mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-26 14:20:31 +01:00
minor : spacing
This commit is contained in:
Georgi Gerganov
parent
fc4c2a6fc3
commit
9c5fd6be14
@ -111,14 +111,14 @@ static void usage(const char * executable) {
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exit(1);
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}
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static void load_imatrix(const std::string& imatrix_file, std::unordered_map<std::string, std::vector<float>>& imatrix_data) {
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static void load_imatrix(const std::string & imatrix_file, std::unordered_map<std::string, std::vector<float>> & imatrix_data) {
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std::ifstream in(imatrix_file.c_str(), std::ios::binary);
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if (!in) {
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printf("%s: failed to open %s\n",__func__,imatrix_file.c_str());
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printf("%s: failed to open %s\n",__func__, imatrix_file.c_str());
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return;
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}
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int n_entries;
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in.read((char*)&n_entries, sizeof(n_entries));
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in.read((char *)&n_entries, sizeof(n_entries));
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if (in.fail() || n_entries < 1) {
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printf("%s: no data in file %s\n", __func__, imatrix_file.c_str());
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return;
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@ -128,25 +128,25 @@ static void load_imatrix(const std::string& imatrix_file, std::unordered_map<std
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std::vector<char> name_as_vec(len+1);
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in.read((char *)name_as_vec.data(), len);
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if (in.fail()) {
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printf("%s: failed reading name for entry %d from %s\n",__func__,i+1,imatrix_file.c_str());
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printf("%s: failed reading name for entry %d from %s\n", __func__, i+1, imatrix_file.c_str());
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return;
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}
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name_as_vec[len] = 0;
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std::string name{name_as_vec.data()};
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auto& e = imatrix_data[std::move(name)];
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auto & e = imatrix_data[std::move(name)];
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int ncall;
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in.read((char*)&ncall, sizeof(ncall));
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in.read((char *)&ncall, sizeof(ncall));
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int nval;
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in.read((char *)&nval, sizeof(nval));
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if (in.fail() || nval < 1) {
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printf("%s: failed reading number of values for entry %d\n",__func__,i);
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printf("%s: failed reading number of values for entry %d\n", __func__, i);
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imatrix_data = {};
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return;
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}
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e.resize(nval);
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in.read((char*)e.data(), nval*sizeof(float));
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in.read((char *)e.data(), nval*sizeof(float));
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if (in.fail()) {
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printf("%s: failed reading data for entry %d\n",__func__,i);
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printf("%s: failed reading data for entry %d\n", __func__, i);
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imatrix_data = {};
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return;
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}
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@ -154,13 +154,13 @@ static void load_imatrix(const std::string& imatrix_file, std::unordered_map<std
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for (auto& v : e) v /= ncall;
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}
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}
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printf("%s: loaded %d importance matrix entries from %s\n",__func__,int(imatrix_data.size()),imatrix_file.c_str());
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printf("%s: loaded %d importance matrix entries from %s\n", __func__, int(imatrix_data.size()), imatrix_file.c_str());
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}
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static void prepare_imatrix(const std::string& imatrix_file,
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const std::vector<std::string>& included_weights,
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const std::vector<std::string>& excluded_weights,
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std::unordered_map<std::string, std::vector<float>>& imatrix_data) {
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static void prepare_imatrix(const std::string & imatrix_file,
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const std::vector<std::string> & included_weights,
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const std::vector<std::string> & excluded_weights,
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std::unordered_map<std::string, std::vector<float>> & imatrix_data) {
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if (!imatrix_file.empty()) {
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load_imatrix(imatrix_file, imatrix_data);
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}
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@ -205,7 +205,7 @@ static ggml_type parse_ggml_type(const char * arg) {
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return result;
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}
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static bool parse_kv_override(const char * data, std::vector<llama_model_kv_override>& overrides) {
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static bool parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides) {
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const char* sep = strchr(data, '=');
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if (sep == nullptr || sep - data >= 128) {
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fprintf(stderr, "%s: malformed KV override '%s'\n", __func__, data);
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@ -219,27 +219,22 @@ static bool parse_kv_override(const char * data, std::vector<llama_model_kv_over
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sep += 4;
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kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT;
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kvo.int_value = std::atol(sep);
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}
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else if (strncmp(sep, "float:", 6) == 0) {
