class_docstr: The base class for layers estimating error.
      
class_docstr_tok: ["The","base","class","for","layers","estimating","error","."]
docstr: Specifies if gradients should also be calculated for the second input,
  which contains the class labels.
docstr_tok: ["Specifies","if","gradients","should","also","be","calculated","for","the","second","input",",","which","contains","the","class","labels","."]
code: def train_labels(self, train):
      """Specifies if gradients should also be calculated for the second input,
      which contains the class labels.
      """
      self._internal.set_train_labels(train)
  
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 6 for calling the Loss obj's underlying member method code with example usage: obj.train_labels(train) without return types