BUILD_TARGETS = main quantize quantize-stats perplexity embedding vdot train-text-from-scratch convert-llama2c-to-ggml simple save-load-state server embd-input-test gguf llama-bench baby-llama beam-search speculative tests/test-c.o
# Binaries only useful for tests
-TEST_TARGETS = tests/test-llama-grammar tests/test-grammar-parser tests/test-double-float tests/test-grad0 tests/test-opt tests/test-quantize-fns tests/test-quantize-perf tests/test-sampling tests/test-tokenizer-0-llama tests/test-tokenizer-0-falcon tests/test-tokenizer-1
+TEST_TARGETS = tests/test-llama-grammar tests/test-grammar-parser tests/test-double-float tests/test-grad0 tests/test-opt tests/test-quantize-fns tests/test-quantize-perf tests/test-sampling tests/test-tokenizer-0-llama tests/test-tokenizer-0-falcon tests/test-tokenizer-1-llama
# Code coverage output files
COV_TARGETS = *.gcno tests/*.gcno *.gcda tests/*.gcda *.gcov tests/*.gcov lcov-report gcovr-report
./$$test_target $(CURDIR)/models/ggml-vocab-llama.gguf; \
elif [ "$$test_target" = "tests/test-tokenizer-0-falcon" ]; then \
continue; \
- elif [ "$$test_target" = "tests/test-tokenizer-1" ]; then \
+ elif [ "$$test_target" = "tests/test-tokenizer-1-llama" ]; then \
continue; \
else \
echo "Running test $$test_target..."; \
tests/test-tokenizer-0-llama: tests/test-tokenizer-0-llama.cpp build-info.h ggml.o llama.o common.o $(OBJS)
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
-tests/test-tokenizer-1: tests/test-tokenizer-1.cpp build-info.h ggml.o llama.o common.o $(OBJS)
+tests/test-tokenizer-1-llama: tests/test-tokenizer-1-llama.cpp build-info.h ggml.o llama.o common.o $(OBJS)
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
tests/test-c.o: tests/test-c.c llama.h
while (offs < text.size()) {
llm_symbol sym;
size_t len = utf8_len(text[offs]);
- GGML_ASSERT(offs + len <= text.size());
sym.text = text.c_str() + offs;
- sym.n = len;
- offs += len;
+ sym.n = std::min(len, text.size() - offs);
+ offs += sym.n;
sym.prev = index - 1;
sym.next = offs == text.size() ? -1 : index + 1;
index++;
auto res = llama_tokenize_internal(model->vocab, text, add_bos);
if (n_max_tokens < (int) res.size()) {
- LLAMA_LOG_ERROR("%s: too many tokens\n", __func__);
+ // LLAMA_LOG_ERROR("%s: too many tokens\n", __func__);
return -((int) res.size());
}
llama_test_executable (test-tokenizer-0-llama test-tokenizer-0-llama.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf)
llama_build_executable(test-tokenizer-0-falcon.cpp)
#llama_test_executable (test-tokenizer-0-falcon test-tokenizer-0-falcon.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf)
-llama_build_executable(test-tokenizer-1.cpp)
-# test-tokenizer-1 requires a BPE vocab. re-enable when we have one.
