def begin(self):
    self._global_step_tensor = training_util.get_global_step()
    if (self._global_step_tensor is None):
        raise RuntimeError('Global step should be created to use FeatureImportanceSummarySaver.')
    graph = ops.get_default_graph()
    self._feature_names_tensor = graph.get_tensor_by_name('gbdt/feature_names:0')
    self._feature_usage_counts_tensor = graph.get_tensor_by_name('gbdt/feature_usage_counts:0')
    self._feature_gains_tensor = graph.get_tensor_by_name('gbdt/feature_gains:0')
def begin(self):
    self._global_step_tensor = training_util.get_global_step()
    if (self._global_step_tensor is None):
        raise RuntimeError('Global step should be created to use FeatureImportanceSummarySaver.')
    graph = ops.get_default_graph()
    self._feature_names_tensor = graph.get_tensor_by_name('gbdt/feature_names:0')
    self._feature_usage_counts_tensor = graph.get_tensor_by_name('gbdt/feature_usage_counts:0')
    self._feature_gains_tensor = graph.get_tensor_by_name('gbdt/feature_gains:0')