def make_test_generator(self, randomise=False, do_not_sample_equalised=False): batch_size = int(np.rint(self.args["batch_size"])) num_losses = self.get_num_losses() test_generator, test_steps = make_generator(dataset=self.validation_set, batch_size=batch_size, num_losses=num_losses, shuffle=randomise) return test_generator, test_steps
def make_validation_generator(self, randomise=False): batch_size = int(np.rint(self.args["batch_size"])) num_losses = self.get_num_losses() val_generator, val_steps = make_generator(dataset=self.validation_set, batch_size=batch_size, num_losses=num_losses, shuffle=randomise) return val_generator, val_steps
def make_train_generator(self, randomise=True, stratify=True): batch_size = int(np.rint(self.args["batch_size"])) num_losses = self.get_num_losses() train_generator, train_steps = make_generator(dataset=self.training_set, batch_size=batch_size, num_losses=num_losses, shuffle=randomise) return train_generator, train_steps