cudnn_rnn_ops.py 文件源码

def restore(self, restored_tensors, restored_shapes):
    weights = restored_tensors[:len(restored_tensors) // 2]
    biases = restored_tensors[len(restored_tensors) // 2:]
    params = self._canonical_to_params(weights, biases)
    if not isinstance(params, tuple):
      params = (params,)
    assign_ops = [
        state_ops.assign(
            variable, param, validate_shape=False)
        for variable, param in zip(self._variables, params)
    ]
    return control_flow_ops.group(*assign_ops)