original_docstring: 
          Compute the gradient of the loss wrt the current network parameters.
          
docstring: Compute the gradient of the loss wrt the current network parameters.
docstring_tokens: Compute the gradient of the loss wrt the current network parameters .
code: def backward(self):
          """
          Compute the gradient of the loss wrt the current network parameters.
          """
          dX_emb = self.loss.grad(retain_grads=True, update_params=False)
          self.embeddings.backward(dX_emb)
code_tokens: def backward ( self ) : dX_emb = self . loss . grad ( retain_grads = True , update_params = False ) self . embeddings . backward ( dX_emb )
short_docstring: Compute the gradient of the loss wrt the current network parameters.
short_docstring_tokens: Compute the gradient of the loss wrt the current network parameters .
comment: """
          Compute the gradient of the loss wrt the current network parameters.
          """