mirror of https://github.com/hpcaitech/ColossalAI
parent
a5dc4253c6
commit
fef5c949c3
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@ -211,7 +211,7 @@ class WorkerBase(ABC):
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refcount = 0
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refcount = 0
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with self.output_list_condition_lock:
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with self.output_list_condition_lock:
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if refcount < lifecycle:
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if refcount <= lifecycle:
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self.output_list[key] = output_work_item
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self.output_list[key] = output_work_item
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self.output_list_condition_lock.notify_all()
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self.output_list_condition_lock.notify_all()
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@ -390,7 +390,7 @@ class WorkerBase(ABC):
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subscribe_forward_futures[target_index] = []
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subscribe_forward_futures[target_index] = []
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else:
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else:
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subscribe_forward_futures[target_index] = producer_worker_rref.rpc_async().get_output_by_key(
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subscribe_forward_futures[target_index] = producer_worker_rref.rpc_async().get_output_by_key(
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producer_output_key, rank=self.pp_rank)
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producer_output_key, rank=self.pp_rank, offsets=offsets)
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else:
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else:
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for i in range(producer_num):
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for i in range(producer_num):
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@ -29,9 +29,6 @@ class FillDrainWorker(WorkerBase):
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target_key = UniqueKey(target_microbatch_id, target_phase)
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target_key = UniqueKey(target_microbatch_id, target_phase)
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with self.work_list_condition_lock:
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self.work_list_condition_lock.wait_for(lambda: target_key in self.work_list)
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return target_key
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return target_key
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@ -120,7 +120,7 @@ def run_master(args):
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logger.info(f'{rank=} numel in the partition:{numel}')
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logger.info(f'{rank=} numel in the partition:{numel}')
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# build optim
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# build optim
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pp_engine.initialize_optimizer(HybridAdam, lr=1e-3)
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pp_engine.initialize_optimizer(torch.optim.Adam, lr=1e-3)
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ranks_tflops = {}
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ranks_tflops = {}
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for n in range(NUM_STEPS):
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for n in range(NUM_STEPS):
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