class_docstr: The base class for layers estimating error.
      
class_docstr_tok: ["The","base","class","for","layers","estimating","error","."]
docstr: Gets the multiplier for the loss function during training.
          
docstr_tok: ["Gets","the","multiplier","for","the","loss","function","during","training","."]
code: def loss_weight(self):
      """Gets the multiplier for the loss function during training."""
      return self._internal.get_loss_weight()
  
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 3 for calling the Loss obj's underlying member method code with example usage: obj.loss_weight() and returns: self