code: def __init__(
      self, embed_dim, num_heads, dropout=0.0, normalize_before=False
  ):
      super().__init__()
      self.multihead_attn = nn.MultiHeadAttention(
          embed_dim, num_heads, dropout=dropout
      )
  
      self.norm = nn.LayerNorm(embed_dim)
      self.dropout = nn.Dropout(dropout)
  
      self.activation = nn.ReLU()
      self.normalize_before = normalize_before
  
      self.init_weight()
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import param_init
  from paddlepanseg.models.param_init import c2_xavier_fill, THLinearInitMixin, th_linear_fill, th_multihead_fill
  from .common import Conv2D, PositionEmbeddingSine
label_desc: Use image node_id 1 to create a new CrossAttentionLayer object from inherited base classes: nn with example: obj = CrossAttentionLayer(embed_dim, num_heads, dropout, normalize_before)