upstream-archive/stable-diffusion.cpp
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add a convert_token_to_id function for photomaker to extract trigger word's token id

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bssrdf
2024-02-06 16:17:07 -05:00
parent df7f64243b
commit ad7ec45ec1
2 changed files with 35 additions and 1 deletions
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30
clip.hpp
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@@ -166,7 +166,7 @@ public:
}
encoder_len = i;
auto it = encoder.find(utf8_to_utf32("img"));
auto it = encoder.find(utf8_to_utf32("img</w>"));
if (it != encoder.end()) {
printf(" trigger word img already in vocab \n");
}else{
@@ -1215,6 +1215,34 @@ struct FrozenCLIPEmbedderWithCustomWords : public GGMLModule {
return tokenize(text, text_model.max_position_embeddings, padding);
}
std::vector<int> convert_token_to_id(std::string text) {
auto on_new_token_cb = [&](std::string& str, std::vector<int32_t>& bpe_tokens) -> bool {
size_t word_end = str.find(",");
std::string embd_name = word_end == std::string::npos ? str : str.substr(0, word_end);
embd_name = trim(embd_name);
std::string embd_path = get_full_path(text_model.embd_dir, embd_name + ".pt");
if (embd_path.size() == 0) {
embd_path = get_full_path(text_model.embd_dir, embd_name + ".ckpt");
}
if (embd_path.size() == 0) {
embd_path = get_full_path(text_model.embd_dir, embd_name + ".safetensors");
}
if (embd_path.size() > 0) {
if (text_model.load_embedding(embd_name, embd_path, bpe_tokens)) {
if (word_end != std::string::npos) {
str = str.substr(word_end);
} else {
str = "";
}
return true;
}
}
return false;
};
std::vector<int> curr_tokens = tokenizer.encode(text, on_new_token_cb);
return curr_tokens;
}
std::pair<std::vector<int>, std::vector<float>> tokenize(std::string text,
size_t max_length = 0,
bool padding = false) {

6
stable-diffusion.cpp
View File

@@ -585,6 +585,12 @@ public:
int height,
bool force_zero_embeddings = false) {
cond_stage_model.set_clip_skip(clip_skip);
auto image_tokens = cond_stage_model.convert_token_to_id(trigger_word);
printf(" length of image tokens: %lu \n", image_tokens.size());
if(image_tokens.size() == 1){
printf(" image token id is: %d \n", image_tokens[0]);
}
auto tokens_and_weights = cond_stage_model.tokenize(text, true);
std::vector<int>& tokens = tokens_and_weights.first;
std::vector<float>& weights = tokens_and_weights.second;