2.3 KiB
Reproducibility
vLLM does not guarantee the reproducibility of the results by default, for the sake of performance. You need to do the following to achieve reproducible results:
- For V1: Turn off multiprocessing to make the scheduling deterministic by setting
VLLM_ENABLE_V1_MULTIPROCESSING=0. - For V0: Set the global seed (see below).
Example: gh-file:examples/offline_inference/reproducibility.py
!!! warning
Applying the above settings [changes the random state in user code](#locality-of-random-state).
!!! note
Even with the above settings, vLLM only provides reproducibility
when it runs on the same hardware and the same vLLM version.
Also, the online serving API (`vllm serve`) does not support reproducibility
because it is almost impossible to make the scheduling deterministic in the
online setting.
Setting the global seed
The seed parameter in vLLM is used to control the random states for various random number generators.
If a specific seed value is provided, the random states for random, np.random, and torch.manual_seed will be set accordingly.
However, in some cases, setting the seed will also change the random state in user code.
Default Behavior
In V0, the seed parameter defaults to None. When the seed parameter is None, the random states for random, np.random, and torch.manual_seed are not set. This means that each run of vLLM will produce different results if temperature > 0, as expected.
In V1, the seed parameter defaults to 0 which sets the random state for each worker, so the results will remain consistent for each vLLM run even if temperature > 0.
!!! note
It is impossible to un-specify a seed for V1 because different workers need to sample the same outputs
for workflows such as speculative decoding.
For more information, see: <gh-pr:17929>
Locality of random state
The random state in user code (i.e. the code that constructs [LLM][vllm.LLM] class) is updated by vLLM under the following conditions:
- For V0: The seed is specified.
- For V1: The workers are run in the same process as user code, i.e.:
VLLM_ENABLE_V1_MULTIPROCESSING=0.
By default, these conditions are not active so you can use vLLM without having to worry about accidentally making deterministic subsequent operations that rely on random state.