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[Cherry-Pick][BugFix] fix rl model_weights_signal to support tp>1 #5639 (#5637)
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This commit is contained in:
Yuanle Liu
2025-12-18 20:44:19 +08:00
committed by GitHub
parent 646d1a0aa2
commit 9c55bc31cd
1 changed files with 4 additions and 13 deletions
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17
fastdeploy/worker/worker_process.py
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@@ -423,17 +423,11 @@ class PaddleDisWorkerProc:
while True:
# run eplb
self._run_eplb(tp_rank)
if tp_rank == 0:
if self.fd_config.load_config.dynamic_load_weight:
if self.model_weights_status.value[0] != ModelWeightsStatus.NORMAL:
self.model_weights_signal[0] = int(self.model_weights_status.value[0])
if self.fd_config.load_config.dynamic_load_weight and self.parallel_config.enable_expert_parallel:
self.model_weights_signal[0] = self._broadcast_model_weights_signal(
src=0, group=self.parallel_config.ep_group
)
if self.fd_config.load_config.dynamic_load_weight and tp_size > 1:
self.model_weights_signal[0] = self._broadcast_model_weights_signal(
src=0, group=self.parallel_config.tp_group
)
self.model_weights_signal[0] = self._broadcast_model_weights_signal(src=0, group=None)
self.insert_step = False
req_dicts = None
@@ -455,11 +449,8 @@ class PaddleDisWorkerProc:
self._tp_barrier_wait()
if self.fd_config.load_config.dynamic_load_weight:
if self.parallel_config.enable_expert_parallel:
paddle.distributed.barrier(self.parallel_config.ep_group)
else:
paddle.distributed.barrier(self.parallel_config.tp_group)
if self.model_weights_signal[0] != ModelWeightsStatus.NORMAL:
paddle.distributed.barrier()
logger.info(
f"Rank: {self.local_rank} to update or clear parameters, signal is {self.model_weights_signal[0]}, [-1:clear, 1:update]"
)