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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def simple_layer_stack(include_encdec_attention, num_layers=6, d_ff=2048, num_heads=8, d_kv=128, dropout_rate=0.1):
 """Create a layer stack. Args: include_encdec_attention: a boolean num_layers: an integer d_ff: an integer num_heads: an integer d_kv: an integer dropout_rate: a float Returns: a LayerStack """

  ret = []
  for _ in xrange(num_layers):
    ret.append(
        transformer_layers.SelfAttention(
            num_heads=num_heads,
            key_value_size=d_kv,
            attention_kwargs={"dropout_rate": dropout_rate}))
    if include_encdec_attention:
      ret.append(
          transformer_layers.EncDecAttention(
              num_heads=num_heads,
              key_value_size=d_kv,
              attention_kwargs={"dropout_rate": dropout_rate}))
    ret.append(
        transformer_layers.DenseReluDense(
            hidden_size=d_ff,
            dropout_rate=dropout_rate))
  return transformer.LayerStack(ret)