gpt-oss model enablement #1754
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gpt-oss model enablement #1754
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…ks but reduces mfu for 20b
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wwwjn
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Sep 24, 2025
torchtitan/models/attention.py
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| block_mask = FlexAttention.block_masks[self.mask_key] | ||
| return FlexAttention.flex_attn(q, k, v, block_mask=block_mask, scale=scale) | ||
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| def _forward_with_sink( |
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LGTM.
I'm curious how expensive it is to always return lse. If it is actually no cost, we can merge the FlexAttention call to the original forward.
cc., @drisspg
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Need to rebase onto #1776 |
wwwjn
commented
Sep 30, 2025
| ] # (mask_type, fixed_block_size, sliding_window) | ||
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| class FlexAttention(torch.nn.Module): |
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Sorry for the disruption. I should have done this earlier.
As for the FlexAttention, @drisspg confirmed that, while it is probably just a minor overhead, the AuxOutput does incur some extra memory and memory write. So let's keep it optional.
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Keep developing on top of #1559. Thanks @KhoomeiK for initial contribution!
Initialized by the same seed checkpoint, set seed=0 and deterministic = True.
Run 1: dp_shard = 2
Run 2: dp_shard = 2, TP degree = 2 (NGPU=4)
Run 3: dp_shard = 2, TP degree =2, EP degree = 2 (NGPU=4)
Run 4: dp_shard = 2, TP degree = 2, EP degree = 2, ETP degree = 2 (NGPU=4)
Run 5: dp_shard=2, EP degree = 2 (NGPU=2)
