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

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Chapters
00:00 Question
01:13 Accepted answer (Score 1)
01:39 Answer 2 (Score 18)
01:57 Answer 3 (Score 4)
02:15 Thank you

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Full question
https://stackoverflow.com/questions/5557...

Answer 1 links:
[Tensorflow]: https://www.tensorflow.org/guide/eager

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Tags
#python #tensorflow #tensorflowdatasets #tensorflow20

#avk47

ANSWER 1

Score 19

I fixed it by enabling eager execution after importing tensorflow:

import tensorflow as tf

tf.enable_eager_execution()

Reference: Tensorflow

ANSWER 2

Score 4

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

ACCEPTED ANSWER

Score 1

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.