TensorFlow 2.0 dataset.__iter__() is only supported when eager execution is enabled

Question

I\'m using the following custom training code in TensorFlow 2:

def parse_function(filename, filename2):
    image = read_image(fn)
    def ret1(): return ima         


        

Answer 1

I fixed it by enabling eager execution after importing tensorflow:

import tensorflow as tf

tf.enable_eager_execution()

Reference: Tensorflow

Answer 2

I fixed this by changing the train function to the following:

def train(model, dataset, optimizer):
    for step, (x1, x2, y) in enumerate(dataset):
        with tf.GradientTape() as tape:
            left, right = model([x1, x2])
            loss = contrastive_loss(left, right, tf.cast(y, tf.float32))
        gradients = tape.gradient(loss, model.trainable_variables)
        optimizer.apply_gradients(zip(gradients, model.trainable_variables))

The two changes are removing the @tf.function and fixing the enumeration.

Answer 3

In case you are using Jupyter notebook after

import tensorflow as tf

tf.enable_eager_execution()

You need to restart the kernel and it works