55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
"""Compare the outputs of HF and vLLM when using beam search.
|
|
|
|
Run `pytest tests/samplers/test_beam_search.py`.
|
|
"""
|
|
import gc
|
|
|
|
import pytest
|
|
import torch
|
|
|
|
# FIXME(zhuohan): The test can not pass if we:
|
|
# 1. Increase max_tokens to 256.
|
|
# 2. Increase beam_width to 8.
|
|
# 3. Use the model "huggyllama/llama-7b".
|
|
MAX_TOKENS = [128]
|
|
BEAM_WIDTHS = [4]
|
|
MODELS = ["facebook/opt-125m"]
|
|
|
|
|
|
@pytest.mark.parametrize("model", MODELS)
|
|
@pytest.mark.parametrize("dtype", ["half"])
|
|
@pytest.mark.parametrize("max_tokens", MAX_TOKENS)
|
|
@pytest.mark.parametrize("beam_width", BEAM_WIDTHS)
|
|
def test_beam_search_single_input(
|
|
hf_runner,
|
|
vllm_runner,
|
|
example_prompts,
|
|
model: str,
|
|
dtype: str,
|
|
max_tokens: int,
|
|
beam_width: int,
|
|
) -> None:
|
|
example_prompts = example_prompts[:1]
|
|
hf_model = hf_runner(model, dtype=dtype)
|
|
hf_outputs = hf_model.generate_beam_search(example_prompts, beam_width,
|
|
max_tokens)
|
|
del hf_model
|
|
|
|
vllm_model = vllm_runner(model, dtype=dtype)
|
|
vllm_outputs = vllm_model.generate_beam_search(example_prompts, beam_width,
|
|
max_tokens)
|
|
del vllm_model
|
|
# NOTE(woosuk): For some reason, the following GC is required to avoid
|
|
# GPU OOM errors in the following tests using `vllm_runner`.
|
|
gc.collect()
|
|
torch.cuda.empty_cache()
|
|
|
|
for i in range(len(example_prompts)):
|
|
hf_output_ids, _ = hf_outputs[i]
|
|
vllm_output_ids, _ = vllm_outputs[i]
|
|
assert len(hf_output_ids) == len(vllm_output_ids)
|
|
for j in range(len(hf_output_ids)):
|
|
assert hf_output_ids[j] == vllm_output_ids[j], (
|
|
f"Test{i} output{j}:\nHF: {hf_output_ids}\n"
|
|
f"vLLM: {vllm_output_ids}")
|