added implementation of DRY sampler

common/sampling.cpp

@@ -267,13 +267,18 @@ static llama_token_data_array llama_sampling_prepare_impl(
 
     const int n_vocab = llama_n_vocab(llama_get_model(ctx_main));
 
+    // repetition penalties
     const int32_t penalty_last_n  = params.penalty_last_n < 0 ? params.n_prev : params.penalty_last_n;
     const float   penalty_repeat  = params.penalty_repeat;
     const float   penalty_freq    = params.penalty_freq;
     const float   penalty_present = params.penalty_present;
-
     const bool    penalize_nl     = params.penalize_nl;
 
+    // DRY sampler parameters
+    const float   dry_multiplier        = params.dry_multiplier;
+    const float   dry_base              = params.dry_base;
+    const int     dry_allowed_length    = params.dry_allowed_length;
+
     auto & prev = ctx_sampling->prev;
     auto & cur  = ctx_sampling->cur;
 
@@ -309,10 +314,20 @@ static llama_token_data_array llama_sampling_prepare_impl(
     if (penalty_tokens_used_size) {
         const float nl_logit = logits[llama_token_nl(llama_get_model(ctx_main))];
 
+        // repetition penalties
         llama_sample_repetition_penalties(ctx_main, &cur_p,
                 penalty_tokens.data() + penalty_tokens.size() - penalty_tokens_used_size,
                 penalty_tokens_used_size, penalty_repeat, penalty_freq, penalty_present);
 
+        // DRY penalties (multiplier > 0 means enabled)
+        if(dry_multiplier > 0.0f) {
+            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_sequence_breakers.data(), params.dry_sequence_breakers.size());
+        }
+        
+
         if (!penalize_nl) {
             for (size_t idx = 0; idx < cur_p.size; idx++) {
                 if (cur_p.data[idx].id == llama_token_nl(llama_get_model(ctx_main))) {

common/sampling.h

@@ -41,6 +41,9 @@ typedef struct llama_sampling_params {
     float       mirostat_eta          = 0.10f;              // learning rate
     bool        penalize_nl           = false;              // consider newlines as a repeatable token
     uint32_t    seed                  = LLAMA_DEFAULT_SEED; // the seed used to initialize llama_sampling_context
+    float       dry_multiplier        = 0.0f;     // 0.0f = disabled, recommended value: 0.8f
+    float       dry_base              = 1.75f;
+    int         dry_allowed_length    = 2;
 
     std::vector<llama_sampler_type> samplers_sequence = {
         llama_sampler_type::TOP_K,
@@ -61,6 +64,7 @@ typedef struct llama_sampling_params {
     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_sequence_breakers; // sequence breakers for the DRY sampler
     bool                     use_penalty_prompt_tokens = false;
 } llama_sampling_params;
 

llama.h

@@ -924,6 +924,18 @@ 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(
+            struct llama_context * ctx,
+          llama_token_data_array * candidates,
+               const llama_token * last_tokens,
+                             int   last_tokens_size,
+                           float   dry_base,
+                           float   dry_multiplier,
+                             int   dry_allowed_length,
+               const llama_token * seq_breakers,
+                             int   seq_breakers_size);
+
     /// @details Tail Free Sampling described in https://www.trentonbricken.com/Tail-Free-Sampling/.
     LLAMA_API void llama_sample_tail_free(
             struct llama_context * ctx,