-#llama_test_executable (test-tokenizer-1.llama test-tokenizer-1.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf)
+llama_build_executable(test-tokenizer-1-llama.cpp)
+llama_test_executable (test-tokenizer-1-llama test-tokenizer-1-llama.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf)
#llama_test_executable(test-tokenizer-1.aquila test-tokenizer-1.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-aquila.gguf)
llama_build_and_test_executable(test-grammar-parser.cpp)
llama_build_and_test_executable(test-llama-grammar.cpp)
#include "llama.h"
#include "common.h"
+#include "console.h"
#include <cstdio>
#include <string>
return 2;
}
+#ifdef _WIN32
+ // We need this for unicode console support
+ console::init(false, false);
+ atexit([]() { console::cleanup(); });
+#endif
+
bool success = true;
for (const auto & test_kv : k_tests()) {
--- /dev/null
+#include "llama.h"
+#include "common.h"
+#include "console.h"
+
+#include <cassert>
+#include <cstdio>
+#include <cstring>
+#include <string>
+#include <codecvt>
+#include <map>
+#include <vector>
+#include <locale>
+
+typedef int codepoint;
+
+std::string codepoint_to_utf8(codepoint cp) {
+ std::string result;
+ if (0x00 <= cp && cp <= 0x7f) {
+ result.push_back(cp);
+ } else if (0x80 <= cp && cp <= 0x7ff) {
+ result.push_back(0xc0 | ((cp >> 6) & 0x1f));
+ result.push_back(0x80 | (cp & 0x3f));
+ } else if (0x800 <= cp && cp <= 0xffff) {
+ result.push_back(0xe0 | ((cp >> 12) & 0x0f));
+ result.push_back(0x80 | ((cp >> 6) & 0x3f));
+ result.push_back(0x80 | (cp & 0x3f));
+ } else if (0x10000 <= cp && cp <= 0x10ffff) {
+ result.push_back(0xf0 | ((cp >> 18) & 0x07));
+ result.push_back(0x80 | ((cp >> 12) & 0x3f));
+ result.push_back(0x80 | ((cp >> 6) & 0x3f));
+ result.push_back(0x80 | (cp & 0x3f));
+ } else {
+ throw std::invalid_argument("invalid codepoint");
+ }
+ return result;
+}
+
+int main(int argc, char **argv) {
+ if (argc < 2) {
+ fprintf(stderr, "Usage: %s <vocab-file>\n", argv[0]);
+ return 1;
+ }
+
+ const std::string fname = argv[1];
+
+ fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str());
+
+ llama_model * model;
+ llama_context * ctx;
+
+ llama_backend_init(false);
+
+ // load the vocab
+ {
+ auto lparams = llama_context_default_params();
+
+ lparams.vocab_only = true;
+
+ model = llama_load_model_from_file(fname.c_str(), lparams);
+
+ if (model == NULL) {
+ fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
+ return 1;
+ }
+
+ ctx = llama_new_context_with_model(model, lparams);
+
+ if (ctx == NULL) {
+ fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
+ llama_free_model(model);
+ return 1;
+ }
+ }
+
+ GGML_ASSERT(llama_vocab_type(ctx) == LLAMA_VOCAB_TYPE_SPM);
+
+#ifdef _WIN32
+ // We need this for unicode console support
+ console::init(false, false);
+ atexit([]() { console::cleanup(); });
+#endif
+
+ const int n_vocab = llama_n_vocab(ctx);
+
+ for (int i = 0; i < n_vocab; ++i) {
+ std::string str = llama_detokenize_spm(ctx, std::vector<int>(1, i));
+ std::vector<llama_token> tokens = llama_tokenize(ctx, str, false);
+ std::string check = llama_detokenize_spm(ctx, tokens);
+ if (check != str) {
+ fprintf(stderr, "%s : error: token %d detokenizes to >%s<(%llu) but tokenization of this detokenizes to >%s<(%llu)\n",
+ __func__, i, str.c_str(), str.length(), check.c_str(), check.length());
+ if(i != 3)
+ return 2;
+ }
+ }
+
+ for (codepoint cp = 0x0000; cp < 0xffff; ++cp) {
+ if (cp < 0xd800 || cp > 0xdfff) {
+ std::string str = codepoint_to_utf8(cp);
+ std::vector<llama_token> tokens = llama_tokenize(ctx, str, false);
+ std::string check = llama_detokenize_spm(ctx, tokens);
+ if (str != check) {
