def test_generate_keras_mode_skip_run_eagerly(self): result = test_combinations.keras_mode_combinations(run_eagerly=[False]) if tf.__internal__.tf2.enabled(): self.assertLen(result, 1) self.assertEqual(result[0], {"mode": "eager", "run_eagerly": False}) else: self.assertLen(result, 2) self.assertEqual(result[0], {"mode": "eager", "run_eagerly": False}) self.assertEqual(result[1], {"mode": "graph", "run_eagerly": False})
class ExampleTest(parameterized.TestCase): def runTest(self): pass @test_combinations.generate( test_combinations.keras_mode_combinations()) def testBody(self): mode = "eager" if tf.executing_eagerly() else "graph" should_run_eagerly = test_utils.should_run_eagerly() test_params.append((mode, should_run_eagerly))
def test_combine_combinations(self): test_cases = [] @test_combinations.generate( test_combinations.times( test_combinations.keras_mode_combinations(), test_combinations.keras_model_type_combinations(), ) ) class ExampleTest(parameterized.TestCase): def runTest(self): pass @parameterized.named_parameters( dict(testcase_name="_arg", arg=True) ) def testBody(self, arg): del arg mode = "eager" if tf.executing_eagerly() else "graph" should_run_eagerly = test_utils.should_run_eagerly() test_cases.append( (mode, should_run_eagerly, test_utils.get_model_type()) ) ts = unittest.makeSuite(ExampleTest) res = unittest.TestResult() ts.run(res) expected_combinations = [ ("eager", False, "functional"), ("eager", False, "sequential"), ("eager", False, "subclass"), ("eager", True, "functional"), ("eager", True, "sequential"), ("eager", True, "subclass"), ] if not tf.__internal__.tf2.enabled(): expected_combinations.extend( [ ("graph", False, "functional"), ("graph", False, "sequential"), ("graph", False, "subclass"), ] ) self.assertAllEqual(sorted(test_cases), expected_combinations)
def test_generate_keras_mode_eager_only(self): result = test_combinations.keras_mode_combinations(mode=["eager"]) self.assertLen(result, 2) self.assertEqual(result[0], {"mode": "eager", "run_eagerly": True}) self.assertEqual(result[1], {"mode": "eager", "run_eagerly": False})
# ============================================================================== """Tests for SimpleRNN layer.""" import tensorflow.compat.v2 as tf import copy from absl.testing import parameterized import numpy as np import keras from keras.testing_infra import test_combinations from keras.testing_infra import test_utils @test_combinations.generate(test_combinations.keras_mode_combinations()) class SimpleRNNLayerTest(tf.test.TestCase, parameterized.TestCase): def test_return_sequences_SimpleRNN(self): num_samples = 2 timesteps = 3 embedding_dim = 4 units = 2 test_utils.layer_test(keras.layers.SimpleRNN, kwargs={ 'units': units, 'return_sequences': True }, input_shape=(num_samples, timesteps, embedding_dim)) @test_utils.run_v2_only