docstr: inputs: str -> placeholder
  opset_version: AvailableTarget enum. Describes the opset version of the function
docstr_tok: ["inputs",":","str","-",">","placeholder","opset_version",":","AvailableTarget","enum",".","Describes","the","opset","version","of","the","function"]
code: def __init__(self, inputs, opset_version=None):
      """
      inputs: str -> placeholder
      opset_version: AvailableTarget enum. Describes the opset version of the function
      """
      self.placeholder_inputs = inputs
      self.opset_version = opset_version
  
      # str -> Var
      self._input_dict = OrderedDict()
      for k, v in self.placeholder_inputs.items():
          v.set_name(k)  # set to user input name
          self._input_dict[k] = v.outputs[0]
      self.function_inputs = tuple(self._input_dict.values())
  
      global k_used_symbols
      global k_num_internal_syms
      for inp in self.function_inputs:
          if types.is_tensor(inp.dtype):
              shapes = inp.dtype.get_shape()
              for s in shapes:
                  if is_symbolic(s):
                      k_used_symbols.add(s)
      super().__init__()
  
imports: import copy
  from collections import Counter, OrderedDict
  from typing import Tuple
  from coremltools import _OPSET
  from coremltools import _logger
  from coremltools.converters.mil._deployment_compatibility import AvailableTarget
  from .None import SPACES, types
  from .operation import Operation
  from .types.symbolic import is_symbolic, k_used_symbols
  from .var import ComplexVar, InternalVar, Var
  from .visitors.dot_visitor import DotVisitor
label_desc: Use image node_id 1 to create a new Function object from inherited base classes: Block with example: obj = Function(inputs, opset_version)