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@ -114,6 +114,8 @@ struct llama_context_params llama_context_default_params() {
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/*.f16_kv =*/ false,
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/*.f16_kv =*/ false,
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/*.logits_all =*/ false,
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/*.logits_all =*/ false,
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/*.vocab_only =*/ false,
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/*.vocab_only =*/ false,
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/*.progress_callback =*/ nullptr,
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/*.progress_ctx =*/ nullptr,
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};
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};
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return result;
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return result;
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@ -130,7 +132,8 @@ static bool llama_model_load(
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int n_parts,
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int n_parts,
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ggml_type memory_type,
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ggml_type memory_type,
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bool vocab_only,
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bool vocab_only,
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llama_progress_handler progress) {
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llama_progress_handler progress_callback,
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void *progress_ctx) {
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fprintf(stderr, "%s: loading model from '%s' - please wait ...\n", __func__, fname.c_str());
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fprintf(stderr, "%s: loading model from '%s' - please wait ...\n", __func__, fname.c_str());
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const int64_t t_start_us = ggml_time_us();
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const int64_t t_start_us = ggml_time_us();
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@ -397,8 +400,8 @@ static bool llama_model_load(
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std::vector<uint8_t> tmp;
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std::vector<uint8_t> tmp;
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if (progress.handler) {
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if (progress_callback) {
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progress.handler(0, progress.ctx);
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progress_callback(0.0, progress_ctx);
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}
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}
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for (int i = 0; i < n_parts; ++i) {
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for (int i = 0; i < n_parts; ++i) {
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@ -591,9 +594,9 @@ static bool llama_model_load(
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//fprintf(stderr, "%42s - [%5d, %5d], type = %6s, %6.2f MB\n", name.data(), ne[0], ne[1], ftype == 0 ? "float" : "f16", ggml_nbytes(tensor)/1024.0/1024.0);
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//fprintf(stderr, "%42s - [%5d, %5d], type = %6s, %6.2f MB\n", name.data(), ne[0], ne[1], ftype == 0 ? "float" : "f16", ggml_nbytes(tensor)/1024.0/1024.0);
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if (++n_tensors % 8 == 0) {
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if (++n_tensors % 8 == 0) {
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if (progress.handler) {
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if (progress_callback) {
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double current_progress = (double(i) + (double(fin.tellg()) / double(file_size))) / double(n_parts);
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double current_progress = (double(i) + (double(fin.tellg()) / double(file_size))) / double(n_parts);
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progress.handler(current_progress, progress.ctx);
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progress_callback(current_progress, progress_ctx);
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}
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}
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fprintf(stderr, ".");
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fprintf(stderr, ".");
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fflush(stderr);
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fflush(stderr);
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@ -612,8 +615,8 @@ static bool llama_model_load(
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lctx.t_load_us = ggml_time_us() - t_start_us;
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lctx.t_load_us = ggml_time_us() - t_start_us;
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if (progress.handler) {
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if (progress_callback) {
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progress.handler(1, progress.ctx);
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progress_callback(1.0, progress_ctx);
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}
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}
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return true;
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return true;
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@ -1414,8 +1417,7 @@ bool llama_model_quantize_internal(const std::string & fname_inp, const std::str
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struct llama_context * llama_init_from_file(
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struct llama_context * llama_init_from_file(
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const char * path_model,
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const char * path_model,
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struct llama_context_params params,
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struct llama_context_params params) {
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llama_progress_handler progress) {
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ggml_time_init();
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ggml_time_init();
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llama_context * ctx = new llama_context;
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llama_context * ctx = new llama_context;
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@ -1429,7 +1431,7 @@ struct llama_context * llama_init_from_file(
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ggml_type type_memory = params.f16_kv ? GGML_TYPE_F16 : GGML_TYPE_F32;
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ggml_type type_memory = params.f16_kv ? GGML_TYPE_F16 : GGML_TYPE_F32;
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if (!llama_model_load(path_model, *ctx, params.n_ctx, params.n_parts, type_memory, params.vocab_only, progress)) {
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if (!llama_model_load(path_model, *ctx, params.n_ctx, params.n_parts, type_memory, params.vocab_only, params.progress_callback, params.progress_ctx)) {
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fprintf(stderr, "%s: failed to load model\n", __func__);
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fprintf(stderr, "%s: failed to load model\n", __func__);
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delete ctx;
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delete ctx;
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return nullptr;
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return nullptr;
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