class_docstr: A scope that tracks all trainable variable accesses within it.
  
  This explicitly ignores variables that are not marked as trainable.
  
  Sample usage:
  
  var = tf.Variable(0.0)
  with VariableWatcher() as variable_watcher:
    var.assign_add(1.0)
  
  assert variable_watcher.watched_variables == [var]
docstr: Returns a tuple of variables accessed under this scope.
docstr_tok: ["Returns","a","tuple","of","variables","accessed","under","this","scope","."]
code: def watched_variables(self):
      """Returns a tuple of variables accessed under this scope."""
      return pywrap_tfe.TFE_Py_VariableWatcherWatchedVariables(
          self._variable_watcher
      )
  
file_path: tensorflow-upstream/tensorflow/python/eager/record.py
imports: import contextlib
  from tensorflow.python import pywrap_tfe
label_desc: Use image node_id 4 for calling the VariableWatcher obj's underlying member method code with example usage: obj.watched_variables() and returns: pywrap_tfe