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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 get_shifted_center_blocks(x, indices):
 """Get right shifted blocks for masked local attention 2d. Args: x: A tensor with shape [batch, heads, height, width, depth] indices: The indices to gather blocks Returns: x_shifted: a tensor of extracted blocks, each block right shifted along length. """

  center_x = gather_blocks_2d(x, indices)

  # Shift right along the length dimension
  def shift_right_2d_blocks(x):
    """Shift the second to last dimension of x right by one."""
    shifted_targets = (
        tf.pad(x, [[0, 0], [0, 0], [0, 0], [1, 0], [0, 0]])[:, :, :, :-1, :])
    return shifted_targets

  x_shifted = shift_right_2d_blocks(center_x)
  return x_shifted