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Modernize use nullptr #15851

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4 changes: 2 additions & 2 deletions examples/batched/batched.cpp
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Expand Up @@ -43,7 +43,7 @@ int main(int argc, char ** argv) {

llama_model * model = llama_model_load_from_file(params.model.path.c_str(), model_params);

if (model == NULL) {
if (model == nullptr) {
LOG_ERR("%s: error: unable to load model\n" , __func__);
return 1;
}
Expand Down Expand Up @@ -76,7 +76,7 @@ int main(int argc, char ** argv) {
llama_sampler_chain_add(smpl, llama_sampler_init_temp (params.sampling.temp));
llama_sampler_chain_add(smpl, llama_sampler_init_dist (params.sampling.seed));

if (ctx == NULL) {
if (ctx == nullptr) {
LOG_ERR("%s: error: failed to create the llama_context\n" , __func__);
return 1;
}
Expand Down
12 changes: 6 additions & 6 deletions examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp
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Expand Up @@ -254,7 +254,7 @@ struct my_llama_layer {
};

struct my_llama_model {
struct ggml_context * ctx = NULL;
struct ggml_context * ctx = nullptr;

std::string name;

Expand Down Expand Up @@ -333,7 +333,7 @@ static void print_params(struct my_llama_hparams * params) {
}

static void print_tensor_info(const struct ggml_context * ctx) {
for (auto * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
for (auto * t = ggml_get_first_tensor(ctx); t != nullptr; t = ggml_get_next_tensor(ctx, t)) {
LOG_INF("%s: Allocating ", __func__);
int64_t total = 1;
int i = 0;
Expand Down Expand Up @@ -443,7 +443,7 @@ struct my_llama_file {

my_llama_file(const char * fname, const char * mode) {
fp = std::fopen(fname, mode);
if (fp == NULL) {
if (fp == nullptr) {
size = 0;
} else {
seek(0, SEEK_END);
Expand Down Expand Up @@ -530,15 +530,15 @@ static std::string llama_escape_whitespaces(const std::string & text) {
static void load_vocab(const char * filename, const Config * config, struct my_llama_vocab * vocab) {
if (is_ggml_file(filename)) {
LOG_INF("%s: Loading vocabulary from gguf file %s\n", __func__, filename);
struct ggml_context * ctx_data = NULL;
struct ggml_context * ctx_data = nullptr;

struct gguf_init_params params = {
/*.no_alloc = */ false,
/*.ctx = */ &ctx_data,
};

struct gguf_context * ctx = gguf_init_from_file(filename, params);
GGML_ASSERT(ctx != NULL);
GGML_ASSERT(ctx != nullptr);

const int model_idx = gguf_find_key(ctx, KV_TOKENIZER_MODEL);
GGML_ASSERT(model_idx >= 0);
Expand Down Expand Up @@ -925,7 +925,7 @@ int main(int argc, char ** argv) {

struct ggml_init_params lcparams;
lcparams.mem_size = 1024ll*1024ll*1024ll*((size_t) params.mem_model_gb);
lcparams.mem_buffer = NULL;
lcparams.mem_buffer = nullptr;
lcparams.no_alloc = false;

model.ctx = ggml_init(lcparams);
Expand Down
6 changes: 3 additions & 3 deletions examples/embedding/embedding.cpp
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Expand Up @@ -57,12 +57,12 @@ static void batch_decode(llama_context * ctx, llama_batch & batch, float * outpu
// try to get token embeddings
embd = llama_get_embeddings_ith(ctx, i);
embd_pos = i;
GGML_ASSERT(embd != NULL && "failed to get token embeddings");
GGML_ASSERT(embd != nullptr && "failed to get token embeddings");
} else {
// try to get sequence embeddings - supported only when pooling_type is not NONE
embd = llama_get_embeddings_seq(ctx, batch.seq_id[i][0]);
embd_pos = batch.seq_id[i][0];
GGML_ASSERT(embd != NULL && "failed to get sequence embeddings");
GGML_ASSERT(embd != nullptr && "failed to get sequence embeddings");
}

float * out = output + embd_pos * n_embd;
Expand Down Expand Up @@ -107,7 +107,7 @@ int main(int argc, char ** argv) {
llama_model * model = llama_init.model.get();
llama_context * ctx = llama_init.context.get();

if (model == NULL) {
if (model == nullptr) {
LOG_ERR("%s: unable to load model\n", __func__);
return 1;
}
Expand Down
6 changes: 3 additions & 3 deletions examples/gguf-hash/gguf-hash.cpp
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Expand Up @@ -285,18 +285,18 @@ static void generate_uuidv5(const unsigned char sha1_digest[20], unsigned char u

static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
const std::string & fname = hash_params.input;
struct ggml_context * ctx_data = NULL;
struct ggml_context * ctx_data = nullptr;

struct gguf_init_params params = {
/*.no_alloc = */ false,
/*.ctx = */ &ctx_data,
};

