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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 _make_local_block(x, depth, batch, heads, num_blocks, block_length):
 """Helper function to create a local version of the keys or values for 1d."""

  prev_block = tf.slice(x, [0, 0, 0, 0, 0],
                        [-1, -1, num_blocks - 1, -1, -1])
  cur_block = tf.slice(x, [0, 0, 1, 0, 0], [-1, -1, -1, -1, -1])
  local_block = tf.concat([prev_block, cur_block], 3)
  return tf.reshape(local_block,
                    [batch, heads, num_blocks - 1, block_length * 2, depth])