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: Start a new pipeline chain.
  
  Args:
      schema (list): The schema for the values being inputted into the pipeline.
  
  Returns:
      Pipeline: Pipeline ready to be chained.
  
  Examples:
      >>> from towhee import pipe
      >>> p = pipe.input('a', 'b', 'c')
docstr_tok: ["Start","a","new","pipeline","chain",".","Args",":","schema","(","list",")",":","The","schema","for","the","values","being","inputted","into","the","pipeline",".","Returns",":","Pipeline",":","Pipeline","ready","to","be","chained",".","Examples",":",">",">",">","from","towhee","import","pipe",">",">",">","p","=","pipe.input","(","'","a","'",",","'","b","'",",","'","c","'",")"]
code: def input(cls, *schema) -> "Pipeline":
      """
      Start a new pipeline chain.
  
      Args:
          schema (list): The schema for the values being inputted into the pipeline.
  
      Returns:
          Pipeline: Pipeline ready to be chained.
  
      Examples:
          >>> from towhee import pipe
          >>> p = pipe.input('a', 'b', 'c')
      """
      dag_dict = {}
      output_schema = cls._check_schema(schema)
      uid = InputConst.name
      dag_dict[uid] = cls._nop_node_dict(output_schema, output_schema)
      return cls(dag_dict)
  
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 3 for calling the Pipeline obj's underlying member method code with example usage: obj.input(cls) and returns: cls