Assigning resources to a `Step`¶

When dealing with complex pipelines that get executed in a distributed environment with abundant resources (CPUs and GPUs), sometimes it's necessary to allocate these resources judiciously among the Steps. This is why distilabel allows to specify the number of replicas, cpus and gpus for each Step. Let's see that with an example:

from distilabel.pipeline import Pipeline
from distilabel.llms import vLLM
from distilabel.steps import StepResources
from distilabel.steps.tasks import PrometheusEval


with Pipeline(name="resources") as pipeline:
    ...

    prometheus = PrometheusEval(
        llm=vLLM(
            model="prometheus-eval/prometheus-7b-v2.0",
            chat_template="[INST] {{ messages[0]['content'] }}\\n{{ messages[1]['content'] }}[/INST]",
        ),
        resources=StepResources(replicas=2, cpus=1, gpus=1)
        mode="absolute",
        rubric="factual-validity",
        reference=False,
        num_generations=1,
        group_generations=False,
    )

In the example above, we're creating a PrometheusEval task (remember that Tasks are Steps) that will use vLLM to serve prometheus-eval/prometheus-7b-v2.0 model. This task is resource intensive as it requires an LLM, which in turn requires a GPU to run fast. With that in mind, we have specified the resources required for the task using the StepResources class, and we have defined that we need 1 GPU and 1 CPU per replica of the task. In addition, we have defined that we need 2 replicas i.e. we will run two instances of the task so the computation for the whole dataset runs faster. In addition, StepResources uses the RuntimeParametersMixin, so we can also specify the resources for each step when running the pipeline:

...

if __name__ == "__main__":
    pipeline.run(
        parameters={
            prometheus.name: {"resources": {"replicas": 2, "cpus": 1, "gpus": 1}}
        }
    )

And that's it! When running the pipeline, distilabel will create the tasks in nodes that have available the specified resources.

Assigning resources to a Step¶

Assigning resources to a `Step`¶