def test_dae_yaml(): """ Train a denoising autoencoder for a single epoch """ limited_epoch_train( os.path.join(pylearn2.__path__[0], "scripts/autoencoder_example/dae.yaml"))
def test_hcae_yaml(): """ Train a higher order contractive autoencoder for a single epoch """ limited_epoch_train( os.path.join(pylearn2.__path__[0], "scripts/autoencoder_example/hcae.yaml"))
def test_mnist(): """ Tests mnist.yaml by running it for only one epoch """ skip_if_no_data() limited_epoch_train(os.path.join(yaml_file_path, 'mnist.yaml')) try: os.remove(os.path.join(save_path, 'mnist.pkl')) os.remove(os.path.join(save_path, 'mnist_best.pkl')) except: pass
def test_mnist(): """ Tests mnist.yaml by running it for only one epoch """ if config.mode == "DEBUG_MODE": yaml_file = 'mnist_fast' else: yaml_file = 'mnist' skip_if_no_data() limited_epoch_train(os.path.join(yaml_file_path, '%s.yaml' % yaml_file)) try: os.remove(os.path.join(save_path, '%s.pkl' % yaml_file)) os.remove(os.path.join(save_path, '%s_best.pkl' % yaml_file)) except: pass
def test_mnist(): """ Tests mnist.yaml by running it for only one epoch """ skip_if_no_data() mode = get_default_mode() if hasattr(mode, "check_py_code"): old_value = mode.check_py_code mode.check_py_code = False try: if config.mode == "DEBUG_MODE": yaml_file = "mnist_fast" else: yaml_file = "mnist" limited_epoch_train(os.path.join(yaml_file_path, "%s.yaml" % yaml_file)) try: os.remove(os.path.join(save_path, "%s.pkl" % yaml_file)) os.remove(os.path.join(save_path, "%s_best.pkl" % yaml_file)) except Exception: pass finally: if hasattr(mode, "check_py_code"): mode.check_py_code = old_value
def test_mnist(): """ Tests mnist.yaml by running it for only one epoch """ skip_if_no_data() mode = get_default_mode() if hasattr(mode, 'check_py_code'): old_value = mode.check_py_code mode.check_py_code = False try: if config.mode == "DEBUG_MODE": yaml_file = 'mnist_fast' else: yaml_file = 'mnist' limited_epoch_train(os.path.join(yaml_file_path, '%s.yaml' % yaml_file)) try: os.remove(os.path.join(save_path, '%s.pkl' % yaml_file)) os.remove(os.path.join(save_path, '%s_best.pkl' % yaml_file)) except Exception: pass finally: if hasattr(mode, 'check_py_code'): mode.check_py_code = old_value
def test_lwta_yaml(): """Test simple model on random data.""" limited_epoch_train(os.path.join(pylearn2.__path__[0], "models/tests/lwta.yaml"))
def test_hcae_yaml(): """ Train a higher order contractive autoencoder for a single epoch """ limited_epoch_train(os.path.join(pylearn2.__path__[0], "scripts/autoencoder_example/hcae.yaml"))
def test_dae_yaml(): """ Train a denoising autoencoder for a single epoch """ limited_epoch_train(os.path.join(pylearn2.__path__[0], "scripts/autoencoder_example/dae.yaml"))
def test_hcae_yaml(): limited_epoch_train( os.path.join(pylearn2.__path__[0], "scripts/autoencoder_example/hcae.yaml"))
def test_lwta_yaml(): """Test simple model on random data.""" limited_epoch_train( os.path.join(pylearn2.__path__[0], "models/tests/lwta.yaml"))