I am trying to replicate a network for facial key point detection like in the following link Daniel Nouri's Blog on KFKD. The blog uses Lasagne but i am trying to do using Tensorflow. I am unable to follow the part of performing data augmentation in Tensorflow.All the methods I saw either did augmentation before training or were applied only on X values not on Y.I want to find the replacement of FlipBatchIterator class used in the blogfrom nolearn.lasagne import BatchIteratorclass FlipBatchIterator(BatchIterator):flip_indices = [    (0, 2), (1, 3),    (4, 8), (5, 9), (6, 10), (7, 11),    (12, 16), (13, 17), (14, 18), (15, 19),    (22, 24), (23, 25),    ]def transform(self, Xb, yb):    Xb, yb = super(FlipBatchIterator, self).transform(Xb, yb)    # Flip half of the images in this batch at random:    bs = Xb.shape[0]    indices = np.random.choice(bs, bs / 2, replace=False)    Xb[indices] = Xb[indices, :, :, ::-1]    if yb is not None:        # Horizontal flip of all x coordinates:        yb[indices, ::2] = yb[indices, ::2] * -1        # Swap places, e.g. left_eye_center_x -> right_eye_center_x        for a, b in self.flip_indices:            yb[indices, a], yb[indices, b] = (                yb[indices, b], yb[indices, a])    return Xb, ybnet3 = NeuralNet(# ...regression=True,batch_iterator_train=FlipBatchIterator(batch_size=128),max_epochs=3000,verbose=1,)
Data Augmentation in Tensorflow
deep learning;tensorflow;data augmentation