class_docstr: The base class for layers estimating error.
      
class_docstr_tok: ["The","base","class","for","layers","estimating","error","."]
docstr: Gets the upper limit for the absolute value of the function gradient.
          
docstr_tok: ["Gets","the","upper","limit","for","the","absolute","value","of","the","function","gradient","."]
code: def max_gradient(self):
      """Gets the upper limit for the absolute value of the function gradient."""
      return self._internal.get_max_gradient()
  
imports: import neoml.PythonWrapper
  from .Dnn import Layer
  from neoml.Utils import check_input_layers
  from abc import ABCMeta, abstractmethod
  import neoml.Blob
label_desc: Use image node_id 7 for calling the Loss obj's underlying member method code with example usage: obj.max_gradient() and returns: self