code: def __init__(
      self,
      dim,
      num_heads=8,
      qkv_bias=False,
      qk_scale=None,
      attn_drop_ratio=0.0,
      proj_drop_ratio=0.0,
      name=None,
  ):
      super(Attention, self).__init__(name=name)
      self.num_heads = num_heads
      head_dim = dim // num_heads
      self.scale = qk_scale or head_dim**-0.5
      self.qkv = layers.Dense(
          dim * 3,
          use_bias=qkv_bias,
          name="qkv",
          kernel_initializer=self.k_ini,
          bias_initializer=self.b_ini,
      )
      self.attn_drop = layers.Dropout(attn_drop_ratio)
      self.proj = layers.Dense(
          dim,
          name="out",
          kernel_initializer=self.k_ini,
          bias_initializer=self.b_ini,
      )
      self.proj_drop = layers.Dropout(proj_drop_ratio)
  
imports: import tensorflow
  from tensorflow.keras import Model, layers, initializers
  import numpy
label_desc: Use image node_id 1 to create a new Attention object from inherited base classes: layers with example: obj = Attention(dim, num_heads, qkv_bias, qk_scale, attn_drop_ratio, proj_drop_ratio, name)