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