code: def testAccumulatorSizeAfterApplyGradAndTakeGrad(self):
      with self.cached_session():
          q = data_flow_ops.ConditionalAccumulator(
              dtypes_lib.float32,
              name="Q",
              shape=tensor_shape.TensorShape([1]),
          )
          accum_op = q.apply_grad((10.0,))
          extract_t = q.take_grad(2)
  
          # Applying gradient multiple times to increase size from 0 to 2.
          self.assertEqual(q.num_accumulated().eval(), 0)
          accum_op.run()
          self.assertEqual(q.num_accumulated().eval(), 1)
          accum_op.run()
          self.assertEqual(q.num_accumulated().eval(), 2)
  
          # Extract will reduce size to 0
          extract_t.op.run()
          self.assertEqual(q.num_accumulated().eval(), 0)
  
          # Take gradients always sets the size back to 0 if successful.
          accum_op = q.apply_grad((10.0,), local_step=1)
          accum_op.run()
          accum_op.run()
          accum_op.run()
          accum_op.run()
          self.assertEqual(q.num_accumulated().eval(), 4)
          extract_t.op.run()
          self.assertEqual(q.num_accumulated().eval(), 0)
  
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 12 for calling the ConditionalAccumulatorTest obj's underlying member method code with example usage: obj.testAccumulatorSizeAfterApplyGradAndTakeGrad() without return types