original_docstring: 
      Compute the cross entropy loss given outputs and labels.
  
      Args:
          outputs: (Variable) dimension batch_size x 6 - output of the model
          labels: (Variable) dimension batch_size, where each element is a value in [0, 1, 2, 3, 4, 5]
  
      Returns:
          loss (Variable): cross entropy loss for all images in the batch
  
      Note: you may use a standard loss function from http://pytorch.org/docs/master/nn.html#loss-functions. This example
            demonstrates how you can easily define a custom loss function.
      
docstring: Compute the cross entropy loss given outputs and labels.
docstring_tokens: Compute the cross entropy loss given outputs and labels .
code: def loss_fn(outputs, labels):
      """
      Compute the cross entropy loss given outputs and labels.
  
      Args:
          outputs: (Variable) dimension batch_size x 6 - output of the model
          labels: (Variable) dimension batch_size, where each element is a value in [0, 1, 2, 3, 4, 5]
  
      Returns:
          loss (Variable): cross entropy loss for all images in the batch
  
      Note: you may use a standard loss function from http://pytorch.org/docs/master/nn.html#loss-functions. This example
            demonstrates how you can easily define a custom loss function.
      """
      return nn.CrossEntropyLoss()(outputs, labels)
code_tokens: def loss_fn ( outputs , labels ) : return nn . CrossEntropyLoss ( ) ( outputs , labels )
short_docstring: Compute the cross entropy loss given outputs and labels.
short_docstring_tokens: Compute the cross entropy loss given outputs and labels .
comment: """
      Compute the cross entropy loss given outputs and labels.
  
      Args:
          outputs: (Variable) dimension batch_size x 6 - output of the model
          labels: (Variable) dimension batch_size, where each element is a value in [0, 1, 2, 3, 4, 5]
  
      Returns:
          loss (Variable): cross entropy loss for all images in the batch
  
      Note: you may use a standard loss function from http://pytorch.org/docs/master/nn.html#loss-functions. This example
            demonstrates how you can easily define a custom loss function.
      """