code: def residual_block(
      input_, kernel_size, scope, activation_fn=tf.nn.relu
  ):
      """A residual block made of two mirror-padded, same-padded convolutions.
  
      This function expects `kernel_size` to be odd.
  
      Args:
        input_: 4-D Tensor, the input.
        kernel_size: int (odd-valued) representing the kernel size.
        scope: str, scope under which to operate.
        activation_fn: activation function.
  
      Returns:
        4-D Tensor, the output.
  
      Raises:
        ValueError: if `kernel_size` is even.
      """
      if kernel_size % 2 == 0:
          raise ValueError("kernel_size is expected to be odd.")
      with tf.variable_scope(scope):
          num_outputs = int(input_.get_shape()[-1])
          h_1 = conv2d(
              input_,
              kernel_size,
              1,
              num_outputs,
              "conv1",
              activation_fn,
          )
          h_2 = conv2d(h_1, kernel_size, 1, num_outputs, "conv2", None)
          return input_ + h_2
  
imports: from magenta.models.image_stylization import ops
  import tensorflow.compat.v1
  import tf_slim
label_desc: Use image node_id 4 for calling a global function with example usage: residual_block(input_, kernel_size, scope, activation_fn) and returns: unknown