def local_self_attention_layer(hparams, prefix):
  """Create self-attention layer based on hyperparameters."""
  return transformer_layers.LocalSelfAttention(
      num_heads=hparams.get(prefix + "num_heads"),
      num_memory_heads=hparams.get(prefix + "num_memory_heads"),
      radius=hparams.local_attention_radius,
      key_value_size=hparams.d_kv,
      shared_kv=hparams.get(prefix + "shared_kv", False),
      attention_kwargs=attention_kwargs_from_hparams(hparams))
def local_self_attention_layer ( hparams , prefix ) : return transformer_layers . LocalSelfAttention ( num_heads = hparams . get ( prefix + "num_heads" ) , num_memory_heads = hparams . get ( prefix + "num_memory_heads" ) , radius = hparams . local_attention_radius , key_value_size = hparams . d_kv , shared_kv = hparams . get ( prefix + "shared_kv" , False ) , attention_kwargs = attention_kwargs_from_hparams ( hparams ) )
Create self-attention layer based on hyperparameters.