code: def testAccumulatorDynamicShape(self):
      with self.cached_session() as sess:
          q = data_flow_ops.ConditionalAccumulator(
              dtypes_lib.float32, name="Q", shape=None
          )
  
          x = array_ops.placeholder(dtypes_lib.float32)
  
          accum_op = q.apply_grad(x)
  
          elems = [
              [[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]],
              [[10.0, 20.0], [30.0, 40.0], [50.0, 60.0]],
          ]
          elems_ave = [
              [(a + b) / len(elems) for a, b in zip(c, d)]
              for c, d in zip(elems[0], elems[1])
          ]
          takeg_t = q.take_grad(1)
  
          for elem in elems:
              sess.run(accum_op, feed_dict={x: elem})
  
          is_all_equal = True
          val = self.evaluate(takeg_t)
          for i in range(len(val)):
              for j in range(len(val[i])):
                  is_all_equal &= val[i][j] == elems_ave[i][j]
          self.assertTrue(is_all_equal)
  
imports: import time
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import data_flow_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 9 for calling the ConditionalAccumulatorTest obj's underlying member method code with example usage: obj.testAccumulatorDynamicShape() without return types