def test_view_of_view_modification():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata[0, :][:, 5:].X = np.ones(5)
    assert np.all(adata.X[0, 5:] == np.ones(5))
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2))
    assert np.all(adata.X[1:3, 1:3] == np.ones((2, 2)))

    adata.X = sparse.csr_matrix(adata.X)
    adata[0, :][:, 5:].X = np.ones(5) * 2
    assert np.all(asarray(adata.X)[0, 5:] == np.ones(5) * 2)
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2)) * 2
    assert np.all(asarray(adata.X)[1:3, 1:3] == np.ones((2, 2)) * 2)
def testMinimizeSparseResourceVariableCentered(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=0.1,
          momentum=0.0,
          epsilon=1.0,
          centered=True).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(
          [[-7/3.0, -4/3.0]], var0.eval(), atol=0.01)