diff --git a/llama.cpp b/llama.cpp index b1d6015e2..51821965e 100644 --- a/llama.cpp +++ b/llama.cpp @@ -1114,7 +1114,7 @@ struct llama_mlock { suggest = false; } - fprintf(stderr, "warning: failed to mlock %zu-byte buffer (after previously locking %zu bytes): %s\n%s", + LLAMA_LOG_WARN("warning: failed to mlock %zu-byte buffer (after previously locking %zu bytes): %s\n%s", size, this->size, errmsg, suggest ? MLOCK_SUGGESTION : ""); return false; } @@ -1123,7 +1123,7 @@ struct llama_mlock { static void raw_unlock(void * addr, size_t size) { if (munlock(addr, size)) { - fprintf(stderr, "warning: failed to munlock buffer: %s\n", std::strerror(errno)); + LLAMA_LOG_WARN("warning: failed to munlock buffer: %s\n", std::strerror(errno)); } } #elif defined(_WIN32) @@ -1141,7 +1141,7 @@ struct llama_mlock { return true; } if (tries == 2) { - fprintf(stderr, "warning: failed to VirtualLock %zu-byte buffer (after previously locking %zu bytes): %s\n", + LLAMA_LOG_WARN("warning: failed to VirtualLock %zu-byte buffer (after previously locking %zu bytes): %s\n", len, size, llama_format_win_err(GetLastError()).c_str()); return false; } @@ -1150,7 +1150,7 @@ struct llama_mlock { // set size and try again. SIZE_T min_ws_size, max_ws_size; if (!GetProcessWorkingSetSize(GetCurrentProcess(), &min_ws_size, &max_ws_size)) { - fprintf(stderr, "warning: GetProcessWorkingSetSize failed: %s\n", + LLAMA_LOG_WARN("warning: GetProcessWorkingSetSize failed: %s\n", llama_format_win_err(GetLastError()).c_str()); return false; } @@ -1163,7 +1163,7 @@ struct llama_mlock { min_ws_size += increment; max_ws_size += increment; if (!SetProcessWorkingSetSize(GetCurrentProcess(), min_ws_size, max_ws_size)) { - fprintf(stderr, "warning: SetProcessWorkingSetSize failed: %s\n", + LLAMA_LOG_WARN("warning: SetProcessWorkingSetSize failed: %s\n", llama_format_win_err(GetLastError()).c_str()); return false; } @@ -1172,7 +1172,7 @@ struct llama_mlock { static void raw_unlock(void * ptr, size_t len) { if (!VirtualUnlock(ptr, len)) { - fprintf(stderr, "warning: failed to VirtualUnlock buffer: %s\n", + LLAMA_LOG_WARN("warning: failed to VirtualUnlock buffer: %s\n", llama_format_win_err(GetLastError()).c_str()); } } @@ -1184,7 +1184,7 @@ struct llama_mlock { } bool raw_lock(const void * addr, size_t len) const { - fprintf(stderr, "warning: mlock not supported on this system\n"); + LLAMA_LOG_WARN("warning: mlock not supported on this system\n"); return false; } @@ -2085,13 +2085,13 @@ namespace GGUFMeta { __func__, override_type_to_str(override->tag), override->key); switch (override->tag) { case LLAMA_KV_OVERRIDE_BOOL: { - printf("%s\n", override->bool_value ? "true" : "false"); + LLAMA_LOG_INFO("%s\n", override->bool_value ? "true" : "false"); } break; case LLAMA_KV_OVERRIDE_INT: { - printf("%" PRId64 "\n", override->int_value); + LLAMA_LOG_INFO("%" PRId64 "\n", override->int_value); } break; case LLAMA_KV_OVERRIDE_FLOAT: { - printf("%.6f\n", override->float_value); + LLAMA_LOG_INFO("%.6f\n", override->float_value); } break; default: // Shouldn't be possible to end up here, but just in case... @@ -6993,7 +6993,7 @@ static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list< if (match + special_token.length() > raw_text_base_offset + raw_text_base_length) break; #ifdef PRETOKENIZERDEBUG - fprintf(stderr, "FF: (%ld %ld %ld) '%s'\n", raw_text->length(), raw_text_base_offset, raw_text_base_length, raw_text->substr(raw_text_base_offset, raw_text_base_length).c_str()); + LLAMA_LOG_WARN("FF: (%ld %ld %ld) '%s'\n", raw_text->length(), raw_text_base_offset, raw_text_base_length, raw_text->substr(raw_text_base_offset, raw_text_base_length).c_str()); #endif auto source = std::distance(buffer.begin(), it); @@ -7006,7 +7006,7 @@ static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list< buffer.emplace_after(it, (*raw_text), left_reminder_offset, left_reminder_length); #ifdef PRETOKENIZERDEBUG - fprintf(stderr, "FL: (%ld %ld) '%s'\n", left_reminder_offset, left_reminder_length, raw_text->substr(left_reminder_offset, left_reminder_length).c_str()); + LLAMA_LOG_WARN("FL: (%ld %ld) '%s'\n", left_reminder_offset, left_reminder_length, raw_text->substr(left_reminder_offset, left_reminder_length).c_str()); #endif