code: def test_variables_across_graphs_nuclear():
      optimizer = cg_lib.ConditionalGradient(0.01, 0.5, ord="nuclear")
      var0 = tf.Variable([1.0, 2.0], dtype=tf.float32, name="var0")
      var1 = tf.Variable([3.0, 4.0], dtype=tf.float32, name="var1")
  
      def loss():
          return tf.math.reduce_sum(var0 + var1)
  
      optimizer.minimize(loss, var_list=[var0, var1])
      optimizer_variables = optimizer.variables()
      # There should be three items. The first item is iteration,
      # and one item for each variable.
      assert optimizer_variables[1].name.startswith(
          "ConditionalGradient/var0"
      )
      assert optimizer_variables[2].name.startswith(
          "ConditionalGradient/var1"
      )
      assert 3 == len(optimizer_variables)
  
imports: import numpy
  import pytest
  import platform
  import tensorflow
  from tensorflow_addons.utils import test_utils
  from tensorflow_addons.optimizers import conditional_gradient
label_desc: Use image node_id 10 for calling a global function with example usage: test_variables_across_graphs_nuclear() and returns: tf