class_docstr: Encapsulation of the basic CFG state changes needed for lowering.
class_docstr_tok: ["Encapsulation","of","the","basic","CFG","state","changes","needed","for","lowering","."]
docstr: Split the current block with a returnable jump to the given block.
  
  The terminator of the current block becomes the terminator of the new last
  block.  The current block gets a `PushGotoOp` pushing the new last block and
  jumping to the given target block.
  
  Args:
    target: The block to jump to.
docstr_tok: ["Split","the","current","block","with","a","returnable","jump","to","the","given","block",".","The","terminator","of","the","current","block","becomes","the","terminator","of","the","new","last","block",".","The","current","block","gets","a","`","PushGotoOp","`","pushing","the","new","last","block","and","jumping","to","the","given","target","block",".","Args",":","target",":","The","block","to","jump","to","."]
code: def split_block(self, target):
      """Split the current block with a returnable jump to the given block.
  
      The terminator of the current block becomes the terminator of the new last
      block.  The current block gets a `PushGotoOp` pushing the new last block and
      jumping to the given target block.
  
      Args:
        target: The block to jump to.
      """
      new_block = inst.Block(
          instructions=[], terminator=self.cur_block().terminator
      )
      self.cur_block().terminator = inst.PushGotoOp(new_block, target)
      self.append_block(new_block)
  
imports: import collections
  from tensorflow_probability.python.experimental.auto_batching import instructions
  from tensorflow_probability.python.experimental.auto_batching import liveness
label_desc: Use image node_id 6 for calling the ControlFlowGraphBuilder obj's underlying member method code with example usage: obj.split_block(target) without return types