def test_word_rnn(device_id): try_set_default_device(cntk_device(device_id)) # Just run and verify it does not crash # Setting global parameters W.use_sampled_softmax = True W.softmax_sample_size = 3 W.use_sparse = True W.hidden_dim = 20 W.num_layers = 2 W.num_epochs = 1 W.sequence_length = 3 W.sequences_per_batch = 2 W.alpha = 0.75 W.learning_rate = 0.02 W.momentum_as_time_constant = 5 W.clipping_threshold_per_sample = 5.0 W.segment_sepparator = '<eos>' W.num_samples_between_progress_report = 2 # Get path to data files. dir = os.path.dirname(os.path.abspath(W.__file__)) W.token_to_id_path = os.path.join(dir, 'test/token2id.txt') W.validation_file_path = os.path.join(dir, 'test/text.txt') W.train_file_path = os.path.join(dir, 'test/text.txt') W.token_frequencies_file_path = os.path.join(dir, 'test/freq.txt') W.train_lm(testing=True)
def test_word_rnn(device_id): from cntk.ops.tests.ops_test_utils import cntk_device set_default_device(cntk_device(device_id)) # Just run and verify it does not crash # Setting global parameters W.use_sampled_softmax = True W.softmax_sample_size = 3 W.use_sparse = True W.hidden_dim = 20 W.num_layers = 2 W.num_epochs = 1 W.sequence_length = 3 W.sequences_per_batch = 2 W.alpha = 0.75 W.learning_rate = 0.02 W.momentum_as_time_constant = 5 W.clipping_threshold_per_sample = 5.0 W.segment_sepparator = '<eos>' W.num_samples_between_progress_report = 2 # Get path to data files. dir = os.path.dirname( os.path.abspath(W.__file__)) W.token_to_id_path = os.path.join(dir, 'test/token2id.txt') W.validation_file_path = os.path.join(dir, 'test/text.txt') W.train_file_path = os.path.join(dir, 'test/text.txt') W.token_frequencies_file_path = os.path.join(dir, 'test/freq.txt') W.train_lm()
def test_ptb_word_rnn(device_id): if cntk_device(device_id).type() != DeviceKind_GPU: pytest.skip('This test only runs on GPU') try_set_default_device(cntk_device(device_id)) prepare_WordLMWithSampledSoftmax_ptb_data() W.num_epochs = 1 W.softmax_sample_size = 3 W.num_layers = 1 current_path = os.getcwd() os.chdir(os.path.join(base_path)) try: error = W.train_lm(testing=True) expected_error = 6.87 assert np.allclose(error, expected_error, atol=TOLERANCE_ABSOLUTE) finally: os.chdir(current_path)