def test_multiple_empty(self): sparsity = linear._compute_fraction_of_zero([ ops.convert_to_tensor([]), ops.convert_to_tensor([]), ]) self.assertTrue(self.evaluate(tf.math.is_nan(sparsity)), 'Expected sparsity=nan, got %s' % sparsity)
def test_empty(self): sparsity = linear._compute_fraction_of_zero([ops.convert_to_tensor([])]) with self.test_session() as sess: sparsity_np = sess.run(sparsity) self.assertTrue( np.isnan(sparsity_np), 'Expected sparsity=nan, got %s' % sparsity_np)
def test_none(self): with self.assertRaises(ValueError): linear._compute_fraction_of_zero([])
def _assertSparsity(self, expected_sparsity, tensor): sparsity = linear._compute_fraction_of_zero([tensor]) self.assertAllClose(expected_sparsity, sparsity)
def _assertSparsity(self, expected_sparsity, tensor): sparsity = linear._compute_fraction_of_zero([tensor]) with self.test_session() as sess: self.assertAllClose(expected_sparsity, sess.run(sparsity))