import models import numpy as np np.random.seed(123) print("Loading data . . . ") (_, Y_train), (_, Y_test) = models.load_data_from_keras() X_train = np.load("results/vgg16_ae_X_train.npy") X_test = np.load("results/vgg16_ae_X_test.npy") """ n = 1000 X_train = X_train[:n] Y_train = Y_train[:n] X_test = X_test[:n] Y_test = Y_test[:n] """ """ m = X_train.min() s = X_train.max() X_train -= m X_train = X_train/s X_test -= m X_test = X_test/s """ print("Training . . . ") model = models.vgg16(lr=1e-3, mbs=50, pred_mbs=500, seed=456) model.start_session() accs = model.train(X_train, Y_train, eval_set=(X_test, Y_test),
import models import numpy as np print("Loading data . . . ") #(X_train, Y_train), (X_test, Y_test) = models.load_data() (X_train, Y_train), _ = models.load_data_from_keras() print("Resizing . . . ") X_train = models.preprocess.resize(X_train) print("Getting center . . . ") center = np.mean(X_train, axis=(0, 1, 2)) print("Writing results . . . ") np.savetxt("results/center_after_resize.txt", center) print("Done")