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[XPU] Add TP broadcast after sampling in XPU model runner. #7096

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[XPU] Add TP broadcast after sampling in XPU model runner. #7096

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27 changes: 27 additions & 0 deletions fastdeploy/worker/xpu_model_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1585,13 +1585,40 @@ class at the server level, which is too granular for ModelRunner.
sampler_output = None
if not self.speculative_decoding:
sampler_output = self.sampler(logits, self.sampling_metadata)
if self.parallel_config.tensor_parallel_size > 1:
paddle.distributed.broadcast(
sampler_output.sampled_token_ids,
self.parallel_config.data_parallel_rank * self.parallel_config.tensor_parallel_size,
group=self.parallel_config.tp_group,
)
Comment on lines +1588 to +1593
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Copilot AI Mar 31, 2026

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这里 src（root rank）的计算表达式在多处重复使用，后面 speculative 分支也同样重复。建议先用局部变量（例如 tp_src_rank = data_parallel_rank * tensor_parallel_size）保存，再传给 broadcast，避免复制粘贴带来的维护风险。

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else:
sampler_output = self.sampler(
logits,
self.sampling_metadata,
self.model_config.max_model_len,
self.share_inputs,
)
if self.parallel_config.tensor_parallel_size > 1:
paddle.distributed.broadcast(
self.share_inputs["accept_tokens"],
self.parallel_config.data_parallel_rank * self.parallel_config.tensor_parallel_size,
group=self.parallel_config.tp_group,
)
Comment on lines +1601 to +1606
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Copilot AI Mar 31, 2026

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speculative 分支里连续多次调用 broadcast，且每次都重复同一个 src 计算逻辑。建议复用同一个 tp_src_rank 变量，并考虑用一个 key 列表循环广播这些张量（accept_tokens/accept_num/step_idx/stop_flags），降低后续新增/修改字段时遗漏的概率。

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paddle.distributed.broadcast(
self.share_inputs["accept_num"],
self.parallel_config.data_parallel_rank * self.parallel_config.tensor_parallel_size,
group=self.parallel_config.tp_group,
)
paddle.distributed.broadcast(
self.share_inputs["step_idx"],
self.parallel_config.data_parallel_rank * self.parallel_config.tensor_parallel_size,
group=self.parallel_config.tp_group,
)
paddle.distributed.broadcast(
self.share_inputs["stop_flags"],
self.parallel_config.data_parallel_rank * self.parallel_config.tensor_parallel_size,
group=self.parallel_config.tp_group,
)

prompt_logprobs_list = None
if not self.speculative_decoding:
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