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Fix copies for DBRX - neuron fix (#30610)

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amyeroberts 2024-05-02 11:00:26 +01:00 committed by GitHub
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1 changed files with 5 additions and 2 deletions
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src/transformers/models/dbrx/modeling_dbrx.py
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@ -1256,8 +1256,11 @@ class DbrxModel(DbrxPreTrainedModel):
causal_mask = causal_mask.clone() # copy to contiguous memory for in-place edit causal_mask = causal_mask.clone() # copy to contiguous memory for in-place edit
if attention_mask.dim() == 2: if attention_mask.dim() == 2:
mask_length = attention_mask.shape[-1] mask_length = attention_mask.shape[-1]
padding_mask = causal_mask[..., :mask_length].eq(0.0) * attention_mask[:, None, None, :].eq(0.0) padding_mask = causal_mask[:, :, :, :mask_length] + attention_mask[:, None, None, :]
causal_mask[..., :mask_length] = causal_mask[..., :mask_length].masked_fill(padding_mask, min_dtype) padding_mask = padding_mask == 0
causal_mask[:, :, :, :mask_length] = causal_mask[:, :, :, :mask_length].masked_fill(
padding_mask, min_dtype
)
elif attention_mask.dim() == 4: elif attention_mask.dim() == 4:
# backwards compatibility: we allow passing a 4D attention mask shorter than the input length with # backwards compatibility: we allow passing a 4D attention mask shorter than the input length with
# cache. In that case, the 4D attention mask attends to the newest tokens only. # cache. In that case, the 4D attention mask attends to the newest tokens only.