2025-10-05 17:49:01 +02:00
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import torch
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2025-10-06 12:00:11 +02:00
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def get_causal_attention_mask(embedding_dimension: int) -> torch.Tensor:
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return torch.triu(torch.ones(embedding_dimension, embedding_dimension, dtype=torch.bool), diagonal=1)
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def get_causal_attention_mask_batched(embedding_dimension: int, batch_size: int ) -> torch.Tensor:
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base_mask = get_causal_attention_mask(embedding_dimension)
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return base_mask.unsqueeze(0).expand(batch_size, -1, -1) # add another dimension at the beginning, big as batch_size
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# the result is that z,x,y where x,y are repeated along z
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