"""Compare the outputs of HF and vLLM when using greedy sampling. This test only tests small models. Big models such as 7B should be tested from test_big_models.py because it could use a larger instance to run tests. Run `pytest tests/models/test_models.py`. """ import pytest from vllm.platforms import current_platform from ...utils import check_logprobs_close MODELS = [ "facebook/opt-125m", # opt "openai-community/gpt2", # gpt2 # "Milos/slovak-gpt-j-405M", # gptj # "bigcode/tiny_starcoder_py", # gpt_bigcode # "EleutherAI/pythia-70m", # gpt_neox "bigscience/bloom-560m", # bloom - testing alibi slopes "microsoft/phi-2", # phi # "stabilityai/stablelm-3b-4e1t", # stablelm # "bigcode/starcoder2-3b", # starcoder2 "google/gemma-1.1-2b-it", # gemma "Qwen/Qwen2.5-0.5B-Instruct", # qwen2 "meta-llama/Llama-3.2-1B-Instruct", # llama ] if not current_platform.is_cpu(): MODELS += [ # fused_moe which not supported on CPU "openbmb/MiniCPM3-4B", ] target_dtype = "half" @pytest.mark.parametrize("model", MODELS) @pytest.mark.parametrize("dtype", [target_dtype]) @pytest.mark.parametrize("max_tokens", [32]) @pytest.mark.parametrize("num_logprobs", [5]) def test_models( hf_runner, vllm_runner, example_prompts, model: str, dtype: str, max_tokens: int, num_logprobs: int, ) -> None: with hf_runner(model, dtype=dtype) as hf_model: hf_outputs = hf_model.generate_greedy_logprobs_limit( example_prompts, max_tokens, num_logprobs) with vllm_runner(model, dtype=dtype) as vllm_model: vllm_outputs = vllm_model.generate_greedy_logprobs( example_prompts, max_tokens, num_logprobs) # This test is for verifying whether the model's extra_repr # can be printed correctly. print(vllm_model.model.llm_engine.model_executor.driver_worker. model_runner.model) check_logprobs_close( outputs_0_lst=hf_outputs, outputs_1_lst=vllm_outputs, name_0="hf", name_1="vllm", )