opt.py 文件源码

def make_node(self, x, y):
        x, y = sparse.as_sparse_variable(x), tensor.as_tensor_variable(y)
        out_dtype = scalar.upcast(x.type.dtype, y.type.dtype)
        if self.inplace:
            assert out_dtype == y.dtype

        indices, indptr, data = csm_indices(x), csm_indptr(x), csm_data(x)
        # We either use CSC or CSR depending on the format of input
        assert self.format == x.type.format
        # The magic number two here arises because L{scipy.sparse}
        # objects must be matrices (have dimension 2)
        assert y.type.ndim == 2
        out = tensor.TensorType(dtype=out_dtype,
                                broadcastable=y.type.broadcastable)()
        return gof.Apply(self,
                         [data, indices, indptr, y],
                         [out])