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Daniel Bevenius dfd9b5f6c7 model-conversion : set pooling type to none in logits.cpp (#15564)
This commit explicitly sets the pooling type to 'none' in the logits.cpp
to support models that have a pooling type specified.

The motivation for this is that some models may have a pooling type set
in the model file (.gguf file) and for this specific case where we only
want to extract logits, we need to ensure that no pooling is used to
so that we are comparing raw logits and not pooled embeddings.
2025-08-25 15:00:43 +02:00

211 lines
6.3 KiB
C++

#include "llama.h"
#include <cstdio>
#include <cstring>
#include <string>
#include <vector>
#include <ctype.h>
#include <filesystem>
static void print_usage(int, char ** argv) {
printf("\nexample usage:\n");
printf("\n %s -m model.gguf [-ngl n_gpu_layers] -embd-mode [prompt]\n", argv[0]);
printf("\n");
}
int main(int argc, char ** argv) {
std::string model_path;
std::string prompt = "Hello, my name is";
int ngl = 0;
bool embedding_mode = false;
{
int i = 1;
for (; i < argc; i++) {
if (strcmp(argv[i], "-m") == 0) {
if (i + 1 < argc) {
model_path = argv[++i];
} else {
print_usage(argc, argv);
return 1;
}
} else if (strcmp(argv[i], "-ngl") == 0) {
if (i + 1 < argc) {
try {
ngl = std::stoi(argv[++i]);
} catch (...) {
print_usage(argc, argv);
return 1;
}
} else {
print_usage(argc, argv);
return 1;
}
} else if (strcmp(argv[i], "-embd-mode") == 0) {
if (i + 1 < argc) {
try {
embedding_mode = true;
} catch (...) {
print_usage(argc, argv);
return 1;
}
} else {
print_usage(argc, argv);
return 1;
}
} else {
// prompt starts here
break;
}
}
if (model_path.empty()) {
print_usage(argc, argv);
return 1;
}
if (i < argc) {
prompt = argv[i++];
for (; i < argc; i++) {
prompt += " ";
prompt += argv[i];
}
}
}
ggml_backend_load_all();
llama_model_params model_params = llama_model_default_params();
model_params.n_gpu_layers = ngl;
llama_model * model = llama_model_load_from_file(model_path.c_str(), model_params);
if (model == NULL) {
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;
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) {
*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);
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) {
fprintf(stderr, "%s: error: failed to tokenize the prompt\n", __func__);
return 1;
}
llama_context_params ctx_params = llama_context_default_params();
ctx_params.n_ctx = n_prompt;
ctx_params.n_batch = n_prompt;
ctx_params.no_perf = false;
if (embedding_mode) {
ctx_params.embeddings = true;
ctx_params.pooling_type = LLAMA_POOLING_TYPE_NONE;
ctx_params.n_ubatch = ctx_params.n_batch;
}
llama_context * ctx = llama_init_from_model(model, ctx_params);
if (ctx == NULL) {
fprintf(stderr , "%s: error: failed to create the llama_context\n" , __func__);
return 1;
}
printf("Input prompt: \"%s\"\n", prompt.c_str());
printf("Tokenized prompt (%d tokens): ", n_prompt);
for (auto id : prompt_tokens) {
char buf[128];
int n = llama_token_to_piece(vocab, id, buf, sizeof(buf), 0, true);
if (n < 0) {
fprintf(stderr, "%s: error: failed to convert token to piece\n", __func__);
return 1;
}
std::string s(buf, n);
printf("%s", s.c_str());
}
printf("\n");
llama_batch batch = llama_batch_get_one(prompt_tokens.data(), prompt_tokens.size());
if (llama_decode(ctx, batch)) {
fprintf(stderr, "%s : failed to eval\n", __func__);
return 1;
}
float * logits;
int n_logits;
const char * type;
if (embedding_mode) {
logits = llama_get_embeddings(ctx);
n_logits = llama_model_n_embd(model) * batch.n_tokens;
type = "-embeddings";
printf("Embeddings size: %d\n", n_logits);
} else {
logits = llama_get_logits_ith(ctx, batch.n_tokens - 1);
n_logits = llama_vocab_n_tokens(vocab);
type = "";
printf("Vocab size: %d\n", n_logits);
}
std::filesystem::create_directory("data");
// Save logits to binary file
char bin_filename[512];
snprintf(bin_filename, sizeof(bin_filename), "data/llamacpp-%s%s.bin", model_name, type);
printf("Saving logits to %s\n", bin_filename);
FILE * f = fopen(bin_filename, "wb");
if (f == NULL) {
fprintf(stderr, "%s: error: failed to open binary output file\n", __func__);
return 1;
}
fwrite(logits, sizeof(float), n_logits, f);
fclose(f);
// Also save as text for debugging
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) {
fprintf(stderr, "%s: error: failed to open text output file\n", __func__);
return 1;
}
for (int i = 0; i < n_logits; i++) {
fprintf(f, "%d: %.6f\n", i, logits[i]); // Added index and changed format
}
fclose(f);
// Print first and last 10 logits for quick verification
printf("First 10 logits: ");
for (int i = 0; i < 10 && i < n_logits; i++) {
printf("%.6f ", logits[i]);
}
printf("\n");
printf("Last 10 logits: ");
for (int i = n_logits - 10; i < n_logits; i++) {
if (i >= 0) printf("%.6f ", logits[i]);
}
printf("\n\n");
printf("Logits saved to %s\n", bin_filename);
printf("Logits saved to %s\n", txt_filename);
llama_free(ctx);
llama_model_free(model);
return 0;
}