code: def _GenerateOrderedInputs(self, size, n):
      inputs = self._GenerateUnorderedInputs(size, 1)
      queue = data_flow_ops.FIFOQueue(
          capacity=1,
          dtypes=[inputs[0].dtype],
          shapes=[inputs[0].get_shape()],
      )
      for _ in range(n - 1):
          op = queue.enqueue(inputs[-1])
          with ops.control_dependencies([op]):
              inputs.append(math_ops.tanh(1.0 + queue.dequeue()))
      return inputs
  
imports: import random
  import time
  from tensorflow.python.client import session
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import data_flow_ops
  from tensorflow.python.ops import gen_control_flow_ops
  from tensorflow.python.ops import gen_state_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 7 for calling the AccumulateNBenchmark obj's underlying member method code with example usage: obj._GenerateOrderedInputs(size, n) and returns: inputs