class_docstr: Neural network implementation.
  A neural network is a directed graph consisting of layers that perform
  calculations on data blobs. It starts with source layers and ends with 
  sink layers.
  
  :param neoml.MathEngine.MathEngine math_engine: The math engine that will perform calculations.
  :param random: The random numbers generator to be used for training and initialization.
  :type random: object, default=None 
class_docstr_tok: ["Neural","network","implementation",".","A","neural","network","is","a","directed","graph","consisting","of","layers","that","perform","calculations","on","data","blobs",".","It","starts","with","source","layers","and","ends","with","sink","layers",".",":","param","neoml.MathEngine.MathEngine","math_engine",":","The","math","engine","that","will","perform","calculations",".",":","param","random",":","The","random","numbers","generator","to","be","used","for","training","and","initialization",".",":","type","random",":","object",",","default=None"]
docstr: Loads the checkpoint from file.
  A new solver will be created, because the old pointers will point
  to an object no longer used by this network.
  
  :param path: The full path to the location from where the network should be loaded.
  :type path: str
docstr_tok: ["Loads","the","checkpoint","from","file",".","A","new","solver","will","be","created",",","because","the","old","pointers","will","point","to","an","object","no","longer","used","by","this","network",".",":","param","path",":","The","full","path","to","the","location","from","where","the","network","should","be","loaded",".",":","type","path",":","str"]
code: def load_checkpoint(self, path):
      """Loads the checkpoint from file.
      A new solver will be created, because the old pointers will point
      to an object no longer used by this network.
  
      :param path: The full path to the location from where the network should be loaded.
      :type path: str
      """
      self._load_checkpoint(str(path))
  
imports: import neoml.PythonWrapper
  import neoml.Random
label_desc: Use image node_id 5 for calling the Dnn obj's underlying member method code with example usage: obj.load_checkpoint(path) without return types