+ fprintf(stderr, "%s : error: codepoint %d detokenizes to >%s<(%llu) instead of >%s<(%llu)\n",
+ __func__, cp, check.c_str(), check.length(), str.c_str(), str.length());
+ if(cp != 0 && cp != 9601)
+ return 3;
+ }
+ }
+ }
+ for (codepoint cp = 0x10000; cp < 0x0010ffff; ++cp) {
+ std::string str = codepoint_to_utf8(cp);
+ std::vector<llama_token> tokens = llama_tokenize(ctx, str, false);
+ std::string check = llama_detokenize_spm(ctx, tokens);
+ if (str != check) {
+ fprintf(stderr, "%s : error: codepoint %d detokenizes to >%s<(%llu) instead of >%s<(%llu)\n",
+ __func__, cp, check.c_str(), check.length(), str.c_str(), str.length());
+ return 4;
+ }
+ }
+
+ llama_free_model(model);
+ llama_free(ctx);
+
+ llama_backend_free();
+
+ return 0;
+}
+++ /dev/null
-#include "llama.h"
-#include "common.h"
-
-#include <cassert>
-#include <cstdio>
-#include <cstring>
-#include <string>
-#include <codecvt>
-#include <map>
-#include <vector>
-#include <locale>
-
-static std::string escape_whitespace(const std::string& text) {
- std::string result = "\xe2\x96\x81";
- for (size_t offs = 0; offs < text.length(); ++offs) {
- if (text[offs] == ' ') {
- result += "\xe2\x96\x81";
- } else {
- result += text[offs];
- }
- }
- return result;
-}
-
-int main(int argc, char **argv) {
- if (argc < 2) {
- fprintf(stderr, "Usage: %s <vocab-file>\n", argv[0]);
- return 1;
- }
-
- const std::string fname = argv[1];
-
- fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str());
-
- llama_model * model;
- llama_context * ctx;
-
- llama_backend_init(false);
-
- // load the vocab
- {
- auto lparams = llama_context_default_params();
-
- lparams.vocab_only = true;
-
- model = llama_load_model_from_file(fname.c_str(), lparams);
-
- if (model == NULL) {
- fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
- return 1;
- }
-
- ctx = llama_new_context_with_model(model, lparams);
-
- if (ctx == NULL) {
- fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
- llama_free_model(model);
- return 1;
- }
- }
-
- GGML_ASSERT(llama_vocab_type(ctx) == LLAMA_VOCAB_TYPE_BPE);
-
- const int n_vocab = llama_n_vocab(ctx);
-
- for (int i = 0; i < n_vocab; ++i) {
- std::string forward = llama_token_to_piece(ctx, i);
- std::vector<llama_token> tokens = llama_tokenize(ctx, forward, false);
- if (tokens.size() == 1) {
- if (i != tokens[0]) {
- std::string backward = llama_token_to_piece(ctx, tokens[0]);
- fprintf(stderr, "%s : error: token %d is string %s but bpe returns token %d %s\n",
- __func__, i, llama_token_to_piece(ctx, i).c_str(), tokens[0], backward.c_str());
- return 2;
- }
- }
- }
-
-#ifdef _WIN32
- std::wstring_convert<typename std::codecvt_utf8<char16_t>, char16_t> u16converter;
- for (char16_t ch = 0x0000; ch < 0xffff; ++ch) {
- std::u16string u16str(1, ch);
- std::string str = u16converter.to_bytes(u16str);
- std::vector<llama_token> tokens = llama_tokenize(ctx, escape_whitespace(str).c_str(), false);
- if (tokens.size() == 1) {
- fprintf(stderr, "%s : info: %s tokenized to %d \n",
- __func__, str.c_str(), tokens[0]);
- }
- }
-
- std::wstring_convert<typename std::codecvt_utf8<char32_t>, char32_t> u32converter;
- for (char32_t ch = 0x0000; ch < 0x0010ffff; ++ch) {
- std::u32string u32str(1, ch);
- std::string str = u32converter.to_bytes(u32str);
- std::vector<llama_token> tokens = llama_tokenize(ctx, escape_whitespace(str).c_str(), false);
- if (tokens.size() == 1) {
- fprintf(stderr, "%s : info: %s tokenized to %d \n", __func__, str.c_str(), tokens[0]);
- }
- }
-#endif
-
- llama_free_model(model);
- llama_free(ctx);
-
- llama_backend_free();
-
- return 0;
-}
overview / pkg / ggml / sources / llama.cpp / commitdiff