Merge pull request #30 from wwoodsTM/test-dry-sampler

Working implementation of DRY with one key issue I could use help with

common/sampling.cpp

@@ -433,10 +433,10 @@ static llama_token_data_array llama_sampling_prepare_impl(
     {
         const int penalty_tokens_used_size = std::min(penalty_tokens.size(), (size_t)dry_penalty_last_n);
         if (penalty_tokens_used_size) {
-            llama_sample_dry(&cur_p,
+            llama_sample_dry(ctx_main, &cur_p,
                         penalty_tokens.data() + penalty_tokens.size() - penalty_tokens_used_size,
                         penalty_tokens_used_size, dry_base, dry_multiplier, dry_allowed_length,
-                        params.dry_seq_breakers.data(), params.dry_seq_breakers.size());
+                        params.dry_seq_breakers);
         }
     }
 

common/sampling.h

@@ -46,6 +46,8 @@ typedef struct llama_sampling_params {
     uint32_t    dry_allowed_length    = 2;
     int32_t     dry_penalty_last_n    = -1;                 // DRY last n tokens to penalize (0 = disable penalty, -1 = context size)
 
+    std::vector<std::string> dry_seq_breakers = {"\n", ":", "\"", "*"};     // default sequence breakers for DRY
+
     std::vector<llama_sampler_type> samplers_sequence = {
         llama_sampler_type::TOP_K,
         llama_sampler_type::TFS_Z,
@@ -63,9 +65,8 @@ typedef struct llama_sampling_params {
     float       cfg_scale     = 1.f; // how strong is guidance
 
     std::unordered_map<llama_token, float> logit_bias; // logit bias for specific tokens
-
     std::vector<llama_token> penalty_prompt_tokens;
-    std::vector<llama_token> dry_seq_breakers; // sequence breakers for the DRY sampler
+
     bool                     use_penalty_prompt_tokens = false;
 } llama_sampling_params;
 

include/llama.h

@@ -1085,16 +1085,17 @@ extern "C" {
                            float   p,
                           size_t   min_keep);
 
-    ///  @details DRY sampler as described in: https://github.com/oobabooga/text-generation-webui/pull/5677
-    LLAMA_API void llama_sample_dry(
-          llama_token_data_array * candidates,
-               const llama_token * last_tokens,
-                          size_t   last_tokens_size,
-                           float   dry_base,
-                           float   dry_multiplier,
-                             int   dry_allowed_length,
-               const llama_token * dry_seq_breakers,
-                          size_t   dry_seq_breakers_size);
+    // ///  @details DRY sampler as described in: https://github.com/oobabooga/text-generation-webui/pull/5677
+    // LLAMA_API void llama_sample_dry(
+    //         struct llama_context * ctx,
+    //       llama_token_data_array * candidates,
+    //            const llama_token * last_tokens,
+    //                       size_t   last_tokens_size,
+    //                        float   dry_base,
+    //                        float   dry_multiplier,
+    //                          int   dry_allowed_length,
+    //             const std::vector<std::string>
+    //                              & dry_seq_breakers);
 
     /// @details Tail Free Sampling described in https://www.trentonbricken.com/Tail-Free-Sampling/.
     LLAMA_API void llama_sample_tail_free(
@@ -1246,6 +1247,18 @@ std::pair<std::vector<uint32_t>, llama_partial_utf8> decode_utf8(
 // This is a temporary workaround in order to fix race conditions when sampling with multiple sequences.
 llama_token llama_sample_token_with_rng(struct llama_context * ctx, llama_token_data_array * candidates, std::mt19937 & rng);
 
+///  @details DRY sampler as described in: https://github.com/oobabooga/text-generation-webui/pull/5677
+LLAMA_API void llama_sample_dry(
+        struct llama_context * ctx,
+        llama_token_data_array * candidates,
+            const llama_token * last_tokens,
+                        size_t   last_tokens_size,
+                        float   dry_base,
+                        float   dry_multiplier,
+                            int   dry_allowed_length,
+            const std::vector<std::string>
+                                & dry_seq_breakers);
+
 #endif // LLAMA_API_INTERNAL
 
 #endif // LLAMA_H

src/llama-sampling.cpp

@@ -232,94 +232,230 @@ void llama_sample_min_p_impl(struct llama_sampling * smpl, llama_token_data_arra
     }
 }
 
