Batching inference outputs are not the same with single inference

[gesanqiu]

If I call the llm.generate with a batch prompts and greedy search, the output of batch inference is different to single batch inference. Is this right? A minimum reprodece script looks like this:

from vllm import LLM, SamplingParams

# Sample prompts.
prompts = [
    "Hello, my name is",
    "The president of the United States is",
    "The capital of France is",
    "The future of AI is",
]
# Create a sampling params object.
sampling_params = SamplingParams(temperature=0)

# Create an LLM.
llm = LLM(model="/workdir/hf_models/llama-2-7b-chat-hf/", trust_remote_code=True)
# Generate texts from the prompts. The output is a list of RequestOutput objects
# that contain the prompt, generated text, and other information.
outputs = llm.generate(prompts, sampling_params)
# Print the outputs.
for output in outputs:
    prompt = output.prompt
    generated_text = output.outputs[0].text
    print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
    
    
for prompt in prompts:
    print(prompt)
    outputs = llm.generate(prompt, sampling_params)
    for output in outputs:
        generated_text = output.outputs[0].text
        print(f"Generated text: {generated_text!r}")

[WoosukKwon]

Hi @gesanqiu, I believe this should not be the case. Could you share a reproducible example?

[gesanqiu]

@WoosukKwon Sorry for made a mistake, this issue is tested on #1508, haven't reproduce this issue on vLLM release version yet. Need to check the dev branch.

[gesanqiu]

#1546 fixed this issue.