DarthAffe/stable-diffusion.cpp
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fixed wtype issue; input images can only be 1 because issue with transformer when batch size > 1 (to be investigated)

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bssrdf committed 2024-02-11 12:54:18 -05:00
1 parent 807c340118
commit 5a13b48b6e
4 files changed
+83 -91
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pmid.hpp
+34 -36
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@@ -204,15 +204,15 @@ struct FuseModule{
struct ggml_tensor * valid_id_embeds = id_embeds;
// # slice out the image token embeddings
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");
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");
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){
@@ -220,24 +220,24 @@ struct FuseModule{
}else if(right){
stacked_id_embeds = ggml_concat(ctx, stacked_id_embeds, right);
}
print_ggml_tensor(stacked_id_embeds, true, "stacked_id_embeds_after_concat");
// print_ggml_tensor(stacked_id_embeds, true, "stacked_id_embeds_after_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_2");
print_ggml_tensor(class_tokens_mask, true, "class_tokens_mask");
print_ggml_tensor(prompt_embeds, true, "prompt_embeds");
// print_ggml_tensor(stacked_id_embeds, true, "stacked_id_embeds_after_permute_2");
// print_ggml_tensor(class_tokens_mask, true, "class_tokens_mask");
// print_ggml_tensor(prompt_embeds, true, "prompt_embeds");
// assert class_tokens_mask.sum() == stacked_id_embeds.shape[0], f"{class_tokens_mask.sum()} != {stacked_id_embeds.shape[0]}"
// prompt_embeds.masked_scatter_(class_tokens_mask[:, None], stacked_id_embeds.to(prompt_embeds.dtype))
// struct ggml_tensor *prompt_embeds_perm = ggml_cont(ctx, ggml_permute(ctx, prompt_embeds, 1, 0, 2, 3));
struct ggml_tensor *prompt_embeds_perm = ggml_cont(ctx, ggml_transpose(ctx, prompt_embeds));
print_ggml_tensor(prompt_embeds_perm, true, "prompt_embeds_perm");
// print_ggml_tensor(prompt_embeds_perm, true, "prompt_embeds_perm");
class_tokens_mask = ggml_repeat(ctx, class_tokens_mask, prompt_embeds_perm);
print_ggml_tensor(class_tokens_mask, true, "class_tokens_mask_repeat");
// print_ggml_tensor(class_tokens_mask, true, "class_tokens_mask_repeat");
class_tokens_mask = ggml_cont(ctx, ggml_transpose(ctx, class_tokens_mask));
print_ggml_tensor(class_tokens_mask, true, "class_tokens_mask_transpose");
// print_ggml_tensor(class_tokens_mask, true, "class_tokens_mask_transpose");
prompt_embeds = ggml_mul(ctx, prompt_embeds, class_tokens_mask);
print_ggml_tensor(prompt_embeds, true, "prompt_embeds_after_mul");
// print_ggml_tensor(prompt_embeds, true, "prompt_embeds_after_mul");
struct ggml_tensor * updated_prompt_embeds = ggml_add(ctx, prompt_embeds, stacked_id_embeds);
print_ggml_tensor(updated_prompt_embeds, true, "updated_prompt_embeds");
// print_ggml_tensor(updated_prompt_embeds, true, "updated_prompt_embeds");
// updated_prompt_embeds = prompt_embeds.view(batch_size, seq_length, -1)
return updated_prompt_embeds;
}
@@ -257,18 +257,18 @@ struct PhotoMakerIDEncoder : public GGMLModule {
fuse_module(2048) {
vision_model = CLIPVisionModel();
// fuse_module = FuseModule(2048);
// wtype = GGML_TYPE_F32;
}
// void init_params(ggml_context* ctx, ggml_backend_t backend, ggml_type wtype, ggml_allocr* alloc) {
void init_params() {
void init_params(ggml_type wtype) {
// LOG_INFO(" PMID wtype: %s", ggml_type_name(wtype));
ggml_allocr* alloc = ggml_allocr_new_from_buffer(params_buffer);
vision_model.init_params(params_ctx, backend, wtype, alloc);
fuse_module.init_params(params_ctx, wtype, alloc);
// visual_projection_2 = ggml_new_tensor_2d(params_ctx, wtype, 1280, 1024); // python [1024, 1280]
visual_projection_2 = ggml_new_tensor_2d(params_ctx, wtype, 1024, 1280); // python [1024, 1280]
