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Tong Li 2025-04-30 11:33:23 +08:00
parent bb8d370b44
commit 3454b10884
1 changed files with 6 additions and 4 deletions
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10
applications/ColossalChat/coati/distributed/producer.py
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@ -132,19 +132,21 @@ class BaseProducer:
): ):
self.model.llm.sleep() # revict KV_cache to avoid OOM self.model.llm.sleep() # revict KV_cache to avoid OOM
# don't sync model for last iteration # don't sync model for last iteration
print(
f"[P{self.producer_idx}] Sync model episode {episode} step {(i + 1) // self.num_microbatches - 1}"
)
torch.cuda.empty_cache() torch.cuda.empty_cache()
if self.consumer_pp_size > 1: if self.consumer_pp_size > 1:
for i in range(self.consumer_pp_size): for i in range(self.consumer_pp_size):
print(f"[P{self.producer_idx}] Sync model PP stage {i}") print(
f"[P{self.producer_idx}] Sync model PP stage {i} episode {episode} step {(i + 1) // self.num_microbatches - 1}"
)
state_dict = ray_broadcast_tensor_dict( state_dict = ray_broadcast_tensor_dict(
None, self.num_producers, device=self.device, group_name=f"sync_model_{i}" None, self.num_producers, device=self.device, group_name=f"sync_model_{i}"
) )
self.load_state_dict(state_dict) self.load_state_dict(state_dict)
else: else:
print(
f"[P{self.producer_idx}] Sync model episode {episode} step {(i + 1) // self.num_microbatches - 1}"
)
state_dict = ray_broadcast_tensor_dict( state_dict = ray_broadcast_tensor_dict(
None, self.num_producers, device=self.device, group_name="sync_model" None, self.num_producers, device=self.device, group_name="sync_model"
) )