code: def test_xla_launch_with_var_on_gpu_device(self):
      @def_function.function(jit_compile=True)
      def foo(x, y):
          return x + y + 1
  
      @def_function.function(jit_compile=True)
      def bar(x, y):
          x.assign(y)
          y.assign_add([1.0, 1.0])
  
      with ops.device("/device:GPU:0"):
          a = constant_op.constant([1.0, 2.0])
          x = variables.Variable([0.0, 1.0])
          result_tensor = foo(x, a)
  
      self.assertAllClose(result_tensor.numpy(), [2.0, 4.0], atol=1e-05)
  
      # The following use case is tested:
      # Variable updates following an XLA computation that reads the updated
      # variables.
      with ops.device("/device:GPU:0"):
          var_a = variables.Variable([0.0, 1.0])
          var_b = variables.Variable([1.0, 2.0])
          bar(var_a, var_b)
          result = foo(var_a, var_b)
  
      self.assertAllClose([1.0, 2.0], var_a.value(), atol=1e-05)
      self.assertAllClose([2.0, 3.0], var_b.value(), atol=1e-05)
      self.assertAllClose(result, [4.0, 6.0], atol=1e-05)
  
file_path: tensorflow/tensorflow/python/compiler/xla/tests/pjrt_compile_test.py
imports: import numpy
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import test
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
label_desc: Use image node_id 4 for calling the PjrtCompileTest obj's underlying member method code with example usage: obj.test_xla_launch_with_var_on_gpu_device() and returns: unknown