class_docstr: Base class for the abstract InputSource. 
class_docstr_tok: ["Base","class","for","the","abstract","InputSource","."]
docstr: Returns:
      list[Tensor]: A list of tensors corresponding to the inputs of the model.
          Will be used as input for the tower function.
          This method should always create and return new tensors when called,
          unless it returns placeholders.
docstr_tok: ["Returns",":","list","[","Tensor","]",":","A","list","of","tensors","corresponding","to","the","inputs","of","the","model",".","Will","be","used","as","input","for","the","tower","function",".","This","method","should","always","create","and","return","new","tensors","when","called",",","unless","it","returns","placeholders","."]
code: def get_input_tensors(self):
      """
      Returns:
          list[Tensor]: A list of tensors corresponding to the inputs of the model.
              Will be used as input for the tower function.
              This method should always create and return new tensors when called,
              unless it returns placeholders.
      """
      return self._get_input_tensors()
  
imports: import copy
  from abc import ABCMeta, abstractmethod
  from contextlib import contextmanager
  import six
  import tensorflow
  from ..callbacks.base import CallbackFactory
  from ..tfutils.common import get_op_tensor_name
  from ..utils import logger
  from ..utils.argtools import call_only_once, memoized_method
  from ..compat import tfv1
label_desc: Use image node_id 1 for calling the InputSource obj's underlying member method code with example usage: obj.get_input_tensors() and returns: self