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Adds attention mask with model.forward(..., cache=None). #89

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Adds attention mask with model.forward(..., cache=None). #89

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17 changes: 11 additions & 6 deletions mistral/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@
from mistral.moe import MoeArgs, MoeLayer

from xformers.ops.fmha import memory_efficient_attention
from xformers.ops.fmha.attn_bias import BlockDiagonalCausalMask


@dataclass
Expand Down Expand Up @@ -80,6 +81,7 @@ def forward(
x: torch.Tensor,
freqs_cis: torch.Tensor,
cache: Optional[CacheView],
mask: Optional[torch.Tensor]=None,
) -> torch.Tensor:
seqlen_sum, _ = x.shape

Expand Down Expand Up @@ -109,9 +111,9 @@ def forward(

# xformers requires (B=1, S, H, D)
xq, key, val = xq[None, ...], key[None, ...], val[None, ...]
output = memory_efficient_attention(
xq, key, val, None if cache is None else cache.mask
)
if mask is None and cache is not None:
mask = cache.mask
output = memory_efficient_attention(xq, key, val, mask)

return self.wo(output.view(seqlen_sum, self.n_heads * self.head_dim))

Expand Down Expand Up @@ -163,9 +165,10 @@ def __init__(self, args: ModelArgs):
self.feed_forward = FeedForward(args=args)

def forward(
self, x: torch.Tensor, freqs_cis: torch.Tensor, cache: Optional[CacheView]
self, x: torch.Tensor, freqs_cis: torch.Tensor, cache: Optional[CacheView],
mask: Optional[torch.Tensor]=None,
) -> torch.Tensor:
r = self.attention.forward(self.attention_norm(x), freqs_cis, cache)
r = self.attention.forward(self.attention_norm(x), freqs_cis, cache, mask)
h = x + r
r = self.feed_forward.forward(self.ffn_norm(h))
out = h + r
Expand Down Expand Up @@ -251,8 +254,10 @@ def forward_partial(
assert sum(seqlens) == num_toks, (sum(seqlens), num_toks)
if cache is not None:
input_metadata = cache.get_input_metadata(seqlens)
mask = None
else:
input_metadata = SimpleInputMetadata.from_seqlens(seqlens, self.device)
mask = BlockDiagonalCausalMask.from_seqlens(seqlens).make_local_attention(max(seqlens))

if self.pipeline_rank == 0:
assert self.tok_embeddings is not None
Expand All @@ -271,7 +276,7 @@ def forward_partial(
cache_view = cache.get_view(local_layer_id, input_metadata)
else:
cache_view = None
h = layer(h, freqs_cis, cache_view)
h = layer(h, freqs_cis, cache_view, mask)

if cache is not None:
cache.update_seqlens(seqlens)
Expand Down