code: def tf_baseline_basic():
      import tensorflow as tf
      import cntk.contrib.crosstalk.crosstalk_tensorflow as crtf
  
      ci = crtf.instance
  
      tf.reset_default_graph()
  
      p1 = tf.get_variable(
          "param1", initializer=param1, dtype=tf.float32
      )
      p2 = tf.get_variable(
          "param2", initializer=param2, dtype=tf.float32
      )
      ci.watch(p1, "p1", var_type=crtf.TrainableType)
      ci.watch(
          {"param1": p1, "param2": p2},
          "p1_p2",
          var_type=crtf.DictTrainableType,
      )
  
      with tf.Session() as sess:
          sess.run(tf.global_variables_initializer())
          ci.set_workdir(workdir)
          ci.set_data(sess, None)
          ci.fetch("p1", save=True)
          ci.fetch("p1_p2", save=True)
          ci.reset()
          sess.close()
  
imports: import pytest
  import numpy
  from cntk.contrib import crosstalk
  import tempfile
label_desc: Use image node_id 2 for calling a global function with example usage: tf_baseline_basic() without return types