

def grad(self, inputs, gout):
    (x_data, x_indices, x_indptr, x_shape) = inputs
    (g_out,) = gout
    (g_data, g_indices, g_indptr, g_shape) = csm_properties(g_out)
    g_data = csm_grad(g_indices.kmap)(x_data, x_indices, x_indptr, x_shape, g_data, g_indices, g_indptr, g_shape)
    return [g_data, DisconnectedType()(), DisconnectedType()(), DisconnectedType()()]

dataset/ETHPy150Open rizar/attention-lvcsr/libs/Theano/theano/sparse/basic.py CSM.grad/VarMisuse@52/83 `self`->`g_indices`