[Core] Adding token ranks along with logprobs #3516
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SwapnilDreams100
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SwapnilDreams100
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rkooo567
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Mar 20, 2024
| @@ -447,6 +447,9 @@ def _sample( | |||
| ] | |||
| return sample_results | |||
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| def _get_ranks(x: torch.Tensor, indices: List[int]) -> torch.Tensor: | |||
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Can you add docstring to this func? Like the shape of x tensors, and what exactly indices mean?
| @@ -17,9 +17,9 @@ | |||
| class Logprob: | |||
| """Infos for supporting OpenAI compatible logprobs.""" | |||
| logprob: float | |||
| rank: Optional[int] = None | |||
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Can you comment what this means here
added 2 commits
March 19, 2024 22:05
Yard1
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Mar 20, 2024
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| batched_ranks_query_result = _get_ranks( | ||
| logprobs[batched_logprobs_query_seq_indices], | ||
| batched_logprobs_query_token_indices) |
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let's move this after line 526, since we'll have to force a CPU<->GPU sync here anyway.
Yard1
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Mar 20, 2024
|
One question I guess is whether these should also be exposed in the openai API responses (but doesn't necessarily need to be addressed in this PR). |
rkooo567
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Mar 21, 2024
xjpang
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Co-authored-by: Swapnil Parekh <[email protected]>
Temirulan
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Co-authored-by: Swapnil Parekh <[email protected]>
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Adds the token rank functionality (for both prompt tokens and sample tokens) within the
Logprobsobject, by adding therankproperty toLogprobs.This PR also adds a couple of tests to verify the ranks in greedy and non-greedy settings.
The implementation here is meant to align with functionality in https://github.com/IBM/text-generation-inference (IBM's fork of HF TGI).