-void llama_sample_dry_impl(llama_token_data_array * candidates, const llama_token * last_tokens, size_t last_tokens_size, float dry_base, float dry_multiplier, int dry_allowed_length, const llama_token * dry_seq_breakers, size_t dry_seq_breakers_size) {
-    // skip dry sampler if we don't have a previous token
-    if (last_tokens_size < 1) return;
+std::vector<llama_token> llama_tokenize(
+  const struct llama_context * ctx,
+           const std::string & text,
+                        bool   add_special,
+                        bool   parse_special) {
+    return llama_tokenize(llama_get_model(ctx), text, add_special, parse_special);
+}
+
+std::vector<llama_token> llama_tokenize(
+    const struct llama_model * model,
+           const std::string & text,
+                        bool   add_special,
+                        bool   parse_special) {
+    // upper limit for the number of tokens
+    int n_tokens = text.length() + 2 * add_special;
+    std::vector<llama_token> result(n_tokens);
+    n_tokens = llama_tokenize(model, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
+    if (n_tokens < 0) {
+        result.resize(-n_tokens);
+        int check = llama_tokenize(model, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
+        GGML_ASSERT(check == -n_tokens);
+    } else {
+        result.resize(n_tokens);
+    }
+    return result;
+}
+
+std::string llama_detokenize(llama_context * ctx, const std::vector<llama_token> & tokens, bool special) {
+    std::string text;
+    text.resize(std::max(text.capacity(), tokens.size()));
+    int32_t n_chars = llama_detokenize(llama_get_model(ctx), tokens.data(), (int32_t)tokens.size(), &text[0], (int32_t)text.size(), false, special);
+    if (n_chars < 0) {
+        text.resize(-n_chars);
+        n_chars = llama_detokenize(llama_get_model(ctx), tokens.data(), (int32_t)tokens.size(), &text[0], (int32_t)text.size(), false, special);
+        GGML_ASSERT(n_chars <= (int32_t)text.size());  // whitespace trimming is performed after per-token detokenization
+    }
+
+    text.resize(n_chars);
+
+    // NOTE: the original tokenizer decodes bytes after collecting the pieces.
+    return text;
+}
+
+std::string llama_detokenize_single(llama_context * ctx, llama_token token, bool special) {
+    std::vector<llama_token> tokens = {token};
+    return llama_detokenize(ctx, tokens, special);
+}
 
-    // get the last token
-    auto last_token = last_tokens[last_tokens_size - 1];
+// Constants for preventing overflow
+const float FLOAT_MAX_LOG = 88.7228391f;
+const int MAX_CHAR_LEN = 40;
+const int MAX_SEQ_LEN = 20;
 
-    // if last token is part of the sequence breakers, skip whole sampler
-    if (std::find(dry_seq_breakers, dry_seq_breakers + dry_seq_breakers_size, last_token) != dry_seq_breakers + dry_seq_breakers_size) {
+
+void llama_sample_dry_impl(struct llama_context * ctx, llama_token_data_array * candidates, const llama_token * last_tokens, size_t last_tokens_size, float dry_base, float dry_multiplier, int dry_allowed_length, const std::vector<std::string> & dry_seq_breakers) {
+    if (last_tokens_size < 1) {
         return;
     }
 
-    // create an unordered map of "next tokens" <-> max match length
+    // Cache for token-to-string conversions
+    std::unordered_map<llama_token, std::string> token_to_string_cache;
+    // Store sequence breakers for more efficient lookup
+    std::unordered_multimap<std::string, std::vector<std::string>> restart_sequences;
+
+    auto detokenize_with_cache = [&](llama_token token) -> std::string {
+        auto it = token_to_string_cache.find(token);
+        if (it != token_to_string_cache.end()) {
+            return it->second;
+        }
+        std::string token_str = llama_detokenize_single(ctx, token, false);
+        token_to_string_cache[token] = token_str;
+        return token_str;
+    };
+
+    // Pre-process dry_seq_breakers
+    for (const auto& breaker : dry_seq_breakers) {
+        std::string breaker_trimmed = breaker.substr(0, MAX_CHAR_LEN);
+        std::vector<llama_token> tokens = llama_tokenize(ctx, breaker_trimmed, false, false);
+
+        if (!tokens.empty()) {
+            std::string head = detokenize_with_cache(tokens[0]);
+            std::vector<std::string> tail;
+
+            for (size_t i = 1; i < tokens.size() && i <= MAX_SEQ_LEN; ++i) {
+                tail.push_back(detokenize_with_cache(tokens[i]));
+            }
+            restart_sequences.emplace(head, tail);
+        }
+    }
+
+    // Find max repetition length considering restart sequences
+    int rep_limit = last_tokens_size;
+
+    for (size_t i = 0; i < last_tokens_size; ++i) {
+        size_t ix = last_tokens_size - 1 - i;
+        std::string token_str = detokenize_with_cache(last_tokens[ix]);
+
+        // Check if the token is a potential sequence breaker
+        auto its = restart_sequences.equal_range(token_str);
+        if (its.first == restart_sequences.end()) continue;
+
+        int longest_match = -1;
+        // Check all potential sequence breakers starting with this token
+        for (auto it = its.first; it != its.second; ++it) {
+            int seq_len = (int)it->second.size();
+            if (seq_len > longest_match && seq_len <= i) {
+                bool match = true;
+                // Check if the following tokens match the sequence breaker
+                for (size_t offset = 0; offset < seq_len; ++offset) {
+                    if (it->second[offset] != detokenize_with_cache(last_tokens[ix + 1 + offset])) {
+                        match = false;
+                        break;
+                    }
+                }
+                if (match) {
+                    longest_match = seq_len;
+                }
+            }
+        }
+
+        if (longest_match >= 0) {
+            rep_limit = static_cast<int>(i) - longest_match;
+            break;
+        }
+    }
+
+    if (rep_limit <= dry_allowed_length) {
+        return;
+    }
+
+    // Store max match length for each token
     std::unordered_map<llama_token, size_t> match_lengths;
 
