(self, inputs, targets)
return self.deltas
Get a list of errors for backpropagating to a Tree container that has multiple output
        nodes.

        Arguments:
            inputs (list(Tensor)): list of Tensors containing input values to be compared to
                                   targets
            targets (Tensor, list(Tensor)): either a list of Tensors containing target values, or
                                            a single target Tensor that will be mapped to each
                                            input
        Returns:
            list of Tensors containing errors for each input
Get a list of errors for backpropagating to a Tree container that has multiple output
        nodes.
Get a list of errors for backpropagating to a Tree container that has multiple output nodes .
def get_errors(self, inputs, targets):
        """
        Get a list of errors for backpropagating to a Tree container that has multiple output
        nodes.

        Arguments:
            inputs (list(Tensor)): list of Tensors containing input values to be compared to
                                   targets
            targets (Tensor, list(Tensor)): either a list of Tensors containing target values, or
                                            a single target Tensor that will be mapped to each
                                            input
        Returns:
            list of Tensors containing errors for each input
        """
        if type(targets) not in (tuple, list):
            targets = [targets] * len(self.costs)

        for cost, i, t, we in zip(self.costs, inputs, targets, self.weights):
            if t is None:
                continue

            cost.get_errors(i, t)
            if isinstance(cost.deltas, list):
                for delta in cost.deltas:
                    delta[:] *= we
            else:
                cost.deltas[:] *= we

        if self.deltas is None:
            self.deltas = [c.deltas for c in self.costs]

        return self.deltas
def get_errors ( self , inputs , targets ) : if type ( targets ) not in ( tuple , list ) : targets = [ targets ] * len ( self . costs ) for cost , i , t , we in zip ( self . costs , inputs , targets , self . weights ) : if t is None : continue cost . get_errors ( i , t ) if isinstance ( cost . deltas , list ) : for delta in cost . deltas : delta [ : ] *= we else : cost . deltas [ : ] *= we if self . deltas is None : self . deltas = [ c . deltas for c in self . costs ] return self . deltas