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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 9, 02:30 UTC

Remove incorrect tokenizer info test (#33565)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

Harry Mellor committed Feb 2, 2026 at 17:11 UTC 6141ebe0dd5ed8d8034c6eb8e011b321bedb1697
1 file changed -20
tests/entrypoints/openai/test_tokenization.py
-20
@@ -301,26 +301,6 @@ async def test_tokenizer_info_schema(server: RemoteOpenAIServer):
301 )
302
303
304 -@pytest.mark.asyncio
305 -async def test_tokenizer_info_added_tokens_structure(
306 - server: RemoteOpenAIServer,
307 -):
308 - """Test added_tokens_decoder structure if present."""
309 - response = requests.get(server.url_for("tokenizer_info"))
310 - response.raise_for_status()
311 - result = response.json()
312 - added_tokens = result.get("added_tokens_decoder")
313 - if added_tokens:
314 - for token_id, token_info in added_tokens.items():
315 - assert isinstance(token_id, str), "Token IDs should be strings"
316 - assert isinstance(token_info, dict), "Token info should be a dict"
317 - assert "content" in token_info, "Token info should have content"
318 - assert "special" in token_info, "Token info should have special flag"
319 - assert isinstance(token_info["special"], bool), (
320 - "Special flag should be boolean"
321 - )
322 -
323 -
304 @pytest.mark.asyncio
305 async def test_tokenizer_info_consistency_with_tokenize(
306 server: RemoteOpenAIServer,