class_docstr: Pipeline is a tool to create data transformation chains.
  
  Args:
      dag (`dict`): The dag for the pipeline.
      clo_node (`str`): The close node in the pipeline dag, defaults to '_input'.
docstr: Close and preload the pipeline, and ready to run with it.
  
  Args:
      output_schema (tuple): Which columns to output.
      config_kws (dict): The config for this pipeline.
  
  
  Returns:
      RuntimePipeline: The runtime pipeline that can be called on inputs.
  
  Examples:
      >>> from towhee import pipe
      >>> p = pipe.input('a').map('a', 'b', lambda x: x+1).output('b')
      >>> p(1).get()
      [2]
docstr_tok: ["Close","and","preload","the","pipeline",",","and","ready","to","run","with","it",".","Args",":","output_schema","(","tuple",")",":","Which","columns","to","output",".","config_kws","(","dict",")",":","The","config","for","this","pipeline",".","Returns",":","RuntimePipeline",":","The","runtime","pipeline","that","can","be","called","on","inputs",".","Examples",":",">",">",">","from","towhee","import","pipe",">",">",">","p","=","pipe.input","(","'","a","'",")",".map","(","'","a","'",",","'","b","'",",","lambda","x",":","x+1",")",".output","(","'","b","'",")",">",">",">","p","(","1",")",".get","(",")","[","2","]"]
code: def output(self, *output_schema) -> "RuntimePipeline":
      """
      Close and preload the pipeline, and ready to run with it.
  
      Args:
          output_schema (tuple): Which columns to output.
          config_kws (dict): The config for this pipeline.
  
  
      Returns:
          RuntimePipeline: The runtime pipeline that can be called on inputs.
  
      Examples:
          >>> from towhee import pipe
          >>> p = pipe.input('a').map('a', 'b', lambda x: x+1).output('b')
          >>> p(1).get()
          [2]
      """
      output_schema = self._check_schema(output_schema)
  
      uid = OutputConst.name
      dag_dict = deepcopy(self._dag)
      dag_dict[uid] = self._nop_node_dict(output_schema, output_schema)
      dag_dict[self._clo_node]["next_nodes"].append(uid)
  
      run_pipe = RuntimePipeline(dag_dict)
      run_pipe.preload()
      return run_pipe
  
imports: import uuid
  from copy import deepcopy
  from towhee.runtime.check_utils import TupleForm
  from towhee.runtime.operator_manager import OperatorAction
  from towhee.runtime.factory import _OperatorWrapper
  from towhee.runtime.runtime_pipeline import RuntimePipeline
  from towhee.runtime.constants import MapConst, WindowAllConst, WindowConst, ReduceConst, FilterConst, TimeWindowConst, FlatMapConst, ConcatConst, InputConst, OutputConst, OPName
label_desc: Use image node_id 4 for calling the Pipeline obj's underlying member method code with example usage: obj.output() and returns: run_pipe