parameters: (self, tensor_names, every_n=100, first_n=1)
docstring: Initializes a PrintTensor monitor.
  
      Args:
        tensor_names: `dict` of tag to tensor names or
            `iterable` of tensor names (strings).
        every_n: `int`, print every N steps. See `PrintN.`
        first_n: `int`, also print the first N steps. See `PrintN.`
docstring_summary: Initializes a PrintTensor monitor.
docstring_tokens: Initializes a PrintTensor monitor .
function: def __init__(self, tensor_names, every_n=100, first_n=1):
      """Initializes a PrintTensor monitor.
  
      Args:
        tensor_names: `dict` of tag to tensor names or
            `iterable` of tensor names (strings).
        every_n: `int`, print every N steps. See `PrintN.`
        first_n: `int`, also print the first N steps. See `PrintN.`
      """
      super(PrintTensor, self).__init__(every_n, first_n)
      if not isinstance(tensor_names, dict):
        tensor_names = {item: item for item in tensor_names}
      self._tensor_names = tensor_names
function_tokens: def __init__ ( self , tensor_names , every_n = 100 , first_n = 1 ) : super ( PrintTensor , self ) . __init__ ( every_n , first_n ) if not isinstance ( tensor_names , dict ) : tensor_names = { item : item for item in tensor_names } self . _tensor_names = tensor_names