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custom reward function support for ppo trainer #2540

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What does this PR do?

Fixes #2518

Adding support for a custom reward function for the PPO trainer.

How it works

Write a custom function that takes a list of texts as input, representing a batch of responses, and outputs a list of scores.

def custom_reward_function(texts: list) -> list:
    """
    Custom reward function that applies a given reward logic to each item in the list.
    
    Args:
        items (list): List of items to evaluate.
    
    Returns:
        list: List of rewards based on the provided reward logic.
    """
    rewards = [reward_logic(item) for item in items]

I will add more documentation and explanations later after running several tests to make sure the implementation is functional.

Before submitting

  • This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
  • Did you read the contributor guideline,
    Pull Request section?
  • Was this discussed/approved via a GitHub issue? Please add a link
    to it if that's the case.
  • Did you make sure to update the documentation with your changes? Here are the
    documentation guidelines.
  • Did you write any new necessary tests?

Who can review?

@qgallouedec

@@ -1049,14 +1049,20 @@ def first_true_indices(bools: torch.Tensor, dtype=torch.long):


def get_reward(
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This is where the primary change are:
modifying the get_reward function to work with both a nn.Module and a Callable.

@HuggingFaceDocBuilderDev

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

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[question] best way to have my own reward model which is backed by rules
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