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ulysses enabling in native attention path #12563

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ulysses enabling in native attention path #12563

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109d2dd
ulysses enabling in native attention path
sywangyi Oct 30, 2025
146cd6d
address review comment
sywangyi Oct 31, 2025
0894b52
add supports_context_parallel for native attention
sywangyi Oct 31, 2025
19ef5d7
Merge branch 'main' into ulysses-native
sayakpaul Oct 31, 2025
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71 changes: 59 additions & 12 deletions src/diffusers/models/attention_dispatch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1538,18 +1538,65 @@ def _native_attention(
) -> torch.Tensor:
if return_lse:
raise ValueError("Native attention backend does not support setting `return_lse=True`.")
query, key, value = (x.permute(0, 2, 1, 3) for x in (query, key, value))
out = torch.nn.functional.scaled_dot_product_attention(
query=query,
key=key,
value=value,
attn_mask=attn_mask,
dropout_p=dropout_p,
is_causal=is_causal,
scale=scale,
enable_gqa=enable_gqa,
)
out = out.permute(0, 2, 1, 3)
if _parallel_config is None:
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Here, 'supports_context_parallel=True' should be also added to register @sywangyi @sayakpaul

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thanks, added

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@sayakpaul sayakpaul Oct 31, 2025 •
edited
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@DefTruth that should also fix #12446 (comment) right? Could you give this a check?

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@DefTruth that should also fix #12446 (comment) right? Could you give this a check?

confirm fixed

query, key, value = (x.permute(0, 2, 1, 3) for x in (query, key, value))
out = torch.nn.functional.scaled_dot_product_attention(
query=query,
key=key,
value=value,
attn_mask=attn_mask,
dropout_p=dropout_p,
is_causal=is_causal,
scale=scale,
enable_gqa=enable_gqa,
)
out = out.permute(0, 2, 1, 3)
elif _parallel_config.context_parallel_config.ring_degree == 1:
ulysses_mesh = _parallel_config.context_parallel_config._ulysses_mesh
world_size = _parallel_config.context_parallel_config.ulysses_degree
group = ulysses_mesh.get_group()

batch_size, seq_len_q_local, num_heads, head_dim = query.shape
_, seq_len_kv_local, _, _ = key.shape
num_heads_local = num_heads // world_size
query = (
query.reshape(batch_size, seq_len_q_local, world_size, num_heads_local, head_dim)
.permute(2, 1, 0, 3, 4)
.contiguous()
)
key = (
key.reshape(batch_size, seq_len_kv_local, world_size, num_heads_local, head_dim)
.permute(2, 1, 0, 3, 4)
.contiguous()
)
value = (
value.reshape(batch_size, seq_len_kv_local, world_size, num_heads_local, head_dim)
.permute(2, 1, 0, 3, 4)
.contiguous()
)
query, key, value = (_all_to_all_single(x, group) for x in (query, key, value))
query, key, value = (x.flatten(0, 1).permute(1, 2, 0, 3).contiguous() for x in (query, key, value))
out = torch.nn.functional.scaled_dot_product_attention(
query=query,
key=key,
value=value,
attn_mask=attn_mask,
dropout_p=dropout_p,
is_causal=is_causal,
scale=scale,
enable_gqa=enable_gqa,
)
out = (
out.reshape(batch_size, num_heads_local, world_size, seq_len_q_local, head_dim)
.permute(2, 1, 0, 3, 4)
.contiguous()
)
out = _all_to_all_single(out, group)
out = out.flatten(0, 1).permute(1, 2, 0, 3).contiguous()
else:
raise ValueError(
"Native attention backend does not support context parallelism with `ring_degree` > 1, try Ulysses Attention instead by specifying `ulysses_degree` > 1."
)
return out


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