code: def test_attention_alias_equivalence(self):
      key1, key2 = random.split(random.key(0), 2)
      query = random.uniform(key1, (3, 5))
      key_value = random.uniform(key1, (9, 5))
      attention_kwargs = dict(
          num_heads=8,
          qkv_features=16,
          kernel_init=initializers.lecun_normal(),
          bias_init=initializers.uniform(),
          deterministic=False,
      )
      module1 = nn.MultiHeadDotProductAttention(**attention_kwargs)
      module2 = nn.MultiHeadAttention(**attention_kwargs)
      out1, v1 = module1.init_with_output(key2, query, key_value)
      out2, v2 = module2.init_with_output(
          key2, query, key_value, key_value
      )
      self.assertTrue((out1 == out2).all())
      self.assertTrue(
          jax.tree_util.tree_all(
              jax.tree_map(lambda x, y: (x == y).all(), v1, v2)
          )
      )
  
imports: import jax
  import jax.numpy
  import numpy
  from absl.testing import absltest, parameterized
  from jax import lax, random
  from jax.nn import initializers
  from flax import errors, jax_utils
  from flax import linen
  from flax.core import pop
label_desc: Use image node_id 14 for calling the AttentionTest obj's underlying member method code with example usage: obj.test_attention_alias_equivalence() without return types