Remove default arguments from sampling functions (#1343)

diff --git a/.gitignore b/.gitignore
index e479c61805a6acce160e777ebe37197b439d92fd..6f275fea45149a0402a8d40a9b3d903a06e1f577 100644 (file)
--- a/.gitignore
+++ b/.gitignore
@@ -21,6 +21,7 @@ build-sanitize-addr/
 build-sanitize-thread/
 
 models/*
+*.bin
 
 /main
 /quantize

diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index 43dca8eb5ea82ed7a3a9ed324e668d9911a60f37..5ac151e14cf6302ab3604e69253eb776385336a1 100644 (file)
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -444,10 +444,10 @@ int main(int argc, char ** argv) {
                         id = llama_sample_token_mirostat_v2(ctx, &candidates_p, mirostat_tau, mirostat_eta, &mirostat_mu);
                     } else {
                         // Temperature sampling
-                        llama_sample_top_k(ctx, &candidates_p, top_k);
-                        llama_sample_tail_free(ctx, &candidates_p, tfs_z);
-                        llama_sample_typical(ctx, &candidates_p, typical_p);
-                        llama_sample_top_p(ctx, &candidates_p, top_p);
+                        llama_sample_top_k(ctx, &candidates_p, top_k, 1);
+                        llama_sample_tail_free(ctx, &candidates_p, tfs_z, 1);
+                        llama_sample_typical(ctx, &candidates_p, typical_p, 1);
+                        llama_sample_top_p(ctx, &candidates_p, top_p, 1);
                         llama_sample_temperature(ctx, &candidates_p, temp);
                         id = llama_sample_token(ctx, &candidates_p);
                     }

diff --git a/llama.cpp b/llama.cpp
index 85af4dc4930dc3d5d9a0d5c3b29ecbea3c1ce5c9..c36c6ced62ccc36b71113332eae42873f01592db 100644 (file)
--- a/llama.cpp
+++ b/llama.cpp
@@ -1791,7 +1791,7 @@ llama_token llama_sample_token_mirostat(struct llama_context * ctx, llama_token_
     float k = powf((epsilon_hat * powf(2, *mu)) / (1 - powf(N, -epsilon_hat)), 1 / s_hat);
 
     // Sample the next word X using top-k sampling
-    llama_sample_top_k(nullptr, candidates, int(k));
+    llama_sample_top_k(nullptr, candidates, int(k), 1);
     if (ctx) {
         ctx->t_sample_us += ggml_time_us() - t_start_sample_us;
     }

diff --git a/llama.h b/llama.h
index e993c464ab10e2525ed52f5f69609c5af316e3ac..58c6e0699a99989c161a0e0e7f7939eb345b081a 100644 (file)
--- a/llama.h
+++ b/llama.h
@@ -202,16 +202,16 @@ extern "C" {
     LLAMA_API void llama_sample_softmax(struct llama_context * ctx, llama_token_data_array * candidates);
 
     /// @details Top-K sampling described in academic paper "The Curious Case of Neural Text Degeneration" https://arxiv.org/abs/1904.09751
-    LLAMA_API void llama_sample_top_k(struct llama_context * ctx, llama_token_data_array * candidates, int k, size_t min_keep = 1);
+    LLAMA_API void llama_sample_top_k(struct llama_context * ctx, llama_token_data_array * candidates, int k, size_t min_keep);
 
     /// @details Nucleus sampling described in academic paper "The Curious Case of Neural Text Degeneration" https://arxiv.org/abs/1904.09751
-    LLAMA_API void llama_sample_top_p(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep = 1);
+    LLAMA_API void llama_sample_top_p(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep);
 
     /// @details Tail Free Sampling described in https://www.trentonbricken.com/Tail-Free-Sampling/.
-    LLAMA_API void llama_sample_tail_free(struct llama_context * ctx, llama_token_data_array * candidates, float z, size_t min_keep = 1);
+    LLAMA_API void llama_sample_tail_free(struct llama_context * ctx, llama_token_data_array * candidates, float z, size_t min_keep);
 
     /// @details Locally Typical Sampling implementation described in the paper https://arxiv.org/abs/2202.00666.
-    LLAMA_API void llama_sample_typical(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep = 1);
+    LLAMA_API void llama_sample_typical(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep);
     LLAMA_API void llama_sample_temperature(struct llama_context * ctx, llama_token_data_array * candidates, float temp);
 
     /// @details Mirostat 1.0 algorithm described in the paper https://arxiv.org/abs/2007.14966. Uses tokens instead of words.

diff --git a/tests/test-sampling.cpp b/tests/test-sampling.cpp
index 8ce59af3dc94327e9c60d68a204616597ad30e8b..9174c1e3739150f71ba6df51b50f725c1699d28f 100644 (file)
--- a/tests/test-sampling.cpp
+++ b/tests/test-sampling.cpp
@@ -32,7 +32,7 @@ void test_top_k(const std::vector<float> & probs,
     llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
     llama_sample_softmax(nullptr, &candidates_p);
     DUMP(&candidates_p);
-    llama_sample_top_k(nullptr, &candidates_p, k);
+    llama_sample_top_k(nullptr, &candidates_p, k, 1);
     DUMP(&candidates_p);
 
     assert(candidates_p.size == expected_probs.size());
@@ -57,7 +57,7 @@ void test_top_p(const std::vector<float> & probs,
     llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
     llama_sample_softmax(nullptr, &candidates_p);
     DUMP(&candidates_p);
-    llama_sample_top_p(nullptr, &candidates_p, p);
+    llama_sample_top_p(nullptr, &candidates_p, p, 1);
     DUMP(&candidates_p);
 
     assert(candidates_p.size == expected_probs.size());
@@ -80,7 +80,7 @@ void test_tfs(const std::vector<float> & probs,
 
     llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
     DUMP(&candidates_p);
-    llama_sample_tail_free(nullptr, &candidates_p, z);
+    llama_sample_tail_free(nullptr, &candidates_p, z, 1);
     DUMP(&candidates_p);
 
     assert(candidates_p.size == expected_probs.size());
@@ -103,7 +103,7 @@ void test_typical(const std::vector<float> & probs,
 
     llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
     DUMP(&candidates_p);
-    llama_sample_typical(nullptr, &candidates_p, p);
+    llama_sample_typical(nullptr, &candidates_p, p, 1);
     DUMP(&candidates_p);
 
     assert(candidates_p.size == expected_probs.size());