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

feat: Control Net support + Textual Inversion (embeddings) (#131)

Browse Source 
* add controlnet to pipeline

* add cli params

* control strength cli param

* cli param keep controlnet in cpu

* add Textual Inversion

* add canny preprocessor

* refactor: change ggml_type_sizef to ggml_row_size

* process hint once time

* ignore the embedding name case

---------

Co-authored-by: leejet <leejet714@gmail.com>
This commit is contained in:
Steward Garcia
2024-01-29 09:38:51 -05:00
committed by GitHub
parent c6071fa82f
commit 36ec16ac99
20 changed files with 1823 additions and 589 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
model.cpp
View File

@@ -89,7 +89,6 @@ const char* unused_tensors[] = {
"model_ema.decay",
"model_ema.num_updates",
"model_ema.diffusion_model",
"control_model",
"embedding_manager",
"denoiser.sigmas",
};
@@ -376,6 +375,11 @@ std::string convert_tensor_name(const std::string& name) {
new_name = convert_open_clip_to_hf_clip(name);
} else if (starts_with(name, "first_stage_model.decoder")) {
new_name = convert_vae_decoder_name(name);
} else if (starts_with(name, "control_model.")) { // for controlnet pth models
size_t pos = name.find('.');
if (pos != std::string::npos) {
new_name = name.substr(pos + 1);
}
} else if (starts_with(name, "lora_")) { // for lora
size_t pos = name.find('.');
if (pos != std::string::npos) {
@@ -1329,11 +1333,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, ggml_backend
size_t nbytes_to_read = tensor_storage.nbytes_to_read();
if (dst_tensor->buffer == NULL || ggml_backend_is_cpu(backend)
#ifdef SD_USE_METAL
|| ggml_backend_is_metal(backend)
#endif
) {
if (dst_tensor->buffer == NULL || ggml_backend_buffer_is_host(dst_tensor->buffer)) {
// for the CPU and Metal backend, we can copy directly into the tensor
if (tensor_storage.type == dst_tensor->type) {
GGML_ASSERT(ggml_nbytes(dst_tensor) == tensor_storage.nbytes());