class_docstr: Gradients Debugger.
  
  Allows retrieval of gradient tensors created by TensorFlow's automatic
  differentiation algorithm, i.e., `tf.gradients` and optimizer classes that
  use it.
class_docstr_tok: ["Gradients","Debugger",".","Allows","retrieval","of","gradient","tensors","created","by","TensorFlow","'s","automatic","differentiation","algorithm",",","i.e.",",","`","tf.gradients","`","and","optimizer","classes","that","use","it","."]
docstr: Get the gradient tensors that this object is aware of.
  
  Returns:
    A dict mapping x-tensor names to gradient tensor objects. x-tensor refers
    to the tensors on the denominator of the differentation.
docstr_tok: ["Get","the","gradient","tensors","that","this","object","is","aware","of",".","Returns",":","A","dict","mapping","x-tensor","names","to","gradient","tensor","objects",".","x-tensor","refers","to","the","tensors","on","the","denominator","of","the","differentation","."]
code: def gradient_tensors(self):
      """Get the gradient tensors that this object is aware of.
  
      Returns:
        A dict mapping x-tensor names to gradient tensor objects. x-tensor refers
        to the tensors on the denominator of the differentation.
      """
      return self._gradient_tensors
  
imports: import re
  import uuid
  from tensorflow.python.debug.lib import debug_data
  from tensorflow.python.debug.lib import debug_graphs
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import gen_array_ops
  from tensorflow.python.ops import variables
label_desc: Use image node_id 12 for calling the GradientsDebugger obj's underlying member method code with example usage: obj.gradient_tensors() and returns: self