feat: add SDXL support (#117)
* add SDXL support * fix the issue with generating large images
This commit is contained in:
leejet
GitHub
parent
004dfbef27
commit
78ad76f3f4
2
.gitmodules
vendored
2
.gitmodules
vendored
@ -1,3 +1,3 @@
|
||||
[submodule "ggml"]
|
||||
path = ggml
|
||||
url = https://github.com/FSSRepo/ggml.git
|
||||
url = https://github.com/leejet/ggml.git
|
||||
|
||||
@ -10,8 +10,8 @@ Inference of [Stable Diffusion](https://github.com/CompVis/stable-diffusion) in
|
||||
|
||||
- Plain C/C++ implementation based on [ggml](https://github.com/ggerganov/ggml), working in the same way as [llama.cpp](https://github.com/ggerganov/llama.cpp)
|
||||
- Super lightweight and without external dependencies
|
||||
- SD1.x and SD2.x support
|
||||
- [SD-Turbo](https://huggingface.co/stabilityai/sd-turbo) support
|
||||
- SD1.x, SD2.x and SDXL support
|
||||
- [SD-Turbo](https://huggingface.co/stabilityai/sd-turbo) and [SDXL-Turbo](https://huggingface.co/stabilityai/sdxl-turbo) support
|
||||
- 16-bit, 32-bit float support
|
||||
- 4-bit, 5-bit and 8-bit integer quantization support
|
||||
- Accelerated memory-efficient CPU inference
|
||||
@ -302,3 +302,4 @@ Thank you to all the people who have already contributed to stable-diffusion.cpp
|
||||
- [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)
|
||||
- [k-diffusion](https://github.com/crowsonkb/k-diffusion)
|
||||
- [latent-consistency-model](https://github.com/luosiallen/latent-consistency-model)
|
||||
- [generative-models](https://github.com/Stability-AI/generative-models/)
|
||||
|
||||
2
ggml
2
ggml
@ -1 +1 @@
|
||||
Subproject commit a0c2ec77a5ef8e630aff65bc535d13b9805cb929
|
||||
Subproject commit e5d3412fa2ea3de8c4a696c03dce73c470442dc1
|
||||
48
model.cpp
48
model.cpp
@ -78,8 +78,9 @@ const char* unused_tensors[] = {
|
||||
"cond_stage_model.transformer.text_model.embeddings.position_ids",
|
||||
"cond_stage_model.model.logit_scale",
|
||||
"cond_stage_model.model.text_projection",
|
||||
"conditioner.embedders.0.transformer.text_model.embeddings.position_ids",
|
||||
"conditioner.embedders.0.model.logit_scale",
|
||||
"conditioner.embedders.0.model.text_projection",
|
||||
"conditioner.embedders.1.model.logit_scale",
|
||||
"model.diffusion_model.time_embedding.cond_proj.weight",
|
||||
"unet.time_embedding.cond_proj.weight",
|
||||
"model_ema.decay",
|
||||
@ -100,11 +101,11 @@ bool is_unused_tensor(std::string name) {
|
||||
}
|
||||
|
||||
std::unordered_map<std::string, std::string> open_clip_to_hf_clip_model = {
|
||||
{"cond_stage_model.model.ln_final.bias", "cond_stage_model.transformer.text_model.final_layer_norm.bias"},
|
||||
{"cond_stage_model.model.ln_final.weight", "cond_stage_model.transformer.text_model.final_layer_norm.weight"},
|
||||
{"cond_stage_model.model.positional_embedding", "cond_stage_model.transformer.text_model.embeddings.position_embedding.weight"},
|
||||
{"cond_stage_model.model.token_embedding.weight", "cond_stage_model.transformer.text_model.embeddings.token_embedding.weight"},
|
||||
|
||||
{"model.ln_final.bias", "transformer.text_model.final_layer_norm.bias"},
|
||||
{"model.ln_final.weight", "transformer.text_model.final_layer_norm.weight"},
|
||||
{"model.positional_embedding", "transformer.text_model.embeddings.position_embedding.weight"},
|
||||
{"model.token_embedding.weight", "transformer.text_model.embeddings.token_embedding.weight"},
|
||||
{"model.text_projection", "transformer.text_model.text_projection"},
|
||||
};
|
||||
|
||||
std::unordered_map<std::string, std::string> open_clip_to_hk_clip_resblock = {
|
||||
@ -133,11 +134,21 @@ std::unordered_map<std::string, std::string> vae_decoder_name_map = {
|
||||
|
||||
std::string convert_open_clip_to_hf_clip(const std::string& name) {
|
||||
std::string new_name = name;
|
||||
std::string prefix;
|
||||
if (starts_with(new_name, "conditioner.embedders.0.")) {
|
||||
new_name = "cond_stage_model." + new_name.substr(strlen("conditioner.embedders.0."));
|
||||
prefix = "cond_stage_model.";
|
||||
new_name = new_name.substr(strlen("conditioner.embedders.0."));
|
||||
} else if (starts_with(new_name, "conditioner.embedders.1.")) {
|
||||
prefix = "cond_stage_model.1.";
|
||||
