Use unsigned for random seed (#2006)

* Use unsigned for random seed. Keep -1 as the value to use a time based seed.

Co-authored-by: Georgi Gerganov <redacted>

diff --git a/examples/common.cpp b/examples/common.cpp
index 5addd10a13fe9662674c8f0384ebe0951f6fa816..3278a064346b428bf103d7f0d2814ad0f5b2a1c0 100644 (file)
--- a/examples/common.cpp
+++ b/examples/common.cpp
@@ -110,7 +110,7 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
                 invalid_param = true;
                 break;
             }
-            params.seed = std::stoi(argv[i]);
+            params.seed = std::stoul(argv[i]);
         } else if (arg == "-t" || arg == "--threads") {
             if (++i >= argc) {
                 invalid_param = true;

diff --git a/examples/common.h b/examples/common.h
index 9d213d6d0414950f1f89aa092fffb34ce5d9efbd..66e5672917996e6cd5f8c9ac69fdaf90e8984a78 100644 (file)
--- a/examples/common.h
+++ b/examples/common.h
@@ -22,7 +22,7 @@
 int32_t get_num_physical_cores();
 
 struct gpt_params {
-    int32_t seed                            = -1;  // RNG seed
+    uint32_t seed                           = -1;  // RNG seed
     int32_t n_threads                       = get_num_physical_cores();
     int32_t n_predict                       = -1;  // new tokens to predict
     int32_t n_ctx                           = 512; // context size

diff --git a/examples/embedding/embedding.cpp b/examples/embedding/embedding.cpp
index 3cd5bb794957c44dd4a2b5d7efb642b452e458a1..2b7eb39c51ff5390913f6f01cf126508c1192b9a 100644 (file)
--- a/examples/embedding/embedding.cpp
+++ b/examples/embedding/embedding.cpp
@@ -24,11 +24,11 @@ int main(int argc, char ** argv) {
 
     fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
 
-    fprintf(stderr, "%s: seed  = %d\n", __func__, params.seed);
+    fprintf(stderr, "%s: seed  = %u\n", __func__, params.seed);
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {

diff --git a/examples/main/README.md b/examples/main/README.md
index 9ba1eb3849b2e57a14f4222a76d1ac43e469f726..37538613042b0f23980115b3358c173f4cd38fa7 100644 (file)
--- a/examples/main/README.md
+++ b/examples/main/README.md
@@ -242,7 +242,7 @@ Example usage: `--logit-bias 29905-inf`
 
 ### RNG Seed
 
--   `-s SEED, --seed SEED`: Set the random number generator (RNG) seed (default: -1, < 0 = random seed).
+-   `-s SEED, --seed SEED`: Set the random number generator (RNG) seed (default: -1, -1 = random seed).
 
 The RNG seed is used to initialize the random number generator that influences the text generation process. By setting a specific seed value, you can obtain consistent and reproducible results across multiple runs with the same input and settings. This can be helpful for testing, debugging, or comparing the effects of different options on the generated text to see when they diverge. If the seed is set to a value less than 0, a random seed will be used, which will result in different outputs on each run.
 

diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index bcdc98d611250995b411a372d4cc2cd7ff38a821..3a171925ba5103aeb0b86116707cc073d2ba744f 100644 (file)
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -94,11 +94,11 @@ int main(int argc, char ** argv) {
 
     fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
 
-    fprintf(stderr, "%s: seed  = %d\n", __func__, params.seed);
+    fprintf(stderr, "%s: seed  = %u\n", __func__, params.seed);
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {

diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp
index f8a6cb516d067e60b9641ae8bbe2754117a0cbcd..dd54ed3c4bd6cd65a62bcaa01156c793ef36a1b4 100644 (file)
--- a/examples/perplexity/perplexity.cpp
+++ b/examples/perplexity/perplexity.cpp
@@ -136,11 +136,11 @@ int main(int argc, char ** argv) {
 
     fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
 
-    fprintf(stderr, "%s: seed  = %d\n", __func__, params.seed);
+    fprintf(stderr, "%s: seed  = %u\n", __func__, params.seed);
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {

diff --git a/examples/server/README.md b/examples/server/README.md
index fa95c00441bc220c1363c5e649fe42fb2c634145..ba4b2fec9d1df08f6d2e1b43f244f83ed2224f08 100644 (file)
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -152,7 +152,7 @@ node .
 
     `mirostat_eta`: Set the Mirostat learning rate, parameter eta (default: 0.1).
 
-    `seed`: Set the random number generator (RNG) seed (default: -1, < 0 = random seed).
+    `seed`: Set the random number generator (RNG) seed (default: -1, -1 = random seed).
 
