feat: implement the complete bpe function (#119)

* implement the complete bpe function
---------

Co-authored-by: leejet <leejet714@gmail.com>

Author: Cyberhan123

.clang-format

@@ -7,7 +7,7 @@ IndentCaseLabels: false
 ColumnLimit: 0
 AccessModifierOffset: -4
 NamespaceIndentation: All
-FixNamespaceComments: false 
+FixNamespaceComments: false
 AlignAfterOpenBracket: true
 AlignConsecutiveAssignments: true
 IndentCaseLabels: true

README.md

@@ -51,7 +51,6 @@ Inference of [Stable Diffusion](https://github.com/CompVis/stable-diffusion) in
     - The current implementation of ggml_conv_2d is slow and has high memory usage
     - Implement Winograd Convolution 2D for 3x3 kernel filtering
 - [ ] Continuing to reduce memory usage (quantizing the weights of ggml_conv_2d)
-- [ ] Implement BPE Tokenizer
 - [ ] Implement [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN/tree/master) upscaler
 - [ ] k-quants support
 

stable-diffusion.cpp

@@ -520,7 +520,6 @@ std::vector<std::pair<int, std::u32string>> bytes_to_unicode() {
 }
 
 // Ref: https://github.com/openai/CLIP/blob/main/clip/simple_tokenizer.py
-// TODO: implement bpe
 class CLIPTokenizer {
 private:
     SDVersion version = VERSION_1_x;
@@ -547,6 +546,21 @@ class CLIPTokenizer {
         return text;
     }
 
+    static std::set<std::pair<std::u32string, std::u32string>> get_pairs(const std::vector<std::u32string>& subwords) {
+        std::set<std::pair<std::u32string, std::u32string>> pairs;
+        if (subwords.size() == 0) {
+            return pairs;
+        }
+        std::u32string prev_subword = subwords[0];
+        for (int i = 1; i < subwords.size(); i++) {
+            std::u32string subword = subwords[i];
+            std::pair<std::u32string, std::u32string> pair(prev_subword, subword);
+            pairs.insert(pair);
+            prev_subword = subword;
+        }
+        return pairs;
+    }
+
 public:
     CLIPTokenizer(SDVersion version = VERSION_1_x)
         : version(version) {}
@@ -565,7 +579,9 @@ class CLIPTokenizer {
             merges.push_back(merges_utf32_str.substr(start, pos - start));
             start = pos + 1;
         }
-        merges = std::vector<std::u32string>(merges.begin() + 1, merges.begin() + 49152 - 256 - 2 + 1);
+        // LOG_DEBUG("merges size %llu", merges.size());
+        GGML_ASSERT(merges.size() == 48895);
+        merges = std::vector<std::u32string>(merges.begin() + 1, merges.end());
         std::vector<std::pair<std::u32string, std::u32string>> merge_pairs;
         for (const auto& merge : merges) {
             size_t space_pos = merge.find(' ');
@@ -596,14 +612,79 @@ class CLIPTokenizer {
         }
     };
 
-    std::u32string bpe(std::u32string token) {
-        std::u32string word = token + utf8_to_utf32("</w>");
-        if (encoder.find(word) != encoder.end()) {
-            return word;
-        } else if (encoder.find(token) != encoder.end()) {
-            return token;
+    std::u32string bpe(const std::u32string& token) {
+        std::vector<std::u32string> word;
+
+        for (int i = 0; i < token.size() - 1; i++) {
+            word.emplace_back(1, token[i]);
+        }
+        word.push_back(token.substr(token.size() - 1) + utf8_to_utf32("</w>"));
+
+        std::set<std::pair<std::u32string, std::u32string>> pairs = get_pairs(word);
+
+        if (pairs.empty()) {
+            return token + utf8_to_utf32("</w>");
         }
-        return utf8_to_utf32(UNK_TOKEN);
+
+        while (true) {
+            auto min_pair_iter = std::min_element(pairs.begin(),
+                                                  pairs.end(),
+                                                  [&](const std::pair<std::u32string, std::u32string>& a,
+                                                      const std::pair<std::u32string, std::u32string>& b) {
+                                                      if (bpe_ranks.find(a) == bpe_ranks.end()) {
+                                                          return false;
+                                                      } else if (bpe_ranks.find(b) == bpe_ranks.end()) {
+                                                          return true;
+                                                      }
+                                                      return bpe_ranks.at(a) < bpe_ranks.at(b);
+                                                  });
+
+            const std::pair<std::u32string, std::u32string>& bigram = *min_pair_iter;
+
+            if (bpe_ranks.find(bigram) == bpe_ranks.end()) {
+                break;
+            }
+
+            std::u32string first  = bigram.first;
+            std::u32string second = bigram.second;
+            std::vector<std::u32string> new_word;
+            int32_t i = 0;
+
+            while (i < word.size()) {
+                auto it = std::find(word.begin() + i, word.end(), first);
+                if (it == word.end()) {
+                    new_word.insert(new_word.end(), word.begin() + i, word.end());
+                    break;
+                }
+                new_word.insert(new_word.end(), word.begin() + i, it);
+                i = static_cast<int32_t>(std::distance(word.begin(), it));
+
+                if (word[i] == first && i < static_cast<int32_t>(word.size()) - 1 && word[i + 1] == second) {
+                    new_word.push_back(first + second);
+                    i += 2;
+                } else {
+                    new_word.push_back(word[i]);
+                    i += 1;
+                }
+            }
+
+            word = new_word;
+
+            if (word.size() == 1) {
+                break;
+            }
+            pairs = get_pairs(word);
+        }
+
+        std::u32string result;
+        for (int i = 0; i < word.size(); i++) {
+            result += word[i];
+            if (i != word.size() - 1) {
+                result += utf8_to_utf32(" ");
+            }
+        }
+
+        return result;
     }
 
     std::vector<int> tokenize(std::string text, size_t max_length = 0, bool padding = false) {

stable-diffusion.h

@@ -5,6 +5,8 @@
 #include <string>
 #include <vector>
 
+#include "ggml/ggml.h"
+
 enum RNGType {
     STD_DEFAULT_RNG,
     CUDA_RNG
@@ -42,10 +44,12 @@ class StableDiffusion {
                     bool free_params_immediately = false,
                     std::string lora_model_dir   = "",
                     RNGType rng_type             = STD_DEFAULT_RNG);
+
     bool load_from_file(const std::string& model_path,
                         const std::string& vae_path,
                         ggml_type wtype,
                         Schedule d = DEFAULT);
+
     std::vector<uint8_t*> txt2img(
         std::string prompt,
         std::string negative_prompt,