visual_projection_2 = ggml_new_tensor_2d(params_ctx, wtype, 1024, 1280); // python [1024, 1280]
ggml_allocr_alloc(alloc, visual_projection_2);
ggml_allocr_free(alloc);
}
@@ -279,17 +279,15 @@ struct PhotoMakerIDEncoder : public GGMLModule {
tensors[prefix + "visual_projection_2.weight"] = visual_projection_2;
}
size_t calculate_mem_size() {
size_t calculate_mem_size() {
wtype = GGML_TYPE_F32;
// LOG_INFO(" PMID wtype: %s", ggml_type_name(wtype));
size_t mem_size = vision_model.calculate_mem_size(wtype);
LOG_INFO("pmid vision memory buffer size = %.2fMB ",
vision_model.calculate_mem_size(wtype) / 1024.0 / 1024.0);
mem_size += fuse_module.calculate_mem_size(wtype);
LOG_INFO("pmid fuse memory buffer size = %.2fMB ",
fuse_module.calculate_mem_size(wtype) / 1024.0 / 1024.0);
mem_size += ggml_row_size(wtype, 1280*1024);
LOG_INFO("pmid porject buffer size = %.2fMB ",
ggml_row_size(wtype, 1280*1024) / 1024.0 / 1024.0);
return mem_size;
}
@@ -325,15 +323,15 @@ struct PhotoMakerIDEncoder : public GGMLModule {
ggml_set_name(right, "right_input");
print_ggml_tensor(prompt_embeds, true, "prompt_embeds");
print_ggml_tensor(class_embedding_temp, true, "class_embedding_temp");
// print_ggml_tensor(prompt_embeds, true, "prompt_embeds");
// print_ggml_tensor(class_embedding_temp, true, "class_embedding_temp");
struct ggml_tensor *shared_id_embeds = vision_model.forward(ctx,
id_pixel_values,
cls,
class_embedding_temp,
positions
); // [batch_size, seq_length, hidden_size]
print_ggml_tensor(shared_id_embeds, true, "shared_id_embeds");
// print_ggml_tensor(shared_id_embeds, true, "shared_id_embeds");
// if(class_tokens_mask->backend == GGML_BACKEND_GPU){
// int *ctm = (int *)malloc(class_tokens_mask->ne[0]);
@@ -350,20 +348,20 @@ struct PhotoMakerIDEncoder : public GGMLModule {
// id_embeds_2 = id_embeds_2.view(b, num_inputs, 1, -1)
// id_embeds = torch.cat((id_embeds, id_embeds_2), dim=-1)
print_ggml_tensor(id_embeds, true, "id_embeds");
print_ggml_tensor(id_embeds_2, true, "id_embeds_2");
// print_ggml_tensor(id_embeds, true, "id_embeds");
// print_ggml_tensor(id_embeds_2, true, "id_embeds_2");
id_embeds = ggml_cont(ctx, ggml_permute(ctx, id_embeds, 2, 0, 1, 3));
id_embeds_2 = ggml_cont(ctx, ggml_permute(ctx, id_embeds_2, 2, 0, 1, 3));
print_ggml_tensor(id_embeds, true, "id_embeds_after_perm");
print_ggml_tensor(id_embeds_2, true, "id_embeds_2_after_perm");
// print_ggml_tensor(id_embeds, true, "id_embeds_after_perm");
// print_ggml_tensor(id_embeds_2, true, "id_embeds_2_after_perm");
id_embeds = ggml_concat(ctx, id_embeds, id_embeds_2); // [batch_size, seq_length, 1, 2048] check whether concat at dim 2 is right
print_ggml_tensor(id_embeds, true, "id_embeds_after_cat");
// print_ggml_tensor(id_embeds, true, "id_embeds_after_cat");
id_embeds = ggml_cont(ctx, ggml_permute(ctx, id_embeds, 1, 2, 0, 3));
print_ggml_tensor(id_embeds, true, "id_embeds_after_cat+perm");
// print_ggml_tensor(id_embeds, true, "id_embeds_after_cat+perm");
struct ggml_tensor * updated_prompt_embeds = fuse_module.forward(ctx,
@@ -371,7 +369,7 @@ struct PhotoMakerIDEncoder : public GGMLModule {
class_tokens_mask,
class_tokens_mask_pos,
left, right);
print_ggml_tensor(updated_prompt_embeds, true, "updated_prompt_embeds_returned");
// print_ggml_tensor(updated_prompt_embeds, true, "updated_prompt_embeds_returned");
return updated_prompt_embeds;
@@ -508,7 +506,7 @@ struct PhotoMakerIDEncoder : public GGMLModule {
positions,
left, right
);
print_ggml_tensor(updated_prompt_embeds, true, "updated_prompt_embeds_returned_forward");
// print_ggml_tensor(updated_prompt_embeds, true, "updated_prompt_embeds_returned_forward");
ggml_build_forward_expand(gf, updated_prompt_embeds);
// ggml_graph_dump_dot(gf, NULL, "id_encoder.dot");
ggml_free(ctx0);