5c38bd81f92f4fb3dc29c8a69c84027b95d694af,torchnlp/nn/sru.py,SRU_Compute,backward,#SRU_Compute#Any#Any#,415

Before Change

        return h, last_hidden

    def backward(self, grad_h, grad_last):
        if self.bidirectional:
            grad_last = torch.cat((grad_last[0], grad_last[1]), 1)
        bidir = 2 if self.bidirectional else 1
        u, x, bias, init, mask_h = self.saved_tensors
        c = self.intermediate
        length = x.size(0) if x.dim() == 3 else 1

After Change

        // Normal use
        grad_x = x.new(*x.size()) if k_ == 3 else None

        if k_ == 3:
            x_ptr = x.contiguous() * scale_x if scale_x != 1 else x.contiguous()
            x_ptr = x_ptr.data_ptr()
        else:
            x_ptr = 0

        stream, _, _, bwd_func, bibwd_func = self.get_functions()
        FUNC = bwd_func if not self.bidirectional else bibwd_func
        FUNC(
            args=[

Instances