Merge 883dc22d44 into f0d4b29edf

tests/test-tokenizer-random.py

@@ -1,3 +1,5 @@
+#!/usr/bin/env python3
+#
 # Test libllama tokenizer == AutoTokenizer.
 # Brute force random words/text generation.
 #
@@ -11,20 +13,24 @@ from __future__ import annotations
 import time
 import logging
 import argparse
+import shutil
 import subprocess
 import random
 import unicodedata
-
 from pathlib import Path
-from typing import Any, Iterator, cast
+from typing import Any, Iterator, cast, Sequence
 from typing_extensions import Buffer
-
+#
+# External Imports
 import cffi
 from transformers import AutoTokenizer, PreTrainedTokenizer
-
+#
 
 logger = logging.getLogger("test-tokenizer-random")
 
+if shutil.which("gcc") is None:
+    raise EnvironmentError("GCC is not available on this system. Please install GCC or use preprocessed headers.")
+
 
 class LibLlama:
 
@@ -408,14 +414,20 @@ def generator_random_vocab_words(tokenizer: TokenizerGroundtruth, iterations=100
 
 
 def compare_tokenizers(tokenizer1: TokenizerGroundtruth, tokenizer2: TokenizerLlamaCpp, generator: Iterator[str]):
-
-    def find_first_mismatch(ids1: list[int] | str, ids2: list[int] | str):
-        for i, (a, b) in enumerate(zip(ids1, ids2)):
-            if a != b:
-                return i
-        if len(ids1) == len(ids2):
-            return -1
-        return min(len(ids1), len(ids2))
+    try:
+        # def find_first_mismatch(ids1: list[int] | str, ids2: list[int] | str):
+        #     for i, (a, b) in enumerate(zip(ids1, ids2)):
+        #         if a != b:
+        #             return i
+        #     if len(ids1) == len(ids2):
+        #         return -1
+        #     return min(len(ids1), len(ids2))
+        # Rewritten to use zip() and next() instead of for loop
+        def find_first_mismatch(ids1: Sequence[Any], ids2: Sequence[Any]) -> int:
+            index = next((i for i, (a, b) in enumerate(zip(ids1, ids2)) if a != b), -1)
+            if index < 0 and len(ids1) != len(ids2):
+                index = min(len(ids1), len(ids2))
+            return index
 
         def check_detokenizer(text: str, text1: str, text2: str) -> bool:
             if text1 == text2:  # equal to TokenizerGroundtruth?
@@ -478,6 +490,8 @@ def compare_tokenizers(tokenizer1: TokenizerGroundtruth, tokenizer2: TokenizerLl
 
         t_total = time.perf_counter() - t_start
         logger.info(f"{generator.__qualname__}: end,  {t_encode1=:.3f} {t_encode2=:.3f}  {t_decode1=:.3f} {t_decode2=:.3f}  {t_total=:.3f}")
+    except Exception as e:
+        logger.exception(f"An error occurred during tokenizer comparison: {e}")
 
 
 def main(argv: list[str] | None = None):
@@ -485,6 +499,9 @@ def main(argv: list[str] | None = None):
     parser.add_argument("vocab_file", type=str, help="path to vocab 'gguf' file")
     parser.add_argument("dir_tokenizer", type=str, help="directory containing 'tokenizer.model' file")
     parser.add_argument("--verbose", action="store_true", help="increase output verbosity")
+    parser.add_argument("--max-errors", type=int, default=10, help="Maximum number of errors before stopping")
+    parser.add_argument("--iterations", type=int, default=100, help="Number of iterations for random generators")
+    parser.add_argument("--tokenizers", nargs="+", help="List of tokenizers to test", default=tokenizers)
     args = parser.parse_args(argv)
 
     logging.basicConfig(level = logging.DEBUG if args.verbose else logging.INFO)