<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _relative_position_to_absolute_position_masked(x):
 """Helper to dot_product_self_attention_relative_v2. Rearrange an attention logits or weights Tensor. The dimensions of the input represent: [batch, heads, query_position, memory_position - query_position + length - 1] The dimensions of the output represent: [batch, heads, query_position, memory_position] Only works with masked_attention. Undefined behavior for regions of the input where memory_position > query_position. Args: x: a Tensor with shape [batch, heads, length, length] Returns: a Tensor with shape [batch, heads, length, length] """

  batch, heads, length, _ = common_layers.shape_list(x)
  x = tf.pad(x, [[0, 0], [0, 0], [0, 0], [1, 0]])
  x = tf.reshape(x, [batch, heads, 1 + length, length])
  x = tf.slice(x, [0, 0, 1, 0], [-1, -1, -1, -1])
  return x