from anna.datasets import supervised_dataset import checkpoints from models import CNNModel print("Start") pid = os.getpid() print("PID: {}".format(pid)) f = open("pid", "wb") f.write(str(pid) + "\n") f.close() model = CNNModel("experiment", "./", learning_rate=1e-2) checkpoint = checkpoints.unsupervised_layer3 util.set_parameters_from_unsupervised_model(model, checkpoint) monitor = util.Monitor(model) # Add dropout model.fc4.dropout = 0.5 model._compile() # Loading CIFAR-10 dataset print("Loading Data") data_path = "/data/cifar10/" reduced_data_path = os.path.join(data_path, "reduced", "cifar10_100") train_data = numpy.load(os.path.join(reduced_data_path, "train_X_split_0.npy")) train_labels = numpy.load(os.path.join(reduced_data_path, "train_y_split_0.npy")) test_data = numpy.load("/data/cifar10/test_X.npy") test_labels = numpy.load("/data/cifar10/test_y.npy")
from anna.datasets import supervised_dataset import checkpoints from models import CNNModel print('Start') pid = os.getpid() print('PID: {}'.format(pid)) f = open('pid', 'wb') f.write(str(pid)+'\n') f.close() model = CNNModel('experiment', './', learning_rate=1e-2) checkpoint = checkpoints.unsupervised_layer3 util.set_parameters_from_unsupervised_model(model, checkpoint) monitor = util.Monitor(model) # Add dropout model.fc4.dropout = 0.5 model._compile() # Loading CIFAR-10 dataset print('Loading Data') train_data = numpy.load('/data/cifar10/train_X.npy') train_labels = numpy.load('/data/cifar10/train_y.npy') test_data = numpy.load('/data/cifar10/test_X.npy') test_labels = numpy.load('/data/cifar10/test_y.npy') train_dataset = supervised_dataset.SupervisedDataset(train_data, train_labels) test_dataset = supervised_dataset.SupervisedDataset(test_data, test_labels)