def get_stats_result(self, request):
        """Return the StatsResult object for this statistic"""
        stats_datasets = StatsMakerDataverses(**request.GET.dict())

        pub_state = self.get_pub_state(request)

        if pub_state == self.PUB_STATE_ALL:
            stats_result = stats_datasets.get_dataverse_counts_by_month()
        elif pub_state == self.PUB_STATE_UNPUBLISHED:
            stats_result = stats_datasets.get_dataverse_counts_by_month_unpublished()
        else:
            stats_result = stats_datasets.get_dataverse_counts_by_month_published()

        return stats_result
def testMinimizeSparseResourceVariable(self, dtype):
    with self.cached_session():
      var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
      x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
      pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
      loss = pred * pred
      sgd_op = rmsprop.RMSPropOptimizer(
          learning_rate=1.0,
          decay=0.0,
          momentum=0.0,
          epsilon=0.0,
          centered=False).minimize(loss)
      variables.global_variables_initializer().run()
      # Fetch params to validate initial values
      self.assertAllCloseAccordingToType([[1.0, 2.0]], var0.eval())
      # Run 1 step of sgd
      sgd_op.run()
      # Validate updated params
      self.assertAllCloseAccordingToType(
          [[0., 1.]], var0.eval(), atol=0.01)