// xxh64 init
XXH64_state_t* xxh64_model_hash_state = NULL;
XXH64_state_t* xxh64_model_hash_state = nullptr;
if (hash_params.xxh64) {
xxh64_model_hash_state = XXH64_createState();
if (xxh64_model_hash_state==NULL) {
if (xxh64_model_hash_state==nullptr) {
abort();
}

Expand Down
6 changes: 3 additions & 3 deletions examples/gguf/gguf.cpp
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Expand Up @@ -40,7 +40,7 @@ static bool gguf_ex_write(const std::string & fname) {

struct ggml_init_params params = {
/*.mem_size =*/ 128ull*1024ull*1024ull,
/*.mem_buffer =*/ NULL,
/*.mem_buffer =*/ nullptr,
/*.no_alloc =*/ false,
};

Expand Down Expand Up @@ -86,7 +86,7 @@ static bool gguf_ex_write(const std::string & fname) {
static bool gguf_ex_read_0(const std::string & fname) {
struct gguf_init_params params = {
/*.no_alloc = */ false,
/*.ctx = */ NULL,
/*.ctx = */ nullptr,
};

struct gguf_context * ctx = gguf_init_from_file(fname.c_str(), params);
Expand Down Expand Up @@ -148,7 +148,7 @@ static bool gguf_ex_read_0(const std::string & fname) {

// read and create ggml_context containing the tensors and their data
static bool gguf_ex_read_1(const std::string & fname, bool check_data) {
struct ggml_context * ctx_data = NULL;
struct ggml_context * ctx_data = nullptr;

struct gguf_init_params params = {
/*.no_alloc = */ false,
Expand Down
2 changes: 1 addition & 1 deletion examples/llama.android/llama/src/main/cpp/llama-android.cpp
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Expand Up @@ -152,7 +152,7 @@ Java_android_llama_cpp_LLamaAndroid_backend_1free(JNIEnv *, jobject) {
extern "C"
JNIEXPORT void JNICALL
Java_android_llama_cpp_LLamaAndroid_log_1to_1android(JNIEnv *, jobject) {
llama_log_set(log_callback, NULL);
llama_log_set(log_callback, nullptr);
}

extern "C"
Expand Down
14 changes: 7 additions & 7 deletions examples/model-conversion/logits.cpp
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Expand Up @@ -78,27 +78,27 @@ int main(int argc, char ** argv) {

llama_model * model = llama_model_load_from_file(model_path.c_str(), model_params);

if (model == NULL) {
if (model == nullptr) {
fprintf(stderr , "%s: error: unable to load model\n" , __func__);
return 1;
}

// Extract basename from model_path
const char * basename = strrchr(model_path.c_str(), '/');
basename = (basename == NULL) ? model_path.c_str() : basename + 1;
basename = (basename == nullptr) ? model_path.c_str() : basename + 1;

char model_name[256];
strncpy(model_name, basename, 255);
model_name[255] = '\0';

char * dot = strrchr(model_name, '.');
if (dot != NULL && strcmp(dot, ".gguf") == 0) {
if (dot != nullptr && strcmp(dot, ".gguf") == 0) {
*dot = '\0';
}
printf("Model name: %s\n", model_name);

const llama_vocab * vocab = llama_model_get_vocab(model);
const int n_prompt = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), NULL, 0, true, true);
const int n_prompt = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), nullptr, 0, true, true);

std::vector<llama_token> prompt_tokens(n_prompt);
if (llama_tokenize(vocab, prompt.c_str(), prompt.size(), prompt_tokens.data(), prompt_tokens.size(), true, true) < 0) {
Expand All @@ -117,7 +117,7 @@ int main(int argc, char ** argv) {
}

llama_context * ctx = llama_init_from_model(model, ctx_params);
if (ctx == NULL) {
if (ctx == nullptr) {
fprintf(stderr , "%s: error: failed to create the llama_context\n" , __func__);
return 1;
}
Expand Down Expand Up @@ -167,7 +167,7 @@ int main(int argc, char ** argv) {
printf("Saving logits to %s\n", bin_filename);

