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[Feature] Add temp_scaled_logprobs and top_p_normalized_logprobs parameters for logits and logprobs post processing (#3536)

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* [feature] Add temp_scaled_logprobs and top_p_normalized_logprobs parameters for logits and logprobs post processing

* infer engine support temp_scaled_logprobs and top_p_normalized_logprobs

* code check

* code check

* fix tokenizer.decoder(-1), return 'Invalid Token'

* check seq len time shape

* logprob clip inf

* code check

---------

Co-authored-by: sunlei1024 <sunlei5788@gmail.com>
This commit is contained in:
chen
2025-08-25 14:11:18 +08:00
committed by GitHub
parent b7890cbe8d
commit 2136990144
5 changed files with 84 additions and 4 deletions
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5
fastdeploy/model_executor/layers/sample/meta_data.py
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@@ -15,7 +15,7 @@
"""
from dataclasses import dataclass
from typing import Optional
from typing import Dict, Optional
import paddle
@@ -46,3 +46,6 @@ class SamplingMetadata:
max_num_logprobs: Optional[int] = None
prompt_ids: Optional[paddle.Tensor] = None
prompt_lens: Optional[paddle.Tensor] = None
temp_scaled_logprobs: Optional[paddle.Tensor] = None
top_p_normalized_logprobs: Optional[paddle.Tensor] = None
share_inputs: Optional[Dict[str, paddle.Tensor]] = None