-    // loop through each previous token (exclude the last token)
+    // Find repeated sequences
     for (size_t i = 0; i < last_tokens_size - 1; ++i) {
-        // skip if the compare token is not the same as the last token
-        if (last_tokens[i] != last_token) {
+        if (last_tokens[i] != last_tokens[last_tokens_size - 1]) {
             continue;
         }
 
-        // get the next token (i + 1 is always less than last_tokens_size)
         auto next_token = last_tokens[i + 1];
+        std::string next_token_str = detokenize_with_cache(next_token);
 
-        // if next token is part of the sequence breakers, skip
-        if (std::find(dry_seq_breakers, dry_seq_breakers + dry_seq_breakers_size, next_token) != dry_seq_breakers + dry_seq_breakers_size) {
+        // Skip if next token is a sequence breaker
+        auto its = restart_sequences.equal_range(next_token_str);
+        if (its.first != restart_sequences.end()) {
             continue;
         }
 
-        // try to extend the match backwards (match length starts at 1 because last token is already matched)
         size_t match_length = 1;
 
-        // loop through the previous tokens
+        // Extend match as far as possible
         for (;; match_length++) {
-            // if we have reached the start of our last tokens, break
-            if (i < match_length) break;
+            if (i < match_length || match_length > rep_limit) {
+                break;
+            }
 
-            // compare token starts at our prev index, going backwards by match length
             auto compare_token = last_tokens[i - match_length];
+            std::string compare_token_str = detokenize_with_cache(compare_token);
 
-            // head token starts at the end of last tokens, going backwards by match length, minus 1 because we start at the last token itself
             auto head_token = last_tokens[last_tokens_size - 1 - match_length];
+            std::string head_token_str = detokenize_with_cache(head_token);
 
-            // break out of the match if any tokens don't match
-            if (compare_token != head_token) {
+            if (compare_token_str != head_token_str) {
                 break;
             }
 
-            // if compare token is part of the sequence breakers, break out of the match
-            if (std::find(dry_seq_breakers, dry_seq_breakers + dry_seq_breakers_size, compare_token) != dry_seq_breakers + dry_seq_breakers_size) {
+            // Check if we've hit a sequence breaker
+            its = restart_sequences.equal_range(compare_token_str);
+            if (its.first != restart_sequences.end()) {
                 break;
             }
         }
 
-        // Check if the next token exists in the map
+        // Update max match length for this token
         auto it = match_lengths.find(next_token);
-
         if (it == match_lengths.end()) {
-            // Key does not exist, insert the new value
             match_lengths[next_token] = match_length;
         } else {
-            // Key exists, update it with the max of the new value or the existing value
             it->second = std::max(it->second, match_length);
         }
     }
 
-    // apply penalties
+    // Calculate max safe exponent
+    int max_exponent = 0;
+    if (dry_base > 1.000001f) {
+        max_exponent = static_cast<int>(FLOAT_MAX_LOG / log(dry_base));
+    }
+
+#ifdef DEBUG
+    LLAMA_LOG_INFO("DRY Sampling parameters:\n");
+    LLAMA_LOG_INFO("  dry_base: %f\n", dry_base);
+    LLAMA_LOG_INFO("  dry_multiplier: %f\n", dry_multiplier);
+    LLAMA_LOG_INFO("  dry_allowed_length: %d\n", dry_allowed_length);
+    LLAMA_LOG_INFO("  max_exponent: %d\n", max_exponent);
+    LLAMA_LOG_INFO("DRY penalties [");
+#endif
+
+    // Apply penalties
     for (const auto& pair : match_lengths) {
         auto next_token = pair.first;
         auto match_length = pair.second;
 
