How to retrieve tensorflow datasets into numpy arrays

Question

I am using tensorflow 2.0.0. I want to inspect the contents of the datats, by extracting its contents and converting to numpy arrays (maybe there are other better ways to do so). Assume a dataset

<SkipDataset shapes: {features: (4,), label: ()}, types: {features: tf.float32, label: tf.int64}>

Then how to extract the features and label here inside the dataset?

Wathek LOUED · Accepted Answer · 2020-01-16 15:31:55Z

1

You can do it using list like in here:

import tensorflow_datasets as tfds 
import tensorflow as tf

mnist = tfds.load(name="mnist", split=tfds.Split.TRAIN)
small = mnist.take(10)

print(list(small))

however be careful with that if your dataset is big.

answered Jan 16, 2020 at 15:31

Wathek LOUED

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