original_docstring: 
          Single training step over minibatch: forward, loss, backprop
          
docstring: Single training step over minibatch: forward, loss, backprop
docstring_tokens: Single training step over minibatch : forward loss backprop
code: def train_step(self, X_train, y_train):
          """
          Single training step over minibatch: forward, loss, backprop
          """
          y_pred, cache = self.forward(X_train, train=True)
          loss = self.loss_funs[self.loss](self.model, y_pred, y_train, self.lam)
          grad = self.backward(y_pred, y_train, cache)
  
          return grad, loss
code_tokens: def train_step ( self , X_train , y_train ) : y_pred , cache = self . forward ( X_train , train = True ) loss = self . loss_funs [ self . loss ] ( self . model , y_pred , y_train , self . lam ) grad = self . backward ( y_pred , y_train , cache ) return grad , loss
short_docstring: Single training step over minibatch: forward, loss, backprop
short_docstring_tokens: Single training step over minibatch : forward loss backprop
comment: """
          Single training step over minibatch: forward, loss, backprop
          """