rntnmodel.py 文件源码

def __iadd__(self, gradient):
        """
        Add two gradient together
        """
        # Tensor layer
        if gradient.dV is not None: # Case for the leaf (indead, only depend of the softmax error so no tensor gradient is set)
            self.dV  += gradient.dV # Tensor of the RNTN layer
            self.dW  += gradient.dW # Regular term of the RNTN layer
            self.db  += gradient.db # Bias for the regular term of the RNTN layer

        # Softmax (Computed in any case)
        self.dWs += gradient.dWs # Softmax classifier
        self.dbs += gradient.dbs # Bias of the softmax classifier

        # Words
        self.dL  += gradient.dL # We merge the two lists (Backpropagate the dL gradient on the upper nodes)

        return self