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github.com/deepseek-ai/EPLB
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Functions
5 in github.com/deepseek-ai/EPLB
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Functions
5
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Types & classes
0
↓ 2 callers
Function
balanced_packing
Pack n weighted objects to m packs, such that each bin contains exactly n/m objects and the weights of all packs are as balanced as possible.
eplb.py:5
↓ 2 callers
Function
inverse
(perm: torch.Tensor)
eplb.py:98
↓ 2 callers
Function
rebalance_experts_hierarchical
Parameters: weight: [num_moe_layers, num_logical_experts] num_physical_experts: number of physical experts after replication
eplb.py:74
↓ 1 callers
Function
replicate_experts
Replicate `num_log` experts to `num_phy` replicas, such that the maximum load of all replicas is minimized. Parameters: weight: [X,
eplb.py:44
Function
rebalance_experts
Entry point for expert-parallelism load balancer. Parameters: weight: [layers, num_logical_experts], the load statistics for all log
eplb.py:131