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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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15
fastdeploy/worker/gpu_model_runner.py
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@@ -267,6 +267,10 @@ class GPUModelRunner(ModelRunnerBase):
self.share_inputs["penalty_score"][idx : idx + 1] = request.get("repetition_penalty", 1.0)
self.share_inputs["frequency_score"][idx : idx + 1] = request.get("frequency_penalty", 0.0)
self.share_inputs["presence_score"][idx : idx + 1] = request.get("presence_penalty", 0.0)
self.share_inputs["temp_scaled_logprobs"][idx : idx + 1] = request.get("temp_scaled_logprobs", False)
self.share_inputs["top_p_normalized_logprobs"][idx : idx + 1] = request.get(
"top_p_normalized_logprobs", False
)
self.share_inputs["min_dec_len"][idx : idx + 1] = request.get("min_tokens", 1)
self.share_inputs["max_dec_len"][idx : idx + 1] = request.get(
@@ -431,6 +435,12 @@ class GPUModelRunner(ModelRunnerBase):
self.share_inputs["presence_score"][idx : idx + 1] = get_attr_from_request(
request, "presence_penalty", 0.0
)
self.share_inputs["temp_scaled_logprobs"][idx : idx + 1] = get_attr_from_request(
request, "temp_scaled_logprobs", False
)
self.share_inputs["top_p_normalized_logprobs"][idx : idx + 1] = get_attr_from_request(
request, "top_p_normalized_logprobs", False
)
self.share_inputs["min_dec_len"][idx : idx + 1] = request.get("min_tokens", 1)
self.share_inputs["max_dec_len"][idx : idx + 1] = request.get(
@@ -543,6 +553,8 @@ class GPUModelRunner(ModelRunnerBase):
self.share_inputs["presence_score"] = paddle.full(
[max_num_seqs, 1], self.model_config.presence_score, dtype="float32"
)
self.share_inputs["temp_scaled_logprobs"] = paddle.full([max_num_seqs, 1], False, dtype="bool")
self.share_inputs["top_p_normalized_logprobs"] = paddle.full([max_num_seqs, 1], False, dtype="bool")
self.share_inputs["min_dec_len"] = paddle.full([max_num_seqs, 1], self.model_config.min_length, dtype="int64")
self.share_inputs["max_dec_len"] = paddle.full(
@@ -748,6 +760,9 @@ class GPUModelRunner(ModelRunnerBase):
bad_words_token_ids=self.share_inputs["bad_tokens"],
eos_token_ids=self.share_inputs["eos_token_id"],
max_num_logprobs=20 if self.enable_logprob else None,
temp_scaled_logprobs=self.share_inputs["temp_scaled_logprobs"],
top_p_normalized_logprobs=self.share_inputs["top_p_normalized_logprobs"],
share_inputs=self.share_inputs,
)
def load_model(self) -> None: