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llama : use LLAMA_LOG_ macros for logging

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Georgi Gerganov 2024-01-14 11:03:19 +02:00
parent a128c38de8
commit 03c5267490
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GPG Key ID: 449E073F9DC10735
1 changed files with 23 additions and 23 deletions
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llama.cpp
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@ -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_vocab::id> 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_vocab::id> 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<const std::unordered_map<std::string, std::vector<float>>*>(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));
}