inp_conv_2d");
print_ggml_tensor(inp, true, "inp_conv_2d");
inp = ggml_reshape_3d(ctx0, inp, num_patches, hidden_size, batch_size);
ggml_set_name(inp, "inp_reshape_3d");
// print_ggml_tensor(inp, true, "inp_reshape_3d");
print_ggml_tensor(inp, true, "inp_reshape_3d");
// inp = ggml_cont(ctx0, ggml_permute(ctx0, inp, 1, 0, 2, 3));
// print_ggml_tensor(ggml_permute(ctx0, inp, 2, 0, 1, 3), true, "inp_permute");
inp = ggml_cont(ctx0, ggml_permute(ctx0, inp, 2, 0, 1, 3));
// print_ggml_tensor(inp, true, "inp_cont");
print_ggml_tensor(inp, true, "inp_cont_perm+cont");
ggml_set_name(inp, "inp_cont");
// ggml_set_name(class_embedding, "class_embedding");
@@ -991,18 +991,18 @@ struct CLIPVisionModel {
// struct ggml_tensor * temp = ggml_new_tensor_3d(ctx0, GGML_TYPE_F32, hidden_size, 1, batch_size);
// ggml_tensor *class_embedding_rep = ggml_add(ctx0, cast_f32_class, class_embedding);
// ggml_set_name(class_embedding_rep, "add_class_embedding_to_zero");
// print_ggml_tensor(class_embedding, true, "model.class_embedding");
print_ggml_tensor(class_embedding, true, "model.class_embedding");
// print_ggml_tensor(class_embedding_rep, true, "class_embedding_rep_bef_repeat");
// print_ggml_tensor(temp, true, "temp");
print_ggml_tensor(temp, true, "temp");
ggml_tensor *class_embedding_rep = ggml_repeat(ctx0, class_embedding, temp);
ggml_set_name(class_embedding_rep, "class_embedding_rep");
// print_ggml_tensor(class_embedding_rep, true, "class_embedding_rep");
print_ggml_tensor(class_embedding_rep, true, "class_embedding_rep");
// class_embedding_rep = ggml_cast(ctx0, class_embedding_rep, inp->type);
// print_ggml_tensor(class_embedding_rep, true, "class_embedding_rep_aft_casting");
struct ggml_tensor *embeddings = ggml_concat(ctx0, class_embedding_rep, inp);
ggml_set_name(embeddings, "embeddings_after_concat");
// print_ggml_tensor(embeddings, true, "embeddings_after_concat");
print_ggml_tensor(embeddings, true, "embeddings_after_concat");
// print_ggml_tensor(ggml_permute(ctx0, embeddings, 0, 3, 1, 2), true, "embeddings_after_concat_permute");
embeddings = ggml_cont(ctx0, ggml_permute(ctx0, embeddings, 0, 2, 1, 3));
ggml_set_name(embeddings, "embeddings_after_permute");
@@ -1019,7 +1019,7 @@ struct CLIPVisionModel {
// ggml_add(ctx0, embeddings, ggml_repeat(ctx0, ggml_get_rows(ctx0, position_embeddings, positions), embeddings));
ggml_add(ctx0, embeddings, ggml_get_rows(ctx0, position_embeddings, positions));
ggml_set_name(embeddings, "embeddings_after_add");
// print_ggml_tensor(embeddings, true, "embeddings_after_add");
print_ggml_tensor(embeddings, true, "embeddings_to_transformer");
// pre-layernorm
embeddings = ggml_nn_layer_norm(ctx0, embeddings, pre_ln_w, pre_ln_w);
@@ -1342,12 +1342,18 @@ struct FrozenCLIPEmbedderWithCustomWords : public GGMLModule {
}
for(uint32_t i = 0; i < tokens.size(); i++){
if(class_token_index[0] <= i && i < class_token_index[0]+num_input_imgs)
if(class_token_index[0]+1 <= i && i < class_token_index[0]+1+num_input_imgs)
class_token_mask.push_back(true);
else
class_token_mask.push_back(false);
}
printf("[");
for (int i = 0; i < tokens.size(); i++) {
printf("%d, ", class_token_mask[i] ? 1 : 0);
}
printf("]\n");
// for (int i = 0; i < tokens.size(); i++) {
// std::cout << tokens[i] << ":" << weights[i] << ", ";
// }

28
pmid.hpp
View File

@@ -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;

4
stable-diffusion.cpp
View File

@@ -1471,8 +1471,8 @@ sd_image_t* txt2img(sd_ctx_t* sd_ctx,
LOG_INFO("apply_loras completed, taking %.2fs", (t1 - t0) * 1.0f / 1000);
if(sd_ctx->sd->stacked_id){
// sd_ctx->sd->pmid_lora.apply(sd_ctx->sd->tensors, sd_ctx->sd->n_threads);
// sd_ctx->sd->pmid_lora.free_compute_buffer();
sd_ctx->sd->pmid_lora.apply(sd_ctx->sd->tensors, sd_ctx->sd->n_threads);
sd_ctx->sd->pmid_lora.free_compute_buffer();
if (sd_ctx->sd->free_params_immediately) {
sd_ctx->sd->pmid_lora.free_params_buffer();
}