parameters: (self, y_tensor=None)
docstring: Constructor of GradientsDebugger.
  
      Args:
        y_tensor: optional: the `tf.Tensor` to be differentiated, i.e., the tensor
          on the numerator of the differentiation.
docstring_summary: Constructor of GradientsDebugger.
docstring_tokens: Constructor of GradientsDebugger .
function: def __init__(self, y_tensor=None):
      """Constructor of GradientsDebugger.
  
      Args:
        y_tensor: optional: the `tf.Tensor` to be differentiated, i.e., the tensor
          on the numerator of the differentiation.
      """
  
      self._uuid = uuid.uuid4().hex
      _gradient_debuggers[self._uuid] = self
  
      # A dict mapping x-tensor names to gradient tensor. x-tensor refers to the
      # independent tf.Tensor, i.e., the tensor on the denominator of the
      # differentiation.
      self._gradient_tensors = {}
      self._y_tensor = y_tensor
  
      self._graph = None
      if y_tensor:
        self._graph = y_tensor.graph
  
      self._is_active_context = False
function_tokens: def __init__ ( self , y_tensor = None ) : self . _uuid = uuid . uuid4 ( ) . hex _gradient_debuggers [ self . _uuid ] = self # A dict mapping x-tensor names to gradient tensor. x-tensor refers to the # independent tf.Tensor, i.e., the tensor on the denominator of the # differentiation. self . _gradient_tensors = { } self . _y_tensor = y_tensor self . _graph = None if y_tensor : self . _graph = y_tensor . graph self . _is_active_context = False