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Rename top_p_sampling to top_k_top_p_sampling (#2791)

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This commit is contained in:
Sunny-bot1
2025-07-10 15:09:25 +08:00
committed by GitHub
parent e45050cae3
commit 1e2319cbef
5 changed files with 23 additions and 16 deletions
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4
fastdeploy/model_executor/layers/sample/ops/__init__.py
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@@ -16,10 +16,10 @@
from .apply_penalty_multi_scores import (
apply_penalty_multi_scores, apply_speculative_penalty_multi_scores)
from .top_p_sampling import top_p_sampling
from .top_k_top_p_sampling import top_k_top_p_sampling
__all__ = [
"apply_penalty_multi_scores",
"apply_speculative_penalty_multi_scores",
"top_p_sampling",
"top_k_top_p_sampling",
]

2
fastdeploy/model_executor/layers/sample/ops/top_p_sampling.py → fastdeploy/model_executor/layers/sample/ops/top_k_top_p_sampling.py
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@@ -25,7 +25,7 @@ if current_platform.is_gcu():
from fastdeploy.model_executor.ops.gcu import \
top_p_sampling as gcu_top_p_sampling
def top_p_sampling(
def top_k_top_p_sampling(
x: paddle.Tensor,
top_p: paddle.Tensor,
top_k: Optional[paddle.Tensor] = None,

6
fastdeploy/model_executor/layers/sample/sampler.py
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@@ -27,7 +27,7 @@ from fastdeploy.model_executor.guided_decoding.base_guided_decoding import \
from fastdeploy.model_executor.layers.sample.meta_data import SamplingMetadata
from fastdeploy.model_executor.layers.sample.ops import (
apply_penalty_multi_scores, apply_speculative_penalty_multi_scores,
top_p_sampling)
top_k_top_p_sampling)
from fastdeploy.platforms import current_platform
@@ -214,7 +214,7 @@ class Sampler(nn.Layer):
probs = F.softmax(logits)
_, next_tokens = top_p_sampling(probs, sampling_metadata.top_p, sampling_metadata.top_k)
_, next_tokens = top_k_top_p_sampling(probs, sampling_metadata.top_p, sampling_metadata.top_k)
self.processor.update_output_tokens(next_tokens, skip_idx_list)
return next_tokens
@@ -367,5 +367,5 @@ class MTPSampler(nn.Layer):
)
probs = F.softmax(logits)
_, next_tokens = top_p_sampling(probs, sampling_metadata.top_p, sampling_metadata.top_k)
_, next_tokens = top_k_top_p_sampling(probs, sampling_metadata.top_p, sampling_metadata.top_k)
return next_tokens