DarthAffe/stable-diffusion.cpp
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fixed stat_merge_step

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bssrdf committed 2024-02-11 22:32:35 -05:00
1 parent f4bf8e0ccf
commit 857af489a9
5 files changed
+18 -10
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clip.hpp
+4 -3
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@@ -995,7 +995,7 @@ struct CLIPVisionModel {
ggml_set_name(class_embedding_rep, "class_embedding_rep"); 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); // class_embedding_rep = ggml_cast(ctx0, class_embedding_rep, inp->type);
// print_ggml_tensor(class_embedding_rep, true, "class_embedding_rep_aft_casting"); // print_ggml_tensor(class_embedding_rep, true, "class_embedding_rep_aft_casting");
struct ggml_tensor *embeddings = ggml_concat(ctx0, class_embedding_rep, inp); struct ggml_tensor *embeddings = ggml_concat(ctx0, class_embedding_rep, inp);
ggml_set_name(embeddings, "embeddings_after_concat"); ggml_set_name(embeddings, "embeddings_after_concat");
@@ -1009,11 +1009,12 @@ struct CLIPVisionModel {
// struct ggml_tensor * positions = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, num_positions); // struct ggml_tensor * positions = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, num_positions);
// print_ggml_tensor(embeddings, true, "embeddings_bef_add"); // print_ggml_tensor(embeddings, true, "embeddings_bef_add");
// print_ggml_tensor(ggml_get_rows(ctx0, position_embeddings, positions), true, "embeddings_add_src1"); // print_ggml_tensor(ggml_get_rows(ctx0, position_embeddings, positions), true, "position_embeddings_bef_add");
// print_ggml_tensor(ggml_repeat(ctx0, ggml_get_rows(ctx0, position_embeddings, positions), embeddings), true, "embeddings_add_src1"); // print_ggml_tensor(ggml_repeat(ctx0, ggml_get_rows(ctx0, position_embeddings, positions), embeddings), true, "embeddings_add_src1");
// embeddings = ggml_cont(ctx0, ggml_permute(ctx0, embeddings, 0, 1, 3, 2)); // embeddings = ggml_cont(ctx0, ggml_permute(ctx0, embeddings, 0, 1, 3, 2));
embeddings = embeddings =
ggml_add(ctx0, embeddings, ggml_repeat(ctx0, ggml_get_rows(ctx0, position_embeddings, positions), embeddings)); // 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"); ggml_set_name(embeddings, "embeddings_after_add");
// print_ggml_tensor(embeddings, true, "embeddings_after_add"); // print_ggml_tensor(embeddings, true, "embeddings_after_add");
ggml
+1 -1
Submodule ggml updated: 2f3b12fbd6...f826935f6b.
ggml_extend.hpp
+1
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@@ -230,6 +230,7 @@ __STATIC_INLINE__ void sd_image_to_tensor(const uint8_t* image_data,
ggml_tensor_set_f32(output, pixel_val, ix, iy, k); ggml_tensor_set_f32(output, pixel_val, ix, iy, k);
} }
} }
} }
} }
pmid.hpp
+1
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@@ -205,6 +205,7 @@ struct FuseModule{
// # slice out the image token embeddings // # slice out the image token embeddings
struct ggml_tensor * image_token_embeds = ggml_get_rows(ctx, prompt_embeds, class_tokens_mask_pos); struct ggml_tensor * image_token_embeds = ggml_get_rows(ctx, prompt_embeds, class_tokens_mask_pos);
// print_ggml_tensor(image_token_embeds, true, "image_token_embeds"); // print_ggml_tensor(image_token_embeds, true, "image_token_embeds");
// print_ggml_tensor(valid_id_embeds, true, "valid_id_embeds");
struct ggml_tensor *stacked_id_embeds = fuse_fn(ctx, image_token_embeds, valid_id_embeds); struct ggml_tensor *stacked_id_embeds = fuse_fn(ctx, image_token_embeds, valid_id_embeds);
// print_ggml_tensor(stacked_id_embeds, true, "stacked_id_embeds_before_concat"); // print_ggml_tensor(stacked_id_embeds, true, "stacked_id_embeds_before_concat");
stable-diffusion.cpp
+11 -6
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@@ -742,6 +742,7 @@ public:
const std::vector<float>& sigmas, const std::vector<float>& sigmas,
int start_merge_step, int start_merge_step,
ggml_tensor* c_id, ggml_tensor* c_id,
ggml_tensor* c_vec_id,
float control_strength) { float control_strength) {
size_t steps = sigmas.size() - 1; size_t steps = sigmas.size() - 1;
// x_t = load_tensor_from_file(work_ctx, "./rand0.bin"); // x_t = load_tensor_from_file(work_ctx, "./rand0.bin");
@@ -816,6 +817,7 @@ public:
if (step <= start_merge_step) if (step <= start_merge_step)
diffusion_model.compute(out_cond, n_threads, noised_input, NULL, c, control_net.controls, control_strength, t_emb, c_vector); diffusion_model.compute(out_cond, n_threads, noised_input, NULL, c, control_net.controls, control_strength, t_emb, c_vector);
else else
// diffusion_model.compute(out_cond, n_threads, noised_input, NULL, c_id, control_net.controls, control_strength, t_emb, c_vec_id);
diffusion_model.compute(out_cond, n_threads, noised_input, NULL, c_id, control_net.controls, control_strength, t_emb, c_vector); diffusion_model.compute(out_cond, n_threads, noised_input, NULL, c_id, control_net.controls, control_strength, t_emb, c_vector);
}else{ }else{
diffusion_model.compute(out_cond, n_threads, noised_input, NULL, c, control_net.controls, control_strength, t_emb, c_vector); diffusion_model.compute(out_cond, n_threads, noised_input, NULL, c, control_net.controls, control_strength, t_emb, c_vector);
@@ -1475,11 +1477,11 @@ sd_image_t* txt2img(sd_ctx_t* sd_ctx,
// ggml_tensor* class_tokens_mask = NULL; // ggml_tensor* class_tokens_mask = NULL;
std::vector<bool> class_tokens_mask; std::vector<bool> class_tokens_mask;
if(sd_ctx->sd->stacked_id){ if(sd_ctx->sd->stacked_id){
int32_t width = input_id_images[0]->width; int32_t w = input_id_images[0]->width;
int32_t height = input_id_images[0]->height; int32_t h = input_id_images[0]->height;
int32_t channels = input_id_images[0]->channel; int32_t channels = input_id_images[0]->channel;
int32_t num_input_images = input_id_images.size(); int32_t num_input_images = input_id_images.size();
init_img = ggml_new_tensor_4d(work_ctx, GGML_TYPE_F32, width, height, channels, num_input_images); init_img = ggml_new_tensor_4d(work_ctx, GGML_TYPE_F32, w, h, channels, num_input_images);
// TODO: move these to somewhere else and be user settable // TODO: move these to somewhere else and be user settable
float mean[] = {0.48145466, 0.4578275, 0.40821073}; float mean[] = {0.48145466, 0.4578275, 0.40821073};
float std[] = {0.26862954, 0.26130258, 0.27577711}; float std[] = {0.26862954, 0.26130258, 0.27577711};
@@ -1557,12 +1559,14 @@ sd_image_t* txt2img(sd_ctx_t* sd_ctx,
int start_merge_step = -1; int start_merge_step = -1;
if(sd_ctx->sd->stacked_id){ if(sd_ctx->sd->stacked_id){
int style_strength_ratio = 20; float style_strength_ratio = 20.f;
start_merge_step = int(style_strength_ratio / 100 * sample_steps); start_merge_step = int(style_strength_ratio / 100.f * sample_steps);
if(start_merge_step > 30) if(start_merge_step > 30)
start_merge_step = 30; start_merge_step = 30;
LOG_INFO("PHOTOMAKER: start_merge_step: %d", start_merge_step);
} }
struct ggml_tensor* x_0 = sd_ctx->sd->sample(work_ctx, struct ggml_tensor* x_0 = sd_ctx->sd->sample(work_ctx,
x_t, x_t,
NULL, NULL,
@@ -1576,6 +1580,7 @@ sd_image_t* txt2img(sd_ctx_t* sd_ctx,
sigmas, sigmas,
start_merge_step, start_merge_step,
prompts_embeds, prompts_embeds,
pooled_prompts_embeds,
control_strength); control_strength);
// struct ggml_tensor* x_0 = load_tensor_from_file(ctx, "samples_ddim.bin"); // struct ggml_tensor* x_0 = load_tensor_from_file(ctx, "samples_ddim.bin");
// print_ggml_tensor(x_0); // print_ggml_tensor(x_0);
@@ -1731,7 +1736,7 @@ sd_image_t* img2img(sd_ctx_t* sd_ctx,
LOG_INFO("sampling using %s method", sampling_methods_str[sample_method]); LOG_INFO("sampling using %s method", sampling_methods_str[sample_method]);
struct ggml_tensor* x_0 = sd_ctx->sd->sample(work_ctx, init_latent, noise, c, c_vector, uc, struct ggml_tensor* x_0 = sd_ctx->sd->sample(work_ctx, init_latent, noise, c, c_vector, uc,
uc_vector, NULL, cfg_scale, sample_method, sigma_sched, uc_vector, NULL, cfg_scale, sample_method, sigma_sched,
-1, NULL, -1, NULL, NULL,
1.0f); 1.0f);
// struct ggml_tensor *x_0 = load_tensor_from_file(ctx, "samples_ddim.bin"); // struct ggml_tensor *x_0 = load_tensor_from_file(ctx, "samples_ddim.bin");
// print_ggml_tensor(x_0); // print_ggml_tensor(x_0);