it++; } @@ -7022,7 +7022,7 @@ static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list< buffer.emplace_after(it, (*raw_text), right_reminder_offset, right_reminder_length); #ifdef PRETOKENIZERDEBUG - fprintf(stderr, "FR: (%ld %ld) '%s'\n", right_reminder_offset, right_reminder_length, raw_text->substr(right_reminder_offset, right_reminder_length).c_str()); + LLAMA_LOG_WARN("FR: (%ld %ld) '%s'\n", right_reminder_offset, right_reminder_length, raw_text->substr(right_reminder_offset, right_reminder_length).c_str()); #endif it++; @@ -7038,7 +7038,7 @@ static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list< raw_text_base_length = right_reminder_length; #ifdef PRETOKENIZERDEBUG - fprintf(stderr, "RR: (%ld %ld) '%s'\n", raw_text_base_offset, raw_text_base_length, raw_text->substr(raw_text_base_offset, raw_text_base_length).c_str()); + LLAMA_LOG_WARN("RR: (%ld %ld) '%s'\n", raw_text_base_offset, raw_text_base_length, raw_text->substr(raw_text_base_offset, raw_text_base_length).c_str()); #endif } else { if (source == 0) { @@ -7095,7 +7095,7 @@ static std::vector llama_tokenize_internal(const llama_vocab & } #ifdef PRETOKENIZERDEBUG - fprintf(stderr,"TT: (%ld %ld %ld) '%s'\n", raw_text.length(), fragment.offset, fragment.length, raw_text.c_str()); + LLAMA_LOG_WARN(TT: (%ld %ld %ld) '%s'\n", raw_text.length(), fragment.offset, fragment.length, raw_text.c_str()); #endif llm_tokenizer_spm tokenizer(vocab); llama_escape_whitespace(raw_text); @@ -7116,7 +7116,7 @@ static std::vector llama_tokenize_internal(const llama_vocab & auto raw_text = fragment.raw_text.substr(fragment.offset, fragment.length); #ifdef PRETOKENIZERDEBUG - fprintf(stderr,"TT: (%ld %ld %ld) '%s'\n", raw_text.length(), fragment.offset, fragment.length, raw_text.c_str()); + LLAMA_LOG_WARN(TT: (%ld %ld %ld) '%s'\n", raw_text.length(), fragment.offset, fragment.length, raw_text.c_str()); #endif llm_tokenizer_bpe tokenizer(vocab); tokenizer.tokenize(raw_text, output); @@ -8641,7 +8641,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s if (params->imatrix) { imatrix_data = static_cast>*>(params->imatrix); if (imatrix_data) { - printf("================================ Have weights data with %d entries\n",int(imatrix_data->size())); + LLAMA_LOG_INFO("================================ Have weights data with %d entries\n",int(imatrix_data->size())); } } @@ -8764,12 +8764,12 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s if (imatrix_data) { auto it = imatrix_data->find(tensor->name); if (it == imatrix_data->end()) { - printf("\n====== %s: did not find weights for %s\n", __func__, tensor->name); + LLAMA_LOG_INFO("\n====== %s: did not find weights for %s\n", __func__, tensor->name); } else { if (it->second.size() == (size_t)tensor->ne[0]) { imatrix = it->second.data(); } else { - printf("\n====== %s: imatrix size %d is different from tensor size %d for %s\n", __func__, + LLAMA_LOG_INFO("\n====== %s: imatrix size %d is different from tensor size %d for %s\n", __func__, int(it->second.size()), int(tensor->ne[0]), tensor->name); } } @@ -8777,10 +8777,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s if ((new_type == GGML_TYPE_IQ2_XXS || new_type == GGML_TYPE_IQ2_XS || (new_type == GGML_TYPE_Q2_K && params->ftype == LLAMA_FTYPE_MOSTLY_Q2_K_S && strcmp(tensor->name, "token_embd.weight") != 0)) && !imatrix) { - fprintf(stderr, "\n\n============================================================\n"); - fprintf(stderr, "Missing importance matrix for tensor %s in a very low-bit quantization\n", tensor->name); - fprintf(stderr, "The result will be garbage, so bailing out\n"); - fprintf(stderr, "============================================================\n\n"); + LLAMA_LOG_ERROR("\n\n============================================================\n"); + LLAMA_LOG_ERROR("Missing importance matrix for tensor %s in a very low-bit quantization\n", tensor->name); + LLAMA_LOG_ERROR("The result will be garbage, so bailing out\n"); + LLAMA_LOG_ERROR("============================================================\n\n"); throw std::runtime_error(format("Missing importance matrix for tensor %s in a very low-bit quantization", tensor->name)); }