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Update sharded_moe.py to support top2 gate with Tutel #6948

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Update sharded_moe.py to support top2 gate with Tutel #6948

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9881404
Update sharded_moe.py to support top2 gate with Tutel
xenshinu Jan 14, 2025
ee99408
Update sharded_moe.py
xenshinu Jan 14, 2025
07cc866
Update sharded_moe.py for formatting
xenshinu Jan 15, 2025
bc2c9fa
Merge branch 'master' into patch-1
loadams Jan 15, 2025
4f9c2a7
Merge branch 'master' into patch-1
loadams Jan 22, 2025
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28 changes: 23 additions & 5 deletions deepspeed/moe/sharded_moe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -292,7 +292,8 @@ def top2gating(logits: Tensor,
min_capacity: int,
drop_tokens: bool = True,
ep_group: Union[torch.distributed.ProcessGroup, None] = None,
top2_2nd_expert_sampling: bool = True) -> Tuple[Tensor, Tensor, Tensor, Tensor]:
top2_2nd_expert_sampling: bool = True,
use_tutel: bool = False) -> Tuple[Tensor, Tensor, Tensor, Tensor]:
"""Implements Top2Gating on logits."""
# everything is in fp32 in this function
gates = F.softmax(logits, dim=1)
Expand All @@ -313,8 +314,12 @@ def top2gating(logits: Tensor,
mask2 = F.one_hot(indices2_s, num_classes=num_experts)

# Compute locations in capacity buffer
locations1 = torch.cumsum(mask1, dim=0) - 1
locations2 = torch.cumsum(mask2, dim=0) - 1
if not use_tutel:
locations1 = torch.cumsum(mask1, dim=0) - 1
locations2 = torch.cumsum(mask2, dim=0) - 1
else:
locations1 = tutel_moe.fast_cumsum_sub_one(mask1)
locations2 = tutel_moe.fast_cumsum_sub_one(mask2)
# Update 2nd's location by accounting for locations of 1st
locations2 += torch.sum(mask1, dim=0, keepdim=True)

Expand Down Expand Up @@ -358,6 +363,19 @@ def top2gating(logits: Tensor,
gates1_s /= denom_s
gates2_s /= denom_s

if use_tutel:
# return critical information for tutel
return l_aux, capacity, num_experts, [
indices1_s,
indices2_s,
], [
locations1_s,
locations2_s,
], [
gates1_s,
gates2_s,
], exp_counts

# Calculate combine_weights and dispatch_mask
gates1 = einsum("s,se->se", gates1_s, mask1_float)
gates2 = einsum("s,se->se", gates2_s, mask2_float)
Expand Down Expand Up @@ -517,7 +535,7 @@ def forward(self,

elif self.k == 2:
gate_output = top2gating(logits, self.capacity_factor if self.training else self.eval_capacity_factor,
self.min_capacity, self.drop_tokens, self.ep_group, self.top2_2nd_expert_sampling)
self.min_capacity, self.drop_tokens, self.ep_group, self.top2_2nd_expert_sampling, use_tutel)
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@xenshinu - thanks for this PR, could you run the pre-commit formatter on your branch to resolve the "Formatting" error? I believe it just wants the use_tutel on a new line here.

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@xenshinu xenshinu Jan 15, 2025 •
edited
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Thanks for pointing that out. I've updated the file and it looks like the pre-commit check has passed.
Can someone take a look to this question?
#6948 (comment)

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@xenshinu - it looks like there are still other errors the formatter is catching, could you try again? Thanks!

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I see. I will finish topK soon and deal with the formatting issue together.

else:
gate_output = topkgating(logits, self.k,
self.capacity_factor if self.training else self.eval_capacity_factor,
Expand Down Expand Up @@ -568,7 +586,7 @@ def __init__(self,
self.timers = SynchronizedWallClockTimer()
self.wall_clock_breakdown = False

self.use_tutel = use_tutel and TUTEL_INSTALLED and gate.k == 1
self.use_tutel = use_tutel and TUTEL_INSTALLED and (gate.k == 1 or gate.k == 2)

if self.use_tutel:
logger.info('Using Tutel optimizations.')
Expand Down
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