     `ignore_eos`: Ignore end of stream token and continue generating (default: false).
 

diff --git a/examples/train-text-from-scratch/train-text-from-scratch.cpp b/examples/train-text-from-scratch/train-text-from-scratch.cpp
index a05881d1640e7a1a47aefba8eca40c6d9fa38d5a..05bfa801679686135b39b84a0193028bf1eb3f77 100644 (file)
--- a/examples/train-text-from-scratch/train-text-from-scratch.cpp
+++ b/examples/train-text-from-scratch/train-text-from-scratch.cpp
@@ -2768,7 +2768,7 @@ void train_print_usage(int /*argc*/, char ** argv, const struct train_params * p
     fprintf(stderr, "  --checkpoint-in FNAME      path from which to load training checkpoint (default '%s')\n", params->fn_checkpoint_in);
     fprintf(stderr, "  --checkpoint-out FNAME     path to save training checkpoint (default '%s')\n", params->fn_checkpoint_out);
     fprintf(stderr, "  --model-out FNAME          path to save ggml model (default '%s')\n", params->fn_model_out);
-    fprintf(stderr, "  -s SEED, --seed SEED       RNG seed (default: -1, use random seed for < 0)\n");
+    fprintf(stderr, "  -s SEED, --seed SEED       RNG seed (default: -1, use random seed for -1)\n");
     fprintf(stderr, "  -c N, --ctx N              Context size used during training (default %d)\n", params->n_ctx);
     fprintf(stderr, "  --embd N                   Embedding size used for new models (default %d)\n", params->n_embd);
     fprintf(stderr, "  --mult N                   Mult size used for new models, influences feedforward size. (default %d)\n", params->n_mult);
@@ -3034,10 +3034,10 @@ int main(int argc, char ** argv) {
         return 1;
     }
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
-    printf("%s: seed: %d\n", __func__, params.seed);
+    printf("%s: seed: %u\n", __func__, params.seed);
     srand(params.seed);
 
     struct llama_context_params llama_params = llama_context_default_params();

diff --git a/llama.cpp b/llama.cpp
index ef80b4e8bd3ead14703b770077e1cd4afdce23fa..049f73e4449cda18be5dbaaa01c0f673a11b9d00 100644 (file)
--- a/llama.cpp
+++ b/llama.cpp
@@ -777,7 +777,7 @@ static bool kv_cache_init(
 
 struct llama_context_params llama_context_default_params() {
     struct llama_context_params result = {
-        /*.seed                        =*/ -1,
+        /*.seed                        =*/ LLAMA_DEFAULT_SEED,
         /*.n_ctx                       =*/ 512,
         /*.n_batch                     =*/ 512,
         /*.gpu_layers                  =*/ 0,
@@ -2541,7 +2541,7 @@ struct llama_context * llama_new_context_with_model(
 
     llama_context * ctx = new llama_context(*model, model->vocab);
 
-    if (params.seed < 0) {
+    if (params.seed == LLAMA_DEFAULT_SEED) {
         params.seed = time(NULL);
     }
 
@@ -2974,8 +2974,8 @@ int llama_get_kv_cache_token_count(const struct llama_context * ctx) {
 
 #define LLAMA_MAX_RNG_STATE (64*1024)
 
-void llama_set_rng_seed(struct llama_context * ctx, int seed) {
-    if (seed < 0) {
+void llama_set_rng_seed(struct llama_context * ctx, uint32_t seed) {
+    if (seed == LLAMA_DEFAULT_SEED) {
         seed = time(NULL);
     }
     ctx->rng.seed(seed);

diff --git a/llama.h b/llama.h
index c2f2e53312b9e36261c2b65ab0982047bc44f8dc..5bb1964bd390dc3da3f0ff5dcb43a9635f3189df 100644 (file)
--- a/llama.h
+++ b/llama.h
@@ -46,6 +46,8 @@
 #define LLAMA_SESSION_MAGIC          LLAMA_FILE_MAGIC_GGSN
 #define LLAMA_SESSION_VERSION        1
 
+#define LLAMA_DEFAULT_SEED           0xFFFFFFFF
+
 #if defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST) || defined(GGML_USE_METAL)
 // Defined when llama.cpp is compiled with support for offloading model layers to GPU.
 #define LLAMA_SUPPORTS_GPU_OFFLOAD
@@ -81,11 +83,11 @@ extern "C" {
     typedef void (*llama_progress_callback)(float progress, void *ctx);
 
    struct llama_context_params {
-        int seed;                              // RNG seed, -1 for random
-        int n_ctx;                             // text context
-        int n_batch;                           // prompt processing batch size
-        int n_gpu_layers;                      // number of layers to store in VRAM
-        int main_gpu;                          // the GPU that is used for scratch and small tensors
+        uint32_t seed;                         // RNG seed, -1 for random
+        int32_t  n_ctx;                        // text context
+        int32_t  n_batch;                      // prompt processing batch size
+        int32_t  n_gpu_layers;                 // number of layers to store in VRAM
+        int32_t  main_gpu;                     // the GPU that is used for scratch and small tensors
         float tensor_split[LLAMA_MAX_DEVICES]; // how to split layers across multiple GPUs
         // called with a progress value between 0 and 1, pass NULL to disable
         llama_progress_callback progress_callback;
@@ -196,7 +198,7 @@ extern "C" {
     LLAMA_API int llama_get_kv_cache_token_count(const struct llama_context * ctx);
 
     // Sets the current rng seed.
-    LLAMA_API void llama_set_rng_seed(struct llama_context * ctx, int seed);
+    LLAMA_API void llama_set_rng_seed(struct llama_context * ctx, uint32_t seed);
 
     // Returns the maximum size in bytes of the state (rng, logits, embedding
     // and kv_cache) - will often be smaller after compacting tokens