-        // if the match length is greater than or equal to our allowed length in config, we apply penalities
-        if (match_length >= (size_t)dry_allowed_length) {
-
-            // find our next token in the candidates->data
+        if (match_length >= static_cast<size_t>(dry_allowed_length)) {
             for (size_t i = 0; i < candidates->size; ++i) {
                 if (candidates->data[i].id == next_token) {
-                    // calculate the penalty
-                    float penalty = dry_multiplier * pow(dry_base, match_length - dry_allowed_length);
-
-                    // apply the dry penalty
+                    int repeat_exp = static_cast<int>(match_length - dry_allowed_length);
+                    if (max_exponent > 0 && repeat_exp > max_exponent) {
+                        repeat_exp = max_exponent;
+                    }
+                    float penalty = dry_multiplier * pow(dry_base, static_cast<float>(repeat_exp));
                     candidates->data[i].logit -= penalty;
+
+#ifdef DEBUG
+                    LLAMA_LOG_INFO("  Token %d: %s (Penalty: %.2f)", next_token, detokenize_with_cache(next_token).c_str(), penalty);
+#endif
                     break;
                 }
             }
         }
     }
+
+#ifdef DEBUG
+    LLAMA_LOG_INFO("]\n");
+#endif
 }
 
 void llama_sample_tail_free_impl(struct llama_sampling * smpl, llama_token_data_array * candidates, float z, size_t min_keep) {

src/llama-sampling.h

@@ -28,7 +28,11 @@ void llama_sample_softmax_impl  (struct llama_sampling * smpl, llama_token_data_
 void llama_sample_top_k_impl    (struct llama_sampling * smpl, llama_token_data_array * candidates, int32_t k, size_t min_keep);
 void llama_sample_top_p_impl    (struct llama_sampling * smpl, llama_token_data_array * candidates, float p, size_t min_keep);
 void llama_sample_min_p_impl    (struct llama_sampling * smpl, llama_token_data_array * candidates, float p, size_t min_keep);
-void llama_sample_dry_impl      (llama_token_data_array * candidates, const llama_token * last_tokens, size_t last_tokens_size, float dry_base, float dry_multiplier, int dry_allowed_length, const llama_token * dry_seq_breakers, size_t dry_seq_breakers_size);
+std::vector<llama_token> llama_tokenize(const struct llama_context * ctx, const std::string & text, bool   add_special, bool   parse_special);
+std::vector<llama_token> llama_tokenize(const struct llama_model * model, const std::string & text, bool   add_special, bool   parse_special);
+std::string llama_detokenize(llama_context * ctx, const std::vector<llama_token> & tokens, bool special);
+std::string llama_detokenize_single(llama_context * ctx, llama_token token, bool special);
+void llama_sample_dry_impl      (struct llama_context  * ctx,  llama_token_data_array * candidates, const llama_token * last_tokens, size_t last_tokens_size, float dry_base, float dry_multiplier, int dry_allowed_length, const std::vector<std::string> & dry_seq_breakers);
 void llama_sample_tail_free_impl(struct llama_sampling * smpl, llama_token_data_array * candidates, float z, size_t min_keep);
 void llama_sample_typical_impl  (struct llama_sampling * smpl, llama_token_data_array * candidates, float p, size_t min_keep);
 void llama_sample_entropy_impl  (struct llama_sampling * smpl, llama_token_data_array * candidates, float min_temp, float max_temp, float exponent_val);

src/llama.cpp

@@ -18948,8 +18948,8 @@ void llama_sample_min_p(struct llama_context * ctx, llama_token_data_array * can
     llama_sample_min_p_impl(ctx ? &ctx->sampling : nullptr, candidates, p, min_keep);
 }
 
-void llama_sample_dry(llama_token_data_array * candidates, const llama_token * last_tokens, size_t last_tokens_size, float dry_base, float dry_multiplier, int dry_allowed_length, const llama_token * dry_seq_breakers, size_t dry_seq_breakers_size) {
-    llama_sample_dry_impl(candidates, last_tokens, last_tokens_size, dry_base, dry_multiplier, dry_allowed_length, dry_seq_breakers, dry_seq_breakers_size);
+void llama_sample_dry(struct llama_context * ctx, llama_token_data_array * candidates, const llama_token * last_tokens, size_t last_tokens_size, float dry_base, float dry_multiplier, int dry_allowed_length, const std::vector<std::string> & dry_seq_breakers) {
+    llama_sample_dry_impl(ctx, candidates, last_tokens, last_tokens_size, dry_base, dry_multiplier, dry_allowed_length, dry_seq_breakers);
 }
 
 void llama_sample_tail_free(struct llama_context * ctx, llama_token_data_array * candidates, float z, size_t min_keep) {