code: def testAssignDependencyAcrossDevices(self):
      with test_util.use_gpu():
          # The variable and an op to increment it are on the GPU.
          var = state_ops.variable_op([1], dtypes.float32)
          self.evaluate(state_ops.assign(var, [1.0]))
          increment = state_ops.assign_add(var, [1.0])
          with ops.control_dependencies([increment]):
              with test_util.force_cpu():
                  # This mul op is pinned to the CPU, but reads the variable from the
                  # GPU. The test ensures that the dependency on 'increment' is still
                  # honored, i.e., the Send and Recv from GPU to CPU should take place
                  # only after the increment.
                  result = math_ops.multiply(var, var)
          self.assertAllClose([4.0], self.evaluate(result))
  
imports: import numpy
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  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 array_ops_stack
  from tensorflow.python.ops import gen_state_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 24 for calling the VariableOpTest obj's underlying member method code with example usage: obj.testAssignDependencyAcrossDevices() without return types