# Tensorflow | tf.data.Dataset.reduce()

• Last Updated : 03 Oct, 2019

With the help of `tf.data.Dataset.reduce()` method, we can get the reduced transformation of all the elements in the dataset by using `tf.data.Dataset.reduce()` method.

Syntax : `tf.data.Dataset.reduce()`
Return : Return combined single result after transformation.

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Note :
These given examples will demonstrate the use of new version of tensorflow 2.0, so if you want to run these examples please run the following commands in command prompt.

`pip install tensorflow==2.0.0-rc2`

Example #1 :
In this example we can see that by using `tf.data.Dataset.reduce()` method, we are able to get the reduced transformation of all the elements from the dataset.

 `# import tensorflow``import` `tensorflow as tf`` ` `# using tf.data.Dataset.reduce() method``gfg ``=` `tf.data.Dataset.from_tensor_slices([``1``, ``2``, ``3``, ``4``, ``5``])`` ` `print``(gfg.``reduce``(``0``, ``lambda` `x, y: x ``+` `y).numpy())`

Output :

15

Example #2 :

 `# import tensorflow``import` `tensorflow as tf`` ` `# using tf.data.Dataset.reduce() method``gfg ``=` `tf.data.Dataset.from_tensor_slices([[``5``, ``10``], [``3``, ``6``]])`` ` `print``(gfg.``reduce``(``0``, ``lambda` `x, y: x ``*` `y).numpy())`

Output :

[15, 60]

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