new_name = new_name.substr(strlen("conditioner.embedders.0."));
|
||||
} else if (starts_with(new_name, "cond_stage_model.")) {
|
||||
prefix = "cond_stage_model.";
|
||||
new_name = new_name.substr(strlen("cond_stage_model."));
|
||||
} else {
|
||||
return new_name;
|
||||
}
|
||||
std::string open_clip_resblock_prefix = "cond_stage_model.model.transformer.resblocks.";
|
||||
std::string hf_clip_resblock_prefix = "cond_stage_model.transformer.text_model.encoder.layers.";
|
||||
std::string open_clip_resblock_prefix = "model.transformer.resblocks.";
|
||||
std::string hf_clip_resblock_prefix = "transformer.text_model.encoder.layers.";
|
||||
|
||||
if (open_clip_to_hf_clip_model.find(new_name) != open_clip_to_hf_clip_model.end()) {
|
||||
new_name = open_clip_to_hf_clip_model[new_name];
|
||||
@ -156,7 +167,7 @@ std::string convert_open_clip_to_hf_clip(const std::string& name) {
|
||||
}
|
||||
}
|
||||
|
||||
return new_name;
|
||||
return prefix + new_name;
|
||||
}
|
||||
|
||||
std::string convert_vae_decoder_name(const std::string& name) {
|
||||
@ -358,7 +369,7 @@ std::string convert_diffusers_name_to_compvis(const std::string& key, char seq)
|
||||
|
||||
std::string convert_tensor_name(const std::string& name) {
|
||||
std::string new_name;
|
||||
if (starts_with(name, "cond_stage_model.model") || starts_with(name, "conditioner.embedders.0.model")) {
|
||||
if (starts_with(name, "cond_stage_model.") || starts_with(name, "conditioner.embedders.")) {
|
||||
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);
|
||||
@ -419,7 +430,7 @@ void preprocess_tensor(TensorStorage tensor_storage,
|
||||
|
||||
tensor_storage.name = new_name;
|
||||
|
||||
if (starts_with(new_name, "cond_stage_model.transformer.text_model.encoder.layers.") &&
|
||||
if (new_name.find("transformer.text_model.encoder.layers.") != std::string::npos &&
|
||||
ends_with(new_name, "attn.in_proj_weight")) {
|
||||
size_t prefix_size = new_name.find("attn.in_proj_weight");
|
||||
std::string prefix = new_name.substr(0, prefix_size);
|
||||
@ -431,7 +442,7 @@ void preprocess_tensor(TensorStorage tensor_storage,
|
||||
|
||||
processed_tensor_storages.insert(processed_tensor_storages.end(), chunks.begin(), chunks.end());
|
||||
|
||||
} else if (starts_with(new_name, "cond_stage_model.transformer.text_model.encoder.layers.") &&
|
||||
} else if (new_name.find("transformer.text_model.encoder.layers.") != std::string::npos &&
|
||||
ends_with(new_name, "attn.in_proj_bias")) {
|
||||
size_t prefix_size = new_name.find("attn.in_proj_bias");
|
||||
std::string prefix = new_name.substr(0, prefix_size);
|
||||
@ -1163,15 +1174,20 @@ bool ModelLoader::init_from_ckpt_file(const std::string& file_path, const std::s
|
||||
}
|
||||
|
||||
SDVersion ModelLoader::get_sd_version() {
|
||||
// return VERSION_1_x;
|
||||
TensorStorage token_embedding_weight;
|
||||
for (auto& tensor_storage : tensor_storages) {
|
||||
if (tensor_storage.name.find("conditioner.embedders.1") != std::string::npos) {
|
||||
return VERSION_XL;
|
||||
}
|
||||
if (tensor_storage.name == "cond_stage_model.transformer.text_model.embeddings.token_embedding.weight" ||
|
||||
tensor_storage.name == "cond_stage_model.model.token_embedding.weight" ||
|
||||
tensor_storage.name == "text_model.embeddings.token_embedding.weight" ||
|
||||
tensor_storage.name == "te.text_model.embeddings.token_embedding.weight" ||
|
||||
tensor_storage.name == "conditioner.embedders.0.model.token_embedding.weight") {
|
||||
tensor_storage.name == "conditioner.embedders.0.model.token_embedding.weight" ||
|
||||
tensor_storage.name == "conditioner.embedders.0.transformer.text_model.embeddings.token_embedding.weight") {
|
||||
token_embedding_weight = tensor_storage;
|
||||
break;
|
||||
// break;
|
||||
}
|
||||
}
|
||||
if (token_embedding_weight.ne[0] == 768) {
|
||||
@ -1275,7 +1291,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, ggml_backend
|
||||
}
|
||||
|
||||
for (auto& tensor_storage : processed_tensor_storages) {
|
||||
// LOG_DEBUG("%s", name.c_str());
|
||||
// LOG_DEBUG("%s", tensor_storage.name.c_str());
|
||||
|
||||
ggml_tensor* dst_tensor = NULL;
|
||||
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
Loading…
Reference in New Issue
Block a user