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Fix sliding attention mask for multi-turn with cache. #767

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Fix sliding attention mask for multi-turn with cache. #767

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17 changes: 16 additions & 1 deletion gemma/gm/nn/gemma4/_transformer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -463,12 +463,27 @@ def _encode_and_get_inputs(
sliding_attention_mask = None
if self.config.use_bidirectional_attention == 'vision':
bidirectional_mask = tokens == _token_utils.SOFT_TOKEN_PLACEHOLDER
sliding_attention_mask = (
sliding_bidir_mask = (
_attention_mask.make_causal_bidirectional_attention_mask(
inputs_mask,
bidirectional_mask=bidirectional_mask,
)
)
# For multi-turn with cache: expand the sliding mask to cover
# cached history tokens. History portion uses the same causal
# mask as attention_mask (those tokens are already in the KV
# cache and _create_sliding_mask will apply the window).
if (
attention_mask is not None
and attention_mask.shape[-1] > sliding_bidir_mask.shape[-1]
):
hist_width = attention_mask.shape[-1] - sliding_bidir_mask.shape[-1]
hist_mask = attention_mask[:, :, :hist_width]
sliding_attention_mask = jnp.concatenate(
[hist_mask, sliding_bidir_mask], axis=-1
)
else:
sliding_attention_mask = sliding_bidir_mask

if self.config.per_layer_input_dim:
per_layer_inputs = self.embedder.encode_per_layer_input(
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