FILE * f = fopen(bin_filename, "wb");
if (f == NULL) {
if (f == nullptr) {
fprintf(stderr, "%s: error: failed to open binary output file\n", __func__);
return 1;
}
Expand All @@ -178,7 +178,7 @@ int main(int argc, char ** argv) {
char txt_filename[512];
snprintf(txt_filename, sizeof(txt_filename), "data/llamacpp-%s%s.txt", model_name, type);
f = fopen(txt_filename, "w");
if (f == NULL) {
if (f == nullptr) {
fprintf(stderr, "%s: error: failed to open text output file\n", __func__);
return 1;
}
Expand Down
4 changes: 2 additions & 2 deletions examples/passkey/passkey.cpp
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Expand Up @@ -66,7 +66,7 @@ int main(int argc, char ** argv) {

llama_model * model = llama_model_load_from_file(params.model.path.c_str(), model_params);

if (model == NULL) {
if (model == nullptr) {
LOG_ERR("%s: unable to load model\n" , __func__);
return 1;
}
Expand All @@ -82,7 +82,7 @@ int main(int argc, char ** argv) {
GGML_ASSERT(ctx_params.n_batch % n_grp == 0 && "n_batch must be divisible by n_grp");

llama_context * ctx = llama_init_from_model(model, ctx_params);
if (ctx == NULL) {
if (ctx == nullptr) {
LOG_ERR("%s: failed to create the llama_context\n" , __func__);
return 1;
}
Expand Down
6 changes: 3 additions & 3 deletions examples/retrieval/retrieval.cpp
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Expand Up @@ -98,9 +98,9 @@ static void batch_process(llama_context * ctx, llama_batch & batch, float * outp

// try to get sequence embeddings - supported only when pooling_type is not NONE
const float * embd = llama_get_embeddings_seq(ctx, batch.seq_id[i][0]);
if (embd == NULL) {
if (embd == nullptr) {
embd = llama_get_embeddings_ith(ctx, i);
if (embd == NULL) {
if (embd == nullptr) {
LOG_ERR("%s: failed to get embeddings for token %d\n", __func__, i);
continue;
}
Expand Down Expand Up @@ -154,7 +154,7 @@ int main(int argc, char ** argv) {
llama_model * model = llama_init.model.get();
llama_context * ctx = llama_init.context.get();

if (model == NULL) {
if (model == nullptr) {
LOG_ERR("%s: unable to load model\n", __func__);
return 1;
}
Expand Down
2 changes: 1 addition & 1 deletion examples/simple-chat/simple-chat.cpp
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Expand Up @@ -101,7 +101,7 @@ int main(int argc, char ** argv) {
const bool is_first = llama_memory_seq_pos_max(llama_get_memory(ctx), 0) == -1;

// tokenize the prompt
const int n_prompt_tokens = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), NULL, 0, is_first, true);
const int n_prompt_tokens = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), nullptr, 0, is_first, true);
std::vector<llama_token> prompt_tokens(n_prompt_tokens);
if (llama_tokenize(vocab, prompt.c_str(), prompt.size(), prompt_tokens.data(), prompt_tokens.size(), is_first, true) < 0) {
GGML_ABORT("failed to tokenize the prompt\n");
Expand Down
6 changes: 3 additions & 3 deletions examples/simple/simple.cpp
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Expand Up @@ -85,7 +85,7 @@ int main(int argc, char ** argv) {

llama_model * model = llama_model_load_from_file(model_path.c_str(), model_params);

if (model == NULL) {
if (model == nullptr) {
fprintf(stderr , "%s: error: unable to load model\n" , __func__);
return 1;
}
Expand All @@ -94,7 +94,7 @@ int main(int argc, char ** argv) {
// tokenize the prompt

// find the number of tokens in the prompt
const int n_prompt = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), NULL, 0, true, true);
const int n_prompt = -llama_tokenize(vocab, prompt.c_str(), prompt.size(), nullptr, 0, true, true);

// allocate space for the tokens and tokenize the prompt
std::vector<llama_token> prompt_tokens(n_prompt);
Expand All @@ -115,7 +115,7 @@ int main(int argc, char ** argv) {

llama_context * ctx = llama_init_from_model(model, ctx_params);

if (ctx == NULL) {
if (ctx == nullptr) {
fprintf(stderr , "%s: error: failed to create the llama_context\n" , __func__);
return 1;
}
Expand Down
8 changes: 4 additions & 4 deletions examples/speculative-simple/speculative-simple.cpp
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Expand Up @@ -33,11 +33,11 @@ int main(int argc, char ** argv) {
llama_backend_init();
llama_numa_init(params.numa);

llama_model * model_tgt = NULL;
//llama_model * model_dft = NULL;
llama_model * model_tgt = nullptr;
//llama_model * model_dft = nullptr;

llama_context * ctx_tgt = NULL;
llama_context * ctx_dft = NULL;
llama_context * ctx_tgt = nullptr;
llama_context * ctx_dft = nullptr;

