TensorFlow create dataset from numpy array

Question

TensorFlow as build it a nice way to store data. This is for example used to store the MNIST data in the example:

>>> mnist
<tensorflow.examples.tutorials.mnist.input_data.read_data_sets.<locals>.DataSets object at 0x10f930630>

Suppose to have a input and output numpy arrays.

>>> x = np.random.normal(0,1, (100, 10))
>>> y = np.random.randint(0, 2, 100)

How can I transform them in a tf dataset?

I want to use functions like next_batch

Answer 1

The Dataset object is only part of the MNIST tutorial, not the main TensorFlow library.

You can see where it is defined here:

GitHub Link

The constructor accepts an images and labels argument so presumably you can pass your own values there.