def test_weighted(self): mape_obj = metrics.MeanAbsolutePercentageError() self.evaluate(variables.variables_initializer(mape_obj.variables)) y_true = constant_op.constant(((0, 1, 0, 1, 0), (0, 0, 1, 1, 1), (1, 1, 1, 1, 0), (0, 0, 0, 0, 1))) y_pred = constant_op.constant(((0, 0, 1, 1, 0), (1, 1, 1, 1, 1), (0, 1, 0, 1, 0), (1, 1, 1, 1, 1))) sample_weight = constant_op.constant((1., 1.5, 2., 2.5)) result = mape_obj(y_true, y_pred, sample_weight=sample_weight) self.assertAllClose(40e7, self.evaluate(result), atol=1e-5)
def test_config(self): mape_obj = metrics.MeanAbsolutePercentageError(name='my_mape', dtype=dtypes.int32) self.assertEqual(mape_obj.name, 'my_mape') self.assertEqual(mape_obj._dtype, dtypes.int32) # Check save and restore config mape_obj2 = metrics.MeanAbsolutePercentageError.from_config( mape_obj.get_config()) self.assertEqual(mape_obj2.name, 'my_mape') self.assertEqual(mape_obj2._dtype, dtypes.int32)
def test_unweighted(self): mape_obj = metrics.MeanAbsolutePercentageError() self.evaluate(variables.variables_initializer(mape_obj.variables)) y_true = constant_op.constant(((0, 1, 0, 1, 0), (0, 0, 1, 1, 1), (1, 1, 1, 1, 0), (0, 0, 0, 0, 1))) y_pred = constant_op.constant(((0, 0, 1, 1, 0), (1, 1, 1, 1, 1), (0, 1, 0, 1, 0), (1, 1, 1, 1, 1))) update_op = mape_obj.update_state(y_true, y_pred) self.evaluate(update_op) result = mape_obj.result() self.assertAllClose(35e7, result, atol=1e-5)