flax.linen.make_attention_mask(query_input, key_input, pairwise_fn=<PjitFunction of <function jax.numpy.multiply>>, extra_batch_dims=0, dtype=<class 'jax.numpy.float32'>)[source]#

Mask-making helper for attention weights.

In case of 1d inputs (i.e., [batch…, len_q], [batch…, len_kv], the attention weights will be [batch…, heads, len_q, len_kv] and this function will produce [batch…, 1, len_q, len_kv].

  • query_input – a batched, flat input of query_length size

  • key_input – a batched, flat input of key_length size

  • pairwise_fn – broadcasting elementwise comparison function

  • extra_batch_dims – number of extra batch dims to add singleton axes for, none by default

  • dtype – mask return dtype


A [batch…, 1, len_q, len_kv] shaped mask for 1d attention.