class_docstr: Represents Operation in MIL.
  
  # Properties
  name (str):
      The name of the operation
  
  input_types (InputSpec, class attr):
      Read-only named input types from all subclasses. Input types are used
      to validate `inputs`.
  
  inputs [_input_vars] (dict of str --> Var):
      An Operation (subclass of Operation) only has access to input Var,
      which is already validated against `input_spec`.
  
  outputs [_output_vars] (list of Var):
      List of output var based on type inference. Read-only
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docstr: Returns:
  list[Var]. Flatten all tuple inputs
docstr_tok: ["Returns",":","list","[","Var","]",".","Flatten","all","tuple","inputs"]
code: def get_flattened_inputs(self):
      """
      Returns:
      list[Var]. Flatten all tuple inputs
      """
      flat_inputs = []
      for v in self.inputs.values():
          if isinstance(v, (list, tuple)):
              flat_inputs.extend(v)
          else:
              flat_inputs.append(v)
      return flat_inputs
  
imports: import logging
  import numpy
  import six
  from coremltools.converters.mil.mil import types
  from coremltools.converters.mil.mil.types.symbolic import is_symbolic, any_symbolic
  from .None import SPACES
  from .block import curr_block, _check_is_compatible_type
  from .input_type import TupleInputType
  from .var import Var, InternalVar, ListVar
label_desc: Use image node_id 3 for calling the Operation obj's underlying member method code with example usage: obj.get_flattened_inputs() and returns: flat_inputs