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[Core] Remove tokenizer group in vLLM (#24078)

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Signed-off-by: Zhuohan Li <zhuohan123@gmail.com>
This commit is contained in:
Zhuohan Li
2025-09-17 01:42:59 -07:00
committed by GitHub
parent c15309a730
commit 6c47f6bfa4
49 changed files with 276 additions and 934 deletions
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29
tests/lora/test_quant_model.py
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@@ -82,31 +82,20 @@ def test_quant_model_lora(tinyllama_lora_files, model):
gpu_memory_utilization=0.2, #avoid OOM
quantization=model.quantization,
trust_remote_code=True,
enable_chunked_prefill=True)
enable_chunked_prefill=True,
tokenizer=tinyllama_lora_files)
if model.quantization is None:
expected_no_lora_output = [
"Here are some examples of orange-brown colors",
"I'm sorry, I don't have"
]
expected_lora_output = [
"#ff8050",
"#ff8080",
]
elif model.quantization == "awq":
expected_no_lora_output = [
"I'm sorry, I don't understand",
"I'm sorry, I don't understand",
]
expected_lora_output = [
"#f07700: A v",
"#f00000: A v",
]
elif model.quantization == "gptq":
expected_no_lora_output = [
"I'm sorry, I don't have",
"I'm sorry, I don't have",
]
expected_lora_output = [
"#f08800: This is",
"#f07788 \n#",
@@ -117,7 +106,6 @@ def test_quant_model_lora(tinyllama_lora_files, model):
# Assert that the outputs changed.
if (model.quantization == "gptq"
and expected_output is expected_lora_output):
assert output != expected_no_lora_output
for i, o in enumerate(output):
assert o.startswith(
'#'), f"Expected example {i} to start with # but got {o}"
@@ -127,12 +115,6 @@ def test_quant_model_lora(tinyllama_lora_files, model):
max_tokens = 10
print("lora adapter created")
output = do_sample(llm,
tinyllama_lora_files,
lora_id=0,
max_tokens=max_tokens)
expect_match(output, expected_no_lora_output)
print("lora 1")
output = do_sample(llm,
tinyllama_lora_files,
@@ -140,13 +122,6 @@ def test_quant_model_lora(tinyllama_lora_files, model):
max_tokens=max_tokens)
expect_match(output, expected_lora_output)
print("no lora")
output = do_sample(llm,
tinyllama_lora_files,
lora_id=0,
max_tokens=max_tokens)
expect_match(output, expected_no_lora_output)
print("lora 2")
output = do_sample(llm,
tinyllama_lora_files,