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} else if (strncmp(sep, "float:", 6) == 0) {
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sep += 6;
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kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT;
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kvo.float_value = std::atof(sep);
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}
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else if (strncmp(sep, "bool:", 5) == 0) {
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} else if (strncmp(sep, "bool:", 5) == 0) {
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sep += 5;
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kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL;
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if (std::strcmp(sep, "true") == 0) {
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kvo.bool_value = true;
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}
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else if (std::strcmp(sep, "false") == 0) {
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} else if (std::strcmp(sep, "false") == 0) {
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kvo.bool_value = false;
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}
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else {
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} else {
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fprintf(stderr, "%s: invalid boolean value for KV override '%s'\n", __func__, data);
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return false;
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}
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}
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else {
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} else {
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fprintf(stderr, "%s: invalid type for KV override '%s'\n", __func__, data);
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return false;
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}
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@ -344,8 +339,7 @@ int main(int argc, char ** argv) {
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if (ftype_str == "COPY") {
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params.only_copy = true;
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}
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}
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else {
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} else {
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fname_out = argv[arg_idx];
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arg_idx++;
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28
llama.cpp
28
llama.cpp
@ -12809,20 +12809,18 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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gguf_set_kv (ctx_out, ml.meta);
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gguf_set_val_u32(ctx_out, "general.quantization_version", GGML_QNT_VERSION);
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gguf_set_val_u32(ctx_out, "general.file_type", ftype);
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if (params->kv_overrides) {
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const std::vector<llama_model_kv_override>& overrides = *(const std::vector<llama_model_kv_override>*)params->kv_overrides;
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for (auto& o : overrides) {
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const std::vector<llama_model_kv_override> & overrides = *(const std::vector<llama_model_kv_override> *)params->kv_overrides;
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for (auto & o : overrides) {
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if (o.key[0] == 0) break;
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if (o.tag == LLAMA_KV_OVERRIDE_TYPE_FLOAT) {
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gguf_set_val_f32(ctx_out, o.key, o.float_value);
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}
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else if (o.tag == LLAMA_KV_OVERRIDE_TYPE_INT) {
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} else if (o.tag == LLAMA_KV_OVERRIDE_TYPE_INT) {
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gguf_set_val_i32(ctx_out, o.key, o.int_value);
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}
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else if (o.tag == LLAMA_KV_OVERRIDE_TYPE_BOOL) {
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} else if (o.tag == LLAMA_KV_OVERRIDE_TYPE_BOOL) {
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gguf_set_val_bool(ctx_out, o.key, o.bool_value);
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}
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else {
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} else {
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LLAMA_LOG_WARN("%s: unknown KV override type for key %s\n", __func__, o.key);
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}
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}
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@ -12836,21 +12834,17 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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// TODO: avoid hardcoded tensor names - use the TN_* constants
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if (name.find("attn_v.weight") != std::string::npos || name.find("attn_qkv.weight") != std::string::npos) {
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++qs.n_attention_wv;
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}
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else if (name.find("ffn_down") != std::string::npos) {
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} else if (name.find("ffn_down") != std::string::npos) {
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++qs.n_ffn_down;
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}
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else if (name.find("ffn_gate") != std::string::npos) {
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} else if (name.find("ffn_gate") != std::string::npos) {
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++qs.n_ffn_gate;
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}
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else if (name.find("ffn_up") != std::string::npos) {
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} else if (name.find("ffn_up") != std::string::npos) {
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++qs.n_ffn_up;
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}
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else if (name == LLM_TN(model.arch)(LLM_TENSOR_OUTPUT, "weight")) {
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} else if (name == LLM_TN(model.arch)(LLM_TENSOR_OUTPUT, "weight")) {
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qs.has_output = true;
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}
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}
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if (qs.n_attention_wv != qs.n_ffn_down || (uint32_t)qs.n_attention_wv != model.hparams.n_layer) {
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if (qs.n_attention_wv != qs.n_ffn_down || (uint32_t) qs.n_attention_wv != model.hparams.n_layer) {
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LLAMA_LOG_WARN("%s ============ Strange model: n_attention_wv = %d, n_ffn_down = %d, hparams.n_layer = %d\n",
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__func__, qs.n_attention_wv, qs.n_ffn_down, model.hparams.n_layer);
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}
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