// load the target model
common_init_result llama_init_tgt = common_init_from_params(params);
Expand Down
8 changes: 4 additions & 4 deletions examples/speculative/speculative.cpp
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Expand Up @@ -64,11 +64,11 @@ int main(int argc, char ** argv) {
llama_backend_init();
llama_numa_init(params.numa);

llama_model * model_tgt = NULL;
llama_model * model_dft = NULL;
llama_model * model_tgt = nullptr;
llama_model * model_dft = nullptr;

llama_context * ctx_tgt = NULL;
llama_context * ctx_dft = NULL;
llama_context * ctx_tgt = nullptr;
llama_context * ctx_dft = nullptr;

// load the target model
common_init_result llama_init_tgt = common_init_from_params(params);
Expand Down
2 changes: 1 addition & 1 deletion examples/training/finetune.cpp
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Expand Up @@ -43,7 +43,7 @@ int main(int argc, char ** argv) {
llama_model_ptr & model = llama_init.model;
llama_context_ptr & ctx = llama_init.context;

if (model == NULL) {
if (model == nullptr) {
LOG_ERR("%s: unable to load model\n", __func__);
return 1;
}
Expand Down
4 changes: 2 additions & 2 deletions src/llama-adapter.cpp
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Expand Up @@ -42,7 +42,7 @@ bool llama_adapter_cvec::init(const llama_model & model) {
if (it == ctx_map.end()) {
ggml_init_params params = {
/*.mem_size =*/ hparams.n_layer*ggml_tensor_overhead(),
/*.mem_buffer =*/ NULL,
/*.mem_buffer =*/ nullptr,
/*.no_alloc =*/ true,
};

Expand Down Expand Up @@ -248,7 +248,7 @@ static void llama_adapter_lora_init_impl(llama_model & model, const char * path_
// add a new context
ggml_init_params params = {
/*.mem_size =*/ n_tensors*ggml_tensor_overhead(),
/*.mem_buffer =*/ NULL,
/*.mem_buffer =*/ nullptr,
/*.no_alloc =*/ true,
};
ggml_context * buft_ctx = ggml_init(params);
Expand Down
2 changes: 1 addition & 1 deletion src/llama-batch.cpp
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Expand Up @@ -80,7 +80,7 @@ bool llama_batch_allocr::init(

if (!batch.seq_id) {
seq_id.resize(batch.n_tokens + 1);
seq_id[batch.n_tokens] = NULL;
seq_id[batch.n_tokens] = nullptr;
for (int32_t i = 0; i < batch.n_tokens; i++) {
seq_id[i] = seq_id_0.data();
}
Expand Down
4 changes: 2 additions & 2 deletions src/llama-context.cpp
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Expand Up @@ -1120,7 +1120,7 @@ int llama_context::decode(const llama_batch & batch_inp) {

// plot the computation graph in dot format (for debugging purposes)
//if (n_past%100 == 0) {
// ggml_graph_dump_dot(gf, NULL, "llama.dot");
// ggml_graph_dump_dot(gf, nullptr, "llama.dot");
//}

auto * t_logits = res->get_logits();
Expand Down Expand Up @@ -2287,7 +2287,7 @@ llama_context * llama_init_from_model(
llama_model * model,
llama_context_params params) {
if (!model) {
LLAMA_LOG_ERROR("%s: model cannot be NULL\n", __func__);
LLAMA_LOG_ERROR("%s: model cannot be nullptr\n", __func__);
return nullptr;
}

Expand Down
2 changes: 1 addition & 1 deletion src/llama-graph.cpp
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Expand Up @@ -744,7 +744,7 @@ ggml_tensor * llm_graph_context::build_ffn(
} else {
cur = ggml_gelu(ctx0, cur);
cb(cur, "ffn_gelu", il);
if (act_scales != NULL) {
if (act_scales != nullptr) {
cur = ggml_div(ctx0, cur, act_scales);
cb(cur, "ffn_act", il);
}
Expand Down
2 changes: 1 addition & 1 deletion src/llama-impl.cpp
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Expand Up @@ -84,7 +84,7 @@ std::string format(const char * fmt, ...) {
va_list ap2;
va_start(ap, fmt);
va_copy(ap2, ap);
int size = vsnprintf(NULL, 0, fmt, ap);
int size = vsnprintf(nullptr, 0, fmt, ap);
GGML_ASSERT(size >= 0 && size < INT_MAX); // NOLINT
std::vector<char> buf(size + 1);
int size2 = vsnprintf(buf.data(), size + 1, fmt, ap2);
Expand Down
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