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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def set_compare_estimator_and_feature_spec(self, estimator, feature_spec):
 """Sets a second model for inference as a TF Estimator. If you wish to compare the results of two models in WIT, use this method to setup the details of the second model. Instead of using TF Serving to host a model for WIT to query, WIT can directly use a TF Estimator object as the model to query. In order to accomplish this, a feature_spec must also be provided to parse the example protos for input into the estimator. Args: estimator: The TF Estimator which will be used for model inference. feature_spec: The feature_spec object which will be used for example parsing. Returns: self, in order to enabled method chaining. """

    # If custom function is set, remove it before setting estimator
    self.delete('compare_custom_predict_fn')

    self.store('compare_estimator_and_spec', {
      'estimator': estimator, 'feature_spec': feature_spec})
    self.set_compare_inference_address('estimator')
    # If no model name has been set, give a default
    if not self.has_compare_model_name():
      self.set_compare_model_name('2')
    return self