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authorBorislav Stanimirov <b.stanimirov@abv.bg>2023-08-04 13:07:21 +0300
committerGitHub <noreply@github.com>2023-08-04 13:07:21 +0300
commitff966e7ca6af127c9405523cdb07ef8fa01bf6d6 (patch)
treeefa2175da1110216b711950568860649281c0fe3
parent8183159cf3def112f6d1fe94815fce70e1bffa12 (diff)
build : fix several cast and printf warnings (#2499)
-rw-r--r--examples/embd-input/embd-input-lib.cpp2
-rw-r--r--examples/grammar-parser.cpp2
-rw-r--r--examples/perplexity/perplexity.cpp8
-rw-r--r--examples/simple/simple.cpp2
4 files changed, 7 insertions, 7 deletions
diff --git a/examples/embd-input/embd-input-lib.cpp b/examples/embd-input/embd-input-lib.cpp
index 2656382..2185b9b 100644
--- a/examples/embd-input/embd-input-lib.cpp
+++ b/examples/embd-input/embd-input-lib.cpp
@@ -30,7 +30,7 @@ struct MyModel* create_mymodel(int argc, char ** argv) {
fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
if (params.seed == LLAMA_DEFAULT_SEED) {
- params.seed = time(NULL);
+ params.seed = uint32_t(time(NULL));
}
fprintf(stderr, "%s: seed = %d\n", __func__, params.seed);
diff --git a/examples/grammar-parser.cpp b/examples/grammar-parser.cpp
index 019d5e1..e76bd11 100644
--- a/examples/grammar-parser.cpp
+++ b/examples/grammar-parser.cpp
@@ -405,7 +405,7 @@ namespace grammar_parser {
for (size_t i = 0, end = state.rules.size(); i < end; i++) {
// fprintf(file, "%zu: ", i);
// print_rule_binary(file, state.rules[i]);
- print_rule(file, i, state.rules[i], symbol_id_names);
+ print_rule(file, uint32_t(i), state.rules[i], symbol_id_names);
// fprintf(file, "\n");
}
} catch (const std::exception & err) {
diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp
index 6870a11..62433e9 100644
--- a/examples/perplexity/perplexity.cpp
+++ b/examples/perplexity/perplexity.cpp
@@ -153,7 +153,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
}
size_t hs_task_count = prompt_lines.size()/6;
- fprintf(stderr, "%s : loaded %lu tasks from prompt.\n", __func__, hs_task_count);
+ fprintf(stderr, "%s : loaded %zu tasks from prompt.\n", __func__, hs_task_count);
// This is needed as usual for LLaMA models
bool prepend_bos = true;
@@ -178,7 +178,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
double ending_logprob[4];
};
- fprintf(stderr, "%s : selecting %lu %s tasks.\n", __func__, hs_task_count, (randomize_tasks?"randomized":"the first") );
+ fprintf(stderr, "%s : selecting %zu %s tasks.\n", __func__, hs_task_count, (randomize_tasks?"randomized":"the first") );
// Select and read data from prompt lines
hs_data_t *hs_data = new hs_data_t[hs_task_count];
@@ -223,7 +223,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
// Stop if query wont fit the ctx window
if (query_size > (size_t)params.n_ctx) {
- fprintf(stderr, "%s : number of tokens in query %lu > n_ctxl\n", __func__, query_size);
+ fprintf(stderr, "%s : number of tokens in query %zu > n_ctxl\n", __func__, query_size);
return;
}
@@ -284,7 +284,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
}
// Print the accumulated accuracy mean x 100
- printf("%li\t%.8lf\n",task_idx+1, acc/double(task_idx+1)*100.0);
+ printf("%zu\t%.8lf\n",task_idx+1, acc/double(task_idx+1)*100.0);
fflush(stdout);
}
diff --git a/examples/simple/simple.cpp b/examples/simple/simple.cpp
index aa2c435..97137a6 100644
--- a/examples/simple/simple.cpp
+++ b/examples/simple/simple.cpp
@@ -123,7 +123,7 @@ int main(int argc, char ** argv)
// Evaluate the tokens :
//---------------------------------
- if ( llama_eval( ctx , tokens_list.data() , tokens_list.size() , llama_get_kv_cache_token_count( ctx ) , params.n_threads ) )
+ if ( llama_eval( ctx , tokens_list.data() , int(tokens_list.size()) , llama_get_kv_cache_token_count( ctx ) , params.n_threads ) )
{
fprintf( stderr, "%s : failed to eval\n" , __func__ );
return 1;